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Kakavand R, Ahmadi R, Parsaei A, Brent Edwards W, Komeili A. Comparison of kinematics and kinetics between OpenCap and a marker-based motion capture system in cycling. Comput Biol Med 2025; 192:110295. [PMID: 40311466 DOI: 10.1016/j.compbiomed.2025.110295] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2025] [Revised: 04/23/2025] [Accepted: 04/25/2025] [Indexed: 05/03/2025]
Abstract
This study evaluates the agreement of marker-based and markerless (OpenCap) motion capture systems in assessing joint kinematics and kinetics during cycling. Markerless systems, such as OpenCap, offer the advantage of capturing natural movements without physical markers, making them more practical for real-world applications. However, the agreement of OpenCap with a marker-based system, particularly in cycling, remains underexplored. Ten participants cycled at varying speeds and resistances while motion data were recorded using both systems. Key metrics, including joint angles, moments, and joint reaction loads, were computed using OpenSim and compared using root mean squared error (RMSE) per trial across participants, Pearson correlation coefficients (r) per trial across participants and repeated measures Bland-Altman to control trials' dependency within subject. Results revealed very strong agreement (r > 0.9) for hip (flexion/extension), knee (flexion/extension), and ankle (dorsiflexion/plantarflexion) joint angles. Relatively high RMSE values of 10.7° (±3.0°) and 12.4° (±4.6°) were observed for left and right ankle dorsiflexion/plantarflexion angles, respectively, per trial across participants. Knee flexion/extension RMSE per trial across participants were 9.3° (±3.8°) and 10.2° (±4.3°) for the left and right limbs, respectively. RMSE values of hip flexion/extension, adduction/abduction and rotation were 7.9° (±2.6°), 3.2° (±1.1°) and 3° (±1.2°) for the left side. Joint reaction forces and moments exhibited moderate to very strong agreement across most degrees of freedom. The RMSE of joint reaction forces ranged from 13.7 to 37.7 %BW. The hip medial-lateral moment had a minimum RMSE of 0.19 %BW × ht, while the highest RMSE of 1.27 %BW × ht was in the knee anterior-posterior moment. Despite strong overall agreement between the systems, variability per trial across participants in RMSE suggested that OpenCap may require further refinement in specific areas. These findings highlight the potential of markerless motion capture systems, such as OpenCap, in biomechanical analyses of cycling while also identifying areas where further refinement may be needed.
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Affiliation(s)
- Reza Kakavand
- Department of Biomedical Engineering, Schulich School of Engineering, University of Calgary, Canada; McCaig Institute for Bone and Joint Health, University of Calgary, Calgary, Canada; Human Performance Laboratory, Faculty of Kinesiology, University of Calgary, Calgary, Canada
| | - Reza Ahmadi
- Department of Biomedical Engineering, Schulich School of Engineering, University of Calgary, Canada
| | - Atousa Parsaei
- Department of Biomedical Engineering, Schulich School of Engineering, University of Calgary, Canada
| | - W Brent Edwards
- Department of Biomedical Engineering, Schulich School of Engineering, University of Calgary, Canada; McCaig Institute for Bone and Joint Health, University of Calgary, Calgary, Canada; Human Performance Laboratory, Faculty of Kinesiology, University of Calgary, Calgary, Canada
| | - Amin Komeili
- Department of Biomedical Engineering, Schulich School of Engineering, University of Calgary, Canada; McCaig Institute for Bone and Joint Health, University of Calgary, Calgary, Canada; Human Performance Laboratory, Faculty of Kinesiology, University of Calgary, Calgary, Canada.
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De Pasquale P, Bonanno M, De Marchis C, Pergolizzi L, Lombardo Facciale A, Paladina G, Maggio MG, Impellizzeri F, Ciancarelli I, Quartarone A, Calabrò RS. Beyond clinical scales: an observational study on instrumental gait analysis and biomechanical patterns in patients with Parkinson's disease. Front Bioeng Biotechnol 2025; 13:1541240. [PMID: 40370594 PMCID: PMC12075126 DOI: 10.3389/fbioe.2025.1541240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2024] [Accepted: 04/07/2025] [Indexed: 05/16/2025] Open
Abstract
Introduction Parkinson's disease (PD), a common neurodegenerative disorder affecting motor functions, is associated with abnormal gait patterns characterized by altered kinematic, kinetic, and electrophysiological parameters. This observational study aims to instrumentally identify and quantify these gait dysfunctions in PD patients compared to normal values from healthy subjects. Methods Sixty-nine PD patients underwent clinical and instrumental evaluations to assess gait. Demographic and clinical data were collected before motor assessment. Clinical scales evaluated the level of impairment, gait, balance, risk of falls and ability to complete activities of daily living. Instrumental evaluations were conducted using optoelectronic, force plates and electromyographic (EMG) systems in a motion analysis laboratory. Statistical analysis involved a non-parametric test to compare pathological and normal data, clustering methods to identify groups based on clinical evaluations, and a combination of non-parametric analysis and linear models to assess dependencies on clinical scales. Results The results showed that PD patients had significant gait kinematic differences compared to normal values, with increased temporal and shortened spatial parameters. In addition, PD patients were grouped into four clusters based on clinical scales. While some gait features were influenced by clinical scales reflecting impairment, gait and balance, and independence, others were more affected by the perceived fear of falling (FoF). Discussion In conclusion, the study identified specific biomechanical gait dysfunctions in kinematic, kinetic, and electrophysiological parameters in PD patients, undetectable by standard clinical scales. Additionally, higher FoF was associated with dysfunctional biomechanical patterns, independent of impairment severity, gait and balance dysfunction, or overall independence.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Irene Ciancarelli
- Department of Life, Health and Environmental Sciences, University of L'Aquila, L’Aquila, Italy
| | - Angelo Quartarone
- IRCCS Centro Neurolesi Bonino-Pulejo, Messina, Italy
- Department of Biomedical, Dental Sciences and Morphological and Functional Images, University of Messina, Messina, Italy
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Choi W, Jeong H, Oh S, Jung TD. Instant gait classification for hip osteoarthritis patients: a non-wearable sensor approach utilizing Pearson correlation, SMAPE, and GMM. Biomed Eng Lett 2025; 15:301-310. [PMID: 40026883 PMCID: PMC11871253 DOI: 10.1007/s13534-024-00448-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2024] [Revised: 10/23/2024] [Accepted: 11/15/2024] [Indexed: 03/05/2025] Open
Abstract
This study aims to establish a methodology for classifying gait patterns in patients with hip osteoarthritis without the use of wearable sensors. Although patients with the same pathological condition may exhibit significantly different gait patterns, an accurate and efficient classification system is needed: one that reduces the effort and preparation time for both patients and clinicians, allowing gait analysis and classification without the need for cumbersome sensors like EMG or camera-based systems. The proposed methodology follows three key steps. First, ground reaction forces are measured in three directions-anterior-posterior, medial-lateral, and vertical-using a force plate during gait analysis. These force data are then evaluated through two approaches: trend similarity is assessed using the Pearson correlation coefficient, while scale similarity is measured with the Symmetric Mean Absolute Percentage Error (SMAPE), comparing results with healthy controls. Finally, Gaussian Mixture Models (GMM) are applied to cluster both healthy controls and patients, grouping the patients into distinct categories based on six quantified metrics derived from the correlation and SMAPE. Using the proposed methodology, 16 patients with hip osteoarthritis were successfully categorized into two distinct gait groups (Group 1 and Group 2). The gait patterns of these groups were further analyzed by comparing joint moments and angles in the lower limbs among healthy individuals and the classified patient groups. This study demonstrates that gait pattern classification can be reliably achieved using only force-plate data, offering a practical tool for personalized rehabilitation in hip osteoarthritis patients. By incorporating quantitative variables that capture both gait trends and scale, the methodology efficiently classifies patients with just 2-3 ms of natural walking. This minimizes the burden on patients while delivering a more accurate and realistic assessment. The proposed approach maintains a level of accuracy comparable to more complex methods, while being easier to implement and more accessible in clinical settings.
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Affiliation(s)
- Wiha Choi
- Department of Robotics and Mechatronics Engineering, DGIST, Daegu, 711-785 Republic of Korea
| | - Hieyong Jeong
- Department of Artificial Intelligence Convergence, Chonnam National University, 77 Yongbongro, Bukgu, Gwangju, 61186 Republic of Korea
| | - Sehoon Oh
- Department of Robotics and Mechatronics Engineering, DGIST, Daegu, 711-785 Republic of Korea
| | - Tae-Du Jung
- School of Medicine, Kyungpook National University Hospital, 680 Gukchaebosang-ro, Jung-gu, Daegu, 41404 Republic of Korea
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Straub RK, Powers CM. Biomechanical predictors of primary ACL injury: A scoping review of prospective studies. Gait Posture 2025; 116:22-29. [PMID: 39603181 DOI: 10.1016/j.gaitpost.2024.11.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/05/2024] [Revised: 11/18/2024] [Accepted: 11/20/2024] [Indexed: 11/29/2024]
Abstract
BACKGROUND ACL injuries commonly occur in non-contact situations, particularly in sports involving jumping, landing, and cutting. Numerous biomechanical predictors for non-contact ACL injury have been proposed, yet existing reviews on biomechanical predictors vary in scope and findings. RESEARCH QUESTION This review aims to identify biomechanical predictors of primary ACL injury using a scoping review. METHODS PubMed and EBSCO host (CINAHL Complete, MEDLINE Complete, SPORTDiscus) were searched from inception to March 1, 2023. Prospective studies that (1) examined discrete kinematic/kinetic variables during whole body movements (e.g., landing from a jump, cutting, and single-leg squatting) using 3D lab-based motion analysis, 2D video, or observational (non-instrumented) methods; and (2) produced a prediction model for the association between biomechanical variables (independent variable) and primary ACL injury (dependent variable) were included. RESULTS 11 studies were included. Jump-landing tasks were the most studied (9 studies), followed by change in direction (2 studies) and single-leg squatting (2 studies). Significant biomechanical predictors for non-contact ACL injury were reported in 7 studies during jump-landing/change in directions tasks. Kinematic predictors included decreased flexion (hip and knee) and increased knee valgus/internal rotation. Kinetic predictors included increased vertical ground reaction forces (landing/takeoff) and increased knee moments (valgus and knee extensor). Limited/conflicting evidence was found for all predictors. None of studies that employed 2D or observational methods (n=3) were able to identify predictors of ACL injury. SIGNIFICANCE Biomechanical predictors of primary ACL injury were identified in 7 of 11 prospective studies included within this scoping review. The majority of the reported risk factors were identified using the drop jump, which was the most studied task (8 of 11 studies). The lack of standardization in biomechanical testing across studies limits the determination of specific predictive variables for primary ACL injury.
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Affiliation(s)
- Rachel K Straub
- University of Southern California, Division of Biokinesiology & Physical Therapy, Los Angeles, CA, USA
| | - Christopher M Powers
- University of Southern California, Division of Biokinesiology & Physical Therapy, Los Angeles, CA, USA.
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Thiele F, Paternoster F, Hummel C, Stöcker F, Holzer D. Assessment of the Accuracy of a Deep Learning Algorithm- and Video-based Motion Capture System in Estimating Snatch Kinematics. INTERNATIONAL JOURNAL OF EXERCISE SCIENCE 2024; 17:1629-1647. [PMID: 39807293 PMCID: PMC11728585 DOI: 10.70252/prvv4165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/16/2025]
Abstract
In weightlifting, quantitative kinematic analysis is essential for evaluating snatch performance. While marker-based (MB) approaches are commonly used, they are impractical for training or competitions. Markerless video-based (VB) systems utilizing deep learning-based pose estimation algorithms could address this issue. This study assessed the comparability and applicability of VB systems in obtaining snatch kinematics by comparing the outcomes to an MB reference system. 21 weightlifters (15 Male, 6 Female) performed 2-3 snatches at 65%, 75%, and 80% of their one-repetition maximum. Snatch kinematics were analyzed using an MB (Vicon Nexus) and VB (Contemplas along with Theia3D) system. Analysis of 131 trials revealed that corresponding lower limb joint center positions of the systems on average differed by 4.7 ± 1.2 cm, and upper limb joint centers by 5.7 ± 1.5 cm. VB and MB lower limb joint angles showed highest agreement in the frontal plane (root mean square difference (RMSD): 11.2 ± 5.9°), followed by the sagittal plane (RMSD: 13.6 ± 4.7°). Statistical Parametric Mapping analysis revealed significant differences throughout most of the movement for all degrees of freedom. Maximum extension angles and velocities during the second pull displayed significant differences (p < .05) for the lower limbs. Our data showed significant differences in estimated kinematics between both systems, indicating a lack of comparability. These differences are likely due to differing models and assumptions, rather than measurement accuracy. However, given the rapid advancements of neural network-based approaches, it holds promise to become a suitable alternative to MB systems in weightlifting analysis.
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Affiliation(s)
- Federico Thiele
- Department of Sport and Health Sciences, Technical University of Munich, Munich, BY, GERMANY
| | - Florian Paternoster
- Department of Sport and Health Sciences, Technical University of Munich, Munich, BY, GERMANY
| | - Chris Hummel
- Applied Sports Science, Department Health and Sports Sciences, Technical University of Munich, Munich, BY, GERMANY
| | - Fabian Stöcker
- Präventionszentrum, Department Health and Sport Sciences, Technical University of Munich, Munich, BY, GERMANY
| | - Denis Holzer
- Department of Sport and Health Sciences, Technical University of Munich, Munich, BY, GERMANY
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Fleisig GS, Slowik JS, Wassom D, Yanagita Y, Bishop J, Diffendaffer A. Comparison of marker-less and marker-based motion capture for baseball pitching kinematics. Sports Biomech 2024; 23:2950-2959. [PMID: 35591756 DOI: 10.1080/14763141.2022.2076608] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 05/06/2022] [Indexed: 10/18/2022]
Abstract
The purpose of this study was to compare baseball pitching kinematics measured with marker-less and marker-based motion capture. Two hundred and seventy-five fastball pitches were captured at 240 Hz simultaneously with a 9-camera marker-less system and a 12-camera marker system. The pitches were thrown by 30 baseball pitchers (age 17.1 ± 3.1 years). Data for each trial were time-synchronised between the two systems using the instant of ball release. Coefficients of Multiple Correlations (CMC) were computed to assess the similarity of waveforms between the two systems. Discrete measurements at foot contact, during arm cocking, and at ball release were compared between the systems using Bland-Altman plots and descriptive statistics. CMC values for the five time series analysed ranged from 0.88 to 0.97, indicating consistency in movement patterns between systems. Biases for discrete measurements ranged in magnitude from 0 to 16 degrees. Standard deviations of the differences between systems ranged from 0 to 14 degrees, while intraclass correlations ranged from 0.64 to 0.92. Thus, the marker-based and marker-less motion capture systems produced similar patterns for baseball pitching kinematics. However, based on the variations between the systems, it is recommended that a database of normative ranges be established for each system.
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Affiliation(s)
- Glenn S Fleisig
- American Sports Medicine Institute, Birmingham, AL, USA
- Dari Motion, Overland Park, KS, USA
| | | | | | - Yuki Yanagita
- American Sports Medicine Institute, Birmingham, AL, USA
| | - Jasper Bishop
- American Sports Medicine Institute, Birmingham, AL, USA
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D'Souza S, Siebert T, Fohanno V. A comparison of lower body gait kinematics and kinetics between Theia3D markerless and marker-based models in healthy subjects and clinical patients. Sci Rep 2024; 14:29154. [PMID: 39587194 PMCID: PMC11589150 DOI: 10.1038/s41598-024-80499-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2024] [Accepted: 11/19/2024] [Indexed: 11/27/2024] Open
Abstract
Three-dimensional (3D) marker-based motion capture is the current gold standard to assess and monitor pathological gait in a clinical setting. However, 3D markerless motion capture based on pose estimation is advancing into the field of gait analysis. This study aims at evaluating the lower-body 3D gait kinematics and kinetics from synchronously recorded Theia3D markerless and CAST marker-based systems. Twelve healthy individuals and 34 clinical patients aged 8-61 years walked at self-selected speed over a 13 m long walkway. Similarity between models was statistically analysed using inter-trial variability, root mean square error, Pearson's correlation coefficient and Statistical Parametric Mapping. Inter-trial variability was on average higher for clinical patients in both models. Overall, the markerless system demonstrated similar gait patterns although hip and knee rotations were non-comparable. Pelvic anterior tilt was significantly underestimated. Significant differences especially in peak values at specific phases of the gait cycle were observed across all planes for all joints (more so for clinical patients than healthy subjects) as well as in the sagittal powers of the hip, knee and ankle. Theia3D markerless system offers great potential in gait analysis. This study brings awareness to potential clinical users and researchers where they can have confidence, as well as areas where caution should be exercised.
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Affiliation(s)
- Sonia D'Souza
- Gait laboratory, Olgahospital/Frauenklinik, Orthopaedic Clinic, Klinikum Stuttgart, Kriegsbergstrasse 62, 70174, Stuttgart, Germany
| | - Tobias Siebert
- Motion and Exercise Science, University of Stuttgart, Stuttgart, Germany.
- Stuttgart Center of Simulation Science, University of Stuttgart, Stuttgart, Germany.
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Aleksic J, Kanevsky D, Mesaroš D, Knezevic OM, Cabarkapa D, Bozovic B, Mirkov DM. Validation of Automated Countermovement Vertical Jump Analysis: Markerless Pose Estimation vs. 3D Marker-Based Motion Capture System. SENSORS (BASEL, SWITZERLAND) 2024; 24:6624. [PMID: 39460104 PMCID: PMC11511341 DOI: 10.3390/s24206624] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2024] [Revised: 10/07/2024] [Accepted: 10/12/2024] [Indexed: 10/28/2024]
Abstract
This study aimed to validate the automated temporal analysis of countermovement vertical jump (CMJ) using MMPose, a markerless pose estimation framework, by comparing it with the gold-standard 3D marker-based motion capture system. Twelve participants performed five CMJ trials, which were simultaneously recorded using the marker-based system and two smartphone cameras capturing both sides of the body. Key kinematic points, including center of mass (CoM) and toe trajectories, were analyzed to determine jump phases and temporal variables. The agreement between methods was assessed using Bland-Altman analysis, root mean square error (RMSE), and Pearson's correlation coefficient (r), while consistency was evaluated via intraclass correlation coefficient (ICC 3,1) and two-way repeated-measures ANOVA. Cohen's effect size (d) quantified the practical significance of differences. Results showed strong agreement (r > 0.98) with minimal bias and narrow limits of agreement for most variables. The markerless system slightly overestimated jump height and CoM vertical velocity, but ICC values (ICC > 0.91) confirmed strong reliability. Cohen's d values were near zero, indicating trivial differences, and no variability due to recording side was observed. Overall, MMPose proved to be a reliable alternative for in-field CMJ analysis, supporting its broader application in sports and rehabilitation settings.
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Affiliation(s)
- Jelena Aleksic
- Faculty of Sport and Physical Education, University of Belgrade, 11000 Belgrade, Serbia; (J.A.); (O.M.K.)
| | | | - David Mesaroš
- School of Electrical Engineering, University of Belgrade, 11000 Belgrade, Serbia;
| | - Olivera M. Knezevic
- Faculty of Sport and Physical Education, University of Belgrade, 11000 Belgrade, Serbia; (J.A.); (O.M.K.)
| | - Dimitrije Cabarkapa
- Jayhawk Athletic Performance Laboratory—Wu Tsai Human Performance Alliance, Department of Health, Sport and Exercise Sciences, University of Kansas, Lawrence, KS 66045, USA;
| | - Branislav Bozovic
- Faculty of Sport and Physical Education, University of Belgrade, 11000 Belgrade, Serbia; (J.A.); (O.M.K.)
| | - Dragan M. Mirkov
- Faculty of Sport and Physical Education, University of Belgrade, 11000 Belgrade, Serbia; (J.A.); (O.M.K.)
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Fujibayashi M, Abe K. A behavioral analysis system MCFBM enables objective inference of songbirds' attention during social interactions. CELL REPORTS METHODS 2024; 4:100844. [PMID: 39232558 PMCID: PMC11440064 DOI: 10.1016/j.crmeth.2024.100844] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Revised: 05/13/2024] [Accepted: 08/07/2024] [Indexed: 09/06/2024]
Abstract
Understanding animal behavior is crucial in behavioral neuroscience, aiming to unravel the mechanisms driving these behaviors. A significant milestone in this field is the analysis of behavioral reactions during social interactions. Despite their importance in social learning, the behavioral aspects of these interaction are not well understood in detail due to the lack of appropriate tools. We introduce a high-precision, marker-based motion-capture system for analyzing behavior in songbirds, accurately tracking body location and head direction in multiple freely moving finches during social interaction. Focusing on zebra finches, our analysis revealed variations in eye use based on individuals presented. We also observed behavioral changes during virtual and live presentations and a conditioned-learning paradigm. Additionally, the system effectively analyzed social interactions among mice. This system provides an efficient tool for advanced behavioral analysis in small animals and offers an objective method to infer their focus of attention.
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Affiliation(s)
- Mizuki Fujibayashi
- Lab of Brain Development, Graduate School of Life Sciences, Tohoku University, Katahira 2-1-1, Aoba-ku, Sendai, Miyagi 980-8577, Japan
| | - Kentaro Abe
- Lab of Brain Development, Graduate School of Life Sciences, Tohoku University, Katahira 2-1-1, Aoba-ku, Sendai, Miyagi 980-8577, Japan; Division for the Establishment of Frontier Sciences of the Organization for Advanced Studies, Tohoku University, Katahira 2-1-1, Aoba-ku, Sendai, Miyagi 980-8577, Japan.
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Mazurek KA, Barnard L, Botha H, Christianson T, Graff-Radford J, Petersen R, Vemuri P, Windham BG, Jones DT, Ali F. A validation study demonstrating portable motion capture cameras accurately characterize gait metrics when compared to a pressure-sensitive walkway. Sci Rep 2024; 14:17464. [PMID: 39075097 PMCID: PMC11286855 DOI: 10.1038/s41598-024-68402-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2024] [Accepted: 07/23/2024] [Indexed: 07/31/2024] Open
Abstract
Digital quantification of gait can be used to measure aging- and disease-related decline in mobility. Gait performance also predicts prognosis, disease progression, and response to therapies. Most gait analysis systems require large amounts of space, resources, and expertise to implement and are not widely accessible. Thus, there is a need for a portable system that accurately characterizes gait. Here, depth video from two portable cameras accurately reconstructed gait metrics comparable to those reported by a pressure-sensitive walkway. 392 research participants walked across a four-meter pressure-sensitive walkway while depth video was recorded. Gait speed, cadence, and step and stride durations and lengths strongly correlated (r > 0.9) between modalities, with root-mean-squared-errors (RMSE) of 0.04 m/s, 2.3 steps/min, 0.03 s, and 0.05-0.08 m for speed, cadence, step/stride duration, and step/stride length, respectively. Step, stance, and double support durations (gait cycle percentage) significantly correlated (r > 0.6) between modalities, with 5% RMSE for step and stance and 10% RMSE for double support. In an exploratory analysis, gait speed from both modalities significantly related to healthy, mild, moderate, or severe categorizations of Charleson Comorbidity Indices (ANOVA, Tukey's HSD, p < 0.0125). These findings demonstrate the viability of using depth video to expand access to quantitative gait assessments.
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Affiliation(s)
| | - Leland Barnard
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Hugo Botha
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | | | | | - Ronald Petersen
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | | | - B Gwen Windham
- Department of Medicine, The MIND Center, University of Mississippi Medical Center, Jackson, MS, USA
| | - David T Jones
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Farwa Ali
- Department of Neurology, Mayo Clinic, Rochester, MN, USA.
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Meletani S, Scataglini S, Mandolini M, Scalise L, Truijen S. Experimental Comparison between 4D Stereophotogrammetry and Inertial Measurement Unit Systems for Gait Spatiotemporal Parameters and Joint Kinematics. SENSORS (BASEL, SWITZERLAND) 2024; 24:4669. [PMID: 39066067 PMCID: PMC11280879 DOI: 10.3390/s24144669] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/06/2024] [Revised: 07/05/2024] [Accepted: 07/08/2024] [Indexed: 07/28/2024]
Abstract
(1) Background: Traditional gait assessment methods have limitations like time-consuming procedures, the requirement of skilled personnel, soft tissue artifacts, and high costs. Various 3D time scanning techniques are emerging to overcome these issues. This study compares a 3D temporal scanning system (Move4D) with an inertial motion capture system (Xsens) to evaluate their reliability and accuracy in assessing gait spatiotemporal parameters and joint kinematics. (2) Methods: This study included 13 healthy people and one hemiplegic patient, and it examined stance time, swing time, cycle time, and stride length. Statistical analysis included paired samples t-test, Bland-Altman plot, and the intraclass correlation coefficient (ICC). (3) Results: A high degree of agreement and no significant difference (p > 0.05) between the two measurement systems have been found for stance time, swing time, and cycle time. Evaluation of stride length shows a significant difference (p < 0.05) between Xsens and Move4D. The highest root-mean-square error (RMSE) was found in hip flexion/extension (RMSE = 10.99°); (4) Conclusions: The present work demonstrated that the system Move4D can estimate gait spatiotemporal parameters (gait phases duration and cycle time) and joint angles with reliability and accuracy comparable to Xsens. This study allows further innovative research using 4D (3D over time) scanning for quantitative gait assessment in clinical practice.
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Affiliation(s)
- Sara Meletani
- Department of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche, via Brecce Bianche 12, 60131 Ancona, Italy; (S.M.); (M.M.); (L.S.)
| | - Sofia Scataglini
- 4D4ALL Lab, Department of Rehabilitation Sciences and Physiotherapy, Center for Health and Technology (CHaT), Faculty of Medicine and Health Sciences, MOVANT, University of Antwerp, 2000 Antwerpen, Belgium;
| | - Marco Mandolini
- Department of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche, via Brecce Bianche 12, 60131 Ancona, Italy; (S.M.); (M.M.); (L.S.)
| | - Lorenzo Scalise
- Department of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche, via Brecce Bianche 12, 60131 Ancona, Italy; (S.M.); (M.M.); (L.S.)
| | - Steven Truijen
- 4D4ALL Lab, Department of Rehabilitation Sciences and Physiotherapy, Center for Health and Technology (CHaT), Faculty of Medicine and Health Sciences, MOVANT, University of Antwerp, 2000 Antwerpen, Belgium;
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Haustein M, Blanke A, Bockemühl T, Büschges A. A leg model based on anatomical landmarks to study 3D joint kinematics of walking in Drosophila melanogaster. Front Bioeng Biotechnol 2024; 12:1357598. [PMID: 38988867 PMCID: PMC11233710 DOI: 10.3389/fbioe.2024.1357598] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Accepted: 05/20/2024] [Indexed: 07/12/2024] Open
Abstract
Walking is the most common form of how animals move on land. The model organism Drosophila melanogaster has become increasingly popular for studying how the nervous system controls behavior in general and walking in particular. Despite recent advances in tracking and modeling leg movements of walking Drosophila in 3D, there are still gaps in knowledge about the biomechanics of leg joints due to the tiny size of fruit flies. For instance, the natural alignment of joint rotational axes was largely neglected in previous kinematic analyses. In this study, we therefore present a detailed kinematic leg model in which not only the segment lengths but also the main rotational axes of the joints were derived from anatomical landmarks, namely, the joint condyles. Our model with natural oblique joint axes is able to adapt to the 3D leg postures of straight and forward walking fruit flies with high accuracy. When we compared our model to an orthogonalized version, we observed that our model showed a smaller error as well as differences in the used range of motion (ROM), highlighting the advantages of modeling natural rotational axes alignment for the study of joint kinematics. We further found that the kinematic profiles of front, middle, and hind legs differed in the number of required degrees of freedom as well as their contributions to stepping, time courses of joint angles, and ROM. Our findings provide deeper insights into the joint kinematics of walking in Drosophila, and, additionally, will help to develop dynamical, musculoskeletal, and neuromechanical simulations.
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Affiliation(s)
- Moritz Haustein
- Institute of Zoology, Biocenter Cologne, University of Cologne, Cologne, Germany
| | - Alexander Blanke
- Bonn Institute for Organismic Biology (BIOB), Animal Biodiversity, University of Bonn, Bonn, Germany
| | - Till Bockemühl
- Institute of Zoology, Biocenter Cologne, University of Cologne, Cologne, Germany
| | - Ansgar Büschges
- Institute of Zoology, Biocenter Cologne, University of Cologne, Cologne, Germany
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13
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Ebers MR, Pitts M, Kutz JN, Steele KM. Human motion data expansion from arbitrary sparse sensors with shallow recurrent decoders. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.01.596487. [PMID: 38895371 PMCID: PMC11185509 DOI: 10.1101/2024.06.01.596487] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
Advances in deep learning and sparse sensing have emerged as powerful tools for monitoring human motion in natural environments. We develop a deep learning architecture, constructed from a shallow recurrent decoder network, that expands human motion data by mapping a limited (sparse) number of sensors to a comprehensive (dense) configuration, thereby inferring the motion of unmonitored body segments. Even with a single sensor, we reconstruct the comprehensive set of time series measurements, which are important for tracking and informing movement-related health and performance outcomes. Notably, this mapping leverages sensor time histories to inform the transformation from sparse to dense sensor configurations. We apply this mapping architecture to a variety of datasets, including controlled movement tasks, gait pattern exploration, and free-moving environments. Additionally, this mapping can be subject-specific (based on an individual's unique data for deployment at home and in the community) or group-based (where data from a large group are used to learn a general movement model and predict outcomes for unknown subjects). By expanding our datasets to unmeasured or unavailable quantities, this work can impact clinical trials, robotic/device control, and human performance by improving the accuracy and availability of digital biomarker estimates.
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Affiliation(s)
- Megan R Ebers
- Department of Applied Mathematics, University of Washington, Seattle, WA 98195
| | - Mackenzie Pitts
- Department of Mechanical Engineering, University of Washington, Seattle, WA 98195
| | - J Nathan Kutz
- Department of Applied Mathematics and Electrical and Computer Engineering, University of Washington, Seattle, WA 98195
| | - Katherine M Steele
- Department of Mechanical Engineering, University of Washington, Seattle, WA 98195
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14
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Kim HY, An YS, Oh SH, Lee HC. Clinical Feasibility of a Markerless Gait Analysis System. Clin Orthop Surg 2024; 16:506-516. [PMID: 38827756 PMCID: PMC11130620 DOI: 10.4055/cios23065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 01/11/2024] [Accepted: 01/11/2024] [Indexed: 06/04/2024] Open
Abstract
Background The gait analysis method that has been used in clinical practice to date is an optical tracking system (OTS) using a marker, but a markerless gait analysis (MGA) system is being developed because of the expensive cost and complicated examination of the OTS. To apply this MGA clinically, a comparative study of the MGA and OTS methods is necessary. The purpose of this study was to evaluate the compatibility between the OTS and the MGA methods and to evaluate the usefulness of the MGA system in actual clinical settings. Methods From March 2021 to August 2021, 14 patients underwent gait analysis using the OTS and MGA system, and the spatiotemporal parameters and kinematic results obtained by the 2 methods were compared. To evaluate the practicality of the MGA system in an actual clinical setting, MGA was performed on 14 symptomatic children with idiopathic toe walking, who had been treated with a corrective cast, and the pre-cast and post-cast results were compared. For the OTS, the Motion Analysis Eagle system was used, and for MGA, DH Walk was used. Results The spatiotemporal parameters showed no significant difference between the OTS and MGA system. The joint angle graphs of the kinematics along the sagittal plane showed similar shapes as a whole, with particularly high correlations in the hip and knee (pelvis: 29.4%, hip joint: 96.7%, knee joint: 94.9%, and ankle joint: 68.5%). A quantified comparison using the CORrelation and Analysis (CORA) score also showed high similarity between the 2 methods. The MGA results of pre-cast application and post-cast removal for children with idiopathic toe walking showed a statistically significant improvement in ankle dorsiflexion after treatment (p < 0.001). Conclusions MGA showed a good correlation with the conventional OTS in terms of spatiotemporal parameters and kinematics. We demonstrated that ankle sagittal kinematics improved after treatment by corrective cast in children with idiopathic toe walking using the MGA method. Thus, after the improvement of a few limitations, the MGA system may soon be able to be clinically applied.
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Affiliation(s)
- Ha Yong Kim
- Department of Orthopedic Surgery, Eulji University College of Medicine, Daejeon, Korea
| | - Young Sun An
- Department of Orthopedic Surgery, Eulji University College of Medicine, Daejeon, Korea
| | - Seung Hak Oh
- Department of Orthopedic Surgery, Eulji University College of Medicine, Daejeon, Korea
| | - Han Cheol Lee
- Department of Orthopedic Surgery, Eulji University College of Medicine, Daejeon, Korea
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15
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De Pasquale P, Bonanno M, Mojdehdehbaher S, Quartarone A, Calabrò RS. The Use of Head-Mounted Display Systems for Upper Limb Kinematic Analysis in Post-Stroke Patients: A Perspective Review on Benefits, Challenges and Other Solutions. Bioengineering (Basel) 2024; 11:538. [PMID: 38927774 PMCID: PMC11200415 DOI: 10.3390/bioengineering11060538] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2024] [Revised: 05/20/2024] [Accepted: 05/21/2024] [Indexed: 06/28/2024] Open
Abstract
In recent years, there has been a notable increase in the clinical adoption of instrumental upper limb kinematic assessment. This trend aligns with the rising prevalence of cerebrovascular impairments, one of the most prevalent neurological disorders. Indeed, there is a growing need for more objective outcomes to facilitate tailored rehabilitation interventions following stroke. Emerging technologies, like head-mounted virtual reality (HMD-VR) platforms, have responded to this demand by integrating diverse tracking methodologies. Specifically, HMD-VR technology enables the comprehensive tracking of body posture, encompassing hand position and gesture, facilitated either through specific tracker placements or via integrated cameras coupled with sophisticated computer graphics algorithms embedded within the helmet. This review aims to present the state-of-the-art applications of HMD-VR platforms for kinematic analysis of the upper limb in post-stroke patients, comparing them with conventional tracking systems. Additionally, we address the potential benefits and challenges associated with these platforms. These systems might represent a promising avenue for safe, cost-effective, and portable objective motor assessment within the field of neurorehabilitation, although other systems, including robots, should be taken into consideration.
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Affiliation(s)
- Paolo De Pasquale
- IRCCS Centro Neurolesi Bonino-Pulejo, Cda Casazza, SS 113, 98124 Messina, Italy; (P.D.P.); (A.Q.); (R.S.C.)
| | - Mirjam Bonanno
- IRCCS Centro Neurolesi Bonino-Pulejo, Cda Casazza, SS 113, 98124 Messina, Italy; (P.D.P.); (A.Q.); (R.S.C.)
| | - Sepehr Mojdehdehbaher
- Department of Mathematics, Computer Science, Physics and Earth Sciences (MIFT), University of Messina, Viale Ferdinando Stagno d’Alcontres, 31, 98166 Messina, Italy;
| | - Angelo Quartarone
- IRCCS Centro Neurolesi Bonino-Pulejo, Cda Casazza, SS 113, 98124 Messina, Italy; (P.D.P.); (A.Q.); (R.S.C.)
| | - Rocco Salvatore Calabrò
- IRCCS Centro Neurolesi Bonino-Pulejo, Cda Casazza, SS 113, 98124 Messina, Italy; (P.D.P.); (A.Q.); (R.S.C.)
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Lohss R, Winter R, Göpfert B, Visscher RMS, Sangeux M, Zentai N, Viehweger E. Biomechanical gait parameters change with increasing virtual height in a child with spastic cerebral palsy: A case report. Clin Case Rep 2024; 12:e8548. [PMID: 38440770 PMCID: PMC10909796 DOI: 10.1002/ccr3.8548] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 11/02/2023] [Accepted: 01/25/2024] [Indexed: 03/06/2024] Open
Abstract
Virtual height exposure coupled with motion capture is feasible to elicit changes in spatiotemporal, kinematic, and kinetic gait parameters in a child with cerebral palsy and should be considered when investigating gait in real-world-scenarios.
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Affiliation(s)
- Regine Lohss
- Laboratory for Movement AnalysisUniversity Children's Hospital BaselBaselSwitzerland
- Department of Biomedical EngineeringUniversity of BaselBaselSwitzerland
| | - Rebecca Winter
- Laboratory for Movement AnalysisUniversity Children's Hospital BaselBaselSwitzerland
- Department of Biomedical EngineeringUniversity of BaselBaselSwitzerland
| | - Beat Göpfert
- Laboratory for Movement AnalysisUniversity Children's Hospital BaselBaselSwitzerland
- Department of Biomedical EngineeringUniversity of BaselBaselSwitzerland
| | - Rosa M. S. Visscher
- Department of Biomedical EngineeringUniversity of BaselBaselSwitzerland
- Careum School of HealthKalaidos University of Applied SciencesZurichSwitzerland
| | - Morgan Sangeux
- Laboratory for Movement AnalysisUniversity Children's Hospital BaselBaselSwitzerland
- Department of Biomedical EngineeringUniversity of BaselBaselSwitzerland
| | - Norbert Zentai
- Department of Biomedical EngineeringUniversity of BaselBaselSwitzerland
| | - Elke Viehweger
- Laboratory for Movement AnalysisUniversity Children's Hospital BaselBaselSwitzerland
- Department of Biomedical EngineeringUniversity of BaselBaselSwitzerland
- Department of OrthopedicsUniversity Children's Hospital BaselBaselSwitzerland
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17
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Ruescas-Nicolau AV, De Rosario H, Bernabé EP, Juan MC. Positioning errors of anatomical landmarks identified by fixed vertices in homologous meshes. Gait Posture 2024; 108:215-221. [PMID: 38118225 DOI: 10.1016/j.gaitpost.2023.11.024] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Revised: 06/21/2023] [Accepted: 11/29/2023] [Indexed: 12/22/2023]
Abstract
BACKGROUND Human movement analysis is usually achieved by tracking markers attached to anatomical landmarks with photogrammetry. Such marker-based systems have disadvantages that have led to the development of markerless procedures, although their accuracy is not usually comparable to that of manual palpation procedures. New motion acquisition systems, such as 3D temporal scanners, provide homologous meshes that can be exploited for this purpose. RESEARCH QUESTION Can fixed vertices of a homologous mesh be used to identify anatomical landmarks with an accuracy equivalent to that of manual palpation? METHODS We used 3165 human shape scans from the CAESAR dataset, with labelled locations of anatomical landmarks. First, we fitted a template mesh to the scans, and assigned a vertex of that mesh to 53 anatomical landmarks in all subjects. Then we defined a nominal vertex for each landmark, as the more centred vertex out of the set assigned for that landmark. We calculated the errors of the template-fitting and the nominal vertex determination procedures, and analysed their relationship to subject's sex, height and body mass index, as well as their size compared to manual palpation errors. RESULTS The template-fitting errors were below 5 mm, and the nominal vertex determination errors reached maximum values of 24 mm. Except for the trochanter, those errors were the same order of magnitude or smaller than inter-examiner errors of lower limb landmarks. Errors increased with height and body mass index, and were smaller for men than for women of the same height and body mass index. SIGNIFICANCE We defined a set of vertices for 53 anatomical landmarks in a homologous mesh, which yields location errors comparable to those obtained by manual palpation for the majority of landmarks. We also quantified how the subject's sex and anthropometric features can affect the size of those errors.
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Affiliation(s)
- Ana V Ruescas-Nicolau
- Instituto de Biomecánica - IBV. Universitat Politècnica de València, edifici 9C. Camí de Vera, s/n 46022 València, Spain.
| | - Helios De Rosario
- Instituto de Biomecánica - IBV. Universitat Politècnica de València, edifici 9C. Camí de Vera, s/n 46022 València, Spain
| | - Eduardo Parrilla Bernabé
- Instituto de Biomecánica - IBV. Universitat Politècnica de València, edifici 9C. Camí de Vera, s/n 46022 València, Spain
| | - M-Carmen Juan
- Instituto Universitario de Automática e Informática Industrial. Universitat Politècnica de València, edifici 1F. Camí de Vera, s/n 46022 València, Spain
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18
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Das K, de Paula Oliveira T, Newell J. Comparison of markerless and marker-based motion capture systems using 95% functional limits of agreement in a linear mixed-effects modelling framework. Sci Rep 2023; 13:22880. [PMID: 38129434 PMCID: PMC10739832 DOI: 10.1038/s41598-023-49360-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 12/07/2023] [Indexed: 12/23/2023] Open
Abstract
Biomechanics analysis of human movement has been proven useful for maintenance of health, injury prevention, and rehabilitation in both sports and clinical populations. A marker-based motion capture system is considered the gold standard method of measurement for three dimensional kinematics measurements. However, the application of markers to anatomical bony points is a time consuming process and constrained by inter-, intra-tester and session reliability issues. The emergence of novel markerless motion capture systems without the use of reflective markers is a rapidly growing field in motion analysis. However an assessment of the level of agreement of a markerless system with an established gold standard marker-based system is needed to ensure the applicability of a markerless system. An extra layer of complexity is involved as the kinematics measurements are functional responses. In this paper a new approach is proposed to generate 95% functional limits of agreement (fLoA) using the linear mixed-effects modelling framework for hierarchical study designs. This approach is attractive as it will allow practitioners to extend their use of linear mixed models to assess agreement in method comparison studies in all domains where functional responses are recorded.
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Affiliation(s)
- Kishor Das
- School of Mathematical and Statistical Sciences, University of Galway, Galway, Ireland.
- CÚRAM, SFI Research Centre for Medical Devices, University of Galway, Galway, Ireland.
| | | | - John Newell
- School of Mathematical and Statistical Sciences, University of Galway, Galway, Ireland
- CÚRAM, SFI Research Centre for Medical Devices, University of Galway, Galway, Ireland
- The Insight Centre for Data Analytics, University of Galway, Galway, Ireland
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Chu H, Kim W, Joo S, Park E, Kim YW, Kim CH, Lee S. Validity and Reliability of POM-Checker for Measuring Shoulder Range of Motion in Healthy Participants: A Pilot Single-Center Comparative Study. Methods Protoc 2023; 6:114. [PMID: 38133134 PMCID: PMC10745328 DOI: 10.3390/mps6060114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 11/22/2023] [Accepted: 11/23/2023] [Indexed: 12/23/2023] Open
Abstract
BACKGROUND The aim of this study was to compare shoulder movement measurements between a Kinect-based markerless ROM assessment device (POM-Checker) and a 3D motion capture analysis system (BTS SMART DX-400). METHODS This was a single-visit clinical trial designed to evaluate the validity and reliability of the POM-Checker. The primary outcome was to assess the equivalence between two measurement devices within the same set of participants, aiming to evaluate the validity of the POM-Checker compared to the gold standard device (3D Motion Analysis System). As this was a pilot study, six participants were included. RESULTS The intraclass correlation coefficient (ICC) and the corresponding 95% confidence intervals (CIs) were used to assess the reproducibility of the measurements. Among the 18 movements analyzed, 16 exhibited ICC values of >0.75, indicating excellent reproducibility. CONCLUSION The results showed that the POM-checker is reliable and validated to measure the range of motion of the shoulder joint.
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Affiliation(s)
- Hongmin Chu
- Department of Internal Medicine and Neuroscience, College of Korean Medicine, Wonkwang University, Iksan 54538, Republic of Korea;
| | - Weonjin Kim
- Team Elysium Inc. R&D Center, Seoul 06682, Republic of Korea; (W.K.); (S.J.); (E.P.); (Y.W.K.)
| | - Seongsu Joo
- Team Elysium Inc. R&D Center, Seoul 06682, Republic of Korea; (W.K.); (S.J.); (E.P.); (Y.W.K.)
| | - Eunsik Park
- Team Elysium Inc. R&D Center, Seoul 06682, Republic of Korea; (W.K.); (S.J.); (E.P.); (Y.W.K.)
| | - Yeong Won Kim
- Team Elysium Inc. R&D Center, Seoul 06682, Republic of Korea; (W.K.); (S.J.); (E.P.); (Y.W.K.)
| | - Cheol-Hyun Kim
- Department of Internal Medicine and Neuroscience, College of Korean Medicine, Wonkwang University, Iksan 54538, Republic of Korea;
- Stroke Korean Medicine Research Center, Wonkwang University, Iksan 54538, Republic of Korea
| | - Sangkwan Lee
- Department of Internal Medicine and Neuroscience, College of Korean Medicine, Wonkwang University, Iksan 54538, Republic of Korea;
- Stroke Korean Medicine Research Center, Wonkwang University, Iksan 54538, Republic of Korea
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20
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Brambilla C, Marani R, Romeo L, Lavit Nicora M, Storm FA, Reni G, Malosio M, D'Orazio T, Scano A. Azure Kinect performance evaluation for human motion and upper limb biomechanical analysis. Heliyon 2023; 9:e21606. [PMID: 38027881 PMCID: PMC10663858 DOI: 10.1016/j.heliyon.2023.e21606] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 09/21/2023] [Accepted: 10/24/2023] [Indexed: 12/01/2023] Open
Abstract
Human motion tracking is a valuable task for many medical applications. Marker-based optoelectronic systems are considered the gold standard in human motion tracking. However, their use is not always feasible in clinics and industrial environments. On the other hand, marker-less sensors became valuable tools, as they are inexpensive, noninvasive and easy to use. However, their accuracy can depend on many factors including sensor positioning, light conditions and body occlusions. In this study, following previous works on the feasibility of marker-less systems for human motion monitoring, we investigate the performance of the Microsoft Azure Kinect sensor in computing kinematic and dynamic measurements of static postures and dynamic movements. According to our knowledge, it is the first time that this sensor is compared with a Vicon marker-based system to assess the best camera positioning while observing the upper body part movements of people performing several tasks. Twenty-five healthy volunteers were monitored to evaluate the effects of the several testing conditions, including the Azure Kinect positions, the light conditions, and lower limbs occlusions, on the tracking accuracy of kinematic, dynamic, and motor control parameters. From the statistical analysis of the performed measurements, the camera in the frontal position was the most reliable, the lighting conditions had almost no effects on the tracking accuracy, while the lower limbs occlusion worsened the accuracy of the upper limbs. The assessment of human static postures and dynamic movements based on experimental data proves the feasibility of applying the Azure Kinect to the biomechanical monitoring of human motion in several fields.
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Affiliation(s)
- Cristina Brambilla
- Institute of Intelligent Industrial Systems and Technologies for Advanced Manufacturing (STIIMA), Italian Council of National Research (CNR), Italy
| | - Roberto Marani
- Institute of Intelligent Industrial Systems and Technologies for Advanced Manufacturing (STIIMA), Italian Council of National Research (CNR), Italy
| | - Laura Romeo
- Institute of Intelligent Industrial Systems and Technologies for Advanced Manufacturing (STIIMA), Italian Council of National Research (CNR), Italy
- Department of Electrical and Information Engineering (DEI), Polytechnic of Bari, Bari, Italy
| | - Matteo Lavit Nicora
- Institute of Intelligent Industrial Systems and Technologies for Advanced Manufacturing (STIIMA), Italian Council of National Research (CNR), Italy
- Industrial Engineering Department, University of Bologna, Bologna, Italy
| | - Fabio A. Storm
- Bioengineering Laboratory, Scientific Institute, IRCCS “Eugenio Medea”, 23842 Bosisio Parini, Lecco, Italy
| | - Gianluigi Reni
- Informatics Department, Autonomous Province of Bolzano, Bolzano, Italy
| | - Matteo Malosio
- Institute of Intelligent Industrial Systems and Technologies for Advanced Manufacturing (STIIMA), Italian Council of National Research (CNR), Italy
| | - Tiziana D'Orazio
- Institute of Intelligent Industrial Systems and Technologies for Advanced Manufacturing (STIIMA), Italian Council of National Research (CNR), Italy
| | - Alessandro Scano
- Institute of Intelligent Industrial Systems and Technologies for Advanced Manufacturing (STIIMA), Italian Council of National Research (CNR), Italy
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The role of individual physical body measurements and activity on spine kinematics during flexion, lateral bending and twist tasks in healthy young adults – Comparing marker(less) data. Biomed Signal Process Control 2023. [DOI: 10.1016/j.bspc.2022.104517] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
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Concurrent and Angle-Trajectory Validity and Intra-Trial Reliability of a Novel Multi-View Image-Based Motion Analysis System. J Hum Kinet 2023; 86:31-40. [PMID: 37181271 PMCID: PMC10170539 DOI: 10.5114/jhk/159587] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/17/2023] Open
Abstract
Sports-related injuries are the most common in the lower extremities among physical regions. To evaluate impaired functional performance in sports training facilities and sports, a marker-less motion analysis system that can measure joint kinematics in bright indoor and outdoor environments is required. The aim of this study was to establish the concurrent and angle-trajectory validity and intra-trial reliability of a novel multi-view image-based motion analysis system with marker-less pose estimation during lower extremity tasks in healthy young men. Ten healthy young men participated voluntarily in this study. The hip and knee joint angles were collected using a multi-view image-based motion analysis system (marker-less) and a Vicon motion capture system (with markers) during the lower extremity tasks. Intraclass correlation coefficient (ICC) analyses were used to identify the concurrent and angle-trajectory validity and intra-trial reliability of the multi-view image-based motion analysis system. In the concurrent validity, the correlation analysis revealed that the ICC3, k values on the hip and knee flexions during knee bending in sitting, standing, and squat movements were from 0.747 to 0.936 between the two systems. In particular, the angle-trajectory validity was very high (ICC3, 1 = 0.859–0.998), indicating a high agreement between the two systems. The intra-trial reliability of each system was excellent (ICC3, 1 = 0.773–0.974), reflecting high reproducibility. We suggest that this novel marker-less motion analysis system is highly accurate and reliable for measuring joint kinematics of the lower extremities during the rehabilitation process and monitoring sports performance of athletes in training facilities.
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Fox AS, Bonacci J, Warmenhoven J, Keast MF. Measurement error associated with gait cycle selection in treadmill running at various speeds. PeerJ 2023; 11:e14921. [PMID: 36949756 PMCID: PMC10026719 DOI: 10.7717/peerj.14921] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Accepted: 01/27/2023] [Indexed: 03/19/2023] Open
Abstract
A common approach in the biomechanical analysis of running technique is to average data from several gait cycles to compute a 'representative mean.' However, the impact of the quantity and selection of gait cycles on biomechanical measures is not well understood. We examined the effects of gait cycle selection on kinematic data by: (i) comparing representative means calculated from varying numbers of gait cycles to 'global' means from the entire capture period; and (ii) comparing representative means from varying numbers of gait cycles sampled from different parts of the capture period. We used a public dataset (n = 28) of lower limb kinematics captured during a 30-second period of treadmill running at three speeds (2.5 m s-1, 3.5 m s-1 and 4.5 m s-1). 'Ground truth' values were determined by averaging data across all collected strides and compared to representative means calculated from random samples (1,000 samples) of n (range = 5-30) consecutive gait cycles. We also compared representative means calculated from n (range = 5-15) consecutive gait cycles randomly sampled (1,000 samples) from within the same data capture period. The mean, variance and range of the absolute error of the representative mean compared to the 'ground truth' mean progressively reduced across all speeds as the number of gait cycles used increased. Similar magnitudes of 'error' were observed between the 2.5 m s-1 and 3.5 m s-1 speeds at comparable gait cycle numbers -where the maximum errors were < 1.5 degrees even with a small number of gait cycles (i.e., 5-10). At the 4.5 m s-1 speed, maximum errors typically exceeded 2-4 degrees when a lower number of gait cycles were used. Subsequently, a higher number of gait cycles (i.e., 25-30) was required to achieve low errors (i.e., 1-2 degrees) at the 4.5 m s-1 speed. The mean, variance and range of absolute error of representative means calculated from different parts of the capture period was consistent irrespective of the number of gait cycles used. The error between representative means was low (i.e., < 1.5 degrees) and consistent across the different number of gait cycles at the 2.5 m s-1 and 3.5 m s-1 speeds, and consistent but larger (i.e., up to 2-4 degrees) at the 4.5 m s-1 speed. Our findings suggest that selecting as many gait cycles as possible from a treadmill running bout will minimise potential 'error.' Analysing a small sample (i.e., 5-10 cycles) will typically result in minimal 'error' (i.e., < 2 degrees), particularly at lower speeds (i.e., 2.5 m s-1 and 3.5 m s-1). Researchers and clinicians should consider the balance between practicalities of collecting and analysing a smaller number of gait cycles against the potential 'error' when determining their methodological approach. Irrespective of the number of gait cycles used, we recommend that the potential 'error' introduced by the choice of gait cycle number be considered when interpreting the magnitude of effects in treadmill-based running studies.
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Affiliation(s)
- Aaron S. Fox
- Centre for Sport Research, School of Exercise and Nutrition Sciences, Deakin University, Geelong, Victoria, Australia
| | - Jason Bonacci
- Centre for Sport Research, School of Exercise and Nutrition Sciences, Deakin University, Geelong, Victoria, Australia
| | - John Warmenhoven
- University of Canberra Research Institute of Sport & Exercise (UCRISE), University of Canberra, Canberra, Australia
- Research & Enterprise, University of Canberra, Canberra, Australia
| | - Meghan F. Keast
- Centre for Sport Research, School of Exercise and Nutrition Sciences, Deakin University, Geelong, Victoria, Australia
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Liang F, Yu S, Pang S, Wang X, Jie J, Gao F, Song Z, Li B, Liao WH, Yin M. Non-human primate models and systems for gait and neurophysiological analysis. Front Neurosci 2023; 17:1141567. [PMID: 37188006 PMCID: PMC10175625 DOI: 10.3389/fnins.2023.1141567] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Accepted: 04/11/2023] [Indexed: 05/17/2023] Open
Abstract
Brain-computer interfaces (BCIs) have garnered extensive interest and become a groundbreaking technology to restore movement, tactile sense, and communication in patients. Prior to their use in human subjects, clinical BCIs require rigorous validation and verification (V&V). Non-human primates (NHPs) are often considered the ultimate and widely used animal model for neuroscience studies, including BCIs V&V, due to their proximity to humans. This literature review summarizes 94 NHP gait analysis studies until 1 June, 2022, including seven BCI-oriented studies. Due to technological limitations, most of these studies used wired neural recordings to access electrophysiological data. However, wireless neural recording systems for NHPs enabled neuroscience research in humans, and many on NHP locomotion, while posing numerous technical challenges, such as signal quality, data throughout, working distance, size, and power constraint, that have yet to be overcome. Besides neurological data, motion capture (MoCap) systems are usually required in BCI and gait studies to capture locomotion kinematics. However, current studies have exclusively relied on image processing-based MoCap systems, which have insufficient accuracy (error: ≥4° and 9 mm). While the role of the motor cortex during locomotion is still unclear and worth further exploration, future BCI and gait studies require simultaneous, high-speed, accurate neurophysiological, and movement measures. Therefore, the infrared MoCap system which has high accuracy and speed, together with a high spatiotemporal resolution neural recording system, may expand the scope and improve the quality of the motor and neurophysiological analysis in NHPs.
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Affiliation(s)
- Fengyan Liang
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Haikou, China
- Department of Rehabilitation Medicine, Affiliated Haikou Hospital of Xiangya Medical College, Central South University, Haikou, China
| | - Shanshan Yu
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Haikou, China
| | - Siqi Pang
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Haikou, China
| | - Xiao Wang
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Haikou, China
| | - Jing Jie
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Haikou, China
| | - Fei Gao
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Zhenhua Song
- Department of Rehabilitation Medicine, Affiliated Haikou Hospital of Xiangya Medical College, Central South University, Haikou, China
| | - Binbin Li
- Department of Rehabilitation Medicine, Affiliated Haikou Hospital of Xiangya Medical College, Central South University, Haikou, China
| | - Wei-Hsin Liao
- Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, China
| | - Ming Yin
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Haikou, China
- *Correspondence: Ming Yin,
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Grouios G, Ziagkas E, Loukovitis A, Chatzinikolaou K, Koidou E. Accelerometers in Our Pocket: Does Smartphone Accelerometer Technology Provide Accurate Data? SENSORS (BASEL, SWITZERLAND) 2022; 23:s23010192. [PMID: 36616798 PMCID: PMC9824767 DOI: 10.3390/s23010192] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 12/19/2022] [Accepted: 12/21/2022] [Indexed: 06/12/2023]
Abstract
This study evaluates accelerometer performance of three new state of the art smartphones and focuses on accuracy. The motivating research question was whether accelerator accuracy obtained with these off-the-shelf modern smartphone accelerometers was or was not statistically different from that of a gold-standard reference system. We predicted that the accuracy of the three modern smartphone accelerometers in human movement data acquisition do not differ from that of the Vicon MX motion capture system. To test this prediction, we investigated the comparative performance of three different commercially available current generation smartphone accelerometers among themselves and to a gold-standard Vicon MX motion capture system. A single subject design was implemented for this study. Pearson's correlation coefficients® were calculated to verify the validity of the smartphones' accelerometer data against that of the Vicon MX motion capture system. The Intraclass Correlation Coefficient (ICC) was used to assess the smartphones' accelerometer performance reliability compared to that of the Vicon MX motion capture system. Results demonstrated that (a) the tested smartphone accelerometers are valid and reliable devices for estimating accelerations and (b) there were not significant differences among the three current generation smartphones and the Vicon MX motion capture system's mean acceleration data. This evidence indicates how well recent generation smartphone accelerometer sensors are capable of measuring human body motion. This study, which bridges a significant information gap between the accuracy of accelerometers measured close to production and their accuracy in actual smartphone research, should be interpreted within the confines of its scope, limitations and strengths. Further research is warranted to validate our arguments, suggestions, and results, since this is the first study on this topic.
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Affiliation(s)
- George Grouios
- Department of Physical Education and Sport Science, Aristotle University of Thessaloniki, 57001 Thessaloniki, Greece
| | - Efthymios Ziagkas
- Department of Physical Education and Sport Science, Aristotle University of Thessaloniki, 57001 Thessaloniki, Greece
| | - Andreas Loukovitis
- Department of Physical Education and Sport Science, Aristotle University of Thessaloniki, 57001 Thessaloniki, Greece
| | - Konstantinos Chatzinikolaou
- Department of Physical Education and Sport Science, Aristotle University of Thessaloniki, 57001 Thessaloniki, Greece
| | - Eirini Koidou
- Department of Physical Education and Sport Science-Serres, Aristotle University of Thessaloniki, Agios Ioannis, 62110 Serres, Greece
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Blythman R, Saxena M, Tierney GJ, Richter C, Smolic A, Simms C. Assessment of deep learning pose estimates for sports collision tracking. J Sports Sci 2022; 40:1885-1900. [DOI: 10.1080/02640414.2022.2117474] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
Affiliation(s)
- Richard Blythman
- V-SENSE, School of Computer Science and Statistics(SCSS), Trinity College Dublin, Dublin, Ireland
| | - Manan Saxena
- School of Engineering, Trinity College Dublin, Dublin, Ireland
| | | | | | - Aljosa Smolic
- V-SENSE, School of Computer Science and Statistics(SCSS), Trinity College Dublin, Dublin, Ireland
| | - Ciaran Simms
- School of Engineering, Trinity College Dublin, Dublin, Ireland
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Ruescas Nicolau AV, De Rosario H, Basso Della-Vedova F, Parrilla Bernabé E, Juan MC, López-Pascual J. Accuracy of a 3D temporal scanning system for gait analysis: Comparative with a marker-based photogrammetry system. Gait Posture 2022; 97:28-34. [PMID: 35868094 DOI: 10.1016/j.gaitpost.2022.07.001] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Revised: 05/26/2022] [Accepted: 07/03/2022] [Indexed: 02/02/2023]
Abstract
BACKGROUND Combining the accuracy of marker-based stereophotogrammetry and the usability and comfort of markerless human movement analysis is a difficult challenge. 3D temporal scanners are a promising solution, since they provide moving meshes with thousands of vertices that can be used to analyze human movements. RESEARCH QUESTION Can a 3D temporal scanner be used as a markerless system for gait analysis with the same accuracy as traditional, marker-based stereophotogrammetry systems? METHODS A comparative study was carried out using a 3D temporal scanner synchronized with a marker-based stereophotogrammetry system. Two gait cycles of twelve healthy adults were measured simultaneously, extracting the positions of key anatomical points from both systems, and using them to analyze the 3D kinematics of the pelvis, right hip and knee joints. Measurement differences of marker positions and joint angles were described by their root mean square. A t-test was performed to rule out instrumental errors, and an F-test to evaluate the amplifications of marker position errors in dynamic conditions. RESULTS The differences in 3D landmark positions were between 1.9 and 2.4 mm in the reference pose. Marker position errors were significantly increased during motion in the medial-lateral and vertical directions. The angle relative errors were between 3% and 43% of the range of motion, with the greatest difference being observed in hip axial rotation. SIGNIFICANCE The differences in the results obtained between the 3D temporal scanner and the marker-based system were smaller than the usual errors due to lack of accuracy in the manual positioning of markers on anatomical landmarks and to soft-tissue artefacts. That level of accuracy is greater than other markerless systems, and proves that such technology is a good alternative to traditional, marker-based motion capture.
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Affiliation(s)
- Ana V Ruescas Nicolau
- Instituto de Biomecánica de Valencia, Universitat Politècnica de València, edifici 9C. Camí de Vera, s/n, 46022 València, Spain.
| | - Helios De Rosario
- Instituto de Biomecánica de Valencia, Universitat Politècnica de València, edifici 9C. Camí de Vera, s/n, 46022 València, Spain.
| | - Fermín Basso Della-Vedova
- Instituto de Biomecánica de Valencia, Universitat Politècnica de València, edifici 9C. Camí de Vera, s/n, 46022 València, Spain.
| | - Eduardo Parrilla Bernabé
- Instituto de Biomecánica de Valencia, Universitat Politècnica de València, edifici 9C. Camí de Vera, s/n, 46022 València, Spain.
| | - M-Carmen Juan
- Instituto Universitario de Automática e Informática Industrial, Universitat Politècnica de València, edifici 1F. Camí de Vera, s/n, 46022 València, Spain.
| | - Juan López-Pascual
- Instituto de Biomecánica de Valencia, Universitat Politècnica de València, edifici 9C. Camí de Vera, s/n, 46022 València, Spain.
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Smart Phone-Based Motion Capture and Analysis: Importance of Operating Envelope Definition and Application to Clinical Use. APPLIED SCIENCES-BASEL 2022. [DOI: 10.3390/app12126173] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Human movement is vital for life, with active engagement affording function, limiting disease, and improving quality; with loss resulting in disability; and the treatment and training leading to restoration and enhancement. To foster these endeavors a need exists for a simple and reliable method for the quantitation of movement, favorable for widespread user availability. We developed a Mobile Motion Capture system (MO2CA) employing a smart-phone and colored markers (2, 5, 10 mm) and here define its operating envelope in terms of: (1) the functional distance of marker detection (range), (2) the inter-target resolution and discrimination, (3) the mobile target detection, and (4) the impact of ambient illumination intensity. MO2CA was able to detect and discriminate: (1) single targets over a range of 1 to 18 ft, (2) multiple targets from 1 ft to 11 ft, with inter-target discrimination improving with an increasing target size, (3) moving targets, with minimal errors from 2 ft to 8 ft, and (4) targets within 1 to 18 ft, with an illumination of 100–300 lux. We then evaluated the utility of motion capture in quantitating regional-finger abduction/adduction and whole body–lateral flex motion, demonstrating a quantitative discrimination between normal and abnormal motion. Overall, our results demonstrate that MO2CA has a wide operating envelope with utility for the detection of human movements large and small, encompassing the whole body, body region, and extremity and digit movements. The definition of the effective operating envelope and utility of smart phone-based motion capture as described herein will afford accuracy and appropriate use for future application studies and serve as a general approach for defining the operational bounds of future video capture technologies that arise for potential clinical use.
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Vélez-Guerrero MA, Callejas-Cuervo M, Álvarez JC, Mazzoleni S. Assessment of the Mechanical Support Characteristics of a Light and Wearable Robotic Exoskeleton Prototype Applied to Upper Limb Rehabilitation. SENSORS (BASEL, SWITZERLAND) 2022; 22:3999. [PMID: 35684618 PMCID: PMC9185240 DOI: 10.3390/s22113999] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Revised: 05/16/2022] [Accepted: 05/18/2022] [Indexed: 02/06/2023]
Abstract
Robotic exoskeletons are active devices that assist or counteract the movements of the body limbs in a variety of tasks, including in industrial environments or rehabilitation processes. With the introduction of textile and soft materials in these devices, the effective motion transmission, mechanical support of the limbs, and resistance to physical disturbances are some of the most desirable structural features. This paper proposes an evaluation protocol and assesses the mechanical support properties of a servo-controlled robotic exoskeleton prototype for rehabilitation in upper limbs. Since this prototype was built from soft materials, it is necessary to evaluate the mechanical behavior in the areas that support the arm. Some of the rehabilitation-supporting movements such as elbow flexion and extension, as well as increased muscle tone (spasticity), are emulated. Measurements are taken using the reference supplied to the system's control stage and then compared with an external high-precision optical tracking system. As a result, it is evidenced that the use of soft materials provides satisfactory outcomes in the motion transfer and support to the limb. In addition, this study lays the groundwork for a future assessment of the prototype in a controlled laboratory environment using human test subjects.
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Affiliation(s)
| | - Mauro Callejas-Cuervo
- Software Research Group, Universidad Pedagógica y Tecnológica de Colombia, Tunja 150002, Colombia;
| | - Juan C. Álvarez
- Multisensor Systems and Robotics Group (SiMuR), Department of Electrical, Electronic, Computer and Systems Engineering, University of Oviedo, C/Pedro Puig Adam, 33203 Gijón, Spain;
| | - Stefano Mazzoleni
- Department of Electrical and Information Engineering, Polytechnic University of Bari, 70126 Bari, Italy;
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Troisi Lopez E, Minino R, Sorrentino P, Manzo V, Tafuri D, Sorrentino G, Liparoti M. Sensitivity to gait improvement after levodopa intake in Parkinson's disease: A comparison study among synthetic kinematic indices. PLoS One 2022; 17:e0268392. [PMID: 35551300 PMCID: PMC9098031 DOI: 10.1371/journal.pone.0268392] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Accepted: 04/28/2022] [Indexed: 02/07/2023] Open
Abstract
The synthetic indices are widely used to describe balance and stability during gait. Some of these are employed to describe the gait features in Parkinson's disease (PD). However, the results are sometimes inconsistent, and the same indices are rarely used to compare the individuals affected by PD before and after levodopa intake (OFF and ON condition, respectively). Our aim was to investigate which synthetic measure among Harmonic Ratio, Jerk Ratio, Golden Ratio and Trunk Displacement Index is representative of gait stability and harmony, and which of these are more sensitive to the variations between OFF and ON condition. We found that all indices, except the Jerk Ratio, significantly improve after levodopa. Only the improvement of the Trunk Displacement Index showed a direct correlation with the motor improvement measured through the clinical scale UPDRS-III (Unified Parkinson's Disease Rating Scale-part III). In conclusion, we suggest that the synthetic indices can be useful to detect motor changes induced by, but not all of them clearly correlate with the clinical changes achieved with the levodopa administration. In our analysis, only the Trunk Displacement Index was able to show a clear relationship with the PD clinical motor improvement.
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Affiliation(s)
- Emahnuel Troisi Lopez
- Department of Motor Sciences and Wellness, University of Naples “Parthenope”, Naples, Italy
| | - Roberta Minino
- Department of Motor Sciences and Wellness, University of Naples “Parthenope”, Naples, Italy
| | - Pierpaolo Sorrentino
- Institut de Neuroscience des Systemès, Aix-Marseille University, Marseille, France
- Institute of Applied Sciences and Intelligent Systems, CNR, Pozzuoli (NA), Italy
| | - Valentino Manzo
- Alzheimer Unit and Movement Disorders Clinic, Department of Neurology, Cardarelli Hospital, Naples, Italy
| | - Domenico Tafuri
- Department of Motor Sciences and Wellness, University of Naples “Parthenope”, Naples, Italy
| | - Giuseppe Sorrentino
- Department of Motor Sciences and Wellness, University of Naples “Parthenope”, Naples, Italy
- Institute of Applied Sciences and Intelligent Systems, CNR, Pozzuoli (NA), Italy
- Institute for Diagnosis and Care, Hermitage Capodimonte, Naples, Italy
| | - Marianna Liparoti
- Department of Motor Sciences and Wellness, University of Naples “Parthenope”, Naples, Italy
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31
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Body-Worn IMU-Based Human Hip and Knee Kinematics Estimation during Treadmill Walking. SENSORS 2022; 22:s22072544. [PMID: 35408159 PMCID: PMC9003309 DOI: 10.3390/s22072544] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Revised: 03/14/2022] [Accepted: 03/16/2022] [Indexed: 12/22/2022]
Abstract
Traditionally, inertial measurement unit (IMU)-based human joint angle estimation techniques are evaluated for general human motion where human joints explore all of their degrees of freedom. Pure human walking, in contrast, limits the motion of human joints and may lead to unobservability conditions that confound magnetometer-free IMU-based methods. This work explores the unobservability conditions emergent during human walking and expands upon a previous IMU-based method for the human knee to also estimate human hip angles relative to an assumed vertical datum. The proposed method is evaluated (N=12) in a human subject study and compared against an optical motion capture system. Accuracy of human knee flexion/extension angle (7.87∘ absolute root mean square error (RMSE)), hip flexion/extension angle (3.70∘ relative RMSE), and hip abduction/adduction angle (4.56∘ relative RMSE) during walking are similar to current state-of-the-art self-calibrating IMU methods that use magnetometers. Larger errors of hip internal/external rotation angle (6.27∘ relative RMSE) are driven by IMU heading drift characteristic of magnetometer-free approaches and non-hinge kinematics of the hip during gait, amongst other error sources. One of these sources of error, soft tissue perturbations during gait, is explored further in the context of knee angle estimation and it was observed that the IMU method may overestimate the angle during stance and underestimate the angle during swing. The presented method and results provide a novel combination of observability considerations, heuristic correction methods, and validation techniques to magnetic-blind, kinematic-only IMU-based skeletal pose estimation during human tasks with degenerate kinematics (e.g., straight line walking).
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Abstract
This work regards the representation of handicrafts for craft training and demonstration in the environment of an ethnographic heritage museum. The craft of mastic cultivation is chosen as a use case. This paper presents the process of representation and presentation of this craft, following an articulated pipeline approach for data collection, annotation, and semantic representation. The outcomes were used to implement an exhibition that targets the presentation of craft context and craft training, through interactive experiences, mobile applications, and a hands-on training where users reenact the gestures of a mastic cultivator. Preliminary evaluation results show high acceptance for the installation and increased user interest.
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Guayacán LC, Manzanera A, Martínez F. Quantification of Parkinsonian Kinematic Patterns in Body-Segment Regions During Locomotion. J Med Biol Eng 2022. [DOI: 10.1007/s40846-022-00691-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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Viswakumar A, Rajagopalan V, Ray T, Gottipati P, Parimi C. Development of a Robust, Simple, and Affordable Human Gait Analysis System Using Bottom-Up Pose Estimation With a Smartphone Camera. Front Physiol 2022; 12:784865. [PMID: 35069246 PMCID: PMC8766671 DOI: 10.3389/fphys.2021.784865] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 12/09/2021] [Indexed: 01/09/2023] Open
Abstract
Gait analysis is used in many fields such as Medical Diagnostics, Osteopathic medicine, Comparative and Sports-related biomechanics, etc. The most commonly used system for capturing gait is the advanced video camera-based passive marker system such as VICON. However, such systems are expensive, and reflective markers on subjects can be intrusive and time-consuming. Moreover, the setup of markers for certain rehabilitation patients, such as people with stroke or spinal cord injuries, could be difficult. Recently, some markerless systems were introduced to overcome the challenges of marker-based systems. However, current markerless systems have low accuracy and pose other challenges in gait analysis with people in long clothing, hiding the gait kinematics. The present work attempts to make an affordable, easy-to-use, accurate gait analysis system while addressing all the mentioned issues. The system in this study uses images from a video taken with a smartphone camera (800 × 600 pixels at an average rate of 30 frames per second). The system uses OpenPose, a 2D real-time multi-person keypoint detection technique. The system learns to associate body parts with individuals in the image using Convolutional Neural Networks (CNNs). This bottom-up system achieves high accuracy and real-time performance, regardless of the number of people in the image. The proposed system is called the “OpenPose based Markerless Gait Analysis System” (OMGait). Ankle, knee, and hip flexion/extension angle values were measured using OMGait in 16 healthy volunteers under different lighting and clothing conditions. The measured kinematic values were compared with a standard video camera based normative dataset and data from a markerless MS Kinect system. The mean absolute error value of the joint angles from the proposed system was less than 90 for different lighting conditions and less than 110 for different clothing conditions compared to the normative dataset. The proposed system is adequate in measuring the kinematic values of the ankle, knee, and hip. It also performs better than the markerless systems like MS Kinect that fail to measure the kinematics of ankle, knee, and hip joints under dark and bright light conditions and in subjects with long robe clothing.
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Affiliation(s)
- Aditya Viswakumar
- Department of Electrical and Electronics Engineering, Birla Institute of Technology and Science Pilani, Hyderabad, India
| | - Venkateswaran Rajagopalan
- Department of Electrical and Electronics Engineering, Birla Institute of Technology and Science Pilani, Hyderabad, India
| | - Tathagata Ray
- Department of Computer Science and Information Systems, Birla Institute of Technology and Science Pilani, Hyderabad, India
| | | | - Chandu Parimi
- Department of Civil Engineering, Birla Institute of Technology and Science Pilani, Hyderabad, India
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Armitano-Lago C, Willoughby D, Kiefer AW. A SWOT Analysis of Portable and Low-Cost Markerless Motion Capture Systems to Assess Lower-Limb Musculoskeletal Kinematics in Sport. Front Sports Act Living 2022; 3:809898. [PMID: 35146425 PMCID: PMC8821890 DOI: 10.3389/fspor.2021.809898] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Accepted: 12/24/2021] [Indexed: 01/06/2023] Open
Abstract
Markerless motion capture systems are promising for the assessment of movement in more real world research and clinical settings. While the technology has come a long way in the last 20 years, it is important for researchers and clinicians to understand the capacities and considerations for implementing these types of systems. The current review provides a SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis related to the successful adoption of markerless motion capture technology for the assessment of lower-limb musculoskeletal kinematics in sport medicine and performance settings. 31 articles met the a priori inclusion criteria of this analysis. Findings from the analysis indicate that the improving accuracy of these systems via the refinement of machine learning algorithms, combined with their cost efficacy and the enhanced ecological validity outweighs the current weaknesses and threats. Further, the analysis makes clear that there is a need for multidisciplinary collaboration between sport scientists and computer vision scientists to develop accurate clinical and research applications that are specific to sport. While work remains to be done for broad application, markerless motion capture technology is currently on a positive trajectory and the data from this analysis provide an efficient roadmap toward widespread adoption.
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Affiliation(s)
- Cortney Armitano-Lago
- Department of Exercise and Sport Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Dominic Willoughby
- Department of Exercise Science, Elon University, Elon, NC, United States
| | - Adam W. Kiefer
- Department of Exercise and Sport Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
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Abstract
Traditional crafts exhibit tangible and intangible dimensions. Intangible dimensions include the practitioner’s gestural know-how in craft practice and have received smaller attention than tangible dimensions in digitization projects. This work presents the process of representation and presentation of the glasswork and is exemplified in the re-creation of a historical object. Following an articulated pipeline approach for data collection, annotation, the crafting process is represented visually and semantically in a way that can be meaningfully presented and utilized in craft training and preservation. The outcomes of the proposed approach were used to implement a Mixed Reality installation. The installation targets craft presentation through an exploration of the workspace, as well as craft training through an interactive experience where users re-enact gestures of a glass master holding a tool and receiving audiovisual feedback on the accuracy of their performance. Preliminary evaluation results show high acceptance of the installation and increased user interest.
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37
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Concurrent validation of inertial sensors for measurement of knee kinematics in individuals with knee osteoarthritis: A technical report. HEALTH AND TECHNOLOGY 2021. [DOI: 10.1007/s12553-021-00616-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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38
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Guayacán LC, Martínez F. Visualising and quantifying relevant parkinsonian gait patterns using 3D convolutional network. J Biomed Inform 2021; 123:103935. [PMID: 34699990 DOI: 10.1016/j.jbi.2021.103935] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Revised: 10/05/2021] [Accepted: 10/10/2021] [Indexed: 10/20/2022]
Abstract
Parkinson's disease (PD) lacks a definitive diagnosis, with the observation of motion patterns being the main method of characterizing disease progression and planning patient treatments. Among PD observations, gait motion patterns, such as step length, flexed posture, and bradykinesia, support the characterization of disease progression. However, this analysis is usually performed with marker-based protocols, which affect the gait and localized segment patterns during locomotion. This work introduces a 3D convolutional gait representation for automatic PD classification that identifies the spatio-temporal patterns used for classification. This approach allows us to obtain an explainable model that classifies markerless sequences and describes the main learned spatio-temporal regions associated with abnormal patterns in a particular video. Initially, a spatio-temporal convolutional network is trained from a set of raw videos and optical flow fields. Then, a PD prediction is obtained from the motion patterns learned by the trained model. Finally, saliency maps, which highlight abnormal motion patterns, are obtained by retro-propagating the output prediction up to the input volume through two different stages: an embedded back-tracking and a pseudo-deconvolution process. From a total of 176 videos from 22 patients, the resulting salient maps highlight lower limb patterns possibly related to step length and speed. In control subjects, the saliency maps highlight the head and trunk posture. The proposed approach achieved an average accuracy score of 94.89%.
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Affiliation(s)
- Luis C Guayacán
- Biomedical Imaging, Vision and Learning Laboratory (BivL2ab), Universidad Industrial de Santander, Bucaramanga (UIS), Colombia
| | - Fabio Martínez
- Biomedical Imaging, Vision and Learning Laboratory (BivL2ab), Universidad Industrial de Santander, Bucaramanga (UIS), Colombia.
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Evaluation of a multi-sensor Leap Motion setup for biomechanical motion capture of the hand. J Biomech 2021; 127:110713. [PMID: 34474208 DOI: 10.1016/j.jbiomech.2021.110713] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2020] [Revised: 06/21/2021] [Accepted: 08/23/2021] [Indexed: 01/09/2023]
Abstract
The Leap Motion controller (LMC) offers a low-cost means of markerless hand tracking, however, its utility is limited by a small field of view and reliance on appropriate sensor positioning. A recent update from Leap Motion has enabled the use of a multiple LMC device on a single computer, allowing the tracking of hands from multiple orientations, potentially overcoming the aforementioned limitations. This study describes a method of implementing a multi-LMC setup and evaluates its effect on the validity and reliability of the derived kinematics. This study implemented a Kabsch algorithm and Kalman filter to re-orientate and fuse the trajectories captured by three LMC at different orientations. Reliability was assessed by comparing between-day differences in maximum joint angles (ΔMJA) and a calculated coefficient of multiple correlations (CMC). Validity was assessed by comparing the LMC to the gold standard, a Vicon markered motion capture (MMC) system, and calculating the ΔMJA and applying the linear fit method. The proposed method was evaluated by comparing the reliability and validity of the single-LMC setups to the multi-LMC setup. A multi-LMC setup proved successful in improving the reliability and validity of kinematic data, most notably where reliability and validity were poor and variation was high between the single-LMC setups. Findings suggest that through implementing the proposed method, limitations associated with single-LMC setups, notably its reliance on optimal sensor positioning, can be overcome.
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Pagnon D, Domalain M, Reveret L. Pose2Sim: An End-to-End Workflow for 3D Markerless Sports Kinematics-Part 1: Robustness. SENSORS (BASEL, SWITZERLAND) 2021; 21:6530. [PMID: 34640862 PMCID: PMC8512754 DOI: 10.3390/s21196530] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Revised: 09/20/2021] [Accepted: 09/21/2021] [Indexed: 11/16/2022]
Abstract
Being able to capture relevant information about elite athletes' movement "in the wild" is challenging, especially because reference marker-based approaches hinder natural movement and are highly sensitive to environmental conditions. We propose Pose2Sim, a markerless kinematics workflow that uses OpenPose 2D pose detections from multiple views as inputs, identifies the person of interest, robustly triangulates joint coordinates from calibrated cameras, and feeds those to a 3D inverse kinematic full-body OpenSim model in order to compute biomechanically congruent joint angles. We assessed the robustness of this workflow when facing simulated challenging conditions: (Im) degrades image quality (11-pixel Gaussian blur and 0.5 gamma compression); (4c) uses few cameras (4 vs. 8); and (Cal) introduces calibration errors (1 cm vs. perfect calibration). Three physical activities were investigated: walking, running, and cycling. When averaged over all joint angles, stride-to-stride standard deviations lay between 1.7° and 3.2° for all conditions and tasks, and mean absolute errors (compared to the reference condition-Ref) ranged between 0.35° and 1.6°. For walking, errors in the sagittal plane were: 1.5°, 0.90°, 0.19° for (Im), (4c), and (Cal), respectively. In conclusion, Pose2Sim provides a simple and robust markerless kinematics analysis from a network of calibrated cameras.
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Affiliation(s)
- David Pagnon
- Laboratoire Jean Kuntzmann, Université Grenoble Alpes, UMR CNRS 5224, 38330 Montbonnot-Saint-Martin, France;
| | - Mathieu Domalain
- Institut Pprime, Université de Poitiers, CNRS UPR 3346, 86360 Chasseneuil-du-Poitou, France;
| | - Lionel Reveret
- Laboratoire Jean Kuntzmann, Université Grenoble Alpes, UMR CNRS 5224, 38330 Montbonnot-Saint-Martin, France;
- INRIA Grenoble Rhône-Alpes, 38330 Montbonnot-Saint-Martin, France
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Dai C, Lyu X, Meng F, He J, Huang Q, Fukuda T. Development of a novel motion capture and gait analysis system for rat locomotion. Adv Robot 2021. [DOI: 10.1080/01691864.2021.1957013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Affiliation(s)
- Chuankai Dai
- Beijing Institute of Technology, Beijing, People's Republic of China
- Beijing Advanced Innovation Center for Intelligent Robots and Systems, Beijing, People's Republic of China
| | - Xiaodong Lyu
- Beijing Institute of Technology, Beijing, People's Republic of China
- Beijing Advanced Innovation Center for Intelligent Robots and Systems, Beijing, People's Republic of China
| | - Fei Meng
- Beijing Institute of Technology, Beijing, People's Republic of China
- Beijing Advanced Innovation Center for Intelligent Robots and Systems, Beijing, People's Republic of China
| | - Jiping He
- Beijing Institute of Technology, Beijing, People's Republic of China
- Beijing Advanced Innovation Center for Intelligent Robots and Systems, Beijing, People's Republic of China
| | - Qiang Huang
- Beijing Institute of Technology, Beijing, People's Republic of China
- Beijing Advanced Innovation Center for Intelligent Robots and Systems, Beijing, People's Republic of China
| | - Toshio Fukuda
- Beijing Institute of Technology, Beijing, People's Republic of China
- Beijing Advanced Innovation Center for Intelligent Robots and Systems, Beijing, People's Republic of China
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Instrumental Validity of the Motion Detection Accuracy of a Smartphone-Based Training Game. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph18168410. [PMID: 34444160 PMCID: PMC8394475 DOI: 10.3390/ijerph18168410] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Revised: 08/01/2021] [Accepted: 08/04/2021] [Indexed: 12/02/2022]
Abstract
Demographic changes associated with an expanding and aging population will lead to an increasing number of orthopedic surgeries, such as joint replacements. To support patients’ home exercise programs after total hip replacement and completing subsequent inpatient rehabilitation, a low-cost, smartphone-based augmented reality training game (TG) was developed. To evaluate its motion detection accuracy, data from 30 healthy participants were recorded while using the TG. A 3D motion analysis system served as reference. The TG showed differences of 18.03 mm to 24.98 mm along the anatomical axes. Surveying the main movement direction of the implemented exercises (squats, step-ups, side-steps), differences between 10.13 mm to 24.59 mm were measured. In summary, the accuracy of the TG’s motion detection is sufficient for use in exergames and to quantify progress in patients’ performance. Considering the findings of this study, the presented exer-game approach has potential as a low-cost, easily accessible support for patients in their home exercise program.
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Roggio F, Ravalli S, Maugeri G, Bianco A, Palma A, Di Rosa M, Musumeci G. Technological advancements in the analysis of human motion and posture management through digital devices. World J Orthop 2021; 12:467-484. [PMID: 34354935 PMCID: PMC8316840 DOI: 10.5312/wjo.v12.i7.467] [Citation(s) in RCA: 45] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Revised: 04/15/2021] [Accepted: 07/12/2021] [Indexed: 02/06/2023] Open
Abstract
Technological development of motion and posture analyses is rapidly progressing, especially in rehabilitation settings and sport biomechanics. Consequently, clear discrimination among different measurement systems is required to diversify their use as needed. This review aims to resume the currently used motion and posture analysis systems, clarify and suggest the appropriate approaches suitable for specific cases or contexts. The currently gold standard systems of motion analysis, widely used in clinical settings, present several limitations related to marker placement or long procedure time. Fully automated and markerless systems are overcoming these drawbacks for conducting biomechanical studies, especially outside laboratories. Similarly, new posture analysis techniques are emerging, often driven by the need for fast and non-invasive methods to obtain high-precision results. These new technologies have also become effective for children or adolescents with non-specific back pain and postural insufficiencies. The evolutions of these methods aim to standardize measurements and provide manageable tools in clinical practice for the early diagnosis of musculoskeletal pathologies and to monitor daily improvements of each patient. Herein, these devices and their uses are described, providing researchers, clinicians, orthopedics, physical therapists, and sports coaches an effective guide to use new technologies in their practice as instruments of diagnosis, therapy, and prevention.
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Affiliation(s)
- Federico Roggio
- Department of Psychology, Educational Science and Human Movement, University of Palermo, Palermo 90144, Italy
| | - Silvia Ravalli
- Department of Biomedical and Biotechnological Sciences, Human Anatomy and Histology Section, School of Medicine, University of Catania, Catania 95123, Italy
| | - Grazia Maugeri
- Department of Biomedical and Biotechnological Sciences, Human Anatomy and Histology Section, School of Medicine, University of Catania, Catania 95123, Italy
| | - Antonino Bianco
- Department of Psychology, Educational Science and Human Movement, University of Palermo, Palermo 90144, Italy
| | - Antonio Palma
- Department of Psychology, Educational Science and Human Movement, University of Palermo, Palermo 90144, Italy
| | - Michelino Di Rosa
- Department of Biomedical and Biotechnological Sciences, Human Anatomy and Histology Section, School of Medicine, University of Catania, Catania 95123, Italy
| | - Giuseppe Musumeci
- Department of Biomedical and Biotechnological Sciences, Human Anatomy and Histology Section, School of Medicine, University of Catania, Catania 95123, Italy
- Research Center on Motor Activities, University of Catania, Catania 95123, Italy
- Department of Biology, College of Science and Technology, Temple University, Philadelphia, PA 19122, United States
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Feasibility and Reliability Assessment of Video-Based Motion Analysis and Surface Electromyography in Children with Fragile X during Gait. SENSORS 2021; 21:s21144746. [PMID: 34300485 PMCID: PMC8309640 DOI: 10.3390/s21144746] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Revised: 07/02/2021] [Accepted: 07/06/2021] [Indexed: 01/23/2023]
Abstract
Fragile X Syndrome (FXS), the leading form of inherited intellectual disability and autism, is characterized by specific musculoskeletal conditions. We hypothesized that gait analysis in FXS could be relevant for the evaluation of motor control of gait, and help the understanding of a possible correlation between functional and intellectual abilities. Typical deficits in executive control and hyperactivity have hampered the use of standard gait analysis. The aim of our study was to quantitatively assess musculoskeletal alterations in FXS children in standard ambulatory conditions, in a friendly environment. Ten FXS children and sixteen controls, with typical neurodevelopment, were evaluated through four synchronized video cameras and surface electromyography; lower limb joints rotations, spatiotemporal parameters, duration of muscle contraction, activation timing and envelope peaks were determined. Reliability and repeatability of the video based kinematics analysis was assessed with respect to stereophotogrammetry. The Kruskal–Wallis Test (p < 0.05) or SPM1D were used to compare different groups of subjects. Results show a consistently altered gait pattern associated with abnormal muscle activity in FXS subjects: reduced knee and excessive hip and ankle flexion, and altered duration and activity onset on all the recorded muscles (Rectus/Biceps Femoris, Tibialis Anterior, Gastrocnemius Lateralis). Results of this study could help with planning personalized rehabilitations.
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Sonnenfeld JJ, Crutchfield CR, Swindell HW, Schwarz WJ, Trofa DP, Ahmad CS, Lynch TS. An Analysis of In Vivo Hip Kinematics in Elite Baseball Batters Using a Markerless Motion-Capture System. Arthrosc Sports Med Rehabil 2021; 3:e909-e917. [PMID: 34195661 PMCID: PMC8220628 DOI: 10.1016/j.asmr.2021.03.006] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Accepted: 03/10/2021] [Indexed: 12/05/2022] Open
Abstract
Purpose The aim of this study was to investigate the kinematics of the asymptomatic baseball batter’s hips by comparing passive range of motion (PROM) and real-time active hip range of motion (AROM) and determine whether differences in ROM exist between lead and trail hips. Methods Parameters of passive hip ROM were obtained using a goniometer and physical examination standards. Active hip ROM during batting swings was captured with the Dynamic Athletic Research Institute’s markerless motion-capture system. Results Twenty-nine elite-level baseball players were recruited for participation. Comparison of lead and trail hips showed no significant differences in PROM. Statistically significant differences in AROM were found between lead and trail legs with large effect sizes for flexion (mean difference [MD°], 11.22), extension (MD°, 30.30), abduction (MD°, 6.24), adduction (MD°, 18.63), external rotation (MD°, 14.87) and total arc of rotation (MD°, 17.17) (P < .001 for all). External rotation in the lead hip approached maximum passive endpoint during early phases of the swing, whereas trail hip extension reached maximum passive endpoint during follow-through. Conclusion There is a significant difference in the AROM of the lead and trail hips during the batting swing, with active extension in the trail hip, active external rotation of the lead hip, and total arc of rotation of the lead hip nearing their respective passive endpoints and suggesting a potential for bony interaction in the hips of baseball batters. Level of Evidence Level 3, Cross-Sectional Study.
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Affiliation(s)
| | | | | | - William J Schwarz
- The Schwarz Institute for Physical Therapy & Sports Performance, Massapequa, New York, U.S.A
| | - David P Trofa
- Columbia University Irving Medical Center, New York, New York
| | | | - T Sean Lynch
- Columbia University Irving Medical Center, New York, New York
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Evaluating the Accuracy of Virtual Reality Trackers for Computing Spatiotemporal Gait Parameters. SENSORS 2021; 21:s21103325. [PMID: 34064807 PMCID: PMC8151659 DOI: 10.3390/s21103325] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 04/23/2021] [Accepted: 05/08/2021] [Indexed: 11/17/2022]
Abstract
Ageing, disease, and injuries result in movement defects that affect daily life. Gait analysis is a vital tool for understanding and evaluating these movement dysfunctions. In recent years, the use of virtual reality (VR) to observe motion and offer augmented clinical care has increased. Although VR-based methodologies have shown benefits in improving gait functions, their validity against more traditional methods (e.g., cameras or instrumented walkways) is yet to be established. In this work, we propose a procedure aimed at testing the accuracy and viability of a VIVE Virtual Reality system for gait analysis. Seven young healthy subjects were asked to walk along an instrumented walkway while wearing VR trackers. Heel strike (HS) and toe off (TO) events were assessed using the VIVE system and the instrumented walkway, along with stride length (SL), stride time (ST), stride width (SW), stride velocity (SV), and stance/swing percentage (STC, SWC%). Results from the VR were compared with the instrumented walkway in terms of detection offset for time events and root mean square error (RMSE) for gait features. An absolute offset between VR- and walkway-based data of (15.3 ± 12.8) ms for HS, (17.6 ± 14.8) ms for TOs and an RMSE of 2.6 cm for SW, 2.0 cm for SL, 17.4 ms for ST, 2.2 m/s for SV, and 2.1% for stance and swing percentage were obtained. Our findings show VR-based systems can accurately monitor gait while also offering new perspectives for VR augmented analysis.
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Sikandar T, Rabbi MF, Ghazali KH, Altwijri O, Alqahtani M, Almijalli M, Altayyar S, Ahamed NU. Using a Deep Learning Method and Data from Two-Dimensional (2D) Marker-Less Video-Based Images for Walking Speed Classification. SENSORS 2021; 21:s21082836. [PMID: 33920617 PMCID: PMC8072769 DOI: 10.3390/s21082836] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Revised: 04/10/2021] [Accepted: 04/13/2021] [Indexed: 01/09/2023]
Abstract
Human body measurement data related to walking can characterize functional movement and thereby become an important tool for health assessment. Single-camera-captured two-dimensional (2D) image sequences of marker-less walking individuals might be a simple approach for estimating human body measurement data which could be used in walking speed-related health assessment. Conventional body measurement data of 2D images are dependent on body-worn garments (used as segmental markers) and are susceptible to changes in the distance between the participant and camera in indoor and outdoor settings. In this study, we propose five ratio-based body measurement data that can be extracted from 2D images and can be used to classify three walking speeds (i.e., slow, normal, and fast) using a deep learning-based bidirectional long short-term memory classification model. The results showed that average classification accuracies of 88.08% and 79.18% could be achieved in indoor and outdoor environments, respectively. Additionally, the proposed ratio-based body measurement data are independent of body-worn garments and not susceptible to changes in the distance between the walking individual and camera. As a simple but efficient technique, the proposed walking speed classification has great potential to be employed in clinics and aged care homes.
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Affiliation(s)
- Tasriva Sikandar
- Faculty of Electrical and Electronics Engineering, Universiti Malaysia Pahang, Pekan 26600, Malaysia; (T.S.); (K.H.G.)
| | - Mohammad F. Rabbi
- School of Allied Health Sciences, Griffith University, Gold Coast, QLD 4222, Australia;
| | - Kamarul H. Ghazali
- Faculty of Electrical and Electronics Engineering, Universiti Malaysia Pahang, Pekan 26600, Malaysia; (T.S.); (K.H.G.)
| | - Omar Altwijri
- Biomedical Technology Department, College of Applied Medical Sciences, King Saud University, Riyadh 11451, Saudi Arabia; (O.A.); (M.A.); (M.A.); (S.A.)
| | - Mahdi Alqahtani
- Biomedical Technology Department, College of Applied Medical Sciences, King Saud University, Riyadh 11451, Saudi Arabia; (O.A.); (M.A.); (M.A.); (S.A.)
| | - Mohammed Almijalli
- Biomedical Technology Department, College of Applied Medical Sciences, King Saud University, Riyadh 11451, Saudi Arabia; (O.A.); (M.A.); (M.A.); (S.A.)
| | - Saleh Altayyar
- Biomedical Technology Department, College of Applied Medical Sciences, King Saud University, Riyadh 11451, Saudi Arabia; (O.A.); (M.A.); (M.A.); (S.A.)
| | - Nizam U. Ahamed
- Neuromuscular Research Laboratory/Warrior Human Performance Research Center, Department of Sports Medicine and Nutrition, University of Pittsburgh, Pittsburgh, PA 15203, USA
- Correspondence:
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Dynamic Joint Motions in Occupational Environments as Indicators of Potential Musculoskeletal Injury Risk. J Appl Biomech 2021; 37:196-203. [PMID: 33690164 DOI: 10.1123/jab.2020-0213] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Revised: 10/29/2020] [Accepted: 11/25/2020] [Indexed: 11/18/2022]
Abstract
The objective of this study was to test the feasibility of using a pair of wearable inertial measurement unit (IMU) sensors to accurately capture dynamic joint motion data during simulated occupational conditions. Eleven subjects (5 males and 6 females) performed repetitive neck, low-back, and shoulder motions simulating low- and high-difficulty occupational tasks in a laboratory setting. Kinematics for each of the 3 joints were measured via IMU sensors in addition to a "gold standard" passive marker optical motion capture system. The IMU accuracy was benchmarked relative to the optical motion capture system, and IMU sensitivity to low- and high-difficulty tasks was evaluated. The accuracy of the IMU sensors was found to be very good on average, but significant positional drift was observed in some trials. In addition, IMU measurements were shown to be sensitive to differences in task difficulty in all 3 joints (P < .05). These results demonstrate the feasibility for using wearable IMU sensors to capture kinematic exposures as potential indicators of occupational injury risk. Velocities and accelerations demonstrate the most potential for developing risk metrics since they are sensitive to task difficulty and less sensitive to drift than rotational position measurements.
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A Lightweight Exoskeleton-Based Portable Gait Data Collection System. SENSORS 2021; 21:s21030781. [PMID: 33498956 PMCID: PMC7865931 DOI: 10.3390/s21030781] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Revised: 01/16/2021] [Accepted: 01/21/2021] [Indexed: 11/17/2022]
Abstract
For the controller of wearable lower-limb assistive devices, quantitative understanding of human locomotion serves as the basis for human motion intent recognition and joint-level motion control. Traditionally, the required gait data are obtained in gait research laboratories, utilizing marker-based optical motion capture systems. Despite the high accuracy of measurement, marker-based systems are largely limited to laboratory environments, making it nearly impossible to collect the desired gait data in real-world daily-living scenarios. To address this problem, the authors propose a novel exoskeleton-based gait data collection system, which provides the capability of conducting independent measurement of lower limb movement without the need for stationary instrumentation. The basis of the system is a lightweight exoskeleton with articulated knee and ankle joints. To minimize the interference to a wearer's natural lower-limb movement, a unique two-degrees-of-freedom joint design is incorporated, integrating a primary degree of freedom for joint motion measurement with a passive degree of freedom to allow natural joint movement and improve the comfort of use. In addition to the joint-embedded goniometers, the exoskeleton also features multiple positions for the mounting of inertia measurement units (IMUs) as well as foot-plate-embedded force sensing resistors to measure the foot plantar pressure. All sensor signals are routed to a microcontroller for data logging and storage. To validate the exoskeleton-provided joint angle measurement, a comparison study on three healthy participants was conducted, which involves locomotion experiments in various modes, including overground walking, treadmill walking, and sit-to-stand and stand-to-sit transitions. Joint angle trajectories measured with an eight-camera motion capture system served as the benchmark for comparison. Experimental results indicate that the exoskeleton-measured joint angle trajectories closely match those obtained through the optical motion capture system in all modes of locomotion (correlation coefficients of 0.97 and 0.96 for knee and ankle measurements, respectively), clearly demonstrating the accuracy and reliability of the proposed gait measurement system.
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A Deep Learning and Computer Vision Based Multi-Player Tracker for Squash. APPLIED SCIENCES-BASEL 2020. [DOI: 10.3390/app10248793] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Sports pose a unique challenge for high-speed, unobtrusive, uninterrupted motion tracking due to speed of movement and player occlusion, especially in the fast and competitive sport of squash. The objective of this study is to use video tracking techniques to quantify kinematics in elite-level squash. With the increasing availability and quality of elite tournament matches filmed for entertainment purposes, a new methodology of multi-player tracking for squash that only requires broadcast video as an input is proposed. This paper introduces and evaluates a markerless motion capture technique using an autonomous deep learning based human pose estimation algorithm and computer vision to detect and identify players. Inverse perspective mapping is utilized to convert pixel coordinates to court coordinates and distance traveled, court position, ‘T’ dominance, and average speeds of elite players in squash is determined. The method was validated using results from a previous study using manual tracking where the proposed method (filtered coordinates) displayed an average absolute percent error to the manual approach of 3.73% in total distance traveled, 3.52% and 1.26% in average speeds <9 m/s with and without speeds <1 m/s, respectively. The method has proven to be the most effective in collecting kinematic data of elite players in squash in a timely manner with no special camera setup and limited manual intervention.
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