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Cited by in F6Publishing
For: Sica M, Tedesco S, Crowe C, Kenny L, Moore K, Timmons S, Barton J, O'Flynn B, Komaris DS. Continuous home monitoring of Parkinson's disease using inertial sensors: A systematic review. PLoS One 2021;16:e0246528. [PMID: 33539481 DOI: 10.1371/journal.pone.0246528] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
Number Citing Articles
1 Khwaounjoo P, Singh G, Grenfell S, Özsoy B, MacAskill MR, Anderson TJ, Çakmak YO. Non-Contact Hand Movement Analysis for Optimal Configuration of Smart Sensors to Capture Parkinson's Disease Hand Tremor. Sensors (Basel) 2022;22:4613. [PMID: 35746395 DOI: 10.3390/s22124613] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
2 Zhang W, Chen J, Liu H. Network Pharmacology and Molecular Docking-Based Prediction of the Molecular Targets and Signaling Pathways of Ginseng in the Treatment of Parkinson's Disease. Natural Product Communications 2022;17:1934578X2211020. [DOI: 10.1177/1934578x221102029] [Reference Citation Analysis]
3 Giannakopoulou KM, Roussaki I, Demestichas K. Internet of Things Technologies and Machine Learning Methods for Parkinson's Disease Diagnosis, Monitoring and Management: A Systematic Review. Sensors (Basel) 2022;22:1799. [PMID: 35270944 DOI: 10.3390/s22051799] [Reference Citation Analysis]
4 Huang C, Zhang F, Xu Z, Wei J. The Diverse Gait Dataset: Gait Segmentation Using Inertial Sensors for Pedestrian Localization with Different Genders, Heights and Walking Speeds. Sensors (Basel) 2022;22:1678. [PMID: 35214579 DOI: 10.3390/s22041678] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
5 Komaris DS, Tarfali G, O'Flynn B, Tedesco S. Unsupervised IMU-based evaluation of at-home exercise programmes: a feasibility study. BMC Sports Sci Med Rehabil 2022;14:28. [PMID: 35183244 DOI: 10.1186/s13102-022-00417-1] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
6 Bendig J, Wolf AS, Mark T, Frank A, Mathiebe J, Scheibe M, Müller G, Stahr M, Schmitt J, Reichmann H, Loewenbrück KF, Falkenburger BH. Feasibility of a Multimodal Telemedical Intervention for Patients with Parkinson's Disease-A Pilot Study. J Clin Med 2022;11:1074. [PMID: 35207351 DOI: 10.3390/jcm11041074] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
7 Kenny L, Moore K, O' Riordan C, Fox S, Barton J, Tedesco S, Sica M, Crowe C, Alamäki A, Condell J, Nordström A, Timmons S. The Views and Needs of People With Parkinson Disease Regarding Wearable Devices for Disease Monitoring: Mixed Methods Exploration. JMIR Form Res 2022;6:e27418. [PMID: 34989693 DOI: 10.2196/27418] [Reference Citation Analysis]
8 Mughal H, Javed AR, Rizwan M, Almadhor AS, Kryvinska N. Parkinson’s Disease Management via Wearable Sensors: A Systematic Review. IEEE Access 2022;10:35219-37. [DOI: 10.1109/access.2022.3162844] [Cited by in Crossref: 4] [Cited by in F6Publishing: 2] [Article Influence: 4.0] [Reference Citation Analysis]
9 Soundararajan R, Prabu AV, Routray S, Malla PP, Ray AK, Palai G, Faragallah OS, Baz M, Abualnaja MM, Eid MMA, Rashed ANZ. Deeply Trained Real-Time Body Sensor Networks for Analyzing the Symptoms of Parkinson’s Disease. IEEE Access 2022;10:63403-21. [DOI: 10.1109/access.2022.3181985] [Reference Citation Analysis]
10 Habets JGV, Herff C, Kubben PL, Kuijf ML, Temel Y, Evers LJW, Bloem BR, Starr PA, Gilron R, Little S. Rapid Dynamic Naturalistic Monitoring of Bradykinesia in Parkinson's Disease Using a Wrist-Worn Accelerometer. Sensors (Basel) 2021;21:7876. [PMID: 34883886 DOI: 10.3390/s21237876] [Reference Citation Analysis]
11 Roth N, Küderle A, Prossel D, Gassner H, Eskofier BM, Kluge F. An Inertial Sensor-Based Gait Analysis Pipeline for the Assessment of Real-World Stair Ambulation Parameters. Sensors (Basel) 2021;21:6559. [PMID: 34640878 DOI: 10.3390/s21196559] [Reference Citation Analysis]
12 Roth N, Küderle A, Ullrich M, Gladow T, Marxreiter F, Klucken J, Eskofier BM, Kluge F. Hidden Markov Model based stride segmentation on unsupervised free-living gait data in Parkinson's disease patients. J Neuroeng Rehabil 2021;18:93. [PMID: 34082762 DOI: 10.1186/s12984-021-00883-7] [Cited by in F6Publishing: 4] [Reference Citation Analysis]