Heart rate (HR) analysis is of paramount importance in healthcare, particularly for monitoring cardiovascular health, a global concern. The advent of wearable sensors has enabled continuous HR monitoring, with researchers attempting to develop early detection systems by forecasting HR in a univariate fashion. This study analyzes real-world HR time series gathered during participants daily routines to critically assess the predictive power of past HR data in short-term, univariate forecasting. The literature emphasizes a minute-by-minute, univariate forecasting approach, where state-of-the-art predictive models predominantly employ autoregressive integrated moving average (ARIMA). Yet, its superiority has been proved without studying its optimized hyper-parameters, which could not only improve forecast accuracy but also provide valuable insights. By leveraging the interpretability of ARIMA, we tune its hyper-parameters within a minute-by-minute forecasting structure to address the central research question: how does historical HR data contribute to generate accurate short-term HR forecasts? Our analysis finds that the random walk model, a special case of ARIMA, consistently performs comparably to, or even better than, more complex ARIMA specifications. This indicates that HR values alone offer limited predictive power for short-term forecasting, casting doubt on the value of further refinement in univariate models for alarm system development. These findings highlight the limitations of univariate HR forecasting in real-time health monitoring. Rather than increasing model complexity, future research might benefit from exploring alternative approaches to improve early warning system capabilities in real-world settings.

The online version contains supplementary material available at 10.1007/s41666-025-00191-y.

New-onset postoperative atrial fibrillation (POAF) is the most common complication following cardiac surgery, associated with adverse outcomes. However, the predictive accuracy of existing models remains unsatisfactory, primarily due to insufficient utilization of electrocardiogram (ECG) data and limitations in model development methodologies. This study aims to develop an accurate prediction model for POAF by comprehensively analyzing the predictive power of various preoperative ECG features.

This study enrolled 92 cardiac surgery patients with no prior history of atrial fibrillation (AF). One-minute ECG segments, extracted from preoperative long-term ECG recordings, were analyzed for P-wave and short-term heart rate variability (HRV) characteristics. A total of 39 HRV indices and 9 P-wave indices were calculated as ECG features. Additionally, clinical baseline characteristics were incorporated into a multi-modal risk assessment model. Using various feature combinations, six machine learning classifiers were applied to assess the predictive efficacy of various models. Finally, an ensemble strategy was implemented to enhance the model's prediction performance for POAF.

Statistical analysis revealed significant differences (p < 0.05) in 15 ECG features between patients with POAF and those without, including RR interval unpredictability and the cardiac sympathetic index. The predictive model based solely on clinical baseline characteristics demonstrated high accuracy (78.26 %), sensitivity (78.57 %), and specificity (78.13 %), with superior sensitivity in identifying patients at high risk for POAF compared to existing models. Furthermore, the multi-modal model, which integrated preoperative ECG features and an ensemble machine learning (EML) strategy, demonstrated a significant improvement in prediction performance, with an average accuracy of 81.52 %, sensitivity of 82.14 %, and specificity of 81.25 %.

The integration of P-wave and short-term HRV features holds promise for improving the prediction of new-onset POAF. ECG-assisted analysis is a valuable tool for elucidating the underlying mechanisms of POAF and advancing clinical strategies for its prevention and management.

Nature-based interventions improve mood and reduce stress, but their effects on heart rate variability (HRV) remain inconsistent. The physiological adjustment effect theory proposes HRV adjusts to an optimal value during nature contact-increasing when baseline HRV is low and decreasing when high. This study tested this theory in patients with depressive and anxiety disorders and investigated its association with mood changes. A randomized crossover trial was conducted with 60 patients. We assessed the correlation between baseline HRV during control images and HRV change after 3 min natural image viewing. We also examined mood changes in comfort, relaxation, and vigor. A significant negative correlation was found between baseline low-frequency/high-frequency (LF/HF) ratio and changes after viewing natural images, indicating a physiological adjustment effect in sympathetic activity. No significant correlation was found with the parasympathetic indicator, HF. Participants with adjustment effects in LF/HF had greater improvement in vigor. Those without these effects had higher alcohol use and tended towards more comorbid hypertension. Natural interventions may enhance vigor through physiological adjustment in sympathetic activity. The lack of adjustment effects is linked to behaviors and conditions associated with autonomic dysfunction, highlighting the need for targeted therapies in depressive and anxiety disorders.

This study introduces a novel estimation methodology for identifying non-stationary physiological noise, specifically applied to complex biomedical signals such as heart rate variability (HRV) series. By treating physiological noise as a dynamical recursive realization of independent and identically distributed (IID) Gaussian random variables, we employ an information-theoretic quantifier, the Approximate Entropy, to estimate noise power through a sliding window process. Our method effectively identifies noise levels in synthetic time series with varying dynamical noise powers, demonstrating accuracy even with relatively short window lengths. We further exploit this approach on real cardiovascular variability recordings during different postural changes, namely, stand-up, slow tilt, and fast tilt. The results reveal significant time-resolved variations in physiological noise, functionally linked with changes in autonomic regulation due to postural shifts. Specifically, in the absolute sense, physiological noise in the cardiovascular system tends to increase in the first 60 s of upright position with respect to a supine resting state, directly following sympathetic dynamics and inversely following vagal dynamics. Then, over 60 s physiological noise tends to decrease with respect to the resting state, almost monotonically. Moreover, results corroborate earlier findings where elevated stochasticity in HRV series biases complexity assessment through entropy analysis. Our work highlights the method's robustness and potential to improve the understanding of physiological noise dynamics, with implications for more accurate cardiovascular signal analysis and potential clinical applications.

To use a multimodal approach to classify individuals with tinnitus from controls, and individuals with mild versus severe tinnitus.

We have previously shown feasibility of a non-invasive imaging technique called functional near-infrared spectroscopy (fNIRS) to detect tinnitus-related changes in cortical activity and classify individuals with tinnitus from controls, as well as individuals with mild versus severe tinnitus. In this study we have used a multimodal approach by recording heart rate, heart rate variability and skin conductance, in addition to fNIRS signals, from individuals with tinnitus and controls.

Twenty-seven participants with tinnitus and 21 controls were recruited.

Our findings show, addition of heart rate measures can improve accuracy of classifying tinnitus severity, in particular loudness as rated subjectively. The f1-score, a measure of classification accuracy, increased from 0.73 to 0.86 when using a support vector machine classifier for differentiating low versus high tinnitus loudness.

Subjective tinnitus is a condition that can only be described by the individual experiencing it, as there are currently no objective measures to determine tinnitus presence and severity, or assess the effectiveness of treatments. Objective measurement of tinnitus is a critical step in developing reliable treatments for this debilitating condition.

Heart rate variability (HRV) measures the variation in the time interval between successive heartbeats, reflecting the influence of the autonomic nervous system (ANS) on heart rate (HR) changes. This review provides an extensive overview of HRV measurement techniques, their applications, and their limitations in healthcare, exploring their potential for prognosis and condition assessment. A scoping review was conducted, gathering literature reviews on HRV spanning the past fifty years using PubMed, Scopus, and Web of Science databases. Our findings identified significant research gaps, including contradictions in the literature and the absence of standardized protocols for HRV measurements, which complicate the establishment of consistent baseline values. Additionally, the lack of protocols for pulse rate variability (PRV) in the context of advanced sensor technology hinders progress in HRV research. Despite these challenges, HRV remains significant in assessing cardiac autonomic function and its potential clinical applications. However, barriers such as device unfamiliarity, data accuracy concerns, and a lack of clinical trials limit its adoption. Further research is required to elucidate the relationship between abnormal HRV and health problems and to establish consistent baseline values for advancing HRV applications.

Traditional major cardiovascular disease (CVD) risk factors include dyslipidemia, hypertension, smoking, diabetes, and obesity. Tea is rich in various bioactive substances such as tea polyphenols, theaflavins, and tea polysaccharides. Due to the regulatory effects on multiple pathways and its anti-inflammatory and antioxidant properties, these active substances have shown significant efficacy in regulating dyslipidemia, hypertension, diabetes, obesity, and cardiac autonomic function. Additionally, tea possesses anti-inflammatory and antithrombotic properties, making it a promising dietary supplement for nutritional interventions in the primary and secondary prevention of CVDs. However, the complex composition of tea, although shown to have certain effects in vivo, does not fully elucidate the specific mechanisms of action. Moreover, the varying application methods across different studies lead to differences in intervention effects and dose-response relationships, sometimes resulting in contradictory findings. This article reviews the potential benefits, mechanisms of action, and application methods of tea for cardiovascular risk factors, elucidating its potential as a nutritional intervention.

In occupational medicine, monitoring individual stress-related physiological responses is an effective tool for minimizing health risks at the workplace. From an audiology perspective, this particularly concerns the effects of auditory stress, which leads to increased listening effort with subsequent hearing fatigue. A study was conducted to investigate whether cardio-respiratory responses can detect the effects of a multi-level combination of physical and auditory stressors. To investigate their measurability and determine whether an interaction exists, a selection of cardio-respiratory vital parameters such as heart rate, features in the time and frequency domain of the heart rate variability, breathing rate, respiratory minute volume, and the respiratory quotient were analyzed. The results showed a significant main effect of physical stress on all assessed parameters. Auditory stress demonstrated a significant impact on breathing frequency, root mean square of successive differences of interbeat intervals, and the power components of the low and high frequency bands of the heart rate variability. No interaction between auditory and physical stressors was observed across any of the examined parameters. From these results we conclude that physiological responses to different sources of stress can be recorded within selected vital parameters, independent of external stimuli such as ambient noise. In an occupational context, we see potential in tracking individual auditory stress by monitoring cardio-respiratory parameters, especially breathing patterns. By knowing the individual (auditory) stress level, conclusions could be drawn about the worker's ability to concentrate and further measures could be taken to combat safety risks in the work environment.

The transportation sector has the potential to enable a greener future if aligned with increasing mobility needs. Making public transport an attractive alternative to individual transportation requires real-world data to investigate reasons and indicators of positive and negative travel experiences. These experiences manifest not only in subjective evaluations but also in physiological reactions like cardiac activity. We present a geo-referenced dataset where participants wore electrocardiograms and reported real-time stress, satisfaction, events, and emotions while traveling by tram, train, and bus. An interactive experience map helps to visually explore the data, with benchmark analyses identifying significant stress hot spots and satisfaction cold spots during journeys. Events and emotions in these spots highlight positive and negative travel experiences in an ecologically valid setting. Data on age and self-identified gender provide insights into differences between user groups. Despite including only 44 participants, the dataset offers a valuable foundation for transportation researchers and mobility providers to combine qualitative and quantitative methods for identifying public transportation users' needs.

Early development of gross motor skills is foundational for the upcoming neurocognitive performance. Here, we studied whether at-home wearable measurements performed by the parents could be used to quantify and track infants' developing motor abilities.

Unsupervised at-home measurements of the infants' spontaneous activity were made repeatedly by the parents using a multisensor wearable suit (altogether 620 measurements from 134 infants at age 4-22 months). Machine learning-based algorithms were developed to detect the reaching of gross motor milestones (GMM), to measure times spent in key postures, and to track the overall motor development longitudinally. Parental questionnaires regarding GMMs were used for developing the algorithms, and the results were benchmarked with the interrater agreement levels established by World Health Organization (WHO). A total of 97 infants were used for the algorithm development and cross-validation, whereas an external validation was done using 37 infants from an independent recruitment in the same hospital.

The algorithms detected the reaching of GMMs very accurately (cross-validation: accuracy, 90.9%-95.5%; external validation, 92.4%-96.8%), which compares well with the human experts in the WHO reference study. The wearable-derived postural times showed strong correlation to parental assessments (ρ = .48-.81). Individual trajectories of motor maturation showed strong correlation to infants' age (ρ = .93).

These findings suggest that infants' gross motor skills can be quantified reliably and automatically from unsupervised at-home wearable recordings. Such methodology could be used in health care practice and in all developmental studies for gaining real-world quantitation and tracking of infants' motor abilities.

Cardiovascular disease (CVD) is a leading cause of death that is sexually dimorphic. This study used an ovine model to investigate whether maternal exposure to an environmental chemical (EC) mixture (biosolids) prior to and throughout pregnancy, affected offspring cardiovascular (CV) structure and function in adulthood. CV function of male and female offspring from ewes grazed on either conventionally fertilised (control, C) or biosolids-treated pasture (B) was assessed. Males exhibited higher blood pressure compared to females with no significant effect of EC exposure. Heart rate variability in females suggested reduced autonomic regulation in the B group. EC-exposed males, but not females, showed significantly increased left ventricular dimensions, end-diastolic and systolic volumes, and cardiac output. The findings indicate sexually dimorphic effects of maternal EC mixture exposure on adult CV structure and function. Further studies are needed to explore the mechanisms and long-term implications of prenatal exposure to ECs on CV health.

Heart rate variability (HRV) of 10 participants was assessed to evaluate the impact of exposure to first- and second-hand smoke from heat-not-burn (HnB) products and conventional cigarettes on cardiovascular health and the autonomic nervous system. The nicotine and cotinine concentrations in the urine of smokers and non-smokers exposed to this smoke were also measured. Nicotine levels in the urine of smokers exposed to HnB products and conventional cigarettes averaged 71.76 and 229.36 ng/ml, respectively. Short-term analyses of HRV in both time- and frequency-domain were performed. There were no significant differences in HRV indicators between both groups at baseline. However, decreases in SDNN, rMSSD, TINN, and pNN50 (%) were observed in smokers exposed to both first- and second-hand smoke from HnB products and conventional cigarettes. No significant trends were noted in non-smokers. The frequency-domain analysis revealed a decrease in low frequency components among smokers.

The final event in modern pentathlon, the laser run, determines the final ranking, and it is not known whether the athletes' heart rates (HRs) and success rates during the shooting in the laser run are affected by environmental conditions. Although heart rate (HR) affects shooting performance, exercise-induced muscle fatigue accompanying increased HR can affect shooting speed and accuracy. The aims of this research were (a) to compare the HRs of pentathletes before and after fatigue, (b) to compare the shooting performance of pentathletes in the field vs. laboratory environment, and (c) to compare the HRs of pentathletes during successful and unsuccessful shootings.

The HRs and shooting performances of the seven national team pentathletes were measured in two separate sessions under laboratory conditions (pre- and post-fatigue) and in the field (laser run event). Bruce protocol was used to create exercise-induced fatigue and the internal loads of the pentathletes were determined with the 10-point Borg scale. The first session consisted of pre- and post-fatigue shooting in the laboratory environment, and the second session consisted of shooting in the laser run event in the field environment. The pentathletes' HRs were monitored in all sessions.

The shooting accuracy of pentathletes in the laboratory is not affected by fatigue, although the HRs before and after the fatigue protocol differ significantly (p < .001). The unsuccessful shot count in the field was not significantly different between laps, and the HR decreased significantly towards the last successful shot in each lap (p < .001). Although shooting accuracy was not significantly different between the field and laboratory, the HRs in the field were significantly higher than those in the scenarios performed in the laboratory (p < .05).

The findings revealed that HR was significantly affected by different environmental conditions and fatigue, but this was not accompanied by shooting accuracy, and significantly higher HR was achieved in unsuccessful shots compared to successful shots. We recommend that pentathletes perform running-shooting training in different weather and field conditions before the competition to adapt to different environments, especially during the competition seasons, instead of shooting in a polygon or laboratory.

In a difficult environment like surgery with continuous exposure to stress, surgeon's health and well-being is affected. The heart rate variability (HRV) is a valid stress indicator. This study aims to provide descriptive data regarding stress during urological intervention using HRV.

This prospective, unicentric study, included urological interventions from June to December 2023. Surgeons were surveyed on general characteristic, and surgical skills level. Beat-by-beat heart rate (HR) recorded using POLAR A300® chest belt. HRV were analyzed in time (mean HR and the root mean square of successive differences [RMSSD]) and frequency (Fast Fourier transformation spectrum high frequency [FFT spectrum HF]) domain. Their baseline collected outside the operating room, 3 events during intervention examined: incision, closure, and adverse events. Visual stress and difficulty scale during intervention were completed. The differences between baseline and events were calculated.

A total of 171 urological interventions were included. Senior surgeons performed 54 (31.58%) and juniors 117 (68.42%). During interventions, seniors had significantly higher median difference of HR (incision: -11.92 [12.74] bpm versus -2.27 [10.99] bpm for juniors, P≤0.0001; closure: -10.73 [13.71] bpm, versus -4.18 [12.30] bpm for juniors, P=0.0005), lower HF (incision: 0.01 [0.07] hz, versus -0.006 [0.03] hz for juniors P≤0.0001; closure: 0.02 [0.06] hz, versus 0.00 [0.02] hz for juniors, P≤0.0001), and lower RMSSD (incision: -3.34 [13.09] ms for seniors versus -7.63 [10.57] ms for juniors, P=0.0098). No significant difference in RMSSD during closure (P=0.2049).

Study demonstrated the possibility to assess HRV in standard medical practice, senior surgeons experienced more physiological changes during interventions.

High heart rate variability (HRV) is increasingly recognized as an indicator of a healthy regulatory system, reflecting the dynamic balance between sympathetic (SNS) and parasympathetic (PSNS) nervous system activity. According to the neurovisceral integration model, this balance is managed by the central autonomic network (CAN), comprised of specific brain regions involved in emotional, attentional, and autonomic regulation. HRV thus reflects the performance of the cognitive, affective, and autonomic regulation system. Numerous studies support the relationship between HRV and the CAN, including research on HRV biofeedback training (HRVBF). Studies on the effectiveness of HRVBF for professions such as police officers have shown improvements in self-regulation, decision-making, and performance. However, few studies have specifically explored HRVBF's influence on HRV metrics in police officers, highlighting a need for further research. This study addresses this gap by randomly assigning 27 Icelandic police officers to intervention or wait-list control groups. The intervention group underwent a five-week HRVBF program, including group and individual training sessions. Results showed significant increases in HRV metrics for the intervention group, indicating improved autonomic function and stress resilience. Mental resilience increased significantly as measured by subjective measures of attentional control, mindful awareness, and reduced fatigue. These findings support the efficacy of HRVBF in enhancing HRV and mental resilience for police officers, suggesting its applicability and potential for integration into existing training programs.

Elite taekwondo (TKD) athletes require physical strength and mastery of complex techniques to excel in a highly competitive environment. This study aimed to investigate the effects of dry cupping posttraining on heart rate variability (HRV) and recovery in TKD athletes. Fourteen male TKD athletes participated in a crossover study and were randomly assigned to either a dry cupping (Group CUP) or a placebo group without cupping (Group PLA) after completing a standardized TKD-specific training program. A 28-day washout period was implemented between the two treatments to minimize potential carryover effects. HRV and rated perceived exertion (RPE) were evaluated at three-time points: before training (Pre), immediately after training (Post), and 30 min after rest or dry cupping (Post30) in both groups. The results indicated that heart rate (HR) at Post and Post30 was significantly higher than at Pre in both groups. Low frequency (LF) and the LF/high frequency (HF) ratio at Post were significantly elevated compared to Pre in both groups. However, at Post30, these values remained significantly higher in Group PLA but not in Group CUP. HF at Post was significantly reduced compared to Pre in both groups, but at Post30, this reduction persisted only in Group PLA and not in Group CUP. Significant differences in the levels of LF, HF, and the LF/HF ratio were observed between Group PLA and Group CUP at Post30. The CUP group also showed significantly lower RPE compared to the PLA group at Post30. In conclusion, dry cupping treatment after TKD training significantly improved HRV parameters and reduced perceived fatigue, suggesting its potential as an effective method for enhancing recovery in TKD athletes.

Piloting an aircraft is a complex multitasking activity that involves managing information in a nonautomatic way and generates a high workload (psychological, cognitive, and physical) for the pilot. The excess of these demands can result in decreased performance and may impair flight safety. Heart rate variability (HRV) has been used in recent studies as a method to investigate operator's workload in complex environments. This measure can assess the stress and recovery ability of the autonomic nervous system. However, a better understanding of flight influence on the pilot's autonomic modulation is necessary. Therefore, this scoping review aims to systematically map the studies related to changes in the autonomic modulation in military pilots during flight, in order to characterize their workload at different times and flight profiles.

A literature search was conducted using MEDLINE (by PubMed), SCOPUS, and LILACS databases. Recent records (2002-2022) that analyzed HRV in military pilots during flight were included. Meanwhile, studies in which piloting activity was not performed were excluded. The study was conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guideline extension for Scoping Reviews and the Updated Methodological Guidance for the Conduct of Scoping Reviews.

A total of 298 records were obtained, of which 19 were included in the scoping review. The studies analyzed flights performed in high- and low-performance aircrafts, helicopters, and flight simulators, using time domain, frequency domain, and nonlinear HRV indices. Real and simulated flights produced significant autonomic changes. Some flights elicited autonomic nervous system responses that persisted up to 5 h after landing. During real flight, the most sensitive indices for identifying variations in pilot workload were root mean square of successive differences between normal heartbeats, standard deviation of interbeat interval of normal sinus beat (SDNN), ratio of low-frequency to high-frequency power, and Poincaré plot standard deviation perpendicular to the line of identity (SD1), whereas the interbeat interval (RR), SDNN, SD1, and Poincaré plot standard deviation along the line of identity (SD2) were the most sensitive indices when comparing segments of simulated flight with different levels of difficulty.

This scoping review provided insight into the influence of flight on autonomic modulation in military pilots. Some key themes were highlighted: Increased sympathetic activity during flight, sensibility of different domains of HRV to flight demands, and autonomic changes during recovery time. Future research efforts may allow us to enhance the understanding of pilot's workload limits and to elucidate the optimal postflight recovery time.

Nocturnal blood pressure (BP) surge is a characteristic phenomenon in patients with obstructive sleep apnea (OSA) associated with sympathetic nerve overactivity. This study aimed to explore the relationship between the sleep-breathing events induced nocturnal BP surge and sympathetic nerve activity.

A total of 85 patients with moderate-to-serve OSA and 44 controls were included in the study between April 2022 and October 2023 based on the inclusion and exclusion criteria. Full-night BP and heart rate variability (HRV) were monitored continuously and synchronized with polysomnography (PSG). The average of nocturnal BPs was taken as the asleep BP and the average of the highest BPs induced by all sleep-breathing events as the asleep peak BP. Nocturnal short-term BP variability (BPV) was calculated as follows: event-related systolic BP elevation (ΔSBP) as the gap between the peak and the lowest value of post-apneic SBP, BP index as the number of ΔSBP ≥ 12 mm Hg within 30 s/h, and the percentage of BP fluctuation induced by sleep-breathing events (PBPF) as the ratio of BP index and apnea-hypopnea index. Patients with OSA were divided into two subgroups (high- and low-BP surge groups) according to the median PBPF. The sympathetic nerve activity was reflected by plasma norepinephrine (NE) level and HRV. The PSG and BP parameters were compared among three groups, and the correlation between nocturnal short-term BPV and sympathetic nerve activity was analyzed.

Patients with OSA were fatter and suffered from dyslipidemia and sympathetic nerve overactivity compared to controls. The high-BP surge group displayed higher sympathetic nerve activity and more severe hypoxia compared with the low-BP surge group. The Pearson correlation analysis showed a positive correlation of the higher nocturnal short-term BPV with increased sympathetic nerve activity (all P < 0.05). After excluding confounding factors, such as age, body mass index, and smoking history, the multiple linear regression revealed a positive correlation of the LF/HF (ratio of low-frequency to high-frequency power, indicating the activity of sympathetic nerve activity) with the BP index (β = 7.337, P < 0.001), ΔSBP (β = 2.797, P < 0.001), and PBPF (β = 9.036, P < 0.001). The plasma NE level also had a positive correlation with the BP index (β = 3.939, P = 0.022) and PBPF (β = 8.752, P < 0.001).

The sleep-breathing events induced nocturnal BP surge was positively correlated with sympathetic nerve activity in patients with moderate-to-serve OSA.

Affect dynamics, or variations in emotional experiences over time, are linked to psychological health and well-being, with moderate emotional variations indicating good psychophysical health. Given the impact of emotional state on cardiac variability, our objective was to develop a quantitative method to measure affect dynamics for better understanding emotion temporal management in Anorexia Nervosa (AN).

The study proposed an experimental and methodological approach to evaluate physiological affect dynamics in clinical settings. It tested affective transitions and temporal changes using emotional images from the International Affective Picture System (IAPS), examining physiological characteristics of a patient with AN. The methodology involved calculating a heart rate variability index, e.g., RMSSD, and using it in a Discrete Time and Discrete Space Markov chain to define, quantify, and predict emotional fluctuations over time.

The patient with Anorexia Nervosa showed a high likelihood of transitioning from positive to negative emotional states, particularly at lower arousal levels. The steady state matrix indicated a tendency to remain in highly activated pleasant states, reflecting difficulties in maintaining emotional balance.

Employing Markov chains provided a quantitative and insightful approach for examining affect dynamics in a patient with AN. This methodology accurately measures emotional transitions and provides a clear and interpretable framework for clinicians and patients. By leveraging Markovian indexes, mental health professionals may gain a comprehensive understanding of emotional fluctuations' patterns. Moreover, graphical representations of emotional transitions may enhance the clinician-patient dialogue, facilitating a clearer emotional and physiological profile for the implementation of personalized treatment procedures.

Long-term COVID-19 (LC), which may affect the autonomic nervous system (ANS), is the term for the symptoms that some patients had for an additional month after contracting the virus. Therefore, during the LC phase, ANS status was evaluated in patients with mild-to-moderate COVID-19 using heart rate variability (HRV), a measurement of ANS function.

A cross-sectional research with 173 participants - both positive and negative for COVID-19 - was conducted. Based on self-reports, patients with COVID-19 were classified as to whether they had LC or not. A 5-minute ECG recorder and data detection and response report were used to measure the ANS.

There were notable age differences across the groups (p = 0.034). Patients with LC under 25 years of age had a lower HRV categorized as a very-low-frequency (VLF) domain (p = 0.012). Compared to the group without LC, a higher number of people in the LC group had aberrant autonomic neuroactivity (p = 0.048).

Mild-to-moderate patients with COVID-19 in young to middle age may develop autonomic dysfunction one month after infection.

Hypertension (HPT) is a chronic disease characterized by the consistent elevation of arterial blood pressure, which is considered to be a significant risk factor for conditions such as stroke, coronary artery disease, and heart failure. The detection and continuous monitoring of HPT can be a demanding process. As a non-contact measuring method, the ballistocardiography (BCG) signal characterizes the repetitive body motion resulting from the forceful ejection of blood into the major blood vessels during each heartbeat. Therefore, it can be applied for HPT detection. HPT detection with BCG signals remains a challenging task. In this study, we propose an end-to-end deep convolutional model BH-Net for HPT detection through BCG signals. We also propose a data augmentation scheme by selecting the J-peak neighborhoods from the BCG time sequences for hypertension detection. Rigorously evaluated via a public data-set, we report an average accuracy of 97.93% and an average F1-score of 97.62%, outperforming the comparative state-of-the-art methods. We also report that the performance of the traditional machine learning methods and the comparative deep learning models was improved with the proposed data augmentation scheme.

Subacute sclerosing panencephalitis (SSPE) is a fatal neurological disorder resulting from persistent measles virus infection within the brain. Although neurological manifestations have been well-documented, the impact of SSPE on cardiac autonomic function, assessed through heart rate variability (HRV), remains understudied.

In this prospective single-center study conducted from January 2022 to March 2023 in Southern India, 30 consecutive SSPE patients and age- and sex-matched controls underwent electrocardiogram recordings for HRV analysis. Various HRV parameters were assessed, including time-domain metrics (SD of normal-to-normal intervals, root mean square of successive differences between normal heartbeats, percentage of successive normal interbeat intervals greater than 50 msec), SD1 and SD2 for Poincaré plot analysis, and frequency-domain metrics (low frequency %, high frequency %, low frequency:high frequency ratio).

In the study, SSPE patients exhibited markedly reduced HRV. Specifically, SD of normal-to-normal intervals ( P = 0.003), percentage of successive normal interbeat intervals greater than 50 msec ( P = 0.03), and SD2 ( P = 0.0016) were significantly lower compared with controls. Frequency-domain analysis did not reveal significant distinctions. Correlation analysis demonstrated a negative relationship between percentage of successive normal interbeat intervals greater than 50 msec and SSPE severity ( r = -0.37, P = 0.042). Heart rate variability did not significantly differ between SSPE stages or with clinical variables. The interbeat interval range showed a narrower distribution in SSPE subjects.

Our study highlights the clinical relevance of HRV analysis in SSPE and autonomic dysfunction throughout the disease course underscoring its importance in SSPE. This investigation provides valuable insights into cardiac autonomic dysfunction probably because of affliction of the central autonomic networks caused by the disease process and may be a contributing factor to mortality in SSPE.

Heart Rate Variability (HRV) originates from the interplay between parasympathetic/sympathetic inputs to the heart, thus serving as an indicator of Autonomic Nervous System regulation. Prior research indicates that decreased HRV, marked by reduced autonomic balance, is related to poorer cognitive performance. While the population with congenital heart disease (CHD) show changes in HRV linked with the heart defect, the association between HRV and cognitive functions in CHD remains unexplored.

46 adolescents with CHD who went through infant open-heart surgery and 64 healthy controls (50.9% males, 12.8 ± 1.4 years) underwent neurodevelopmental testing and photoplethysmograph acquisition. Group differences and associations with cognitive functions were analysed with linear regression. P values were FDR-corrected.

Adolescents with CHD showed lower HRV (quantified by high-frequency power) compared to controls (p < 0.001). Lower HRV was correlated with worse executive function (β = 0.24, p = 0.044) and lower IQ (β = 0.26, p = 0.010) in the whole sample and with lower IQ (β = 0.35, p = 0.014) in the CHD group. These associations were robust to confounders, including age, sex, and socioeconomic status.

Our findings demonstrate an association between HRV and cognitive functions in adolescents with complex CHD. Early detection of alterations in HRV/autonomic regulation may help to identify children with CHD at risk for cognitive impairments.

Adolescents with congenital heart disease (CHD) showed lower heart rate variability (HRV), indicating an imbalanced autonomic nervous system. Lower HRV was associated with lower IQ and executive function (EF) in the whole sample. The association between HRV and IQ was significantly stronger in CHD than in healthy controls. This study provides the first evidence of a link between altered HRV and cognitive impairments in the CHD population. Neurodevelopmental impairments seen in adolescents with CHD could be linked to their altered cardiac autonomic nervous activity, marked by low HRV.

Heart rate variability (HRV) analysis during sleep plays a key role for understanding autonomic nervous system function and assessing cardiovascular health. The UNICA Sleep HRV analysis (UNICA-HRV) tool is a novel, open-source MATLAB tool designed to fill the gap in current HRV analysis tools. In particular, the integration of ECG and HRV data with hypnogram information, which illustrates the progression through the different sleep stages, eases the computation of HRV metrics in polysomnographic recordings. This integration is crucial for accurate phase-specific analysis, as autonomic regulation changes markedly across different sleep stages. The tool supports single- and multiple-subject analyses and is tailored to enhance usability and accessibility for researchers and clinicians without requiring extensive technical expertise. It implements and supports a variety of data inputs and configurations, allowing for flexible, detailed HRV analyses across sleep stages, employing classical and advanced metrics, such as time-domain, frequency-domain, non-linear, complexity, and Poincaré plot indexes. Validation of the tool against established tools like Kubios and PhysioZoo indicates its robustness and precision in generating reliable HRV metrics, that are essential not only for sleep research, but also for clinical diagnostics. The introduction of UNICA-HRV represents a significant simplification for sleep studies, and its open-source nature (licensed under a Creative Commons Attribution 4.0 International License) allows to easily extend the functionality to other needs.

Background and Objectives: The aim of our study is to determine the effects of analgesia nociception index (ANI) monitoring on intraoperative opioid consumption, postoperative analgesia, and the recovery unit length of stay in patients with a preoperative femoral nerve block (FNB) undergoing total knee arthroplasty (TKA) surgery under general anesthesia. Materials and Methods: Seventy-four patients in the American Society of Anesthesiologists Physical Status (ASA-PS) I-III scheduled for TKA under general anesthesia were included in this study. After FNB, the patients were divided into two groups (control group (n = 35)-ANI group (n = 35)). After standard anesthesia induction in both groups, maintenance was conducted using sevoflurane and remifentanil infusion with a bispectral index (BIS) between 40 and 60. In the control group, the intraoperative remifentanil infusion dose was adjusted using conventional methods, and in the ANI group, the dose was adjusted using ANI values of 50-70. The duration of operation, duration of surgery, extubation time, tourniquet duration and pressure, and the amount of remifentanil consumed intraoperatively were recorded. Results: Intraoperative remifentanil consumption was lower in the ANI group compared to the control group (p = 0.001). The time to reach a Modified Aldrete Scale score (MAS) ≥ 9 was shorter in the ANI group (p < 0.001). NRS scores in the recovery unit and 4, 8, 12, and 24 h postoperatively were lower in the ANI group compared to the control group (p = 0.006, p < 0.05). There was a weak significant inverse relationship between the last ANI values measured before extubation and NRS scores in the postoperative recovery unit (r: -0.070-0.079, p: 0.698-0.661). No difference was observed between the groups in other data. Conclusions: In patients undergoing TKA with FNB under general anesthesia, ANI monitoring decreased the amount of opioids consumed intraoperatively and postoperative pain scores and shortened the length of stay in the recovery unit. We suggest that ANI monitoring in intraoperative analgesia management may be helpful in determining the dose of opioid needed by the patient and individualized analgesia management.

A basic mechanism of domestication is the selection for fearlessness and acceptance of humans as social partners, which may affect risk-taking behavior and the ability to use humans as social support, both at the behavioural and physiological levels. We combined behavioural observations with heart rate parameters (i.e., HR and heart rate variability, HRV) in equally raised and housed wolves and dogs to assess the responses to food offered in the vicinity of a potential stressor (an unknown spinning object) with and without social support from a familiar human. Based on previous studies on neophobia in wolves and dogs, we expected dogs to be less scared of the object, approach more quickly, show less ambivalent behaviour, lower HR, and higher HRV, than wolves, especially at the presence of a human partner. However, we found that mainly age and the presence of a familiar human affected the behaviour of our subjects: older wolves and dogs were generally bolder and faster to approach the food and the familiar human's presence increased the likelihood of taking it. HR rate parameters were affected by age and the stage of the test. Wolves and dogs showed particularly high HRs at the beginning and end of the test sessions. We conclude that in our paradigm, wolves' and dogs' risk-proneness varied with age, rather than species. Additionally, the presence of a familiar human increased the motivation of both, dogs and wolves to take the food.

The rise in individuals living alone in ageing societies raises concerns about social isolation and associated health risks, notably lonely deaths among the elderly. Traditional electrocardiogram (ECG) monitoring systems, reliant on intrusive and potentially irritating electrodes, pose practical challenges. This study examines the efficacy of conductive textile electrodes (CTEs) vis-á-vis conventional electrodes (CEs) in ECG monitoring, along with the effect of electrode positioning. Twenty subjects without cardiovascular conditions, were monitored using a commercial ECG device (HiCardi+) with both CEs and CTEs. The CTEs were tested in two experiments: at the nape and left hand (position 1), and at the nape and legs (position 2). Each experiment placed one HiCardi + SmartPatch with CE at its standard position, while the other used CTEs. ECG signals were processed using the Pan-Tompkins algorithm, and heart rate variability (HRV) metrics were analysed. Significant improvements in signal-to-noise ratio (SNR) were observed after filtering. There were no significant differences (p > 0.05) in time-domain HRV metrics between CEs and CTEs, though CTEs showed superior R peak characteristics and reduced noise sensitivity. Additionally, no significant position effect (p > 0.05) was noted within the CTE group. Nonlinear analysis further confirmed the efficacy of the CTEs. Our findings suggest that CTEs offer a comfortable, non-intrusive alternative to conventional ECG electrodes, enhancing ECG monitoring and contributing to the development of a "lonely death prevention system".

The time-resolved analysis of heart rate (HR) and heart rate variability (HRV) is crucial for the evaluation of the dynamic changes of autonomic activity under different clinical and behavioural conditions. Standard HRV analysis is performed in the frequency domain because the sympathetic activations tend to increase low-frequency HRV oscillations, while the parasympathetic ones increase high-frequency HRV oscillations. However, a strict separation of HRV into frequency bands may cause biased estimations, especially in the low-frequency range. To overcome this limitation, we propose a robust estimator that combines HR and HRV dynamics, based on the correlation of the Poincaré plot descriptors of interbeat intervals from the electrocardiogram. To validate our method, we used electrocardiograms gathered from open databases where standardized paradigms were applied to elicit changes in autonomic activity. Our proposal outperforms the standard spectral approach for the estimation of low- and high-frequency fluctuations in HRV, and its performance is comparable with newer methods. Our method constitutes a valuable, robust, time-resolved and cost-effective tool for a better understanding of autonomic activity through HR and HRV in a healthy state and potentially for pathological conditions.

Aside from stressors that each of us experience directly, we also share the stress of the people around us. Such empathic stress exists on psychological and physiological levels, including subjective, sympathetic, parasympathetic and endocrine activation. The objective of this review is to offer an overview of methodology over the past fifteen years of empathic stress research and derive practical considerations for future research endeavors in the field. We used a keyword search strategy in the databases Web of Science, PsycInfo and PubMed to find empathic stress studies published until December 2023, and included 17 studies into our review. The reviewed laboratory studies provide initial yet consistent evidence for the existence of empathic stress across different populations, in intimate and stranger dyads, with direct and virtual contact, across multiple levels of the stress system, and based on diverse statistical analysis methods. We discuss all findings and derive practical considerations for future empathic stress research. The diversity of methods established provides a solid foundation upon which future studies can expand.

Background/Objectives: One prior study revealed that a newly developed auto-titrating mandibular advancement device (AMAD) could potentially enhance polysomnographic outcomes in individuals with obstructive sleep apnea (OSA). However, evidence regarding its impact on autonomic nervous system dysregulation in OSA remains limited. In this study, we aimed to compare the effects of conventional mandibular advancement devices (MADs) and AMDA on autonomic function. Methods: We retrospectively reviewed data from patients who visited a sleep center with complaints of snoring and sleep apnea (30 and 15 patients in the conventional MAD and AMAD groups, respectively). We assessed heart rate variability (HRV) frequency-domain metrics such as total power (TP), very low frequency (VLF), low frequency (LF), and high frequency (HF) using ultra-short-term and short-term modalities, assessing sympathetic and parasympathetic activity changes across treatment groups. Results: Conventional MAD treatment was associated with reductions in LF and LF/HF ratios, whereas AMAD treatment was linked to decreases in TP, VLF, LF, and LF/HF ratios. Notably, in patients with moderate OSA, LF values were significantly lower in the AMAD group than in the conventional MAD group. Conclusions: These findings suggest that both devices could reduce sympathetic over-activity in patients with OSA, with AMAD demonstrating greater efficacy, particularly in those with moderate OSA.

Cardiovascular autonomic neuropathy (CAN) is a chronic complication of diabetes. As obesity is a major risk factor for CAN, we hypothesized that metabolic bariatric surgery (MBS) could improve CAN indices in Korean patients with obesity.

Patients who underwent bariatric surgery between February 2020 and June 2022 were prospectively recruited. CAN was conducted once before surgery and again after surgery, using the Ewing method and heart rate variability (HRV) analysis (standard deviation of the NN interval [SDNN], root mean square of successive RR interval difference [RMSSD], and spectral analysis).

A total of 47 patients were included. The mean age was 39.8 ± 8.7 years, 15 (31.9%) were male, and 26 (55.3%) had diabetes. Resting HR before surgery was 81.0 ± 12.3 bpm, which decreased significantly to 68.0 ± 9.3 bpm after surgery (P < 0.001). Changes in HR and BP according to the Valsalva maneuver, postural changes, and handgrip were not significantly different before and after surgery. However, SDNN significantly increased from 25.2 [15.1, 33.5] to 38.0 [25.4, 45.0] ms (P < 0.001), and RMSSD also significantly increased from 17.0 [9.2, 31.8] to 28.2 [15.3, 45.6] ms (P = 0.001). Both low-frequency power (LF) and high-frequency power (HF) increased significantly, and the LF/HF ratio significantly decreased from 2.1 ± 1.6 to 1.3 ± 1.3 (P = 0.010). Loss of weight, fat mass, and lean body mass were independently associated with improving the HRV variables.

MBS improved HRV variables, and these changes were mainly associated with postoperative weight loss.

Traditional self-reported measures in health science education often overlook the physiological processes underlying cognitive and emotional responses.

This review aims to analyze the frequency, sensitivity, and utility of physiological markers in understanding cognitive and emotional dynamics in learning environments.

A systematic PubMed search identified 156 records, with 13 studies meeting inclusion criteria. Markers analyzed included heart rate (HR), heart rate variability (HRV), cortisol, alpha-amylase, testosterone, s-IgA, blood pressure, oxygen saturation, and respiratory rate.

HR and HRV were sensitive to educational stressors. Cortisol and alpha-amylase showed mixed results, while testosterone and s-IgA showed limited utility in directly assessing stress responses. No consistent link was found between any marker and immediate learning success.

Physiological markers in learning environments can offer valuable insights into emotional and cognitive dynamics but should not be misconstrued as direct indicators of learning outcomes.

The artificial light at night (ALAN) exposure has emerged as a significant environmental and public health concern globally. However, there is far less evidence on the health effects of indoor ALAN than on outdoor ALAN. Moreover, evidence on cardiovascular effects of indoor ALAN is more limited. To evaluate the association between short-term exposure to ALAN during sleep with heart rate variability (HRV) in young healthy adults, as well as the mediating role of blood oxygen saturation (SpO2), and to further explore the intervention effects of shading habits, this prospective repeated measurement study was conducted among 81 adults with 150 nights (1324h) of HRV monitoring. HRV and SpO2 were monitored during sleep, concurrently with the measurement of indoor and outdoor ALAN. Shading habits were defined as whether to wear blindfolds or draw bed curtains during sleep, and were collected by questionnaires. Linear mixed-effect model was conducted to assess the association between ALAN exposure and HRV indices. The role of SpO2 in the association was analyzed using mediation analyses. We found that indoor ALAN exposure reduced parasympathetic activity and imbalanced cardiac autonomic function. We also found that the use of outdoor ALAN may underestimate or misestimate the potential health effects of ALAN. A significant mediation effects were observed on standard deviation of normal-to-normal intervals (SDNN; p-value for ACME = 0.014) and the ratio of low frequency power to high frequency power (LF/HF; p-value for ACME = 0.026) through minimum SpO2 after indoor ALAN exposure. The association between indoor ALAN and HRV was more pronounced among participants without shading habits during sleep. This study provides general population-based evidence that short-term exposure to indoor ALAN was significantly associated with impaired HRV, and SpO2 partially mediated the association. Improve shading habits during sleep may mitigate the adverse effects of indoor ALAN.

Imaging Photoplethysmography (IPPG) is an emerging and efficient optical method for non-contact measurement of pulse waves using an image sensor. While the contactless way brings convenience, the inevitable distance between the sensor and the subject results in massive specular reflection interference on the skin surface, which leads to a low Signal to Interference plus Noise Ratio (SINR) of IPPG. To ease this challenge, this work proposes a novel modulation illumination approach to measure the accurate arterial pulse wave via surface reflection interference isolation from IPPG. Based on the proposed skin reflection model, a specific modulation illumination is designed to separate the surface reflections and obtain the subcutaneous diffuse reflections containing the pulse wave information. Compared with the results under ambient illumination and constant supplemental illumination, the SINR of the proposed method is improved by 4.56 and 3.74 dB, respectively.

This study investigates changes in cardiorespiratory coupling during clinic breathing training and its impact on autonomic nervous functioning compared with heart rate variability (HRV). A total of 39 subjects undergoing dynamic electrocardiogram-recorded breathing training were analyzed. Subjects were divided into early- and late-training periods, and further categorized based on changes in HRV indexes. Subtypes were identified using time-frequency cardiorespiratory coupling diagrams. Significant differences were observed in the high-frequency (HF) index between training stages in the subgroup with increasing HF-HRV (p = 0.0335). Both unimodal and bimodal subtypes showed significant high-frequency coupling (HFC) in the mid-training period compared with early and late stages (both p < 0.0001), suggesting improved parasympathetic cardiac regulation or reduced sympathetic control. This study highlights the potential of nonstationary cardiorespiratory coupling analysis alongside traditional HRV in evaluating the therapeutic effect of breathing training on autonomic nervous function. Cardiorespiratory coupling analysis could provide valuable adjunctive information to HRV measures for assessing the impact of breathing training.

While Early Live Adversity (ELA) is a known risk factor for mental and physical diseases, the investigation into the mechanisms behind this connection is ongoing. In the present study, we investigated whether ELA blunts the relaxation response in healthy adults. Using a within-subjects design, we employed a paced breathing exercise (four seconds inhale, six seconds exhale) and a 360° nature video as relaxation interventions while measuring physiological relaxation using heart rate variability and subjective relaxation using the Relaxation State Questionnaire. A total of 103 participants (63.11% female; agemean = 22.73 ± 3.43 years) completed the Parental Bonding Instrument and the Childhood Trauma Questionnaire to assess ELA retrospectively. For subjective relaxation, a blunted relaxation reaction was associated with lower scores of paternal care and higher scores of paternal overprotection, physical abuse, physical neglect, and emotional abuse. For heart rate variability emotional abuse in interaction with nicotine consumption was related to a blunted relaxation response. This indicates that experiencing ELA negatively affects the relaxation capability in a healthy sample and emphasizes the importance of assessing relaxation at a physiological and subjective level.

Eco-friendly sensors fabricated from biocompatible and biodegradable materials are promising candidates for wearable and implantable electronics due to their environmental sustainability and biosafety. This article reports a fully biodegradable electromechanical sensor (FBES) utilizing a sandwich structure with macro ripple structured polylactic acid (PLA) electret films acting as sensitive layers and molybdenum (Mo) sheets serving as electrodes for a wearable device application. The stability of the space charge stored within the PLA film has been enhanced by introducing an internal cellular structure and improving the polarization process. A macro ripple structure of the PLA layer with higher deformation is a great guarantee for boosting the pressure sensitivity. The results indicate that inserting cell microstructures and optimizing the polarization process significantly improve the charge storage stability of PLA films by nearly 55%. This enhancement is attributed to several factors, including the extended charge drift path of the charges in cellular films, a synergy effect of surface charges, and "macroscopic" dipole charges distributed in the cells. The fabricated sensor achieves a high sensitivity of 1000 pC/kPa, a wide pressure detection range of 0.03-62.4 kPa, and satisfactory stability. Such sensors are not only sensitive to body movements but also to subtle physiological signals, satisfying the diverse needs of wearable healthcare. Importantly, all the composition materials of the sensor can be completely degraded after their service, aligning with the environmentally friendly principles of green development.

Although wearable devices for continuous monitoring of vital signs have undergone significant advancements, their need for frequent recharging precludes continuous operation, potentially leading to adverse outcomes being overlooked. Additionally, the scattered locations of the sensors hamper wearability. Herein, we present a compact vital-sensing band with uninterrupted power supply designed for continuous monitoring of core body temperature (CBT) and pulse rate. The band─which comprises two sensors, a power source (i.e., a flexible thermoelectric generator (TEG) and a battery), and a flexible circuit─is worn on the forearm. The CBT is calculated by measuring the skin temperature and heat flux, while a triboelectric nanogenerator-based self-powered pressure sensor is utilized for pulse rate monitoring. The TEG is a flexible unit that converts body heat into electricity, accumulating a total energy of 314 mJ (100%). Out of this total energy, only 43.2 mJ (7.2%) is utilized for CBT measurements, while the remaining 270.80 mJ (92.8%) is stored in the battery. This enables reliable and continuous operation of the vital-sensing band, highlighting its potential for use in healthcare applications.

Omega-3 long-chain polyunsaturated fatty acids (LC-PUFAs) have been reported to improve sleep quality in several studies, but meta-analyses have been inconclusive. We conducted this study to investigate the effects of omega-3 LC-PUFAs on sleep in clinical trials. The study was planned in accordance with the criteria of the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-2020), and was performed by searching PubMed, The Cochrane Library, and Ichushi-web databases. Randomized controlled trials and clinical trials with control groups were included. Finally, eight studies were selected for inclusion in this study. Sleep efficiency was significantly higher in the omega-3 LC-PUFA group than in the control group, while sleep latency and total sleep duration did not differ significantly. Subjectively assessed sleep was significantly improved by omega-3 LC-PUFA, but heterogeneity was so high that a subgroup analysis based on dose of omega-3 supplementation was performed. It showed low heterogeneity and significant improvement in the omega-3 LC-PUFA group compared with the control group. Omega-3 LC-PUFAs have been shown to may improve sleep quality. Further studies are needed to confirm the relationship between omega-3 LC-PUFAs and sleep. The protocol for this review was registered in UMIN000052527.

This study aims to explore the physiological effect of forest bathing on stress management.

A total of 29 volunteers participated in this pre-post design, which lacked a control group. Several physiological parameters were recorded, including heart rate (HR), heart rate variability (HRV), electrodermal activity (EDA), blood pressure (BP), immunoglobulin A (IGA), and salivary cortisol (sCort). Additionally, the Perceived Stress Scale (PSS-10) was administered before forest exposure. Measurements were taken before and after participants spent 2 days fully immersed in a forest environment. To further assess stress management, participants completed a Mental Arithmetic Task (MAT) before and after forest immersion, during which EDA, HRV, and HR were monitored using an Empatica E4 wristband. Measurements were taken at baseline, during MAT, and afterward (recovery).

Participants exhibited moderate perceived stress levels before forest immersion (mean PSS-10 = 21.22, SD = 3.78). Post-forest exposure, there was a significant decrease in sCort (p < 0.05) and EDA (p < 0.001), while HRV increased (p < 0.001), and diastolic blood pressure rose (p < 0.05). ANOVA results from the MAT showed a significant increase in parasympathetic activity across all conditions post-immersion (p < 0.05), except during recovery, while EDA decreased in all conditions post-forest exposure (p < 0.05).

Shinrin-yoku significantly improved stress management at a physiological level and could be a valuable intervention for individuals experiencing stress. However, longitudinal studies with a control group are necessary to determine whether these effects are sustained over time. Nonetheless, this study highlights the potential benefits of forest immersion for stress reduction by enhancing sympathovagal balance and the adaptability of the stress response system.

Millimeter wave (mmWave) radar technology has potential applications in vital signs detection and medicine. In order to minimize the influence of human micro-movements and respiratory harmonics on heart rate estimation, the vital signs detection method based on mmWave radar is studied in this paper. First, we use median filtering to eliminate baseline drift caused by human micromotion. Next, a differential recursive least squares multiple classification (DR-MUSIC) algorithm is proposed based on the combination of recursive least squares-based adaptive filter (RLS) and multiple signal classification (MUSIC) algorithm. This algorithm effectively suppresses respiratory harmonics and separates respiratory and heartbeat signals. Finally, heart rate value can be precisely estimated using spectral peak search. We invite a number of people to participate in the experiment, which demonstrate that the method successfully suppresse the impact of respiratory harmonics at low SNR. The error rate between the estimated heart rate and the reference heart rate is only 1.69% to 2.61%, which is significantly better than the existing algorithms.

Heart rate variability (HRV) was shown to be affected by performing religious activities.

To examine the relationship between the level of Quran (the holy book of Muslims) memorisation and HRV among teenagers.

This experimental study included 16 Tahfiz students and 16 non-Tahfiz students (n = 32). The HRV was measured in three tasks: Recalling familiar verses, memorising new verses, and recalling the newly memorised verses of the Quran. HRV analysis was done using these parameters: Standard deviation of N-N (heartbeat peak) interval; low frequency (LF); high frequency (HF) and LF/HF ratio.

There were significant differences between tasks for all parameters (P < 0.05). However, between the groups, only the LF/HF ratio had significant differences, with F = 5.04, P < 0.05. Pearson correlation showed a moderate positive correlation between the number of pages memorised and the LF/HF ratio (r = 0.61, P < 0.05).

Quran memorisation increased the HRV and our results suggested that this activity could be developed as an effective sympathovagal modulation training activity.

This study explores the gender differences in psychological stress perception and autonomic modulation among teachers.

Utilizing heart rate variability (HRV) as a measure of autonomic function and a suite of validated psychological tests, the study examines the discrepancies in stress, anxiety, burnout, and personality traits between male and female educators.

Results indicate that despite higher reported levels of stress and anxiety, women demonstrate a higher HRV, suggesting a stronger parasympathetic response.

These findings highlight the complex interplay between psychological stressors and physiological responses, emphasizing the need for gender-specific interventions in stress management within the educational sector. Implications for enhancing educators' well-being and performance through tailored strategies are discussed.

The construction industry is actively developing remote-controlled excavators to address labor shortages and improve work safety. However, visually induced motion sickness (VIMS) remains a concern in the remote operation of construction machinery. To predict the occurrence and severity of VIMS, we developed a prototype system that acquires multiple physiological signals with different mechanisms under a low burden and detects VIMS from the collected data. Signals during VIMS were recorded from nine healthy adult males operating excavator simulators equipped with multiple displays and a head-mounted display. Light gradient-boosting machine-based VIMS detection binary classification models were constructed using approximately 30,000 s of time-series data, comprising 23 features derived from the physiological signals. These models were validated using leave-one-out cross-validation on seven participants who experienced severe VIMS and evaluated through area under the curve (AUC) scores. The mean receiver operating characteristic curve AUC score was 0.84, and the mean precision-recall curve AUC score was 0.71. All features were incorporated into the models, with saccade frequency and skin conductance response identified as particularly important. These trends aligned with subjective assessments of VIMS severity. This study contributes to advancing the use of remote-controlled machinery by addressing a critical challenge to operator performance and safety.