Assessing the Accuracy of Popular Commercial Technologies That Measure Resting Heart Rate and Heart Rate Variability

Digital biomarkers for non-motor symptoms in Parkinson's disease: the state of the art

Digital biomarkers that remotely monitor symptoms have the potential to revolutionize outcome assessments in future disease-modifying trials in Parkinson's disease (PD), by allowing objective and recurrent measurement of symptoms and signs collected in the participant's own living environment. This biomarker field is developing rapidly for assessing the motor features of PD, but the non-motor domain lags behind. Here, we systematically review and assess digital biomarkers under development for measuring non-motor symptoms of PD. We also consider relevant developments outside the PD field. We focus on technological readiness level and evaluate whether the identified digital non-motor biomarkers have potential for measuring disease progression, covering the spectrum from prodromal to advanced disease stages. Furthermore, we provide perspectives for future deployment of these biomarkers in trials. We found that various wearables show high promise for measuring autonomic function, constipation and sleep characteristics, including REM sleep behavior disorder. Biomarkers for neuropsychiatric symptoms are less well-developed, but show increasing accuracy in non-PD populations. Most biomarkers have not been validated for specific use in PD, and their sensitivity to capture disease progression remains untested for prodromal PD where the need for digital progression biomarkers is greatest. External validation in real-world environments and large longitudinal cohorts remains necessary for integrating non-motor biomarkers into research, and ultimately also into daily clinical practice.

Heart Rate Variability in Professional and Semiprofessional Soccer: A Scoping Review

In modern soccer, fitness and fatigue monitoring tools tend to be focused on noninvasive, time-efficient and player-friendly measures. Heart rate variability (HRV) has been suggested as an effective method for monitoring training response and readiness to perform. However, there is still a lack of consensus on HRV monitoring when it comes to soccer. Thus, this scoping review aims to map existing evidence on HRV in professional and semiprofessional soccer settings, and to identify knowledge gaps to inform future research directions. A search of databases (PubMed, Scopus, Web of Science, Google Scholar) according to the PRISMA-ScR statement was employed. Studies were screened for eligibility on inclusion criteria: (1) HRV was among the topics discussed in the article; (2) adult professional or semiprofessional soccer players were involved in the study; (3) both male and female participants; (4) no geographical area exclusion; (5) articles published in English; and (6) article full text available. The search of the selected databases revealed 8456 records. The titles and abstracts of all articles were retrieved for screening of eligibility, leaving 30 articles for further consideration. Following screening against set criteria, a total of 25 studies were included in this review, the sample size of which ranged from 6 to 124 participants. The participants in the included studies were professional and semiprofessional soccer players, interviewed clubs staff, and practitioners. Along with other monitoring strategies, morning vagally mediated HRV analysis via (ultra)short-term orthostatic measurements may be an efficient way to assess training adaptations and readiness to perform in professional and semiprofessional soccer players. Further research is required to make definitive recommendations.

The Relationship between Heart Rate Variability, Pain Intensity, Pain Catastrophizing, Disability, Quality of Life and Range of Cervical Motion in Patients with Chronic Non-Specific Neck Pain: A Cross-Sectional Study

The purpose of the present cross-sectional study was to examine the relationship between heart rate variability (HRV) and the range of cervical motion, disability, pain intensity, pain catastrophizing, and quality of life in patients with chronic, non-specific neck pain. Thirty-five patients, aged 20-48 years, with chronic non-specific neck pain, completed validated questionnaires regarding neck pain intensity, pain-associated disability, catastrophic thoughts, and quality of life. The range of cervical motion was assessed using a digital goniometer. HRV indices were recorded in three positions (supine, sitting, and standing) through a smartphone application. Several significant correlations were observed between HRV indices and neck pain disability, the helplessness factor of catastrophizing, neck rotation, and quality of life. These correlations were only observed in the standing position. Pain catastrophizing was positively correlated with disability and pain intensity during active neck movement (Pearson r = 0.544, p < 0.01; Pearson r = 0.605, p < 0.01, respectively). Quality of life was negatively correlated with pain intensity during active movement (Pearson r = -0.347, p < 0.05). HRV indices were correlated with the psychological and physical domains of neck pain. These cardiac indices have been related to neck pain variables in some previous studies. Further research is needed to confirm this relationship in different daily conditions.

Analysis of Sleep, Nocturnal Physiology, and Physical Demands of NCAA Women's Ice Hockey Across a Championship Season

ABSTRACT

Merrigan, JJ, Stone, JD, Kraemer, WJ, Friend, C, Lennon, K, Vatne, EA, and Hagen, JA. Analysis of sleep, nocturnal physiology, and physical demands of NCAA women's ice hockey across a championship season. J Strength Cond Res 38(4): 694-703, 2024-The aims of this study were to evaluate the (a) relationships between daily physical demands and nighttime sleep, heart rate (HR), and heart rate variability (HRV); (b) weekly changes in physical demands and sleep; and (c) differences among positions and between training and competition during a competitive season in National Collegiate Athletic Association (NCAA) women's ice hockey. Twenty-five NCAA Division I women's ice hockey athletes wore a sensor at night to monitor sleep quantity or quality (e.g., time asleep and sleep efficiency) and physiology (e.g., HR and HRV). During training and competitions (31 regular season and 7 postseason), athletes wore performance monitoring systems to assess workload demands (e.g., training impulse and TRIMP). As internal workload (TRIMP, Time >80% of HRmax, Average HR) during training or competition increased, nocturnal HRV decreased, HR increased, and Sleep Duration, Sleep Score, and Readiness Score decreased that night. Across the season, athletes experienced lower HRV, but exhibited longer sleep durations. Training Distance, Duration, Time >80% HRmax, Average HR, and TRIMP decreased, whereas competition Total Distance, Duration, and TRIMP increased across weeks throughout the season. There were differences across positions and season blocks when evaluating these data at the mesocycle level. Athletes slept longer before competition compared with training, but physiological data did not differ. Competitions had greater physiological demands than training. We speculate that the increased focus on sleep hygiene, as evidenced by the increase in sleep over the season, may have served as a recovery aid to combat physiological stress of accumulated demands of competitions that increased over time into postseason tournaments.

Accuracy and clinical utility of heart rate variability derived from a wearable heart rate monitor in patients undergoing major abdominal surgery

Low heart rate variability (HRV) can potentially identify patients at risk of intraoperative hypotension. However, it is unclear whether cheaper, readily accessible consumer heart rate (HR) monitors can provide similar utility to clinical Holter electrocardiograph (ECG) monitors. The objectives of this study were (1) to assess the validity of using the Polar H10 HR monitor as an alternative to a clinical Holter ECG and (2) to test total power (TP) as a predictor of intraoperative hypotension. The primary outcome was the level of agreement between Polar H10 and Holter ECG. Twenty-three patients undergoing major abdominal surgery with general anesthesia had 5-minute HR recordings taken concurrently with both devices during a pre-anesthetic consultation. Agreement between Polar H10 and Holter ECG was compared via Bland-Altman analysis and Lin's Concordance Correlation Coefficient. Patients were divided into groups based on TP <  500 m s 2 and TP >  500 m s 2 . Intraoperative hypotension was defined as MAP < 60 mmHg, systolic blood pressure < 80 mmHg, or 35% decrease in MAP from baseline. There was substantial agreement between Polar H10 and Holter ECG for average R-R interval, TP and other HRV indices. Reduced TP (< 500 ms 2 ) had a high sensitivity (80%) and specificity (100%) in predicting intraoperative hypotension. Patients with reduced TP were significantly more likely to require vasoactive drugs to maintain blood pressure.The substantial agreement between Polar H10 and Holter ECG may justify its use clinically. The use of preoperative recordings of HRV has the potential to become part of routine preoperative assessment as a useful screening tool to predict hemodynamic instability in patients undergoing general anesthesia.

Heart Rate Variability (HRV) serves as an objective correlate of distress and symptom burden in multiple sclerosis

Background

Autonomic nervous system (ANS) dysfunction is frequently seen in people living with multiple sclerosis (MS). Heart rate variability (HRV) is an easy and objective index for evaluating ANS functioning, and it has been previously used to explore the association between ANS and the experience of symptom burden in other chronic diseases. Given ANS functioning can be influenced by physical and psychological factors, this study investigated whether emotional distress and/or the presence of ANS dysfunction is associated with symptom severity in people living with MS.

Methods

Participants with MS and healthy controls (HC) with no history of cardiac conditions were recruited to self-collect HR data sampled from a chest strap HR monitor (PolarH10). Short-term HR signal was collected for five minutes, and time and frequency HRV analyses were performed and compared between groups. HRV values were then compared to self-reported distress (Kessler Psychological Distress Scale) and MS participants' self-reported measures of symptom burden (SymptoMScreen).

Results

A total of n = 23 adults with MS (51 ± 12 years, 65 % female, median Patient Determined Disease Steps [PDDS]: 3.0) and n = 23 HCs (43 ± 18 years, 40 % female) completed the study procedures. All participants were able to complete the chest strap placement and HR data capture independently. Participants with MS, compared to the HC participants, had a significantly lower parasympathetic activation as shown by lower values of the root mean square of successive differences between normal heartbeats (RMSSD: 21.86 ± 9.84 vs. 43.13 ± 20.98 ms, p = 0.002) and of high-frequency (HF) power band (HF-HRV: 32.69 ± 12.01 vs. 42.39 ± 7.96 nu, p = 0.016), indicating an overall lower HRV in the MS group. Among individuals with MS, HF-HRV was significantly correlated with the severity of self-reported MS symptoms (r = -0.548, p = 0.010). Participants with MS also reported higher levels of distress compared to HC participants (18.32 ± 6.05 vs. 15.00 ± 4.61, p = 0.050), and HRV correlated with the severity of distress in MS participants (r = -0.569, p = 0.007). A significant mediation effect was also observed, with emotional distress fully mediating the association between HRV and symptom burden.

Conclusions

These findings suggest the potential for ANS dysfunction, as measured by HRV (i.e., lower value of HF power), to be utilized as an objective marker of symptom burden in people living with MS. Moreover, it is apparent that the relationship between HRV and symptom burden is mediated by emotional distress.

Evaluation of Wrist-Worn Photoplethysmography Trackers with an Electrocardiogram in Patients with Ischemic Heart Disease: A Validation Study

PURPOSE

Photoplethysmography measurement of heart rate with wrist-worn trackers has been introduced in healthy individuals. However, additional consideration is necessary for patients with ischemic heart disease, and the available evidence is limited. The study aims to evaluate the validity and reliability of heart rate measures by a wrist-worn photoplethysmography (PPG) tracker compared to an electrocardiogram (ECG) during incremental treadmill exercise among patients with ischemic heart disease.

METHODS

Fifty-one participants performed the standard incremental treadmill exercise in a controlled laboratory setting with 12-lead ECG attached to the patient's body and wearing wrist-worn PPG trackers.

RESULTS

At each stage, the absolute percentage error of the PPG was within 10% of the standard acceptable range. Further analysis using a linear mixed model, which accounts for individual variations, revealed that PPG yielded the best performance at the baseline low-intensity exercise. As the stages progressed, heart rate validity decreased but was regained during recovery. The reliability was moderate to excellent.

CONCLUSIONS

Low-cost trackers AMAZFIT Cor and Bip validity and reliability were within acceptable ranges, especially during low-intensity exercise among patients with ischemic heart disease recovering from cardiac procedures. Though using the tracker as part of the diagnosis tool still requires more supporting studies, it can potentially be used as a self-monitoring tool with precautions.

Preliminary Technical Validation of LittleBeats™: A Multimodal Sensing Platform to Capture Cardiac Physiology, Motion, and Vocalizations

Across five studies, we present the preliminary technical validation of an infant-wearable platform, LittleBeats™, that integrates electrocardiogram (ECG), inertial measurement unit (IMU), and audio sensors. Each sensor modality is validated against data from gold-standard equipment using established algorithms and laboratory tasks. Interbeat interval (IBI) data obtained from the LittleBeats™ ECG sensor indicate acceptable mean absolute percent error rates for both adults (Study 1, N = 16) and infants (Study 2, N = 5) across low- and high-challenge sessions and expected patterns of change in respiratory sinus arrythmia (RSA). For automated activity recognition (upright vs. walk vs. glide vs. squat) using accelerometer data from the LittleBeats™ IMU (Study 3, N = 12 adults), performance was good to excellent, with smartphone (industry standard) data outperforming LittleBeats™ by less than 4 percentage points. Speech emotion recognition (Study 4, N = 8 adults) applied to LittleBeats™ versus smartphone audio data indicated a comparable performance, with no significant difference in error rates. On an automatic speech recognition task (Study 5, N = 12 adults), the best performing algorithm yielded relatively low word error rates, although LittleBeats™ (4.16%) versus smartphone (2.73%) error rates were somewhat higher. Together, these validation studies indicate that LittleBeats™ sensors yield a data quality that is largely comparable to those obtained from gold-standard devices and established protocols used in prior research.

Heart Rate Variability Measurement through a Smart Wearable Device: Another Breakthrough for Personal Health Monitoring?

Heart rate variability (HRV) is a measurement of the fluctuation of time between each heartbeat and reflects the function of the autonomic nervous system. HRV is an important indicator for both physical and mental status and for broad-scope diseases. In this review, we discuss how wearable devices can be used to monitor HRV, and we compare the HRV monitoring function among different devices. In addition, we have reviewed the recent progress in HRV tracking with wearable devices and its value in health monitoring and disease diagnosis. Although many challenges remain, we believe HRV tracking with wearable devices is a promising tool that can be used to improve personal health.

Heart Rate and Heart Rate Variability in Healthy Preterm-Born Young Adults and Association with Vitamin D: A Wearable Device Assessment

Prematurity has been associated with impaired parasympathetic cardiac regulation later in life. Changes in heart rate (HR) and heart rate variability (HRV) may indicate a risk for future cardiac dysfunction. The putative role of Vitamin D on cardiac autonomic function in individuals born preterm (PT) remains unknown. This study involves monitoring autonomic cardiac regulation and Vitamin D concentrations in 30 PT and 16 full-term (FT) young adults in a free-living context. The PT subjects were born between 1994 and 1997 at Oulu University Hospital. The inclusion criteria were (1) being born ≤ 32 gestation weeks or (2) being born < 34 gestation weeks with a birth weight under 1500 g. Participants wore an Oura ring sleep tracer, a smart ring device, for 2 weeks to monitor cardiac autonomic function. Parameters related to autonomic cardiac regulation, lowest nighttime resting HR, and the root mean square of successive differences (RMSSD) to describe HRV were collected. PT males exhibited a tendency toward lower RMSSD (71.8 ± 22.6) compared to FT males (95.63 ± 29.0; p = 0.10). Female participants had a similar mean RMSSD in the FT and PT groups at 72.04 ± 33.2 and 74.0 ± 35.0, respectively. Serum 25-hydroxyvitamin D concentration did not correlate with cardiac autonomic function parameters. When assessing the lowest resting nighttime HRs and HRVs in a long-term, real-world context, healthy female PT young adults performed similarly to their FT peers. In contrast, the present study's results suggest that male PT young adults exhibit impaired autonomic cardiac function, potentially putting them at risk for cardiovascular disease later in adulthood.

Psychophysiology, Cognitive Function, and Musculoskeletal Status Holistically Explain Tactical Performance Readiness and Resilience

ABSTRACT

Thompson, AG, Ramadan, JH, Alexander, JS, and Galster, SM. Psychophysiology, cognitive function, and musculoskeletal status holistically explain tactical performance readiness and resilience. J Strength Cond Res 37(12): 2443-2456, 2023-This study aimed to advance the techniques used in quantifying holistic readiness and resilience within military personnel. Tactical performers, instructors, and applied human performance scientists designed a weeklong competition to reflect realistic operational demands, test specific underlying performance constructs, and elucidate how modernized assessments could drive programmatic action. By placing first in their installation's local preliminary competition, 34 active-duty Marines earned the opportunity to compete in a series of 7 intense events for the title of champion. All inferential statistics were set to a p ≤ 0.05 level of significance. Morning heart rate variability identified top from bottom quartile finishers before a single competition event. By day 3, morning countermovement jump force production (normalized reactive strength index-modified) and cognitive psychomotor vigilance were significant indicators of performance resilience and final competition group rank. Heart rate variability also tracked performer readiness across time, identifying within-group and between-group differences among top, bottom, and field. Collectively, these holistic assessments proved significant markers of acute and chronic tactical performance capabilities. In summary, the incorporation of psychophysiological monitoring, cognitive performance testing, and musculoskeletal force plate evaluations could help inform selection and support needs, drive workload or recovery modulation, and provide critical metrics for evaluating training efficacy and operational readiness. Defense organizations should consider routinely incorporating and actioning similar holistic status monitoring strategies in training and operational settings. Moreover, leveraging other tactical competitions may provide key opportunities for advancing the standard of practice through additional scientific investigation.

Validity and Efficacy of the Elite HRV Smartphone Application during Slow-Paced Breathing

Slow-paced breathing is a clinical intervention used to increase heart rate variability (HRV). The practice is made more accessible via cost-free smartphone applications like Elite HRV. We investigated whether Elite HRV can accurately measure and augment HRV via its slow-paced breathing feature. Twenty young adults completed one counterbalanced cross-over protocol involving 10 min each of supine spontaneous (SPONT) and paced (PACED; 6 breaths·min-1) breathing while RR intervals were simultaneously recorded via a Polar H10 paired with Elite HRV and reference electrocardiography (ECG). Individual differences in HRV between devices were predominately skewed, reflecting a tendency for Elite HRV to underestimate ECG-derived values. Skewness was typically driven by a limited number of outliers as median bias values were ≤1.3 ms and relative agreement was ≥very large for time-domain parameters. Despite no significant bias and ≥large relative agreement for frequency-domain parameters, limits of agreement (LOAs) were excessively wide and tended to be wider during PACED for all HRV parameters. PACED significantly increased low-frequency power (LF) for Elite HRV and ECG, and between-condition differences showed very large relative agreement. Elite HRV-guided slow-paced breathing effectively increased LF values, but it demonstrated greater precision during SPONT and in computing time-domain HRV.

Adaptive yoga versus low-impact exercise for adults with chronic acquired brain injury: a pilot randomized control trial protocol

Background

Each year, millions of Americans sustain acquired brain injuries (ABI) which result in functional impairments, such as poor balance and autonomic nervous system (ANS) dysfunction. Although significant time and energy are dedicated to reducing functional impairment in acute phase of ABI, many individuals with chronic ABI have residual impairments that increase fall risk, decrease quality of life, and increase mortality. In previous work, we have found that yoga can improve balance in adults with chronic (i.e., ≥6 months post-injury) ABI. Moreover, yoga has been shown to improve ANS and brain function in healthy adults. Thus, adults with chronic ABI may show similar outcomes. This protocol details the methods used to examine the effects of a group yoga program, as compared to a group low-impact exercise, on primary and secondary outcomes in adults with chronic ABI.

Methods

This study is a single-blind randomized controlled trial comparing group yoga to group low-impact exercise. Participants must be ≥18 years old with chronic ABI and moderate balance impairments. Group yoga and group exercise sessions occur twice a week for 1 h for 8 weeks. Sessions are led by trained adaptive exercise specialists. Primary outcomes are balance and ANS function. Secondary outcomes are brain function and structure, cognition, quality of life, and qualitative experiences. Data analysis for primary and most secondary outcomes will be completed with mixed effect statistical methods to evaluate the within-subject factor of time (i.e., pre vs. post intervention), the between-subject factor of group (yoga vs. low-impact exercise), and interaction effects. Deductive and inductive techniques will be used to analyze qualitative data.

Discussion

Due to its accessibility and holistic nature, yoga has significant potential for improving balance and ANS function, along with other capacities, in adults with chronic ABI. Because there are also known benefits of exercise and group interaction, this study compares yoga to a similar, group exercise intervention to explore if yoga has a unique benefit for adults with chronic ABI.Clinical trial registration:ClinicalTrials.gov, NCT05793827. Registered on March 31, 2023.

Remote monitoring technologies for measuring cardiovascular functions in community-dwelling adults: a systematic review

Remote monitoring technologies (RMTs) allow continuous, unobtrusive, and real-time monitoring of the cardiovascular system. An overview of existing RMTs measuring cardiovascular physiological variables is lacking. This systematic review aimed to describe RMTs measuring cardiovascular functions in community-dwelling adults. An electronic search was conducted via PubMed, EMBASE, and Cochrane Library from January 1, 2020, to April 7, 2022. Articles reporting on non-invasive RMTs used unsupervised in community-dwelling adults were included. Reviews and studies in institutionalized populations were excluded. Two reviewers independently assessed the studies and extracted the technologies used, cardiovascular variables measured, and wearing locations of RMTs. Validation of the RMTs was examined based on the COSMIN tool, and accuracy and precision were presented. This systematic review was registered with PROSPERO (CRD42022320082). A total of 272 articles were included representing 322,886 individuals with a mean or median age from 19.0 to 88.9 years (48.7% female). Of all 335 reported RMTs containing 216 distinct devices, photoplethysmography was used in 50.3% of RMTs. Heart rate was measured in 47.0% of measurements, and the RMT was worn on the wrist in 41.8% of devices. Nine devices were reported in more than three articles, of which all were sufficiently accurate, six were sufficiently precise, and four were commercially available in December 2022. The top four most reported technologies were AliveCor KardiaMobile®, Fitbit Charge 2, and Polar H7 and H10 Heart Rate Sensors. With over 200 distinct RMTs reported, this review provides healthcare professionals and researchers an overview of available RMTs for monitoring the cardiovascular system.

Consumer Wearable Sleep Trackers: Are They Ready for Clinical Use?

As the importance of good sleep continues to gain public recognition, the market for sleep-monitoring devices continues to grow. Modern technology has shifted from simple sleep tracking to a more granular sleep health assessment. We examine the available functionalities of consumer wearable sleep trackers (CWSTs) and how they perform in healthy individuals and disease states. Additionally, the continuum of sleep technology from consumer-grade to medical-grade is detailed. As this trend invariably grows, we urge professional societies to develop guidelines encompassing the practical clinical use of CWSTs and how best to incorporate them into patient care plans.

The Future of Stress Management: Integration of Smartwatches and HRV Technology

In the modern world, stress has become a pervasive concern that affects individuals' physical and mental well-being. To address this issue, many wearable devices have emerged as potential tools for stress detection and management by measuring heart rate, heart rate variability (HRV), and various metrics related to it. This literature review aims to provide a comprehensive analysis of existing research on HRV tracking and biofeedback using smartwatches pairing with reliable 3rd party mobile apps like Elite HRV, Welltory, and HRV4Training specifically designed for stress detection and management. We apply various algorithms and methodologies employed for HRV analysis and stress detection including time-domain, frequency-domain, and non-linear analysis techniques. Prominent smartwatches, such as Apple Watch, Garmin, Fitbit, Polar, and Samsung Galaxy Watch, are evaluated based on their HRV measurement accuracy, data quality, sensor technology, and integration with stress management features. We describe the efficacy of smartwatches in providing real-time stress feedback, personalized stress management interventions, and promoting overall well-being. To assist researchers, doctors, and developers with using smartwatch technology to address stress and promote holistic well-being, we discuss the data's advantages and limitations, future developments, and the significance of user-centered design and personalized interventions.

Whole-body photobiomodulation improves post-exercise recovery but does not affect performance or physiological response during maximal anaerobic cycling

This study aims to examine the effects of acute whole-body photobiomodulation (wbPBM), applied pre-exercise, on bouts of anaerobic cycling (Wingate) performances. Forty-eight healthy, active males and females participated in this single-blind, randomized, crossover study. Participants visited the laboratory three times to complete repeat (4 ×) Wingate testing, with one week between each visit. All participants completed baseline testing during their first visit and randomly received either the wbPBM or placebo condition before testing on the second visit, followed by the opposite condition on the third visit. There were no significant condition × time interactions for any variable (peak power, average power, power decrement, lactate, heart rate, ratings of perceived exertion, heart rate variability (HRV), root-mean square of differences between R-R intervals (rMSSD), power in the high-frequency range (HF) average, power in the low-frequency range (LF) average, total power, LF/HF, or power in the very-low-frequency range average). A main condition effect was only noted for heart rate, where peak heart rate was significantly higher for wbPBM (145, 141-148 bpm) than placebo (143, 139-146 bpm; p = 0.006) and baseline testing (143, 140-146; p = 0.049) throughout the entire testing session (i.e., collapsed across all timepoints). Furthermore, HRV (rMSSD) the following morning after testing was significantly higher for the wbPBM session compared to placebo (p = 0.043). There were no differences in perceived recovery (p = 0.713) or stress (p = 0.978) scores between wbPBM and placebo. Implementing 20 min of wbPBM immediately prior to maximal bouts of anaerobic cycling did not improve performance (i.e., power output) or physiological responses (e.g., lactate). However, wbPBM elicited the ability to work at a higher heart rate throughout testing and seemed to enhance recovery through improved HRV the following morning.

Wearable and Portable Devices for Acquisition of Cardiac Signals while Practicing Sport: A Scoping Review

Wearable and portable devices capable of acquiring cardiac signals are at the frontier of the sport industry. They are becoming increasingly popular for monitoring physiological parameters while practicing sport, given the advances in miniaturized technologies, powerful data, and signal processing applications. Data and signals acquired by these devices are increasingly used to monitor athletes' performances and thus to define risk indices for sport-related cardiac diseases, such as sudden cardiac death. This scoping review investigated commercial wearable and portable devices employed for cardiac signal monitoring during sport activity. A systematic search of the literature was conducted on PubMed, Scopus, and Web of Science. After study selection, a total of 35 studies were included in the review. The studies were categorized based on the application of wearable or portable devices in (1) validation studies, (2) clinical studies, and (3) development studies. The analysis revealed that standardized protocols for validating these technologies are necessary. Indeed, results obtained from the validation studies turned out to be heterogeneous and scarcely comparable, since the metrological characteristics reported were different. Moreover, the validation of several devices was carried out during different sport activities. Finally, results from clinical studies highlighted that wearable devices are crucial to improve athletes' performance and to prevent adverse cardiovascular events.

Does Wearable-Measured Heart Rate Variability During Sleep Predict Perceived Morning Mental and Physical Fitness?

The emergence of wearable sensor technology may provide opportunities for automated measurement of psychophysiological markers of mental and physical fitness, which can be used for personalized feedback. This study explores to what extent within-subject changes in resting heart rate variability (HRV) during sleep predict the perceived mental and physical fitness of military personnel on the subsequent morning. Participants wore a Garmin wrist-worn wearable and filled in a short morning questionnaire on their perceived mental and physical fitness during a period of up to 46 days. A custom-built smartphone app was used to directly retrieve heart rate and accelerometer data from the wearable, on which open-source algorithms for sleep detection and artefact filtering were applied. A sample of 571 complete observations in 63 participants were analyzed using linear mixed models. Resting HRV during sleep was a small predictor of perceived physical fitness (marginal R² = .031), but not of mental fitness. The items on perceived mental and physical fitness were strongly correlated (r = .77). Based on the current findings, resting HRV during sleep appears to be more related to the physical component of perceived fitness than its mental component. Recommendations for future studies include improvements in the measurement of sleep and resting HRV, as well as further investigation of the potential impact of resting HRV as a buffer on stress-related outcomes.

Practices and Applications of Heart Rate Variability Monitoring in Endurance Athletes

Heart rate variability reflects fluctuations in the changes in consecutive heartbeats, providing insight into cardiac autonomic function and overall physiological state. Endurance athletes typically demonstrate better cardiac autonomic function than non-athletes, with lower resting heart rates and greater variability. The availability and use of heart rate variability metrics has increased in the broader population and may be particularly useful to endurance athletes. The purpose of this review is to characterize current practices and applications of heart rate variability analysis in endurance athletes. Important considerations for heart rate variability analysis will be discussed, including analysis techniques, monitoring tools, the importance of stationarity of data, body position, timing and duration of the recording window, average heart rate, and sex and age differences. Key factors affecting resting heart rate variability will be discussed, including exercise intensity, duration, modality, overall training load, and lifestyle factors. Training applications will be explored, including heart rate variability-guided training and the identification and monitoring of maladaptive states such as overtraining. Lastly, we will examine some alternative uses of heart rate variability, including during exercise, post-exercise, and for physiological forecasting and predicting performance.

Wearable-Measured Sleep and Resting Heart Rate Variability as an Outcome of and Predictor for Subjective Stress Measures: A Multiple N-of-1 Observational Study

The effects of stress may be alleviated when its impact or a decreased stress-resilience are detected early. This study explores whether wearable-measured sleep and resting HRV in police officers can be predicted by stress-related Ecological Momentary Assessment (EMA) measures in preceding days and predict stress-related EMA outcomes in subsequent days. Eight police officers used an Oura ring to collect daily Total Sleep Time (TST) and resting Heart Rate Variability (HRV) and an EMA app for measuring demands, stress, mental exhaustion, and vigor during 15-55 weeks. Vector Autoregression (VAR) models were created and complemented by Granger causation tests and Impulse Response Function visualizations. Demands negatively predicted TST and HRV in one participant. TST negatively predicted demands, stress, and mental exhaustion in two, three, and five participants, respectively, and positively predicted vigor in five participants. HRV negatively predicted demands in two participants, and stress and mental exhaustion in one participant. Changes in HRV lasted longer than those in TST. Bidirectional associations of TST and resting HRV with stress-related outcomes were observed at a weak-to-moderate strength, but not consistently across participants. TST and resting HRV are more consistent predictors of stress-resilience in upcoming days than indicators of stress-related measures in prior days.

Intra- and Interrater Reliability of Short-Term Measurement of Heart Rate Variability on Rest in Individuals Post-COVID-19

Individuals affected by COVID-19 have an alteration in autonomic balance, associated with impaired cardiac parasympathetic modulation and, consequently, a decrease in heart rate variability (HRV). This study examines the inter- and intrarater reliability of HRV) parameters derived from short-term recordings in individuals post-COVID. Sixty-nine participants of both genders post-COVID were included. The RR interval, the time elapsed between two successive R-waves of the QRS signal on the electrocardiogram (RRi), were recorded during a 10 min period in a supine position using a portable heart rate monitor (Polar^® V800 model). The data were transferred into Kubios^® HRV standard analysis software and analyzed within the stable sessions containing 256 sequential RRi. The intraclass correlation coefficient (ICC) ranged from 0.920 to 1.000 according to the intrarater analysis by Researcher 01 and 0.959 to 0.999 according to the intrarater by Researcher 02. The interrater ICC ranged from 0.912 to 0.998. The coefficient of variation was up to 9.23 for Researcher 01 intrarater analysis, 6.96 for Researcher 02 intrarater analysis and 8.83 for interrater analysis. The measurement of HRV in post-COVID-19 individuals is reliable and presents a small amount of error inherent to the method, supporting its use in the clinical environment and in scientific research.

The Apple Watch for Monitoring Mental Health-Related Physiological Symptoms: Literature Review

BACKGROUND

An anticipated surge in mental health service demand related to COVID-19 has motivated the use of novel methods of care to meet demand, given workforce limitations. Digital health technologies in the form of self-tracking technology have been identified as a potential avenue, provided sufficient evidence exists to support their effectiveness in mental health contexts.

OBJECTIVE

This literature review aims to identify current and potential physiological or physiologically related monitoring capabilities of the Apple Watch relevant to mental health monitoring and examine the accuracy and validation status of these measures and their implications for mental health treatment.

METHODS

A literature review was conducted from June 2021 to July 2021 of both published and gray literature pertaining to the Apple Watch, mental health, and physiology. The literature review identified studies validating the sensor capabilities of the Apple Watch.

RESULTS

A total of 5583 paper titles were identified, with 115 (2.06%) reviewed in full. Of these 115 papers, 19 (16.5%) were related to Apple Watch validation or comparison studies. Most studies showed that the Apple Watch could measure heart rate acceptably with increased errors in case of movement. Accurate energy expenditure measurements are difficult for most wearables, with the Apple Watch generally providing the best results compared with peers, despite overestimation. Heart rate variability measurements were found to have gaps in data but were able to detect mild mental stress. Activity monitoring with step counting showed good agreement, although wheelchair use was found to be prone to overestimation and poor performance on overground tasks. Atrial fibrillation detection showed mixed results, in part because of a high inconclusive result rate, but may be useful for ongoing monitoring. No studies recorded validation of the Sleep app feature; however, accelerometer-based sleep monitoring showed high accuracy and sensitivity in detecting sleep.

CONCLUSIONS

The results are encouraging regarding the application of the Apple Watch in mental health, particularly as heart rate variability is a key indicator of changes in both physical and emotional states. Particular benefits may be derived through avoidance of recall bias and collection of supporting ecological context data. However, a lack of methodologically robust and replicated evidence of user benefit, a supportive health economic analysis, and concerns about personal health information remain key factors that must be addressed to enable broader uptake.

Validity of the Polar H10 Sensor for Heart Rate Variability Analysis during Resting State and Incremental Exercise in Recreational Men and Women

Heart rate variability (HRV) is frequently applied in sport-specific settings. The rising use of freely accessible applications for its recording requires validation processes to ensure accurate data. It is the aim of this study to compare the HRV data obtained by the Polar H10 sensor chest strap device and an electrocardiogram (ECG) with the focus on RR intervals and short-term scaling exponent alpha 1 of Detrended Fluctuation Analysis (DFA a1) as non-linear metric of HRV analysis. A group of 25 participants performed an exhaustive cycling ramp with measurements of HRV with both recording systems. Average time between heartbeats (RR), heart rate (HR) and DFA a1 were recorded before (PRE), during, and after (POST) the exercise test. High correlations were found for the resting conditions (PRE: r = 0.95, rc = 0.95, ICC3,1 = 0.95, POST: r = 0.86, rc = 0.84, ICC3,1 = 0.85) and for the incremental exercise (r > 0.93, rc > 0.93, ICC3,1 > 0.93). While PRE and POST comparisons revealed no differences, significant bias could be found during the exercise test for all variables (p < 0.001). For RR and HR, bias and limits of agreement (LoA) in the Bland−Altman analysis were minimal (RR: bias of 0.7 to 0.4 ms with LoA of 4.3 to −2.8 ms during low intensity and 1.3 to −0.5 ms during high intensity, HR: bias of −0.1 to −0.2 ms with LoA of 0.3 to −0.5 ms during low intensity and 0.4 to −0.7 ms during high intensity). DFA a1 showed wider bias and LoAs (bias of 0.9 to 8.6% with LoA of 11.6 to −9.9% during low intensity and 58.1 to −40.9% during high intensity). Linear HRV measurements derived from the Polar H10 chest strap device show strong agreement and small bias compared with ECG recordings and can be recommended for practitioners. However, with respect to DFA a1, values in the uncorrelated range and during higher exercise intensities tend to elicit higher bias and wider LoA.

Comparison of Apple Watch Series 4 vs. KardiaMobile: A Tale of Two Devices

Background

The Apple Watch Series 4 (AW4) and the KardiaMobile single bipolar lead model (KM) are 2 of the most popular US Food & Drug Administration (FDA)-approved commercial heart trackers. However, a lack of knowledge remains regarding their rhythm-detection accuracy in real-life clinical situations. This paper aims to determine the practicality of using an AW4 or a KM in modern medical practice, by assessing the accuracy of each in identifying heart rhythms and heart rate.

Methods

Participants from the Toronto Heart Centre clinic were enrolled from January 2019 to December 2019. They had a 12-lead electrocardiogram (ECG), followed by wearing the AW4 watch (OS 5.3), and pressing on the KM electrode plates, within the span of 5 minutes of one another. Each session involved a 12-lead ECG, an ECG from each device, and AW4’s photoplethysmography function (APPG).

Results

Of 200 participants, 162 (81%) were in sinus rhythm, and 38 (19%) had atrial fibrillation. The rhythm-detection accuracy for sinus rhythm was 100% for the AW4, and 99.03% for the KM. For atrial fibrillation, accuracy was 90.48% for the AW4, and 100% for the KM. The heart rate accuracy for sinus rhythm was 94.39% for the KM, 90.65% for the APPG, and 96.26% for the Apple ECG function. The heart rate accuracy for atrial fibrillation was 91.30% for the KM, 82.61% for the APPG, and 86.96% for the Apple ECG function.

Conclusions

Both the AW4 and the KM could reliably detect rhythm and heart rate in real-life clinical situations. However, a nonsignificant trend occurred toward better rhythm detection and accuracy with KM, compared with AW4. The difference is mainly due to artifacts (eg, tremors) and the fit of the strap for AW4. The findings have important implications for how these consumer devices can be used in real-life clinical settings.

Full-Body Photobiomodulation Therapy Is Associated with Reduced Sleep Durations and Augmented Cardiorespiratory Indicators of Recovery

Research is emerging on the use of Photobiomodulation therapy (PBMT) and its potential for augmenting human performance, however, relatively little research exists utilizing full-body administration methods. As such, further research supporting the efficacy of whole-body applications of PBMT for behavioral and physiological modifications in applicable, real-world settings are warranted. The purpose of this analysis was to observe cardiorespiratory and sleep patterns surrounding the use of full-body PBMT in an elite cohort of female soccer players. Members of a women’s soccer team in a “Power 5 conference” of the National Collegiate Athletic Association (NCAA) were observed across one competitive season while wearing an OURA Ring nightly and a global positioning system (GPS) sensor during training. Within-subject comparisons of cardiorespiratory physiology, sleep duration, and sleep composition were evaluated the night before and after PBMT sessions completed as a standard of care for team recovery. Compared to pre-intervention, mean heart rate (HR) was significantly lower the night after a PBMT session (p = 0.0055). Sleep durations were also reduced following PBMT, with total sleep time (TST) averaging 40 min less the night after a session (p = 0.0006), as well as significant reductions in light sleep (p = 0.0307) and rapid eye movement (REM) sleep durations (p = 0.0019). Sleep durations were still lower following PBMT, even when controlling for daily and accumulated training loads. Enhanced cardiorespiratory indicators of recovery following PBMT, despite significant reductions in sleep duration, suggest that it may be an effective modality for maintaining adequate recovery from the high stress loads experienced by elite athletes.

Technical, Regulatory, Economic, and Trust Issues Preventing Successful Integration of Sensors into the Mainstream Consumer Wearables Market

Sensors that track physiological biomarkers of health must be successfully incorporated into a fieldable, wearable device if they are to revolutionize the management of remote patient care and preventative medicine. This perspective article discusses logistical considerations that may impede the process of adapting a body-worn laboratory sensor into a commercial-integrated health monitoring system with a focus on examples from sleep tracking technology.

Trends in Daily Heart Rate Variability Fluctuations Are Associated with Longitudinal Changes in Stress and Somatisation in Police Officers

The emergence of wearable sensors that allow for unobtrusive monitoring of physiological and behavioural patterns introduces new opportunities to study the impact of stress in a real-world context. This study explores to what extent within-subject trends in daily Heart Rate Variability (HRV) and daily HRV fluctuations are associated with longitudinal changes in stress, depression, anxiety, and somatisation. Nine Dutch police officers collected daily nocturnal HRV data using an Oura ring during 15–55 weeks. Participants filled in the Four-Dimensional Symptoms Questionnaire every 5 weeks. A sample of 47 five-week observations was collected and analysed using multiple regression. After controlling for trends in total sleep time, moderate-to-vigorous physical activity and alcohol use, an increasing trend in the seven-day rolling standard deviation of the HRV (HRVsd) was associated with increases in stress and somatisation over 5 weeks. Furthermore, an increasing HRV trend buffered against the association between HRVsd trend and somatisation change, undoing this association when it was combined with increasing HRV. Depression and anxiety could not be related to trends in HRV or HRVsd, which was related to observed floor effects. These results show that monitoring trends in daily HRV via wearables holds promise for automated stress monitoring and providing personalised feedback.

Validity of the Wrist-Worn Polar Vantage V2 to Measure Heart Rate and Heart Rate Variability at Rest

Heart rate (HR) and heart rate variability (HRV) can be monitored with wearable devices throughout the day. Resting HRV in particular, reflecting cardiac parasympathetic activity, has been proposed to be a useful marker in the monitoring of health and recovery from training. This study examined the validity of the wrist-based photoplethysmography (PPG) method to measure HR and HRV at rest. Recreationally endurance-trained participants recorded pulse-to-pulse (PP) and RR intervals simultaneously with a PPG-based watch and reference heart rate sensor (HRS) at a laboratory in a supine position (n = 39; 5-min recording) and at home during sleep (n = 29; 4-h recording). In addition, analyses were performed from pooled laboratory data (n = 11344 PP and RR intervals). Differences and correlations were analyzed between the HRS- and PPG-derived HR and LnRMSSD (the natural logarithm of the root mean square of successive differences). A very good agreement was found between pooled PP and RR intervals with a mean bias of 0.17 ms and a correlation coefficient of 0.993 (p < 0.001). In the laboratory, HR did not differ between the devices (mean bias 0.0 bpm), but PPG slightly underestimated the nocturnal recordings (mean bias -0.7 bpm, p < 0.001). PPG overestimated LnRMSSD both in the laboratory (mean bias 0.20 ms, p < 0.001) and nocturnal recordings (mean bias 0.17 ms, p < 0.001). However, very strong intraclass correlations in the nocturnal recordings were found between the devices (HR: 0.998, p < 0.001; LnRMSSD: 0.931, p < 0.001). In conclusion, PPG was able to measure HR and HRV with adequate accuracy in recreational athletes. However, when strict absolute values are of importance, systematic overestimation, which seemed to especially concern participants with low LnRMSSD, should be acknowledged.

What Is behind Changes in Resting Heart Rate and Heart Rate Variability? A Large-Scale Analysis of Longitudinal Measurements Acquired in Free-Living

The aim of this study was to investigate the relationship between heart rate and heart rate variability (HRV) with respect to individual characteristics and acute stressors. In particular, the relationship between heart rate, HRV, age, sex, body mass index (BMI), and physical activity level was analyzed cross-sectionally in a large sample of 28,175 individuals. Additionally, the change in heart rate and HRV in response to common acute stressors such as training of different intensities, alcohol intake, the menstrual cycle, and sickness was analyzed longitudinally. Acute stressors were analyzed over a period of 5 years for a total of 9 million measurements (320±374 measurements per person). HRV at the population level reduced with age (p < 0.05, r = -0.35, effect size = moderate) and was weakly associated with physical activity level (p < 0.05, r = 0.21, effect size = small) and not associated with sex (p = 0.35, d = 0.02, effect size = negligible). Heart rate was moderately associated with physical activity level (p < 0.05, r = 0.30, effect size = moderate) and sex (p < 0.05, d = 0.63, effect size = moderate) but not with age (p = 0.35, r = -0.01). Similar relationships between BMI, resting heart rate (p < 0.05, r = 0.19, effect size = small), and HRV (p < 0.05, r = -0.10, effect size = small) are shown. In response to acute stressors, we report a 4.6% change in HRV (p < 0.05, d = 0.36, effect size = small) and a 1.3% change in heart rate (p < 0.05, d = 0.38, effect size = small) in response to training, a 6% increase in heart rate (p < 0.05, d = 0.97, effect size = large) and a 12% reduction in HRV (p < 0.05, d = 0.55, effect size = moderate) after high alcohol intake, a 1.6% change in heart rate (p < 0.05, d = 1.41, effect size = large) and a 3.2% change in HRV (p < 0.05, d = 0.80, effect size = large) between the follicular and luteal phases of the menstrual cycle, and a 6% increase in heart rate (p < 0.05, d = 0.97, effect size = large) and 10% reduction in HRV (p < 0.05, d = 0.47, effect size = moderate) during sickness. Acute stressors analysis revealed how HRV is a more sensitive but not specific marker of stress. In conclusion, a short resting heart rate and HRV measurement upon waking using a smartphone app can effectively be used in free-living to quantify individual stress responses across a large range of individuals and stressors.

Consumer Wearables for Patient Monitoring in Otolaryngology: A State of the Art Review

OBJECTIVE

Consumer wearables, such as the Apple Watch or Fitbit devices, have become increasingly commonplace over the past decade. The application of these devices to health care remains an area of significant yet ill-defined promise. This review aims to identify the potential role of consumer wearables for the monitoring of otolaryngology patients.

DATA SOURCES

PubMed.

REVIEW METHODS

A PubMed search was conducted to identify the use of consumer wearables for the assessment of clinical outcomes relevant to otolaryngology. Articles were included if they described the use of wearables that were designed for continuous wear and were available for consumer purchase in the United States. Articles meeting inclusion criteria were synthesized into a final narrative review.

CONCLUSIONS

In the perioperative setting, consumer wearables could facilitate prehabilitation before major surgery and prediction of clinical outcomes. The use of consumer wearables in the inpatient setting could allow for early recognition of parameters suggestive of poor or declining health. The real-time feedback provided by these devices in the remote setting could be incorporated into behavioral interventions to promote patients' engagement with healthy behaviors. Various concerns surrounding the privacy, ownership, and validity of wearable-derived data must be addressed before their widespread adoption in health care.

IMPLICATIONS FOR PRACTICE

Understanding how to leverage the wealth of biometric data collected by consumer wearables to improve health outcomes will become a high-impact area of research and clinical care. Well-designed comparative studies that elucidate the value and clinical applicability of these data are needed.

Applying Heart Rate Variability to Monitor Health and Performance in Tactical Personnel: A Narrative Review

Human performance optimization of tactical personnel requires accurate, meticulous, and effective monitoring of biological adaptations and systemic recovery. Due to an increased understanding of its importance and the commercial availability of assessment tools, the use of heart rate variability (HRV) to address this need is becoming more common in the tactical community. Measuring HRV is a non-invasive, practical method for objectively assessing a performer's readiness, workload, and recovery status; when combined with additional data sources and practitioner input, it provides an affordable and scalable solution for gaining actionable information to support the facilitation and maintenance of operational performance. This narrative review discusses the non-clinical use of HRV for assessing, monitoring, and interpreting autonomic nervous system resource availability, modulation, effectiveness, and efficiency in tactical populations. Broadly, HRV metrics represent a complex series of interactions resulting from internal and external stimuli; therefore, a general overview of HRV applications in tactical personnel is discussed, including the influence of occupational specific demands, interactions between cognitive and physical domains, and recommendations on implementing HRV for training and recovery insights into critical health and performance outcomes.

Can Residential Greenspace Exposure Improve Pain Experience? A Comparison between Physical Visit and Image Viewing

Reducing the burden of pain via greenspace exposure is a rising research topic. However, insufficient evidence has been found in relation to the environmental effect itself. Residential greenspace, as a convenient but limited natural environment for urban dwellers, has benefits and services yet to be discovered. Therefore, the current study recruited 24 young adults to evaluate the effects of physical visit to, or image viewing of, residential greenspace on pain perception and related psychophysiological outcomes, via simulated pain. Pain threshold and tolerance were recorded via the level of pain stimuli, and pain intensity was evaluated using the Visual Analog Scale (VAS). The state scale of the State-Trait Anxiety Inventory (STAI-S) and two adjective pairs were employed to measure the state anxiety and subjective stress, respectively. Meanwhile, heart rate (HR), heart rate variability (HRV), and blood pressure (BP) were measured to investigate physiological responses. Besides, Scenic Beauty Estimation (SBE) was also employed to assess participants' preference regarding the experimental environments. The results revealed that visiting the greenspace significantly increased the pain threshold and tolerance, while no significant effect was observed for image viewing. On the other hand, no significant difference was observed in pain-related psychophysiological indices between the experimental settings, but significantly negative associations were found between the scores of SBE and subjective stress and state anxiety. In conclusion, the current study brings experimental evidence of improving pain experience via residential greenspace exposure, while the related psychophysiological benefits require further investigation.

The Promise of Sleep: A Multi-Sensor Approach for Accurate Sleep Stage Detection Using the Oura Ring

Consumer-grade sleep trackers represent a promising tool for large scale studies and health management. However, the potential and limitations of these devices remain less well quantified. Addressing this issue, we aim at providing a comprehensive analysis of the impact of accelerometer, autonomic nervous system (ANS)-mediated peripheral signals, and circadian features for sleep stage detection on a large dataset. Four hundred and forty nights from 106 individuals, for a total of 3444 h of combined polysomnography (PSG) and physiological data from a wearable ring, were acquired. Features were extracted to investigate the relative impact of different data streams on 2-stage (sleep and wake) and 4-stage classification accuracy (light NREM sleep, deep NREM sleep, REM sleep, and wake). Machine learning models were evaluated using a 5-fold cross-validation and a standardized framework for sleep stage classification assessment. Accuracy for 2-stage detection (sleep, wake) was 94% for a simple accelerometer-based model and 96% for a full model that included ANS-derived and circadian features. Accuracy for 4-stage detection was 57% for the accelerometer-based model and 79% when including ANS-derived and circadian features. Combining the compact form factor of a finger ring, multidimensional biometric sensory streams, and machine learning, high accuracy wake-sleep detection and sleep staging can be accomplished.