Accuracy of Optical Heart Rate Sensing Technology in Wearable Fitness Trackers for Young and Older Adults: Validation and Comparison Study

Allostatic Load Is Associated with Overuse Musculoskeletal Injury during US Marine Corps Officer Candidates School

INTRODUCTION

Overuse musculoskeletal injuries (MSKI) remain a significant medical challenge in military personnel undergoing military training courses; further understanding of the biological process leading to overuse MSKI development and biological signatures for injury risk are warranted. The purpose of this study was to determine the association between overuse MSKI occurrence and physiological characteristics of allostatic load characterized as maladaptive biological responses to chronic stress measured by wearable devices in US Marine Corps officer candidates during a 10-wk training course.

METHODS

Devices recorded energy expenditure (EE), daytime heart rate (HR), sleeping HR, and sleep architecture (time and percentage of deep, light, rapid eye movement sleep, awake time, total sleep). Flux was calculated as the raw or absolute difference in the average value for that day or night and the day or night beforehand. Linear mixed-effect model analysis accounting for cardiorespiratory fitness assessed the association between overuse MSKI occurrence and device metrics ( α = 0.05).

RESULTS

Sixty-nine participants (23 females) were included. Twenty-one participants (eight females) sustained overuse MSKI. Overuse MSKI occurrence in male participants was positively associated with daytime HR ( β = 5.316, P = 0.008), sleeping HR ( β = 2.708, P = 0.032), relative EE ( β = 8.968, P = 0.001), absolute flux in relative EE ( β = 2.994, P = 0.002), absolute EE ( β = 626.830, P = 0.001), and absolute flux in absolute EE ( β = 204.062, P = 0.004). Overuse MSKI occurrence in female participants was positively associated with relative EE ( β = 5.955, P = 0.026), deep sleep time ( β = 0.664, P < 0.001), and percent deep sleep ( β = 12.564, P < 0.001) and negatively associated with absolute flux in sleeping HR ( β = -0.660, P = 0.009).

CONCLUSIONS

Overuse MSKI occurrences were associated with physiological characteristics of allostatic load, including chronically elevated HR and EE and greater time in restorative sleep stages, which may serve as biological signatures for overuse MSKI risk.

Short- and medium-term cumulative effects of traffic-related air pollution on resting heart rate in the elderly: A wearable device study

BACKGROUND

Epidemiological evidence regarding the association between air pollution and resting heart rate (RHR), a predictor of cardiovascular disease and mortality, is limited and inconsistent.

OBJECTIVES

We used wearable devices and time-series analysis to assess the exposure-response relationship over an extended lag period.

METHODS

Ninety-seven elderly individuals (>65 years) from the Taipei Basin participated from May to November 2020 and wore Garmin® smartwatches continuously until the end of 2021 for heart rate monitoring. RHR was defined as the daily average of the lowest 30-min heart rate. Air pollution exposure data, covering lag periods from 0 to 60 days, were obtained from nearby monitoring stations. We used distributed lag non-linear models and linear mixed-effect models to assess cumulative effects of air pollution. Principal component analysis was utilized to explore underlying patterns in air pollution exposure, and subgroup analyses with interaction terms were conducted to explore the modification effects of individual factors.

RESULTS

After adjusting for co-pollutants in the models, an interquartile range increase of 0.18 ppm in carbon monoxide (CO) was consistently associated with increased RHR across lag periods of 0-1 day (0.31, 95 % confidence interval [CI]: 0.24-0.38), 0-7 days (0.68, 95 % CI: 0.57-0.79), and 0-50 days (1.02, 95 % CI: 0.82-1.21). Principal component analysis identified two factors, one primarily influenced by CO and nitrogen dioxide (NO2), indicative of traffic sources. Increases in the varimax-rotated traffic-related score were correlated with higher RHR over 0-1 day (0.36, 95 % CI: 0.25-0.47), 0-7 days (0.62, 95 % CI: 0.46-0.77), and 0-50 days (1.27, 95 % CI: 0.87-1.67) lag periods. Over a 0-7 day lag, RHR responses to traffic pollution were intensified by higher temperatures (β = 0.80 vs. 0.29; interaction p-value [P_int] = 0.011). Males (β = 0.66 vs. 0.60; P_int < 0.0001), hypertensive individuals (β = 0.85 vs. 0.45; P_int = 0.028), diabetics (β = 0.96 vs. 0.52; P_int = 0.042), and those with lower physical activity (β = 0.70 vs. 0.54; P_int < 0.0001) also exhibited stronger responses. Over a 0-50 day lag, males (β = 0.99 vs. 0.96; P_int < 0.0001), diabetics (β = 1.66 vs. 0.69; P_int < 0.0001), individuals with lower physical activity (β = 1.49 vs. 0.47; P_int = 0.0006), and those with fewer steps on lag day 1 (β = 1.17 vs. 0.71; P_int = 0.029) showed amplified responses.

CONCLUSIONS

Prolonged exposure to traffic-related air pollution results in cumulative cardiovascular risks, persisting for up to 50 days. These effects are more pronounced on warmer days and in individuals with chronic conditions or inactive lifestyles.

Impact of Skin Pigmentation on Pulse Oximetry Blood Oxygenation and Wearable Pulse Rate Accuracy: Systematic Review and Meta-Analysis

BACKGROUND

Photoplethysmography (PPG) is a technology routinely used in clinical practice to assess blood oxygenation (SpO2) and pulse rate (PR). Skin pigmentation may influence accuracy, leading to health outcomes disparities.

OBJECTIVE

This systematic review and meta-analysis primarily aimed to evaluate the accuracy of PPG-derived SpO2 and PR by skin pigmentation. Secondarily, we aimed to evaluate statistical biases and the clinical relevance of PPG-derived SpO2 and PR according to skin pigmentation.

METHODS

We identified 23 pulse oximetry studies (n=59,684; 197,353 paired SpO2-arterial blood observations) and 4 wearable PR studies (n=176; 140,771 paired PPG-electrocardiography observations). We evaluated accuracy according to skin pigmentation group by comparing SpO2 accuracy root-mean-square values to the regulatory threshold of 3% and PR 95% limits of agreement values to +5 or -5 beats per minute (bpm), according to the standards of the American National Standards Institute, Association for the Advancement of Medical Instrumentation, and the International Electrotechnical Commission. We evaluated biases and clinical relevance using mean bias and 95% CI.

RESULTS

For SpO2, accuracy root-mean-square values were 3.96%, 4.71%, and 4.15%, and pooled mean biases were 0.70% (95% CI 0.17%-1.22%), 0.27% (95% CI -0.64% to 1.19%), and 1.27% (95% CI 0.58%-1.95%) for light, medium, and dark pigmentation, respectively. For PR, 95% limits of agreement values were from -16.02 to 13.54, from -18.62 to 16.84, and from -33.69 to 32.54, and pooled mean biases were -1.24 (95% CI -5.31 to 2.83) bpm, -0.89 (95% CI -3.70 to 1.93) bpm, and -0.57 (95% CI -9.44 to 8.29) bpm for light, medium, and dark pigmentation, respectively.

CONCLUSIONS

SpO2 and PR measurements may be inaccurate across all skin pigmentation groups, breaching U.S. Food and Drug Administration guidance and industry standard thresholds. Pulse oximeters significantly overestimate SpO2 for both light and dark skin pigmentation, but this overestimation may not be clinically relevant. PRs obtained from wearables exhibit no statistically or clinically significant bias based on skin pigmentation.

From lab to life: Evaluating the reliability and validity of psychophysiological data from wearable devices in laboratory and ambulatory settings

Despite the increasing popularity of ambulatory assessment, the reliability and validity of psychophysiological signals from wearable devices is unproven in daily life settings. We evaluated the reliability and validity of physiological signals (electrocardiogram, ECG; photoplethysmography, PPG; electrodermal activity, EDA) collected from two wearable devices (Movisens EcgMove4 and Empatica E4) in the lab (N = 67) and daily life (N = 20) among adults aged 18-64 with Mindware as the laboratory gold standard. Results revealed that both wearable devices' valid data rates in daily life were lower than in the laboratory (Movisens ECG 82.94 vs. 93.10%, Empatica PPG 8.79 vs. 26.14%, and Empatica EDA 41.16 vs. 42.67%, respectively). The poor valid data rates of Empatica PPG signals in the laboratory could be partially attributed to participants' hand movements (r = - .27, p = .03). In laboratory settings, heart rate (HR) derived from both wearable devices exhibited higher concurrent validity than heart rate variability (HRV) metrics (ICCs 0.98-1.00 vs. 0.75-0.97). The number of skin conductance responses (SCRs) derived from Empatica showed higher concurrent validity than skin conductance level (SCL, ICCs 0.38 vs. 0.09). Movisens EcgMove4 provided more reliable and valid HRV measurements than Empatica E4 in both laboratory (split-half reliability: 0.95-0.99 vs. 0.85-0.98; concurrent validity: 0.95-1.00 vs. 0.75-0.98; valid data rate: 93.10 vs. 26.14%) and ambulatory settings (split-half reliability: 0.99-1.00 vs. 0.89-0.98; valid data rate: 82.94 vs. 8.79%). Although the reliability and validity of wearable devices are improving, findings suggest researchers should select devices that yield consistently robust and valid data for their measures of interest.

Validity of Current Smartwatches for Triathlon Training: How Accurate Are Heart Rate, Distance, and Swimming Readings?

Smartwatches are one of the most relevant fitness trends of the past two decades, and they collect increasing amounts of health and movement data. The accuracy of these data may be questionable and requires further investigation. Therefore, the aim of the present study is to validate smartwatches for use in triathlon training. Ten different smartwatches were tested for accuracy in measuring heart rates, distances (via global navigation satellite systems, GNSSs), swim stroke rates and the number of swim laps in a 50 m Olympic-size pool. The optical heart rate measurement function of each smartwatch was compared to that of a chest strap. Thirty participants (15 females, 15 males) ran five 3 min intervals on a motorised treadmill to evaluate the accuracy of the heart rate measurements. Moreover, for each smartwatch, running and cycling distance tracking was tested over six runs of 4000 m on a 400 m tartan stadium track, six hilly outdoor runs over 3.4 km, and four repetitions of a 36.8 km road bike course, respectively. Three swimming protocols ranging from 200 m to 400 m were performed in triplicate in a 50 m Olympic-size pool, evaluating the tracked distance and the detected number of strokes. The mean absolute percentage errors (MAPEs) for the average heart rate measurements varied between 3.1% and 8.3%, with the coefficient of determination ranging from 0.22 to 0.79. MAPE results ranged from 0.8% to 12.1% for the 4000 m run on the 400 m track, from 0.2% to 7.5% for the 3.4 km outdoor run, and from 0.0% to 4.2% for the 36.8 km bike ride. For the swimming tests, in contrast, the deviations from the true distance varied greatly, starting at a 0.0% MAPE for the 400 m freestyle and reaching 91.7% for the 200 m medley with style changes every 25 m. In summary, for some of the smartwatches, the measurement results deviated substantially from the true values. Measurements taken while road cycling over longer distances with only a few curves were in relative terms more accurate than those taken during outdoor runs and even more accurate than those taken on the 400 m track. In the swimming exercises, the accuracy of the measured distances was severely deteriorated by the medley changes among the majority of the smartwatches. Altogether, the results of this study should help in assessing the accuracy and thus the suitability of smartwatches for general triathlon training.

Why do generation X customers use wearable fitness technology equipment after recovering from coronavirus? The role of perceived health risks

The health sector has prioritized the physical health of vulnerable Generation X individuals at high Coronavirus risk. Despite vaccination efforts, both infected and healthy people continue facing health threats. Unlike other industries devastated by COVID-19, wearable fitness technology equipment (WFTE) is essential for health-focused individuals. This research examined customers' intention to use WFTE using an adapted Technology Acceptance Model (TAM) framework. A key contribution is the inclusion of perceived health risk and its impact on WFTE value perceptions and usage attitudes post-pandemic. The study gathered qualitative data from coronavirus patients and survey data from 513 participants. Structural equation modeling analysis supported the theoretical model. While the standard TAM evaluated intent to use WFTE, this study uniquely examined how WFTE's functional, hedonic, and symbolic value shapes its perceived value. Perceived health risk was found to significantly impact perceived WFTE value and usage attitudes after the pandemic recovery. Findings offer managerial implications to boost WFTE adoption among the vulnerable Generation X demographic.

Case example of a female solo sailor competing in the Vendée Globe reveals extraordinary biological demands

The Vendée Globe is a non-stop, unassisted, single-handed round the world sailing race. It is regarded as the toughest sailing race, requiring high cognitive functioning and constant alertness. Little is known about the amount of sleep restriction and nutritional deficit experienced at sea and effects that fatigue have on sailors' performance. This report aimed to investigate these aspects by monitoring one of the female participants of the latest Vendée Globe. Sleep, food intake and stress were self-reported daily using specific app. Cognitive assessments were digitally completed. Heart rate and activity intensity were measured using a wrist-worn wearable device. Mean self-report sleep duration per 24 h was 3 hours 40 minutes. By the end of the 95 race days, the sailor reached a caloric deficit of 27,900 kcal. On average, the sailor spent 50 minutes per day in moderate-to-vigorous activity. Cognitive assessments did not show any effect of fatigue or stress on completion time or performance. Recent technological and communication advancement for offshore sailors, enabled continuous data to be monitored in near real time, even from the Southern Ocean. Moving forward this will enable greater understanding of when sailors will be at risk of poor decision making, illness or injury.

Exercising with a robotic exoskeleton can improve memory and gait in people with Parkinson's disease by facilitating progressive exercise intensity

People with Parkinson's disease (PwPD) can benefit from progressive high-intensity exercise facilitated with a lower-extremity exoskeleton, but the mechanisms explaining these benefits are unknown. We explored the relationship between exercise intensity progression and memory and gait outcomes in PwPD who performed 8 weeks (2 × per week) of progressive exercise with and without a lower-extremity powered exoskeleton, as the planned exploratory endpoint analysis of an open-label, parallel, pilot randomized controlled trial. Adults 50-85 years old with a confirmed diagnosis of PD participated. Twenty-seven participants randomized to exercise with (Exo = 13) or without (Nxo = 14) the exoskeleton were included in this exploratory endpoint analysis. Detailed exercise logs were kept and actigraphy was used to measure activity count*min-1 (ACPM) during all exercise sessions. Only the Exo group were able to progressively increase their ACPM over the entire 8-week intervention, whereas the Nxo group plateaued after 4 weeks. Exercise intensity progression correlated with change in the memory sub-scale of the SCOPA-COG and change in gait endurance from the 6MWT, consistent with the prevailing hypotheses linking high-intensity interval exercise to improved muscle and brain function via angiogenic and neurotrophic mechanisms. Facilitating high-intensity exercise with advanced rehabilitation technology is warranted for improving memory and gait endurance in PwPD.Registration: ClinicalTrials.gov, NCT03583879 (7/10/2018).

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.

Sports Heart Monitors as Reliable Diagnostic Tools for Training Control and Detecting Arrhythmias in Professional and Leisure-Time Endurance Athletes: An Expert Consensus Statement

There are countless types of portable heart rate monitoring medical devices used variously by leisure-time exercisers, professional athletes, and chronically ill patients. Almost all the currently used heart rate monitors are capable of detecting arrhythmias, but this feature is not widely known or used among their millions of consumers. The aims of this paper were as follows: (1) to analyze the currently available sports heart rate monitors and assess their advantages and disadvantage in terms of heart rate and rhythm monitoring in endurance athletes; (2) to discuss what types of currently available commercial heart rate monitors are most convenient/adjustable to the needs of different consumers (including occasionally physically active adults and cardiac patients), bearing in mind the potential health risks, especially heart rhythm disturbances connected with endurance training; (3) to suggest a set of "optimal" design features for next-generation smart wearable devices based on the consensus opinion of an expert panel of athletes, coaches, and sports medicine doctors. Ninety-two experts aged 20 years and over, involved in endurance sports on a daily basis, were invited to participate in consensus-building discussions, including 56 long-distance runners, 18 cyclists, nine coaches, and nine physicians (sports medicine specialists, cardiologists, and family medicine doctors). The overall consensus endorsed by these experts indicates that the "optimal" sports heart rate monitor should be a one-piece device of the smartwatch type (with two or more electrodes), with integrated smartphone features, and able to collect and continually transmit data without exhibiting artifacts. It should continuously record at least a single-lead electrocardiography, send an alert after an unexpected fall, be of reasonable weight, come at an affordable price, and be user friendly.

Empowering Participatory Research in Urban Health: Wearable Biometric and Environmental Sensors for Activity Recognition

Participatory exposure research, which tracks behaviour and assesses exposure to stressors like air pollution, traditionally relies on time-activity diaries. This study introduces a novel approach, employing machine learning (ML) to empower laypersons in human activity recognition (HAR), aiming to reduce dependence on manual recording by leveraging data from wearable sensors. Recognising complex activities such as smoking and cooking presents unique challenges due to specific environmental conditions. In this research, we combined wearable environment/ambient and wrist-worn activity/biometric sensors for complex activity recognition in an urban stressor exposure study, measuring parameters like particulate matter concentrations, temperature, and humidity. Two groups, Group H (88 individuals) and Group M (18 individuals), wore the devices and manually logged their activities hourly and minutely, respectively. Prioritising accessibility and inclusivity, we selected three classification algorithms: k-nearest neighbours (IBk), decision trees (J48), and random forests (RF), based on: (1) proven efficacy in existing literature, (2) understandability and transparency for laypersons, (3) availability on user-friendly platforms like WEKA, and (4) efficiency on basic devices such as office laptops or smartphones. Accuracy improved with finer temporal resolution and detailed activity categories. However, when compared to other published human activity recognition research, our accuracy rates, particularly for less complex activities, were not as competitive. Misclassifications were higher for vague activities (resting, playing), while well-defined activities (smoking, cooking, running) had few errors. Including environmental sensor data increased accuracy for all activities, especially playing, smoking, and running. Future work should consider exploring other explainable algorithms available on diverse tools and platforms. Our findings underscore ML's potential in exposure studies, emphasising its adaptability and significance for laypersons while also highlighting areas for improvement.

Assessment of Heart Rate Monitoring During Exercise With Smart Wristbands and a Heart Rhythm Patch: Validation and Comparison Study

BACKGROUND

The integration of wearable devices into fitness routines, particularly in military settings, necessitates a rigorous assessment of their accuracy. This study evaluates the precision of heart rate measurements by locally manufactured wristbands, increasingly used in military academies, to inform future device selection for military training activities.

OBJECTIVE

This research aims to assess the reliability of heart rate monitoring in chest straps versus wearable wristbands.

METHODS

Data on heart rate and acceleration were collected using the Q-Band Q-69 smart wristband (Mobile Action Technology Inc) and compared against the Zephyr Bioharness standard measuring device. The Lin concordance correlation coefficient, Pearson product moment correlation coefficient, and intraclass correlation coefficient were used for reliability analysis.

RESULTS

Participants from a Northern Taiwanese medical school were enrolled (January 1-June 31, 2021). The Q-Band Q-69 demonstrated that the mean absolute percentage error (MAPE) of women was observed to be 13.35 (SD 13.47). Comparatively, men exhibited a lower MAPE of 8.54 (SD 10.49). The walking state MAPE was 7.79 for women and 10.65 for men. The wristband's accuracy generally remained below 10% MAPE in other activities. Pearson product moment correlation coefficient analysis indicated gender-based performance differences, with overall coefficients of 0.625 for women and 0.808 for men, varying across walking, running, and cooldown phases.

CONCLUSIONS

This study highlights significant gender and activity-dependent variations in the accuracy of the MobileAction Q-Band Q-69 smart wristband. Reduced accuracy was notably observed during running. Occasional extreme errors point to the necessity of caution in relying on such devices for exercise monitoring. The findings emphasize the limitations and potential inaccuracies of wearable technology, especially in high-intensity physical activities.

Using wearable activity trackers for research in the global south: Lessons learned from adolescent psychotherapy research in Kenya

Wearable activity trackers have emerged as valuable tools for health research, providing high-resolution data on measures such as physical activity. While most research on these devices has been conducted in high-income countries, there is growing interest in their use in the global south. This perspective discusses the challenges faced and strategies employed when using wearable activity trackers to test the effects of a school-based intervention for depression and anxiety among Kenyan youth. Lessons learned include the importance of validating data output, establishing an internal procedure for international procurement, providing on-site support for participants, designating a full-time team member for wearable activity tracker operation, and issuing a paper-based information sheet to participants. The insights shared in this perspective serve as guidance for researchers undertaking studies with wearables in similar settings, contributing to the evidence base for mental health interventions targeting youth in the global south. Despite the challenges to set up, deploy and extract data from wearable activity trackers, we believe that wearables are a relatively economical approach to provide insight into the daily lives of research participants, and recommend their use to other researchers.

Assessing the Validity of Several Heart Rate Monitors in Wearable Technology While Mountain Biking

Purpose

This study sought to assess the validity of several heart rate (HR) monitors in wearable technology during mountain biking (MTB), compared to the Polar H7® HR monitor, used as the criterion device.

Methods

A total of 20 participants completed two MTB trials while wearing six HR monitors (5 test devices, 1 criterion). HR was recorded on a second-by-second basis for all devices analyzed. After data processing, validity measures were calculated, including 1. error analysis: mean absolute percentage errors (MAPE), mean absolute error (MAE), and mean error (ME), and 2. Correlation analysis: Lin's concordance correlation coefficient (CCC) and Pearson's correlation coefficient (r). Thresholds for validity were set at MAPE < 10% and CCC > 0.7.

Results

The only device that was found to be valid during mountain biking was the Suunto Spartan Sport watch with accompanying HR monitor, with a MAPE of 0.66% and a CCC of 0.99 for the overall, combined data.

Conclusion

If a person would like to track their HR during mountain biking, for pacing, training, or other reasons, the devices best able to produce valid results are chest-based, wireless electrocardiogram (ECG) monitors, secured by elastic straps to minimize the movement of the device, such as the Suunto chest-based HR monitor.

Innovative and disruptive technologies to prescribe, encourage, and evaluate physical exercise in healthy adults: a protocol of exploratory study followed by a noninferiority, investigator-blinded randomized clinical trial

BACKGROUND

Cardiovascular diseases are a leading cause of mortality worldwide. A significant contributing factor to this mortality is the lack of engagement in preventive activities. Consequently, strategies for enhancing adherence to and duration of physical activity (PA) have become pivotal. This project aims to create and validate innovative, disruptive, and secure technologies that ensure appropriate exercise intensity, bolster adherence to PA, and monitor health biomarker responses pre-, during, and post-physical activity.

METHODS

This exploratory study, followed by a noninferiority, investigator-blinded randomized clinical trial, will be divided into three phases: (1) development and validation of a sensor for real-time biofeedback during a functional assessment test; (2) integration of biofeedback and gamification into an app for the structured prescription of physical training within a controlled setting; and (3) implementation of biofeedback and gamification into an app for the prescription and monitoring of physical training in an uncontrolled setting. Phase 1 entails a validation test of a biosensor-monitoring heart rate (HR) and steps-during a modified shuttle walk test. In phase 2, the biosensor interfaces with a gamified smartphone application. The training regimen spans 6 weeks, 5 days weekly, with each session lasting 60 min: a five-min warm-up involving stationary gait, followed by 50 min of training at the target HR on the step and concluding with a five-min cool-down at a stationary pace. After 6 weeks of training, a new functional capacity test is conducted. Phase 3 involves an investigator-blinded, randomized clinical trial to demonstrate noninferiority. Participants are randomly assigned to either the intervention group (IG) or the control group (CG). IG participants practice exercise using the gamified application in an uncontrolled environment according to the prescribed method outlined in phase 2. CG participants receive PA practice guidelines exclusively.

DISCUSSION

Anticipated outcomes include improved exercise adherence through the gamified application, better maintenance of prescribed exercise intensity, and enhanced health biomarkers. The results of this study will inform health-related decision-making.

TRIAL REGISTRATION

The study protocol received approval from the Ethics Committee of Universidade Federal de Ciências da Saúde de Porto Alegre (54,492,221.80000.5345) and has been registered with the Brazilian Registry of Clinical Trials (ReBEC, RBR-359p69v).

Heart rate responses, agreement and accuracy among persons with severe disabilities participating in the indirect movement program: Team Twin-an observational study

Introduction

Heart rate (HR) monitors are rarely used by people living with disabilities (PLWD), and their accuracy is undocumented. Thus, this study aims to describe the HR response during the Team Twin co-running program and, secondly, to assess the agreement and accuracy of using HR monitors among PLWD.

Methods

This 16-week single-arm observational study included 18 people with various disabilities. During the study, the subjects wore a Garmin Vivosmart 4 watch (wrist). To evaluate the agreement and accuracy we applied Garmin's HRM-DUAL™ chest-worn HR monitors for comparison with the Vivosmart 4. The HR response analysis was performed descriptively and with a mixed regression model. The HR agreement and accuracy procedure was conducted on a subsample of five subjects and analyzed using Lin's concordance analysis, Bland and Altman's limits of agreement, and Cohen's kappa analysis of intensity zone agreement. This study was prospectively registered at Clinical Trials.gov (NCT04536779).

Results

The subjects had a mean age of 35 (±12.6), 61% were male, 72% had cerebral palsy were 85% had GMFCS V-IV. HR was monitored for 202:10:33 (HH:MM:SS), with a mean HR of 90 ± 17 bpm during training and race. A total of 19% of the time was spent in intensity zones between light and moderate (30%-59% HR reserve) and 1% in vigorous (60%-84% HR reserve). The remaining 80% were in the very light intensity zone (<29% HR reserve). HR was highest at the start of race and training and steadily decreased. Inter-rater agreement was high (k = 0.75), limits of agreement were between -16 and 13 bpm, and accuracy was acceptable (Rc = 0.86).

Conclusion

Disability type, individual, and contextual factors will likely affect HR responses and the agreement and accuracy for PLWD. The Vivosmart 4, while overall accurate, had low precision due to high variability in the estimation. These findings implicate the methodical and practical difficulties of utilizing HR monitors to measure HR and thus physical activity in adapted sports activities for severely disabled individuals.

PhysioKit: An Open-Source, Low-Cost Physiological Computing Toolkit for Single- and Multi-User Studies

The proliferation of physiological sensors opens new opportunities to explore interactions, conduct experiments and evaluate the user experience with continuous monitoring of bodily functions. Commercial devices, however, can be costly or limit access to raw waveform data, while low-cost sensors are efforts-intensive to setup. To address these challenges, we introduce PhysioKit, an open-source, low-cost physiological computing toolkit. PhysioKit provides a one-stop pipeline consisting of (i) a sensing and data acquisition layer that can be configured in a modular manner per research needs, and (ii) a software application layer that enables data acquisition, real-time visualization and machine learning (ML)-enabled signal quality assessment. This also supports basic visual biofeedback configurations and synchronized acquisition for co-located or remote multi-user settings. In a validation study with 16 participants, PhysioKit shows strong agreement with research-grade sensors on measuring heart rate and heart rate variability metrics data. Furthermore, we report usability survey results from 10 small-project teams (44 individual members in total) who used PhysioKit for 4-6 weeks, providing insights into its use cases and research benefits. Lastly, we discuss the extensibility and potential impact of the toolkit on the research community.

The effect of the COVID-19 pandemic on substance use patterns and physiological dysregulation in pregnant and postpartum women

BACKGROUND

The SARS-CoV-2/COVID-19 pandemic has been associated with increased stress levels and higher alcohol use, including in pregnant and postpartum women. In the general population, alcohol use is associated with dysregulation in the autonomic nervous system (ANS), which is indexed by heart rate variability (HRV). The objectives of this study were to: (1) characterize changes in substance use during the SARS-CoV-2/COVID-19 pandemic via a baseline self-report survey followed by mobile ecological momentary assessment (mEMA) of substance use; and (2) examine the associations between momentary substance use and ambulatory HRV measures in pregnant and postpartum women.

METHODS

Pregnant and postpartum women were identified from the ENRICH-2 prospective cohort study. Participants were administered a baseline structured phone interview that included the Coronavirus Perinatal Experiences (COPE) survey and ascertained the prevalence of substance use. Over a 14-day period, momentary substance use was assessed three times daily, and HRV measurements were captured via wearable electronics. Associations between momentary substance use and HRV measures (root mean square of successive differences [RMSSD] and low frequency/high frequency [LF/HF] ratio) were examined using a mixed effects model that included within-subject (WS) and between-subject (BS) effects and adjusted for pregnancy status and participant age.

RESULTS

The sample included 49 pregnant and 22 postpartum women. From a combination of a baseline and 14-day mEMA surveys, 21.2% reported alcohol use, 16.9% reported marijuana use, and 8.5% reported nicotine use. WS effects for momentary alcohol use were associated with the RMSSD (β = -0.14; p = 0.005) and LF/HF ratio (β = 0.14; p = 0.01) when controlling for pregnancy status and maternal age. No significant associations were observed between HRV measures and instances of marijuana or nicotine use.

CONCLUSIONS

These findings highlight the negative effect of the SARS-CoV-2/COVID-19 pandemic on the psychological health of pregnant and postpartum women associated with substance use, and in turn, ANS dysregulation, which potentially puts some women at risk of developing a substance use disorder.

Personalized, Naturalistic Virtual Reality Scenarios Coupled With Web-Based Progressive Muscle Relaxation Training for the General Population: Protocol for a Proof-of-Principle Randomized Controlled Trial

BACKGROUND

Virtual reality (VR) is an innovative tool that can facilitate exposure to either stressful or relaxing stimuli and enables individuals who have difficulties visualizing scenes to be involved in a more realistic sensorimotor experience. It also facilitates multisensory stimulation, a sense of presence, and achievement of relaxation. VR scenarios representing visual and auditory elements of natural relaxing environments can facilitate the learning of relaxation techniques such as the progressive muscle relaxation technique (PMRT). A complementary standardized technique deployed to reduce anxiety symptoms is the integration of PMRT and guided imagery (GI). Exposure to a pleasant imaginary environment helps the establishment of an association between a relaxing scenario and the relaxation technique, consequently promoting relaxation. Empirical evidence has shown that VR scenarios can increase the effects of relaxation techniques by enabling people to experience emotional conditions in more vivid settings.

OBJECTIVE

The main aim of this pilot study protocol is to investigate the impact on state anxiety of PMRT, associated with a personalized relaxing scenario in VR, and the role of VR scenarios in facilitating the recall of relaxing images and a sense of presence. A secondary aim is to understand if relaxing sessions administered via Zoom are more effective for managing anxiety and stress than a procedural setting based on audio-track guidance.

METHODS

Based on a longitudinal, between-subject design, 108 university students will be randomly exposed to one of three experimental conditions: (1) PMRT via Zoom and GI exposure, (2) PMRT via Zoom and personalized VR exposure, and (3) PMRT based on audio-track guidance and personalized VR exposure. Individuals are assessed before and after 7 training sessions based on self-report questionnaires investigating anxiety, depression, quality of life, coping strategies, sense of presence, engagement, and side effects related to VR exposure. Heart rate data are also detected by an Mi Band 2 sensor.

RESULTS

The experimental procedure is ongoing. In this paper, preliminary data from a sample of 40 participants will be illustrated. The experimental phase is expected to conclude in May 2023, and the final results of the research will be presented in June 2023.

CONCLUSIONS

The results of this study will help shape the experimental design to apply it on a subsequent randomized controlled trial, also considering clinical samples. This work is expected to measure whether VR is a more engaging and helpful technique in promoting relaxation and decreasing anxiety levels than GI, by making the visualization process easier and by helping people to face more realistic sensory experiences. Assessing the efficacy of the PMRT in alternative delivery modes may extend its applications, especially in situations where the standard procedure is more challenging to be administered. To our knowledge, no equivalent study has been published so far on this matter.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05478941; https://clinicaltrials.gov/ct2/show/NCT05478941.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/44183.

Measure by measure: Resting heart rate across the 24-hour cycle

BACKGROUND

Photoplethysmography (PPG) sensors, typically found in wrist-worn devices, can continuously monitor heart rate (HR) in large populations in real-world settings. Resting heart rate (RHR) is an important biomarker of morbidities and mortality, but no universally accepted definition nor measurement criteria exist. In this study, we provide a working definition of RHR and describe a method for accurate measurement of this biomarker, recorded using PPG derived from wristband measurement across the 24-hour cycle.

METHODS

433 healthy subjects wore a wrist device that measured activity and HR for up to 3 months. HR during inactivity was recorded and the duration of inactivity needed for HR to stabilise was ascertained. We identified the lowest HR during each 24-hour cycle (true RHR) and examined the time of day or night this occurred. The variation of HR during inactivity through the 24-hour cycle was also assessed. The sample was also subdivided according to daily activity levels for subset analysis.

FINDINGS

Adequate data was obtained for 19,242 days and 18,520 nights. HR stabilised in most subjects after 4 minutes of inactivity. Mean (SD) RHR for the sample was 54.5 (8.0) bpm (day) and 50.5 (7.6) bpm (night). RHR values were highest in the least active group (lowest MET quartile). A circadian variation of HR during inactivity was confirmed, with the lowest values being between 0300 and 0700 hours for most subjects.

INTERPRETATION

RHR measured using a PPG-based wrist-worn device is significantly lower at night than in the day, and a circadian rhythm of HR during inactivity was confirmed. Since RHR is such an important health metric, clarity on the definition and measurement methodology used is important. For most subjects, a minimum rest time of 4 minutes provides a reliable measurement of HR during inactivity and true RHR in a 24-hour cycle is best measured between 0300 and 0700 hours. Funding: This study was funded by Google.

Cardiorespiratory Assessments in Panic Disorder Facilitated by Wearable Devices: A Systematic Review and Brief Comparison of the Wearable Zephyr BioPatch with the Quark-b2 Stationary Testing System

Abnormalities in cardiorespiratory measurements have repeatedly been found in patients with panic disorder (PD) during laboratory-based assessments. However, recordings performed outside laboratory settings are required to test the ecological validity of these findings. Wearable devices, such as sensor-imbedded garments, biopatches, and smartwatches, are promising tools for this purpose. We systematically reviewed the evidence for wearables-based cardiorespiratory assessments in PD by searching for publications on the PubMed, PsycINFO, and Embase databases, from inception to 30 July 2022. After the screening of two-hundred and twenty records, eight studies were included. The limited number of available studies and critical aspects related to the uncertain reliability of wearables-based assessments, especially concerning respiration, prevented us from drawing conclusions about the cardiorespiratory function of patients with PD in daily life. We also present preliminary data on a pilot study conducted on volunteers at the Villa San Benedetto Menni Hospital for evaluating the accuracy of heart rate (HR) and breathing rate (BR) measurements by the wearable Zephyr BioPatch compared with the Quark-b2 stationary testing system. Our exploratory results suggested possible BR and HR misestimation by the wearable Zephyr BioPatch compared with the Quark-b2 system. Challenges of wearables-based cardiorespiratory assessment and possible solutions to improve their reliability and optimize their significant potential for the study of PD pathophysiology are presented.

Exploring the effects of a wearable biocueing app (Sense-IT) as an addition to aggression regulation therapy in forensic psychiatric outpatients

Objective

Preventing and reducing violence is of high importance for both individuals and society. However, the overall efficacy of current treatment interventions aimed at reducing aggressive behavior is limited. New technological-based interventions may enhance treatment outcomes, for instance by facilitating out-of-session practice and providing just-in-time support. Therefore, the aim of this study was to assess the effects of the Sense-IT biocueing app as an addition to aggression regulation therapy (ART) on interoceptive awareness, emotion regulation, and aggressive behavior among forensic outpatients.

Methods

A combination of methods was used. Quantitatively, a pretest-posttest design was applied to explore group changes in aggression, emotion regulation, and anger bodily sensations associated with the combination of biocueing intervention and ART. Measures were assessed at pretest, after 4 weeks posttest, and after one-month follow-up. During the 4 weeks, a single-case experimental ABA design was applied for each participant. Biocueing was added in the intervention phase. During all phases anger, aggressive thoughts, aggressive behavior, behavioral control, and physical tension were assessed twice a day, and heart rate was measured continuously. Qualitative information regarding interoceptive awareness, coping, and aggression was collected at posttest. 25 forensic outpatients participated.

Results

A significant decrease in self-reported aggression was found between pre- and posttest. Furthermore, three-quarters of participants reported increased interoceptive awareness associated with the biocueing intervention. However, the repeated ambulatory measurements of the single-case experimental designs (SCEDs) did not indicate a clear effect favoring the addition of biocueing. On group level, no significant effects were found. On the individual level, effects favoring the intervention were only found for two participants. Overall, effect sizes were small.

Conclusion

Biocueing seems a helpful addition to increase interoceptive awareness among forensic outpatients. However, not all patients benefit from the current intervention and, more specifically, from its behavioral support component aimed at enhancing emotion regulation. Future studies should therefore focus on increasing usability, tailoring the intervention to individual needs, and on integration into therapy. Individual characteristics associated with effective support by a biocueing intervention should be further investigated, as the use of personalized and technological-based treatment interventions is expected to increase in the coming years.

Accuracy and Validity of Commercial Smart Bands for Heart Rate Measurements During Cardiopulmonary Exercise Test

OBJECTIVE

To assess the accuracies and validities of popular smart bands for heart rate (HR) measurement in cardiovascular disease (CVD) patients during a graded exercise test (GXT).

METHODS

Seventy-eight patients were randomly assigned to wear two different smart bands out of three possible choices: Samsung Galaxy Fit 2, Xiaomi Mi Band 5, or Partron PWB-250 on each wrist. A 12-lead exercise electrocardiogram (ECG) and patch-type single-lead ECG were used to assess the comparative HR accuracy of the smart bands. The HR was recorded during the GXT using the modified Bruce protocol.

RESULTS

The concordance correlation coefficients (rc) were calculated to provide a measure of agreement between each device and the ECG. In all conditions, the Mi Band 5 and Galaxy Fit 2' correlations were rc>0.90, while the PWB-250 correlation was rc=0.58 at rest. When evaluating the accuracy according to the magnitude of HR, all smart bands performed well (rc>0.90) when the HR was below 100 but accuracy tended to decrease with higher HR values.

CONCLUSION

This study showed that the three smart bands had a high level of accuracy for HR measurements during low-intensity exercise. However, during moderate-intensity and high-intensity exercise, all the three smart bands performed less accurately. Further studies are needed to find a more optimal smart band for HR measurement that can be used for precise HR monitoring during formal cardiac rehabilitation exercise training, including at high and maximal intensity (Clinical Trial Registration No. cris.nih.go.kr/KCT0007036).

Sensor technology in eating disorders research: A systematic review

OBJECTIVE

Sensor technologies offer exciting potential to objectively measure psychopathological correlates of eating pathology and eating disorder (ED) research utilizing sensors has rapidly proliferated in the past several years. The aims of the present review are: (1) characterize the types of sensors that have been utilized in ED research, (2) identify the psychopathological factors relevant to EDs that have been assessed using sensors, (3) describe the data supporting the validity and reliability of these sensors, (4) discuss limitations associated with these sensors, and (5) identify gaps that persist within the ED literature with regard to use of sensor technologies.

METHOD

A systematic search was conducted of PubMed, PsycINFO, Web of Science, ProQuest, and "gray" literature sources. Eligible publications were empirical studies that utilized sensors to measure at least one psychological variable among clinical ED populations.

RESULTS

Sensors have been utilized with ED samples to measure eating behaviors, physical activity, sleep, autonomic nervous system activity, eyeblink startle response, visual attention, and visual-haptic object integration. The reliability and validity of these sensors varies widely and there are a number of significant gaps that remain in the literature with regard to the types of sensors utilized, context in which sensors have been used, and populations studied.

DISCUSSION

The existing literature utilizing sensors within ED research largely support the feasibility and acceptability of these tools. Sensors should continue to be utilized within the field, with a specific focus on examining the reliability and validity of these tools within ED samples and increasing the diversity of samples studied.

PUBLIC SIGNIFICANCE STATEMENT

Sensor technologies, such as those included in modern smartwatches, offer new opportunities to measure factors that may maintain or contribute to symptoms of eating disorders. This article describes the types of sensors that have been used in eating disorders research, challenges that may arise in using these sensors, and discusses new applications of these sensors that may be pursued in future research.

Wearable activity trackers-advanced technology or advanced marketing?

Wearable devices represent one of the most popular trends in health and fitness. Rapid advances in wearable technology present a dizzying display of possible functions: from thermometers and barometers, magnetometers and accelerometers, to oximeters and calorimeters. Consumers and practitioners utilize wearable devices to track outcomes, such as energy expenditure, training load, step count, and heart rate. While some rely on these devices in tandem with more established tools, others lean on wearable technology for health-related outcomes, such as heart rhythm analysis, peripheral oxygen saturation, sleep quality, and caloric expenditure. Given the increasing popularity of wearable devices for both recreation and health initiatives, understanding the strengths and limitations of these technologies is increasingly relevant. Need exists for continued evaluation of the efficacy of wearable devices to accurately and reliably measure purported outcomes. The purposes of this review are (1) to assess the current state of wearable devices using recent research on validity and reliability, (2) to describe existing gaps between physiology and technology, and (3) to offer expert interpretation for the lay and professional audience on how best to approach wearable technology and employ it in the pursuit of health and fitness. Current literature demonstrates inconsistent validity and reliability for various metrics, with algorithms not publicly available or lacking high-quality validation studies. Advancements in wearable technology should consider standardizing validation metrics, providing transparency in used algorithms, and improving how technology can be tailored to individuals. Until then, it is prudent to exercise caution when interpreting metrics reported from consumer-wearable devices.

An Experimental Feasibility Study Evaluating the Adequacy of a Sportswear-Type Wearable for Recording Exercise Intensity

Sportswear-type wearables with integrated inertial sensors and electrocardiogram (ECG) electrodes have been commercially developed. We evaluated the feasibility of using a sportswear-type wearable with integrated inertial sensors and electrocardiogram (ECG) electrodes for evaluating exercise intensity within a controlled laboratory setting. Six male college athletes were asked to wear a sportswear-type wearable while performing a treadmill test that reached up to 20 km/h. The magnitude of the filtered tri-axial acceleration signal, recorded by the inertial sensor, was used to calculate the acceleration index. The R-R intervals of the ECG were used to determine heart rate; the external validity of the heart rate was then evaluated according to oxygen uptake, which is the gold standard for physiological exercise intensity. Single regression analysis between treadmill speed and the acceleration index in each participant showed that the slope of the regression line was significantly greater than zero with a high coefficient of determination (walking, 0.95; jogging, 0.96; running, 0.90). Another single regression analysis between heart rate and oxygen uptake showed that the slope of the regression line was significantly greater than zero, with a high coefficient of determination (0.96). Together, these results indicate that the sportswear-type wearable evaluated in this study is a feasible technology for evaluating physical and physiological exercise intensity across a wide range of physical activities and sport performances.

Is the Xiaomi Mi Band 4 an Accuracy Tool for Measuring Health-Related Parameters in Adults and Older People? An Original Validation Study

Background: The aim of this study was to analyse the validity and accuracy of the low-cost Xiaomi Mi Band 4 (MB4) fitness tracker in relation to step count and heart rate in free-living conditions. Methods: 46 participants join in this study (38.65 ± 14.36 years old). The MB4 was compared with a video recording in laboratory conditions, also with the Sense Wear and Firstbeat monitors in free-living conditions. Results: No significant differences were found in the number of steps in the laboratory protocol between devices, in both, at low and high walking speed. For the free-living conditions, the MB4 showed high values of convergent validity in relation to the Firstbeat monitor during recording in both rest and walking situations. Moreover, the MB4 showed adequate values of convergent validity with the Sense Wear monitor during the 24 h recording, at medium speeds, and climbing stairs. Conclusion: The accuracy and precision of the MB4 is reasonable and can be used to monitor the average of step count and heart rate in free-living conditions.

Recent Advances in Wearable Optical Sensor Automation Powered by Battery versus Skin-like Battery-Free Devices for Personal Healthcare-A Review

Currently, old-style personal Medicare techniques rely mostly on traditional methods, such as cumbersome tools and complicated processes, which can be time consuming and inconvenient in some circumstances. Furthermore, such old methods need the use of heavy equipment, blood draws, and traditional bench-top testing procedures. Invasive ways of acquiring test samples can potentially cause patient discomfort and anguish. Wearable sensors, on the other hand, may be attached to numerous body areas to capture diverse biochemical and physiological characteristics as a developing analytical tool. Physical, chemical, and biological data transferred via the skin are used to monitor health in various circumstances. Wearable sensors can assess the aberrant conditions of the physical or chemical components of the human body in real time, exposing the body state in time, thanks to unintrusive sampling and high accuracy. Most commercially available wearable gadgets are mechanically hard components attached to bands and worn on the wrist, with form factors ultimately constrained by the size and weight of the batteries required for the power supply. Basic physiological signals comprise a lot of health-related data. The estimation of critical physiological characteristics, such as pulse inconstancy or variability using photoplethysmography (PPG) and oxygen saturation in arterial blood using pulse oximetry, is possible by utilizing an analysis of the pulsatile component of the bloodstream. Wearable gadgets with “skin-like” qualities are a new type of automation that is only starting to make its way out of research labs and into pre-commercial prototypes. Flexible skin-like sensing devices have accomplished several functionalities previously inaccessible for typical sensing devices due to their deformability, lightness, portability, and flexibility. In this paper, we studied the recent advancement in battery-powered wearable sensors established on optical phenomena and skin-like battery-free sensors, which brings a breakthrough in wearable sensing automation.

Anomaly Detection Framework for Wearables Data: A Perspective Review on Data Concepts, Data Analysis Algorithms and Prospects

Wearable devices use sensors to evaluate physiological parameters, such as the heart rate, pulse rate, number of steps taken, body fat and diet. The continuous monitoring of physiological parameters offers a potential solution to assess personal healthcare. Identifying outliers or anomalies in heart rates and other features can help identify patterns that can play a significant role in understanding the underlying cause of disease states. Since anomalies are present within the vast amount of data generated by wearable device sensors, identifying anomalies requires accurate automated techniques. Given the clinical significance of anomalies and their impact on diagnosis and treatment, a wide range of detection methods have been proposed to detect anomalies. Much of what is reported herein is based on previously published literature. Clinical studies employing wearable devices are also increasing. In this article, we review the nature of the wearables-associated data and the downstream processing methods for detecting anomalies. In addition, we also review supervised and un-supervised techniques as well as semi-supervised methods that overcome the challenges of missing and un-annotated healthcare data.

Heart Rate and Distance Measurement of Two Multisport Activity Trackers and a Cellphone App in Different Sports: A Cross-Sectional Validation and Comparison Field Study

Options for monitoring sports have been continuously developed by using activity trackers to determine almost all vital and movement parameters. The aim of this study was to validate heart rate and distance measurements of two activity trackers (Polar Ignite; Garmin Forerunner 945) and a cellphone app (Polar Beat app using iPhone 7 as a hardware platform) in a cross-sectional field study. Thirty-six moderate endurance-trained adults (20 males/16 females) completed a test battery consisting of walking and running 3 km, a 1.6 km interval run (standard 400 m outdoor stadium), 3 km forest run (outdoor), 500/1000 m swim and 4.3/31.5 km cycling tests. Heart rate was recorded via a Polar H10 chest strap and distance was controlled via a map, 400 m stadium or 50 m pool. For all tests except swimming, strong correlation values of r > 0.90 were calculated with moderate exercise intensity and a mean absolute percentage error of 2.85%. During the interval run, several significant deviations (p < 0.049) were observed. The swim disciplines showed significant differences (p < 0.001), with the 500 m test having a mean absolute percentage error of 8.61%, and the 1000 m test of 55.32%. In most tests, significant deviations (p < 0.001) were calculated for distance measurement. However, a maximum mean absolute percentage error of 4.74% and small mean absolute error based on the total route lengths were calculated. This study showed that the accuracy of heart rate measurements could be rated as good, except for rapid changing heart rate during interval training and swimming. Distance measurement differences were rated as non-relevant in practice for use in sports.

Wristbands in Home-Based Rehabilitation-Validation of Heart Rate Measurement

The possibility of using a smartwatch as a rehabilitation tool to monitor patients’ heart rates during exercise has gained the attention of many researchers. This study aimed to evaluate the accuracy and precision of the HR measurement performed by two wrist monitors: the Fitbit Charge 4 and the Xiaomi Mi Band 5. Thirty-one healthy volunteers were asked to perform a stress test on a treadmill. Their heart rates were recorded simultaneously by the wristbands and an electrocardiogram (ECG) at 1 min intervals. The mean absolute error percentage (MAPE), Lin’s concordance correlation coefficient (LCCC), and Bland–Altman analysis were calculated to compare the precision and accuracy of heart rate measurements. The estimated validation criteria were MAPE < 10% and LCCC < 0.8. The overall MAPE and LCCC of the Fitbit were 10.19% (±11.79%) and 0.753 (95% CI: 0.717–0.785), respectively. The MAPE and LCCC of the Xiaomi were 6.89% (±9.75) and 0.903 (0.886–0.917), respectively. The precision and accuracy of both devices decreased with the increased exercise intensity. The accuracy of wearable wrist-worn heart rate monitors varies and depends on the intensity of training. Therefore, the decision to use such a device as a heart rate monitor during in-home rehabilitation should be made with caution.

Tourist Experiences Recommender System Based on Emotion Recognition with Wearable Data

The collection of physiological data from people has been facilitated due to the mass use of cheap wearable devices. Although the accuracy is low compared to specialized healthcare devices, these can be widely applied in other contexts. This study proposes the architecture for a tourist experiences recommender system (TERS) based on the user's emotional states who wear these devices. The issue lies in detecting emotion from Heart Rate (HR) measurements obtained from these wearables. Unlike most state-of-the-art studies, which have elicited emotions in controlled experiments and with high-accuracy sensors, this research's challenge consisted of emotion recognition (ER) in the daily life context of users based on the gathering of HR data. Furthermore, an objective was to generate the tourist recommendation considering the emotional state of the device wearer. The method used comprises three main phases: The first was the collection of HR measurements and labeling emotions through mobile applications. The second was emotional detection using deep learning algorithms. The final phase was the design and validation of the TERS-ER. In this way, a dataset of HR measurements labeled with emotions was obtained as results. Among the different algorithms tested for ER, the hybrid model of Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks had promising results. Moreover, concerning TERS, Collaborative Filtering (CF) using CNN showed better performance.

Wearable Devices for Physical Activity and Healthcare Monitoring in Elderly People: A Critical Review

The availability of wearable devices (WDs) to collect biometric information and their use during activities of daily living is significantly increasing in the general population. These small electronic devices, which record fitness and health-related outcomes, have been broadly utilized in industries such as medicine, healthcare, and fitness. Since they are simple to use and progressively cheaper, they have also been used for numerous research purposes. However, despite their increasing popularity, most of these WDs do not accurately measure the proclaimed outcomes. In fact, research is equivocal about whether they are valid and reliable methods to specifically evaluate physical activity and health-related outcomes in older adults, since they are mostly designed and produced considering younger subjects' physical and mental characteristics. Additionally, their constant evolution through continuous upgrades and redesigned versions, suggests the need for constant up-to-date reviews and research. Accordingly, this article aims to scrutinize the state-of-the-art scientific evidence about the usefulness of WDs, specifically on older adults, to monitor physical activity and health-related outcomes. This critical review not only aims to inform older consumers but also aid researchers in study design when selecting physical activity and healthcare monitoring devices for elderly people.

Remote Monitoring of Critically-Ill Post-Surgical Patients: Lessons from a Biosensor Implementation Trial

Biosensors represent one of the numerous promising technologies envisioned to extend healthcare delivery. In perioperative care, the healthcare delivery system can use biosensors to remotely supervise patients who would otherwise be admitted to a hospital. This novel technology has gained a foothold in healthcare with significant acceleration due to the COVID-19 pandemic. However, few studies have attempted to narrate, or systematically analyze, the process of their implementation. We performed an observational study of biosensor implementation. The data accuracy provided by the commercially available biosensors was compared to those offered by standard clinical monitoring on patients admitted to the intensive care unit/perioperative unit. Surveys were also conducted to examine the acceptance of technology by patients and medical staff. We demonstrated a significant difference in vital signs between sensors and standard monitoring which was very dependent on the measured variables. Sensors seemed to integrate into the workflow relatively quickly, with almost no reported problems. The acceptance of the biosensors was high by patients and slightly less by nurses directly involved in the patients’ care. The staff forecast a broad implementation of biosensors in approximately three to five years, yet are eager to learn more about them. Reliability considerations proved particularly troublesome in our implementation trial. Careful evaluation of sensor readiness is most likely necessary prior to system-wide implementation by each hospital to assess for data accuracy and acceptance by the staff.

Recommendations for determining the validity of consumer wearable heart rate devices: expert statement and checklist of the INTERLIVE Network

Assessing vital signs such as heart rate (HR) by wearable devices in a lifestyle-related environment provides widespread opportunities for public health related research and applications. Commonly, consumer wearable devices assessing HR are based on photoplethysmography (PPG), where HR is determined by absorption and reflection of emitted light by the blood. However, methodological differences and shortcomings in the validation process hamper the comparability of the validity of various wearable devices assessing HR. Towards Intelligent Health and Well-Being: Network of Physical Activity Assessment (INTERLIVE) is a joint European initiative of six universities and one industrial partner. The consortium was founded in 2019 and strives towards developing best-practice recommendations for evaluating the validity of consumer wearables and smartphones. This expert statement presents a best-practice validation protocol for consumer wearables assessing HR by PPG. The recommendations were developed through the following multi-stage process: (1) a systematic literature review based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses, (2) an unstructured review of the wider literature pertaining to factors that may introduce bias during the validation of these devices and (3) evidence-informed expert opinions of the INTERLIVE Network. A total of 44 articles were deemed eligible and retrieved through our systematic literature review. Based on these studies, a wider literature review and our evidence-informed expert opinions, we propose a validation framework with standardised recommendations using six domains: considerations for the target population, criterion measure, index measure, testing conditions, data processing and the statistical analysis. As such, this paper presents recommendations to standardise the validity testing and reporting of PPG-based HR wearables used by consumers. Moreover, checklists are provided to guide the validation protocol development and reporting. This will ensure that manufacturers, consumers, healthcare providers and researchers use wearables safely and to its full potential.

Shedding Light on Nocturnal Movements in Parkinson's Disease: Evidence from Wearable Technologies

In Parkinson’s disease (PD), abnormal movements consisting of hypokinetic and hyperkinetic manifestations commonly lead to nocturnal distress and sleep impairment, which significantly impact quality of life. In PD patients, these nocturnal disturbances can reflect disease-related complications (e.g., nocturnal akinesia), primary sleep disorders (e.g., rapid eye movement behaviour disorder), or both, thus requiring different therapeutic approaches. Wearable technologies based on actigraphy and innovative sensors have been proposed as feasible solutions to identify and monitor the various types of abnormal nocturnal movements in PD. This narrative review addresses the topic of abnormal nocturnal movements in PD and discusses how wearable technologies could help identify and assess these disturbances. We first examine the pathophysiology of abnormal nocturnal movements and the main clinical and instrumental tools for the evaluation of these disturbances in PD. We then report and discuss findings from previous studies assessing nocturnal movements in PD using actigraphy and innovative wearable sensors. Finally, we discuss clinical and technical prospects supporting the use of wearable technologies for the evaluation of nocturnal movements.

Srivastava S. Wearable Skin Sensors and Their Challenges: A Review of Transdermal, Optical, and Mechanical Sensors

Wearable technology and mobile healthcare systems are both increasingly popular solutions to traditional healthcare due to their ease of implementation and cost-effectiveness for remote health monitoring. Recent advances in research, especially the miniaturization of sensors, have significantly contributed to commercializing the wearable technology. Most of the traditional commercially available sensors are either mechanical or optical, but nowadays transdermal microneedles are also being used for micro-sensing such as continuous glucose monitoring. However, there remain certain challenges that need to be addressed before the possibility of large-scale deployment. The biggest challenge faced by all these wearable sensors is our skin, which has an inherent property to resist and protect the body from the outside world. On the other hand, biosensing is not possible without overcoming this resistance. Consequently, understanding the skin structure and its response to different types of sensing is necessary to remove the scientific barriers that are hindering our ability to design more efficient and robust skin sensors. In this article, we review research reports related to three different biosensing modalities that are commonly used along with the challenges faced in their implementation for detection. We believe this review will be of significant use to researchers looking to solve existing problems within the ongoing research in wearable sensors.