Using Fitness Trackers and Smartwatches to Measure Physical Activity in Research: Analysis of Consumer Wrist-Worn Wearables

Unveiling wearables: exploring the global landscape of biometric applications and vital signs and behavioral impact

The development of neuroscientific techniques enabling the recording of brain and peripheral nervous system activity has fueled research in cognitive science. Recent technological advancements offer new possibilities for inducing behavioral change, particularly through cost-effective Internet-based interventions. However, limitations in laboratory equipment volume have hindered the generalization of results to real-life contexts. The advent of Internet of Things (IoT) devices, such as wearables, equipped with sensors and microchips, has ushered in a new era in behavior change techniques. Wearables, including smartwatches, electronic tattoos, and more, are poised for massive adoption, with an expected annual growth rate of 55% over the next five years. These devices enable personalized instructions, leading to increased productivity and efficiency, particularly in industrial production. Additionally, the healthcare sector has seen a significant demand for wearables, with over 80% of global consumers willing to use them for health monitoring. This research explores the primary biometric applications of wearables and their impact on users' well-being, focusing on the integration of behavior change techniques facilitated by IoT devices. Wearables have revolutionized health monitoring by providing real-time feedback, personalized interventions, and gamification. They encourage positive behavior changes by delivering immediate feedback, tailored recommendations, and gamified experiences, leading to sustained improvements in health. Furthermore, wearables seamlessly integrate with digital platforms, enhancing their impact through social support and connectivity. However, privacy and data security concerns must be addressed to maintain users' trust. As technology continues to advance, the refinement of IoT devices' design and functionality is crucial for promoting behavior change and improving health outcomes. This study aims to investigate the effects of behavior change techniques facilitated by wearables on individuals' health outcomes and the role of wearables in promoting a healthier lifestyle.

The Effect of an AI-Based, Autonomous, Digital Health Intervention Using Precise Lifestyle Guidance on Blood Pressure in Adults With Hypertension: Single-Arm Nonrandomized Trial

BACKGROUND

Home blood pressure (BP) monitoring with lifestyle coaching is effective in managing hypertension and reducing cardiovascular risk. However, traditional manual lifestyle coaching models significantly limit availability due to high operating costs and personnel requirements. Furthermore, the lack of patient lifestyle monitoring and clinician time constraints can prevent personalized coaching on lifestyle modifications.

OBJECTIVE

This study assesses the effectiveness of a fully digital, autonomous, and artificial intelligence (AI)-based lifestyle coaching program on achieving BP control among adults with hypertension.

METHODS

Participants were enrolled in a single-arm nonrandomized trial in which they received a BP monitor and wearable activity tracker. Data were collected from these devices and a questionnaire mobile app, which were used to train personalized machine learning models that enabled precision lifestyle coaching delivered to participants via SMS text messaging and a mobile app. The primary outcomes included (1) the changes in systolic and diastolic BP from baseline to 12 and 24 weeks and (2) the percentage change of participants in the controlled, stage-1, and stage-2 hypertension categories from baseline to 12 and 24 weeks. Secondary outcomes included (1) the participant engagement rate as measured by data collection consistency and (2) the number of manual clinician outreaches.

RESULTS

In total, 141 participants were monitored over 24 weeks. At 12 weeks, systolic and diastolic BP decreased by 5.6 mm Hg (95% CI -7.1 to -4.2; P<.001) and 3.8 mm Hg (95% CI -4.7 to -2.8; P<.001), respectively. Particularly, for participants starting with stage-2 hypertension, systolic and diastolic BP decreased by 9.6 mm Hg (95% CI -12.2 to -6.9; P<.001) and 5.7 mm Hg (95% CI -7.6 to -3.9; P<.001), respectively. At 24 weeks, systolic and diastolic BP decreased by 8.1 mm Hg (95% CI -10.1 to -6.1; P<.001) and 5.1 mm Hg (95% CI -6.2 to -3.9; P<.001), respectively. For participants starting with stage-2 hypertension, systolic and diastolic BP decreased by 14.2 mm Hg (95% CI -17.7 to -10.7; P<.001) and 8.1 mm Hg (95% CI -10.4 to -5.7; P<.001), respectively, at 24 weeks. The percentage of participants with controlled BP increased by 17.2% (22/128; P<.001) and 26.5% (27/102; P<.001) from baseline to 12 and 24 weeks, respectively. The percentage of participants with stage-2 hypertension decreased by 25% (32/128; P<.001) and 26.5% (27/102; P<.001) from baseline to 12 and 24 weeks, respectively. The average weekly participant engagement rate was 92% (SD 3.9%), and only 5.9% (6/102) of the participants required manual outreach over 24 weeks.

CONCLUSIONS

The study demonstrates the potential of fully digital, autonomous, and AI-based lifestyle coaching to achieve meaningful BP improvements and high engagement for patients with hypertension while substantially reducing clinician workloads.

TRIAL REGISTRATION

ClinicalTrials.gov NCT06337734; https://clinicaltrials.gov/study/NCT06337734.

Quantifying lumbar sagittal plane kinematics using a wrist-worn inertial measurement unit

Wearable sensors like inertial measurement units (IMUs), and those available as smartphone or smartwatch applications, are increasingly used to quantify lumbar mobility. Currently, wearable sensors have to be placed on the back to measure lumbar mobility, meaning it cannot be used in unsupervised environments. This study aims to compare lumbar sagittal plane angles quantified from a wrist-worn against that of a lumbar-worn sensor. Twenty healthy participants were recruited. An IMU was placed on the right wrist and the L3 spinal level. Participants had to position their right forearm on their abdomen, parallel to the floor. Three sets of three consecutive repetitions of flexion, and extension were formed. Linear mixed models were performed to quantify the effect of region (lumbar vs. wrist) on six outcomes [minimum, maximum, range of motion (ROM) of flexion and extension]. Only flexion ROM was significantly different between the wrist and lumbar sensors, with a mean of 4.54° (95% CI = 1.82°-7.27°). Across all outcomes, the maximal difference between a wrist-worn and lumbar-worn sensor was <8°. A wrist-worn IMU sensor could be used to measure gross lumbar sagittal plane mobility in place of a lumbar-worn IMU. This may be useful for remote monitoring during rehabilitation.

Learning From Alarms: A Robust Learning Approach for Accurate Photoplethysmography-Based Atrial Fibrillation Detection Using Eight Million Samples Labeled With Imprecise Arrhythmia Alarms

Atrial fibrillation (AF) is a common cardiac arrhythmia with serious health consequences if not detected and treated early. Detecting AF using wearable devices with photoplethysmography (PPG) sensors and deep neural networks has demonstrated some success using proprietary algorithms in commercial solutions. However, to improve continuous AF detection in ambulatory settings towards a population-wide screening use case, we face several challenges, one of which is the lack of large-scale labeled training data. To address this challenge, we propose to leverage AF alarms from bedside patient monitors to label concurrent PPG signals, resulting in the largest PPG-AF dataset so far (8.5 M 30-second records from 24,100 patients) and demonstrating a practical approach to build large labeled PPG datasets. Furthermore, we recognize that the AF labels thus obtained contain errors because of false AF alarms generated from imperfect built-in algorithms from bedside monitors. Dealing with label noise with unknown distribution characteristics in this case requires advanced algorithms. We, therefore, introduce and open-source a novel loss design, the cluster membership consistency (CMC) loss, to mitigate label errors. By comparing CMC with state-of-the-art methods selected from a noisy label competition, we demonstrate its superiority in handling label noise in PPG data, resilience to poor-quality signals, and computational efficiency.

Assessing the Impact of COVID-19 on Amateur Runners' Performance: An Analysis through Monitoring Devices

This retrospective study aimed to analyze the return to running of non-professional runners after experiencing asymptomatic or mild COVID-19. Participants aged 18-55 years who maintained a training load of ≥10 km/week for at least three months prior to diagnosis and utilized Garmin/Polar apps were included. From these devices, parameters such as pace, distance, total running time, cadence, and heart rate were collected at three intervals: pre-COVID, immediately post-COVID, and three months after diagnosis. The Wilcoxon signed rank test was used for analysis (significance was set at ≤0.05). Twenty-one participants (57.1% male; mean age 35.0 ± 9.8 years) were included. The results revealed a significant decrease in running duration and distance two weeks after diagnosis, without significant changes in other parameters. Three months after infection, no differences were observed compared to pre-infection data, indicating a return to the pre-disease training load. These findings underscore the transient impact of COVID-19 on training performance among non-professional runners with mild or asymptomatic symptoms, highlighting the importance of tailored strategies for resuming running after infection.

Attributes, Methods, and Frameworks Used to Evaluate Wearables and Their Companion mHealth Apps: Scoping Review

BACKGROUND

Wearable devices, mobile technologies, and their combination have been accepted into clinical use to better assess the physical fitness and quality of life of patients and as preventive measures. Usability is pivotal for overcoming constraints and gaining users' acceptance of technology such as wearables and their companion mobile health (mHealth) apps. However, owing to limitations in design and evaluation, interactive wearables and mHealth apps have often been restricted from their full potential.

OBJECTIVE

This study aims to identify studies that have incorporated wearable devices and determine their frequency of use in conjunction with mHealth apps or their combination. Specifically, this study aims to understand the attributes and evaluation techniques used to evaluate usability in the health care domain for these technologies and their combinations.

METHODS

We conducted an extensive search across 4 electronic databases, spanning the last 30 years up to December 2021. Studies including the keywords "wearable devices," "mobile apps," "mHealth apps," "physiological data," "usability," "user experience," and "user evaluation" were considered for inclusion. A team of 5 reviewers screened the collected publications and charted the features based on the research questions. Subsequently, we categorized these characteristics following existing usability and wearable taxonomies. We applied a methodological framework for scoping reviews and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist.

RESULTS

A total of 382 reports were identified from the search strategy, and 68 articles were included. Most of the studies (57/68, 84%) involved the simultaneous use of wearables and connected mobile apps. Wrist-worn commercial consumer devices such as wristbands were the most prevalent, accounting for 66% (45/68) of the wearables identified in our review. Approximately half of the data from the medical domain (32/68, 47%) focused on studies involving participants with chronic illnesses or disorders. Overall, 29 usability attributes were identified, and 5 attributes were frequently used for evaluation: satisfaction (34/68, 50%), ease of use (27/68, 40%), user experience (16/68, 24%), perceived usefulness (18/68, 26%), and effectiveness (15/68, 22%). Only 10% (7/68) of the studies used a user- or human-centered design paradigm for usability evaluation.

CONCLUSIONS

Our scoping review identified the types and categories of wearable devices and mHealth apps, their frequency of use in studies, and their implementation in the medical context. In addition, we examined the usability evaluation of these technologies: methods, attributes, and frameworks. Within the array of available wearables and mHealth apps, health care providers encounter the challenge of selecting devices and companion apps that are effective, user-friendly, and compatible with user interactions. The current gap in usability and user experience in health care research limits our understanding of the strengths and limitations of wearable technologies and their companion apps. Additional research is necessary to overcome these limitations.

Wearable activity tracker study exploring rheumatoid arthritis patients' disease activity using patient-reported outcome measures, clinical measures, and biometric sensor data (the wear study)

Background

Digital health studies using electronic patient reported outcomes (ePROs), wearables, and clinical data to provide a more comprehensive picture of patient health.

Methods

Newly initiated patients on upadacitinib or adalimumab for RA will be recruited from community settings in the Excellence NEtwork in RheumatoloGY (ENRGY) practice-based research network. Over the period of three to six months, three streams of data will be collected (1) linkable physician-derived data; (2) self-reported daily and weekly ePROs through the ArthritisPower registry app; and (3) biometric sensor data passively collected via wearable. These data will be analyzed to evaluate correlations among the three types of data and patient improvement on the newly initiated medication.

Conclusions

Results from this study will provide valuable information regarding the relationships between physician data, wearable data, and ePROs in patients newly initiating an RA treatment, and demonstrate the feasibility of digital data capture for Remote Patient Monitoring of patients with rheumatic disease.

Standardizing Physical Activity Monitoring in Patients With Degenerative Lumbar Disorders

BACKGROUND AND OBJECTIVES

Degenerative thoracolumbar disorders (DTDs) typically cause pain and functional impairment. However, little is known regarding the DTD impact on patient's real-life physical activity. The objective of this study is to validate a wearable measure of physical activity monitoring in patients with DTD and to create gender- and sex-specific performance thresholds that are standardized to the mean of a control population.

METHODS

A commercially available smartwatch (Apple Watch) was used to monitor preoperative physical activity in patients undergoing surgery for DTD. Mean preoperative physical activity 2 weeks before the scheduled surgery was expressed as raw step count. Standardized z-scores were referenced to age- and sex-specific values of a control population from a large public database. Step counts were assessed for convergent validity with established patient-reported outcome measures, and impairment in activity was stratified into performance groups based on z-score cutoff values.

RESULTS

Sixty-five patients (62% female) with a mean (±SD) age of 63.8 (±12.8) years had a mean preoperative daily step count of 5556 (±3978). Physical activity showed significant correlation with patient-reported outcome measures, including Oswestry disability index (r = -0.26, 95% CI: -0.47-0.01), 36-Item Short Form Survey Physical Component Summary score (r = 0.30, 95% CI: 0.06-0.51), and Patient-Reported Outcomes Measurement Information System Physical Function (r = 0.49, 95% CI: 0.27-0.65). "No," "Mild," "moderate," and "severe impairment" in activity performance were defined as corresponding z-scores of >0, 0 to -0.99, -1 to -1.99, and ≤-2, accounting for 22%, 34%, 40%, and 5% of the study population. Each one-step category increase in activity impairment resulted in increased subjective disability as measured by the Oswestry Disability Index, 36-Item Short Form Survey Physical Component Summary, and Patient-Reported Outcomes Measurement Information System Physical Function (all P -values <.05).

CONCLUSION

We establish the first wearable objective measure of real-life physical activity for patients with DTD, with the first age- and sex-adjusted standard scores to enable clinicians and researchers to set treatment goals and directly compare activity levels between individual patients with DTD and normal controls.

Accuracy of the SenseWear Armband during Short Bouts of Exercise

A goal of mobile monitoring is to approximate metabolic energy expenditure (EE) during activities of daily living and exercise. Many physical activity monitors are inaccurate with respect to estimated EE and differentiating between activities that occur over short intervals. The objective of our study was to assess the validity of the SenseWear Armband (SWA) compared to indirect calorimetry (IC) during short intervals of walking and running. Twenty young, fit participants walked (preferred speed) and ran (75%, 85%, and 95% of predicted VO2max run speeds) on a treadmill. EE estimates from IC, SWA, and prediction equations that used the SWA, speed, and heart rate were examined during each 4 min interval and across the whole protocol (Total). The level of significance was p < 0.05. The SWA overestimated EE relative to IC by 1.62 kcal·min-1 while walking and 1.05 kcal·min-1 while running at 75%. However, it underestimated EE at the 85% (0.05 kcal·min-1) and 95% (0.92 kcal·min-1) speeds, but not significantly, and overestimated total EE by 28.29 kcal. Except for walking, our results suggest that the SWA displayed a good level of agreement (ICC = 0.76 to 0.84) with IC measures. Activity-specific algorithms using SWA, speed, and heart rate improved EE estimates, based on the standard error of the estimates, but perhaps not enough to justify extra sensors. The SWA may enable EE estimation of locomotion outside the laboratory, including those with short bouts of high intensity activity, but continued development of the SWA, or devices like it, is needed to enable accurate monitoring.

Development of a multi-wear-site, deep learning-based physical activity intensity classification algorithm using raw acceleration data

BACKGROUND

Accelerometers are widely adopted in research and consumer devices as a tool to measure physical activity. However, existing algorithms used to estimate activity intensity are wear-site-specific. Non-compliance to wear instructions may lead to misspecifications. In this study, we developed deep neural network models to classify device placement and activity intensity based on raw acceleration data. Performances of these models were evaluated by making comparisons to the ground truth and results derived from existing count-based algorithms.

METHODS

54 participants (26 adults 26.9±8.7 years; 28 children, 12.1±2.3 years) completed a series of activity tasks in a laboratory with accelerometers attached to each of their hip, wrist, and chest. Their metabolic rates at rest and during activity periods were measured using the portable COSMED K5; data were then converted to metabolic equivalents, and used as the ground truth for activity intensity. Deep neutral networks using the Long Short-Term Memory approach were trained and evaluated based on raw acceleration data collected from accelerometers. Models to classify wear-site and activity intensity, respectively, were evaluated.

RESULTS

The trained models correctly classified wear-sites and activity intensities over 90% of the time, which outperformed count-based algorithms (wear-site correctly specified: 83% to 85%; wear-site misspecified: 64% to 75%). When additional parameters of age, height and weight of participants were specified, the accuracy of some prediction models surpassed 95%.

CONCLUSIONS

Results of the study suggest that accelerometer placement could be determined prospectively, and non-wear-site-specific algorithms had satisfactory accuracies. The performances, in terms of intensity classification, of these models also exceeded typical count-based algorithms. Without being restricted to one specific wear-site, research protocols for accelerometers wear could allow more autonomy to participants, which may in turn improve their acceptance and compliance to wear protocols, and in turn more accurate results.

Criterion-Related Validity of Consumer-Wearable Activity Trackers for Estimating Steps in Primary Schoolchildren under Controlled Conditions: Fit-Person Study

The purposes were to examine the criterion-related validity of the steps estimated by consumer-wearable activity trackers (wrist-worn activity trackers: Fitbit Ace 2, Garmin Vivofit Jr, and Xiomi Mi Band 5; smartphone applications: Pedometer, Pedometer Pacer Health, and Google Fit/Apple Health) and their comparability in primary schoolchildren under controlled conditions. An initial sample of 66 primary schoolchildren (final sample = 56; 46.4% females), aged 9-12 years old (mean = 10.4 ± 1.0 years), wore three wrist-worn activity trackers (Fitbit Ace 2, Garmin Vivofit Jr 2, and Xiaomi Mi Band 5) on their non-dominant wrist and had three applications in two smartphones (Pedometer, Pedometer Pacer Health, and Google Fit/Apple Health for Android/iOS installed in Samsung Galaxy S20+/iPhone 11 Pro Max) in simulated front trouser pockets. Primary schoolchildren's steps estimated by the consumer-wearable activity trackers and the video-based counting independently by two researchers (gold standard) were recorded while they performed a 200-meter course in slow, normal and brisk pace walking, and running conditions. Results showed that the criterion-related validity of the step scores estimated by the three Samsung applications and the Garmin Vivofit Jr 2 were good-excellent in the four walking/running conditions (e.g., MAPE = 0.6-2.3%; lower 95% CI of the ICC = 0.81-0.99), as well as being comparable. However, the Apple applications, Fitbit Ace 2, and Xiaomi Mi Band 5 showed poor criterion-related validity and comparability on some walking/running conditions (e.g., lower 95% CI of the ICC < 0.70). Although, as in real life primary schoolchildren also place their smartphones in other parts (e.g., schoolbags, hands or even somewhere away from the body), the criterion-related validity of the Garmin Vivofit Jr 2 potentially would be considerably higher than that of the Samsung applications. The findings of the present study highlight the potential of the Garmin Vivofit Jr 2 for monitoring primary schoolchildren's steps under controlled conditions.

Towards Learning Discrete Representations via Self-Supervision for Wearables-Based Human Activity Recognition

Human activity recognition (HAR) in wearable and ubiquitous computing typically involves translating sensor readings into feature representations, either derived through dedicated pre-processing procedures or integrated into end-to-end learning approaches. Independent of their origin, for the vast majority of contemporary HAR methods and applications, those feature representations are typically continuous in nature. That has not always been the case. In the early days of HAR, discretization approaches had been explored-primarily motivated by the desire to minimize computational requirements on HAR, but also with a view on applications beyond mere activity classification, such as, for example, activity discovery, fingerprinting, or large-scale search. Those traditional discretization approaches, however, suffer from substantial loss in precision and resolution in the resulting data representations with detrimental effects on downstream analysis tasks. Times have changed, and in this paper, we propose a return to discretized representations. We adopt and apply recent advancements in vector quantization (VQ) to wearables applications, which enables us to directly learn a mapping between short spans of sensor data and a codebook of vectors, where the index comprises the discrete representation, resulting in recognition performance that is at least on par with their contemporary, continuous counterparts-often surpassing them. Therefore, this work presents a proof of concept for demonstrating how effective discrete representations can be derived, enabling applications beyond mere activity classification but also opening up the field to advanced tools for the analysis of symbolic sequences, as they are known, for example, from domains such as natural language processing. Based on an extensive experimental evaluation of a suite of wearable-based benchmark HAR tasks, we demonstrate the potential of our learned discretization scheme and discuss how discretized sensor data analysis can lead to substantial changes in HAR.

Effect of Intrapersonal and Interpersonal Behavior Change Strategies on Physical Activity Among Older Adults: A Randomized Clinical Trial

Importance

Despite guidelines that recommend physical activity (PA), little is known about which types of behavior change strategies (BCSs) effectively promote sustained increases in PA in older adults who are insufficiently active.

Objective

To determine whether intrapersonal BCSs (eg, goal setting) or interpersonal BCSs (eg, peer-to-peer sharing or learning) combined with the Otago Exercise Program (17 strength and balance exercises and a walking program that are learned and individually tailored, with instruction to perform 3 times per week at home or location of choice) and a wearable PA monitor help older adults sustain increases in their PA.

Design, Setting, and Participants

This 2 × 2 factorial randomized clinical trial (Community-Based Intervention Effects on Older Adults' Physical Activity) of community-dwelling older adults 70 years or older with PA levels below minimum national PA guidelines was conducted in urban community centers. Dates of enrollment were from November 17, 2017, to June 15, 2021, with final follow-up assessments completed on September 2, 2022.

Interventions

Participants were randomized to intrapersonal (eg, goal setting) BCSs, interpersonal (eg, problem-solving with peer-to-peer sharing and learning) BCSs, intrapersonal and interpersonal BCSs, or an attention control group. All interventions included a PA monitor and 8 weekly small-group meetings with discussion, practice, and instructions to implement the exercise program and relevant BCSs independently between meetings and after the intervention.

Main Outcomes and Measures

The primary outcome was daily minutes of objectively measured total PA (light, moderate, or vigorous intensities) averaged over 7 to 10 days, measured at baseline and after the intervention at 1 week, 6 months, and 12 months.

Results

Among 309 participants (mean [SD] age, 77.4 [5.0] years; 240 women [77.7%]), 305 (98.7%) completed the intervention, and 302 (97.7%) had complete data. Participants receiving PA interventions with interpersonal BCS components exhibited greater increases in total PA than did those who did not at 1 week (204 vs 177 PA minutes per day; adjusted difference, 27.1 [95% CI, 17.2-37.0]; P < .001), 6 months (195 vs 175 PA minutes per day; adjusted difference, 20.8 [95% CI, 10.0-31.6]; P < .001), and 12 months (195 vs 168 PA minutes per day; adjusted difference, 27.5 [95% CI, 16.2-38.8]; P < .001) after the intervention. Compared with participants who did not receive interventions with intrapersonal BCS components, participants who received intrapersonal BCSs exhibited no significant changes in total PA at 1 week (192 vs 190 PA minutes per day; adjusted difference, 1.8 [95% CI, -8.6 to 12.2]; P = .73), 6 months (183 vs 187 PA minutes per day; adjusted difference, -3.9 [95% CI, -15.0 to 7.1]; P = .49), or 12 months (177 vs 186 PA minutes per day; adjusted difference, -8.8 [95% CI, -20.5 to 2.9]; P = .14) after the intervention. Interactions between intrapersonal and interpersonal BCSs were not significant.

Conclusions and Relevance

In this randomized clinical trial, older adults with low levels of PA who received interpersonal BCSs, the exercise program, and a PA monitor exhibited significant increases in their PA for up to 12 months after the intervention. Intrapersonal BCSs elicited no significant PA changes and did not interact with interpersonal BCSs. Our findings suggest that because effects of a PA intervention on sustained increases in older adults' PA were augmented with interpersonal but not intrapersonal BCSs, approaches to disseminating and implementing the intervention should be considered.

Trial Registration

ClinicalTrials.gov Identifier: NCT03326141.

Does stress induction affect cognitive performance or avoidance of cognitive effort?

Previous research has shown that acute psychosocial stress impairs cognitive abilities, but recent studies suggest that this may be due to a decrease in willingness to engage in cognitive effort rather than a direct effect on performance. The aim of the present study was to replicate this last research and verify the influence of acute stress on avoidance of cognitive effort and cognitive performance. Fifty young, healthy individuals (26 females, 24 males) aged between 18 and 40 years were randomly assigned to two groups: a stress condition and a control condition. We used a Demand Selection Task paradigm (DST), in which participants chose between performing tasks that required either high or low cognitive effort. Stress was induced through the Trier Social Stress Test (TSST) and measured with both subjective and psychophysiological measurements. The results indicated that acute stress significantly increased participants' preference for less demanding behaviors, while no significant alterations in cognitive performance in task change activities were found. This study offers new perspectives on how stress affects behavior and decision-making in everyday life.

Leveraging Emerging Technologies to Expand Accessibility and Improve Precision in Rehabilitation and Exercise for People with Disabilities

Physical rehabilitation and exercise training have emerged as promising solutions for improving health, restoring function, and preserving quality of life in populations that face disparate health challenges related to disability. Despite the immense potential for rehabilitation and exercise to help people with disabilities live longer, healthier, and more independent lives, people with disabilities can experience physical, psychosocial, environmental, and economic barriers that limit their ability to participate in rehabilitation, exercise, and other physical activities. Together, these barriers contribute to health inequities in people with disabilities, by disproportionately limiting their ability to participate in health-promoting physical activities, relative to people without disabilities. Therefore, there is great need for research and innovation focusing on the development of strategies to expand accessibility and promote participation in rehabilitation and exercise programs for people with disabilities. Here, we discuss how cutting-edge technologies related to telecommunications, wearables, virtual and augmented reality, artificial intelligence, and cloud computing are providing new opportunities to improve accessibility in rehabilitation and exercise for people with disabilities. In addition, we highlight new frontiers in digital health technology and emerging lines of scientific research that will shape the future of precision care strategies for people with disabilities.

Are individuals with disabilities using wearable devices? A secondary data analysis of 2017 BRFSS

PURPOSE

The study aims to investigate the prevalence of individuals with disabilities who reported using wearable devices, to examine the association between wearable device usage and disability status, and to determine the characteristic of individuals with disabilities associated with wearable device usage using the 2017 Behavioural Risk Factor Surveillance System (BRFSS) through secondary data analysis.

MATERIALS AND METHODS

Data from the 2017 BRFSS of eight states were used in the analysis. Descriptive analysis, chi-square analysis, and multivariable logistic regressions were performed. Subsample analyses were also conducted for individuals with disabilities and different types of disability, including visual impairments, hearing impairments, cognitive disability, independent living disability, self-care disability, and mobility disability on wearable device usage.

RESULTS

14.6% (95% CI [11.7, 17.5]) of participants with disabilities were wearable device users. Individuals with disabilities were .63 (95% CI [.48, .83], p < 0.001) and .67 (95% CI [.50, .90], p = 0.007) times the odds of individuals without disabilities in using wearable devices, respectively, according to unadjusted and adjusted logistic regression. Individuals with mobility disability were less likely to utilise wearable devices than their counterparts. Among individuals with disabilities, those who were age 65 years or older had a lower odds of using wearable devices (OR = .55, 95% CI [0.35, 0.85), p = 0.007).

CONCLUSION

Individuals with disabilities are using wearable devices in collecting various health-related information. Further research is needed to determine reasons why individuals with disabilities are not using wearable devices and how individuals with disabilities are using wearable devices.IMPLICATIONS FOR REHABILITATIONWearable devices can track various health-related information such as physical activity levels, sleep patterns, calories intakes, and chronic health conditions.Using nationally represent data, individuals with disabilities have access and utilise wearable devices in free living setting.Compare to individuals without disabilities, individuals with disabilities are less likely to utilise wearable devices in free living setting.Further research is needed to determine the accessibility of wearable devices for individuals with disabilities and its usage in rehabilitation setting.

User characteristics associated with use of wrist-worn wearables and physical activity apps by adults with and without impaired speech-in-noise recognition: a cross-sectional analysis

OBJECTIVE

To study weekly use of smartwatches, fitness watches and physical activity apps among adults with and without impaired speech-in-noise (SIN) recognition, to identify subgroups of users.

DESIGN

Cross-sectional study.

STUDY SAMPLE

Adults (aged 28-80 years) with impaired (n = 384) and normal SIN recognition (n = 341) as measured with a web-based digits-in-noise test, from the Netherlands Longitudinal Study on Hearing. Multiple logistic regression analyses were used to study differences and to build an association model.

RESULTS

Employed adults in both groups are more likely to use each type of fitness technology (all ORs >3.4, all p-values < 0.004). Specific to fitness watch use, adults living with others use it more (OR 2.5, 95%CI 1.1;5.8, p = 0.033) whereas those abstaining from alcohol (OR 0.3, 95%CI 0.1;0.6) or consuming >2 glasses/week (OR 0.4, 95%CI 0.2;0.81, overall p = 0.006) and hearing aid users (OR 0.5, 95%CI 0.2;0.9, p = 0.024) make less use.

CONCLUSIONS

Subgroups of adults more and less likely to use fitness technology exist, but do not differ between adults with and without impaired SIN recognition. More research is needed to confirm these results and to develop interventions to increase physical activity levels among adults with hearing loss.

Promoting physical activity in clinical practice through wearable technology

ABSTRACT

The negative health consequences of physical inactivity continue to be a global problem that must be addressed from the highest levels of government down to local primary care providers. Physical activity has been identified as a useful patient vital sign in health care. Advanced practice nurses should aggressively prescribe physical activity as an evidence-based intervention to help mitigate the increased mortality and morbidity associated with a sedentary lifestyle. A focused literature review was conducted using PubMed, CINAHL, and the Cochrane online databases. Fitness wearables and mobile health trackers are a catalyst for lifestyle behavior change and cultivate a health care partnership between the patient and their provider. The evolution of fitness wearables into mainstream health care hinges on the ability of devices to integrate into electronic health records, uniformity of manufacturer standards, intuitiveness, and the assurance of user privacy and security. It is incumbent on nurse practitioners to educate themselves about the reliability and practicality of fitness trackers for their patient population. Future research should focus on adopting quality standards for all consumer devices, the seamless integration of device data into electronic health records and ensuring personal privacy and security.

Wolf Creek XVII part 3: Automated cardiac arrest diagnosis

Introduction

Automated cardiac arrest diagnosis offers the possibility to significantly shorten the interval between onset of out-of-hospital cardiac arrest (OHCA) and notification of EMS, providing the opportunity for earlier resuscitation and possibly increased survival.

Methods

Automated cardiac arrest diagnosis was one of six focus topics for the Wolf Creek XVII Conference held on June 14-17 2023 in Ann Arbor, Michigan, USA. Conference invitees included international thought leaders and scientists in the field of cardiac arrest resuscitation from academia and industry. Participants submitted via online survey knowledge gaps, barriers to translation and research priorities for each focus topic. Expert panels used the survey results and their own perspectives and insights to create and present a preliminary unranked list for each category that was debated, revised and ranked by all attendees to identify the top 5 for each category.

Results

Top knowledge gaps include the accuracy of automated OHCA detection technologies and the feasibility and reliability of automated EMS activation. The main barriers to translation are the risk of false positives potentially overburdening EMS, development and application costs of technology and the challenge of integrating new technology in EMS IT systems. The top research priorities are large-scale evaluation studies to measure real world performance and user research regarding the willingness to adopt these technologies.

Conclusion

Automated cardiac arrest diagnosis has the potential to significantly impact time to resuscitation and survival of OHCA because it could convert unwitnessed events into witnessed events. Validation and feasibility studies are needed. The specificity of the technology must be high not to overburden limited EMS resources. If adequate event classification is achieved, future research could shift toward event prediction, focusing on identifying potential digital biomarkers and signatures of imminent cardiac arrest. Implementation could be challenging due to high costs of development, regulatory considerations and instantiation logistics.

Use of Consumer Wearables in Health Research: Issues and Considerations

As wearable devices, which allow individuals to track and self-manage their health, become more ubiquitous, the opportunities are growing for researchers to use these sensors within interventions and for data collection. They offer access to data that are captured continuously, passively, and pragmatically with minimal user burden, providing huge advantages for health research. However, the growth in their use must be coupled with consideration of their potential limitations, in particular, digital inclusion, data availability, privacy, ethics of third-party involvement, data quality, and potential for adverse consequences. In this paper, we discuss these issues and strategies used to prevent or mitigate them and recommendations for researchers using wearables as part of interventions or for data collection.

Wearable sensors for prediction of intraamniotic infection in women with preterm premature rupture of membranes: a prospective proof of principle study

PURPOSE

To evaluate the use of wearable sensors for prediction of intraamniotic infection in pregnant women with PPROM.

MATERIALS AND METHODS

In a prospective proof of principle study, we included 50 patients diagnosed with PPROM at the University Hospital Zurich between November 2017 and May 2020. Patients were instructed to wear a bracelet during the night, which measures physiological parameters including wrist skin temperature, heart rate, heart rate variability, and breathing rate. A two-way repeated measures ANOVA was performed to evaluate the difference over time of both the wearable device measured parameters and standard clinical monitoring values, such as body temperature, pulse, leucocytes, and C-reactive protein, between women with and without intraamniotic infection.

RESULTS

Altogether, 23 patients (46%) were diagnosed with intraamniotic infection. Regarding the physiological parameters measured with the bracelet, we observed a significant difference in breathing rate (19 vs 16 per min, P < .01) and heart rate (72 vs 67 beats per min, P = .03) in women with intraamniotic infection compared to those without during the 3 days prior to birth. In parallel to these changes standard clinical monitoring values were significantly different in the intraamniotic infection group compared to women without infection in the 3 days preceding birth.

CONCLUSION

Our results suggest that wearable sensors are a promising, noninvasive, patient friendly approach to support the early detection of intraamniotic infection in women with PPROM. However, confirmation of our findings in larger studies is required before implementing this technique in standard clinical management.

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.

Cognitive and biomarker responses in healthy older adults to a 18-hole golf round and different walking types: a randomised cross-over study

Introduction

The global burden of age-related cognitive decline is increasing, with the number of people aged 60 and over expected to double by 2050. This study compares the acute effects of age-appropriate cognitively demanding aerobic exercises involving walking, on cognitive functions and exerkine responses such as brain-derived neurotrophic factor (BDNF) and cathepsin B (CTSB) in older, healthy adults.

Methods/design

Healthy older golfers (n=25, 16 male and 9 female, 69±4 years) were enrolled in a 5-day randomised cross-over study and completed three different exercise trials (18-hole golf round, 6 km Nordic walking, 6 km walking) in a real-life environment, in random order and at a self-selected pace. Differences in cognition (the Trail-Making Test (TMT) AB) and exerkines (BDNF and CTSB) were analysed within groups using the Wilcoxon signed-rank test and between groups using the Kruskal-Wallis test.

Results

All exercise types resulted in a significant decrease in the TMT A-test (p<0.05; golf: -4.43±1.5 s, Nordic walking: -4.63±1.6 s, walking: -6.75±2.26 s), where Nordic walking and walking demonstrated a decrease in the TMT B-test (p<0.05; Nordic walking: -9.62±7.2 s, walking: -7.55±3.2 s). In addition, all exercise types produced significant decreases in the TMT AB test scores (p<0.05), and Nordic walking (p=0.035) showed decreases in the TMTB-TMTA-test. There were no immediate postexercise changes in the levels of BDNF or CTSB.

Conclusion

Acute bouts of golf, Nordic walking and walking improved cognitive functions irrespective of exerkines in healthy older adults. In addition, Nordic walking and walking in general enhanced executive functions. No significant effects were seen on the levels of BDNF and CTSB.

Trial registration number

ISRCTN10007294.

Physical and psychological recovery after vaginal childbirth with and without epidural analgesia: A prospective cohort study

BACKGROUND

Enhanced recovery is the gold standard in modern perioperative management, including that for cesarean deliveries. However, qualitative and quantitative data on the physical and psychological recovery of women after vaginal childbirth are limited. Whether neuraxial labor analgesia influences postpartum recovery is unknown.

METHODS

Primiparous women anticipating a vaginal childbirth between January 2020 and May 2021 were enrolled. Women with major comorbidities or postpartum complications and those who underwent a cesarean delivery were excluded. Daily step count was measured using a wrist-worn activity tracker (FitbitTM Inspire HR) for 120 hours after vaginal childbirth. Subjective fatigue levels and health-related quality of life were assessed using the Multidimensional Fatigue Inventory (MFI) and EuroQol 5 Dimension 5 Level (EQ-5D-5L), respectively, at the 3rd trimester antenatal visit, on postpartum day 1 and 3, and at the one-month postpartum visit. Rest and dynamic pain scores and the location of pain were documented by participants during postpartum hospitalization.

RESULTS

Among 300 women who were enrolled antenatally, 95 and 116 had a vaginal delivery without (NCB group) and with (EPL group) epidural analgesia, respectively. The median number of steps per 24 hours increased daily in both groups, and no significant difference was detected between the groups. Postpartum pain was mild overall, with median rest and dynamic pain scores being less than 4 and similar between the groups. MFI and EQ-5D-5L scores were the worst on postpartum day 1 in both groups and gradually improved to antepartum level by the one-month postpartum visit. Higher MFI score on postpartum day 1, but not the use of epidural analgesia, was associated with lower odds of achieving adequate postpartum ambulation (defined as >3500 steps between 48 and 72 hours postpartum).

CONCLUSION

The use of epidural analgesia was not associated with worse recovery outcomes during postpartum hospitalization.

TRIAL REGISTRATION

UMIN-CTR, #UMIN000039343, registered on January 31, 2020.

Overview of the impact of sleep monitoring on optimal performance, immune system function and injury risk reduction in athletes: A narrative review

Sleep is essential for a range of physiological and mental functions in professional athletes. There is proof that athletes may experience lower quality and quantity of sleep. While adequate sleep has been shown to have restorative effects on the immune system and endocrine system, facilitate nervous system recovery and the metabolic cost of wakefulness, and play a significant role in learning, memory, and synaptic plasticity, which can affect sports recovery, injury risk reduction, and performance. Sports performance may suffer significantly from a lack of sleep, especially under maximal and long-term exercise. Due to the potential harm, these factors may do to an athlete's endocrine, metabolic, and nutritional health, sports performance is impacted by reduced sleep quality or quantity. There are several neurotransmitters associated with the sleep-wake cycle that have been discovered. They comprise cholinergic hormone, orexin, melanin, galanin, serotonin, gamma-aminobutyric acid, histamine, and serotonin. Therefore, dietary modifications that affect the neurotransmitters in the brain also may affect sleep; particularly for athletes who require more physical and psychological recovery owing to the tremendous physiological and psychological demands placed on them during training and performance. This review explores the variables that influence the quantity and quality of sleep-in populations of athletes and assesses their possible effects. In addition, several recommendations for improving sleep are presented. Even though there has been much research on variables that impact sleep, future studies may highlight the significance of these aspects for athletes.

Accuracy of consumer-based activity trackers as measuring tool and coaching device in breast and colorectal cancer survivors

PURPOSE

Consumer-based activity trackers are used to measure and promote PA. We studied the accuracy of a wrist- and waist-worn activity tracker in cancer survivors and compared these results to a healthy age-matched control group.

METHODS

Twenty-two cancer survivors and 35 healthy subjects wore an activity tracker at the waist and at the wrist combined with a reference activity monitor at the waist (Dynaport Movemonitor). The devices were worn for 14 consecutive days. The mean daily step count from both activity trackers was compared with the reference activity monitor to investigate accuracy and agreement (paired t-test, intraclass correlation, Bland-Altman plots). To evaluate the accuracy as a coaching tool, day-by-day differences within patients were calculated. The Kendall correlation coefficient was used to test the consistency of ranking daily steps between the activity trackers and the reference activity monitor.

RESULTS

The wrist-worn wearable significantly overestimated the daily step count in the cancer group (mean ± SDΔ: + 1305 (2685) steps per day; p = 0.033) and in the healthy control group (mean ± SDΔ: + 1598 (2927) steps per day; p = 0.003). The waist-worn wearable underestimated the step count in both groups, although this was not statistically significant. As a coaching device, moderate (r = 0.642-0.670) and strong (r = 0.733-0.738) accuracy was found for the wrist- and waist-worn tracker, respectively, for detecting day-by-day variability in both populations.

CONCLUSION

Our results show that wrist-worn activity trackers significantly overestimate daily step count in both cancer survivors and healthy control subjects. Based on the accuracy, in particular, the waist-worn activity tracker could possibly be used as a coaching tool.

Using mobile health to encourage physical activity in individuals with intellectual disability: a pilot mixed methods feasibility study

Background

Many individuals with intellectual disability (ID) have a sedentary lifestyle. Few interventions aimed at increasing their level of physical activity (PA) have shown lasting effects.

Aim

To assess the feasibility and acceptability of a pilot intervention study using innovative mobile health (mHealth) support systems to encourage PA in individuals with ID.

Methods

Nine individuals with ID and a low level of PA, aged 16-36 years, were included in the present convergent triangulation mixed method design. Two mHealth support systems (apps) were developed and tested. PA was measured with a Fitbit smartwatch, accelerometer, the International Physical Activity Questionnaire-Short Form (IPAQ-S), and Goal attainment scaling. Data were collected through online pre-, mid- (4 weeks), and post-intervention (12 weeks) questionnaires and activity trackers. Semi-structured qualitative interviews with participants and/or a family or staff member were held after the 12-week follow-up. Data were analyzed using conventional nonparametric statistics and thematic analyses.

Results

The response rate and retention to the trial were 16% and 100%, respectively. Data quality was high, except for missing data from Fitbit activity trackers of approximately 30% from the 4- and 12-week follow-up stages. The feasibility challenges with activity trackers include rashes, size, non-acceptance, and loss of motivation. Participants and family members/staff reported interest in the study theme and were pleased with the data collection method. All but one participant achieved their PA goals. Most participants reported being satisfied with the apps as they were enjoyable or provided a reminder for performing physical and other activities. Social support for PA among family members also increased. However, app support from staff and family members was needed, and apps were not used regularly. Two of nine participants (22%) had increased their PA measured as steps per day with Fitbit at the 12-week follow-up.

Conclusions

The acceptability and feasibility of using tailored mobile applications in natural settings to increase PA among adults with ID are promising. This study aligns with previous studies in showing the challenges to increasing PA, which requires the inclusion of family members, staff, and stakeholders. The intervention requires modifications before a randomized controlled trial can be conducted.

Load Monitoring and Its Relationship with Healthcare in Sports

Load monitoring consists of training/match demand quantification as well as wellness and readiness to maximize the likelihood of optimal athletic performance [...].

Validity of activity wristbands for estimating daily physical activity in primary schoolchildren under free-living conditions: School-Fit study

Introduction

The use of activity wristbands to monitor and promote schoolchildren's physical activity (PA) is increasingly widespread. However, their validity has not been sufficiently studied, especially among primary schoolchildren. Consequently, the main purpose was to examine the validity of the daily steps and moderate-to-vigorous PA (MVPA) scores estimated by the activity wristbands Fitbit Ace 2, Garmin Vivofit Jr 2, and the Xiaomi Mi Band 5 in primary schoolchildren under free-living conditions.

Materials and methods

An initial sample of 67 schoolchildren (final sample = 62; 50% females), aged 9-12 years old (mean = 10.4 ± 1.0 years), participated in the present study. Each participant wore three activity wristbands (Fitbit Ace 2, Garmin Vivofit Jr 2, and Xiaomi Mi Band 5) on his/her non-dominant wrist and a research-grade accelerometer (ActiGraph wGT3X-BT) on his/her hip as the reference standard (number of steps and time in MVPA) during the waking time of one day.

Results

Results showed that the validity of the daily step scores estimated by the Garmin Vivofit Jr 2 and Xiaomi Mi Band 5 were good and acceptable (e.g., MAPE = 9.6/11.3%, and lower 95% IC of ICC = 0.87/0.73), respectively, as well as correctly classified schoolchildren as meeting or not meeting the daily 10,000/12,000-step-based recommendations, obtaining excellent/good and good/acceptable results (e.g., Garmin Vivofit Jr 2, k = 0.75/0.62; Xiaomi Mi Band 5, k = 0.73/0.53), respectively. However, the Fitbit Ace 2 did not show an acceptable validity (e.g., daily steps: MAPE = 21.1%, and lower 95% IC of ICC = 0.00; step-based recommendations: k = 0.48/0.36). None of the three activity wristbands showed an adequate validity for estimating daily MVPA (e.g., MAPE = 36.6-90.3%, and lower 95% IC of ICC = 0.00-0.41) and the validity for the MVPA-based recommendation tended to be considerably lower (e.g., k = -0.03-0.54).

Conclusions

The activity wristband Garmin Vivofit Jr 2 obtained the best validity for monitoring primary schoolchildren's daily steps, offering a feasible alternative to the research-grade accelerometers. Furthermore, this activity wristband could be used during PA promotion programs to provide accurate feedback to primary schoolchildren to ensure their accomplishment with the PA recommendations.

Continuous Monitoring of Health and Mobility Indicators in Patients with Cardiovascular Disease: A Review of Recent Technologies

Cardiovascular diseases kill 18 million people each year. Currently, a patient's health is assessed only during clinical visits, which are often infrequent and provide little information on the person's health during daily life. Advances in mobile health technologies have allowed for the continuous monitoring of indicators of health and mobility during daily life by wearable and other devices. The ability to obtain such longitudinal, clinically relevant measurements could enhance the prevention, detection and treatment of cardiovascular diseases. This review discusses the advantages and disadvantages of various methods for monitoring patients with cardiovascular disease during daily life using wearable devices. We specifically discuss three distinct monitoring domains: physical activity monitoring, indoor home monitoring and physiological parameter monitoring.

Wearable-based accelerometer activity profile as digital biomarker of inflammation, biological age, and mortality using hierarchical clustering analysis in NHANES 2011-2014

Repeated disruptions in circadian rhythms are associated with implications for health outcomes and longevity. The utilization of wearable devices in quantifying circadian rhythm to elucidate its connection to longevity, through continuously collected data remains largely unstudied. In this work, we investigate a data-driven segmentation of the 24-h accelerometer activity profiles from wearables as a novel digital biomarker for longevity in 7,297 U.S. adults from the 2011-2014 National Health and Nutrition Examination Survey. Using hierarchical clustering, we identified five clusters and described them as follows: "High activity", "Low activity", "Mild circadian rhythm (CR) disruption", "Severe CR disruption", and "Very low activity". Young adults with extreme CR disturbance are seemingly healthy with few comorbid conditions, but in fact associated with higher white blood cell, neutrophils, and lymphocyte counts (0.05-0.07 log-unit, all p < 0.05) and accelerated biological aging (1.42 years, p < 0.001). Older adults with CR disruption are significantly associated with increased systemic inflammation indexes (0.09-0.12 log-unit, all p < 0.05), biological aging advance (1.28 years, p = 0.021), and all-cause mortality risk (HR = 1.58, p = 0.042). Our findings highlight the importance of circadian alignment on longevity across all ages and suggest that data from wearable accelerometers can help in identifying at-risk populations and personalize treatments for healthier aging.

ehealth technology in cardiac exercise therapeutics for pediatric patients with congenital and acquired heart conditions: a summary of evidence and future directions

Many children and adolescents with congenital and acquired heart disease (CHD) are physically inactive and participate in an insufficient amount of moderate-to-vigorous intensity exercise. Although physical activity (PA) and exercise interventions are effective at improving short- and long-term physiological and psychosocial outcomes in youth with CHD, several barriers including resource limitations, financial costs, and knowledge inhibit widespread implementation and dissemination of these beneficial programs. New and developing eHealth, mHealth, and remote monitoring technologies offer a potentially transformative and cost-effective solution to increase access to PA and exercise programs for youth with CHD, yet little has been written on this topic. In this review, a cardiac exercise therapeutics (CET) model is presented as a systematic approach to PA and exercise, with assessment and testing guiding three sequential PA and exercise intervention approaches of progressive intensity and resource requirements: (1) PA and exercise promotion within a clinical setting; (2) unsupervised exercise prescription; and (3) medically supervised fitness training intervention (i.e., cardiac rehabilitation). Using the CET model, the goal of this review is to summarize the current evidence describing the application of novel technologies within CET in populations of children and adolescents with CHD and introduce potential future applications of these technologies with an emphasis on improving equity and access to patients in low-resource settings and underserved communities.

Validity of the Xiaomi Mi Band 2, 3, 4 and 5 Wristbands for Assessing Physical Activity in 12-to-18-Year-Old Adolescents under Unstructured Free-Living Conditions. Fit-Person Study

The purpose was to assess the validity of four generations of Xiaomi Mi Band wristbands for the assessment of step count and physical activity (PA) levels among adolescents aged 12-18 years under free-living conditions. One hundred adolescents were invited to participate in the present study. The final sample consisted of 62 high-school students (34 females), aged 12-18 years old (Mage = 14.1 ± 1.6 years), who wore an ActiGraph accelerometer on their hip (PA and step count reference measures) and four activity wristbands (Xiaomi Mi Band 2, 3, 4, and 5) on their non-dominant wrist during the waking time of one day. Results showed that the agreement between daily PA levels (i.e., slow, brisk, and slow-brisk pace walking, total PA and moderate-to-vigorous PA) measured by Xiaomi Mi Band wristbands and the accelerometer were poor (ICC, 95% CI = 0.06-0.78, 0.00-0.92; MAPE = 50.1-150.6%). However, agreement between daily step count measured by the accelerometer and the Xiaomi Mi Band wristbands were between acceptable (MAPE = 12.2-13.6%) to excellent (ICC, 95% CI = 0.94-0.95, 0.90-0.97). Furthermore, the Xiaomi Mi Band wristbands have a good to excellent validity for correctly classifying adolescents as meeting or not meeting the recommended 10,000 steps per day (P = 0.89-0.95, k = 0.71-0.87) and the recommended 60 minutes of moderate-to-vigorous PA per day (P = 0.89-0.94, k = 0.69-0.83). Furthermore, comparability between the four Xiaomi Mi Band generations were poor to excellent (ICC, 95% CI = 0.22-0.99, 0.00-1.00) for the daily PA levels outputs, although it was excellent (ICC, 95% CI = 0.99-1.00, 0.96-1.00; MAPE = 0.0-0.1%) for daily step count. Different models of Xiaomi Mi Band wristbands were comparable and presented good validity for measuring adolescents' step count, and they accurately classified adolescents as meeting or not meeting the PA recommendations under free-living conditions.

Comprehensive assessment of postoperative mobility during the first days after mini-invasive lung surgery: A prospective observational study

STUDY OBJECTIVE

Postoperative physical therapy and early mobilization are major elements for enhanced recovery after surgery. In contrast with supervised physical therapy sessions that can be monitored, self-mobilization is not easily quantifiable and has so far been estimated mainly through patient auto-reports. This study aimed to perform a comprehensive and objective evaluation of postoperative mobility.

DESIGN

Prospective observational study.

SETTING

Postoperative setting.

PATIENTS

Patients undergoing mini-invasive lung surgery.

INTERVENTIONS

Measurement of postoperative mobility during the first five postoperative days using an accelerometer (ActiGraph GT3X).

MEASUREMENTS

The primary outcome was the number of daily steps. Secondary outcomes included physical activity duration and intensity, sedentary time, number of breaks in sedentary time, sedentary patterns, daily evaluation by physiotherapists, postoperative complications, and acceptability of wearing the accelerometer.

MAIN RESULTS

Sixty patients were included in the study, of whom 56 provided at least one day of valid accelerometry data. There was no significant change during the first four PODs concerning the number of daily steps nor the mean cadence. One-minute cadence peak, total activity counts, and duration of light-intensity physical activity increased over time (p = 0.032, p = 0.001 and p = 0.001, respectively). Sedentary patterns changed favorably over time, with a decrease in prolonged sedentary bouts (≥ 60 consecutive min) (p < 0.001), and an increase in shorter bouts (< 10 min) (p = 0.001). Similar results were observed when analysis was adjusted for the day of the week when the surgery took place. The median acceptability of wearing the accelerometer was excellent (median 10 [9-10] on a 10-point Likert scale). Three patients had major complications.

CONCLUSIONS

Our findings suggest that daily steps may not be the only relevant indicator of early mobility following thoracic surgery and that accelerometry is suitable to follow patients' early postoperative activity.

Clinical Impact of Physical Activity and Cough on Disease Progression in Fibrotic Interstitial Lung Disease

Physical activity limitations and cough are common in patients with interstitial lung disease (ILD), potentially leading to reduced health-related quality of life. We aimed to compare physical activity and cough between patients with subjective, progressive idiopathic pulmonary fibrosis (IPF) and fibrotic non-IPF ILD. In this prospective observational study, wrist accelerometers were worn for seven consecutive days to track steps per day (SPD). Cough was evaluated using a visual analog scale (VAS_cough) at baseline and weekly for six months. We included 35 patients (IPF: n = 13; non-IPF: n = 22; mean ± SD age 61.8 ± 10.8 years; FVC 65.3 ± 21.7% predicted). Baseline mean ± SD SPD was 5008 ± 4234, with no differences between IPF and non-IPF ILD. At baseline, cough was reported by 94.3% patients (mean ± SD VAS_cough 3.3 ± 2.6). Compared to non-IPF ILD, patients with IPF had significantly higher burden of cough (p = 0.020), and experienced a greater increase in cough over six months (p = 0.009). Patients who died or underwent lung transplantation (n = 5), had significantly lower SPD (p = 0.007) and higher VAS_cough (p = 0.047). Long-term follow up identified VAS_cough (HR: 1.387; 95%-CI 1.081-1.781; p = 0.010) and SPD (per 1000 SPD: HR 0.606; 95%-CI: 0.412-0.892; p = 0.011) as significant predictors for transplant-free survival. In conclusion, although activity didn't differ between IPF and non-IPF ILD, cough burden was significantly greater in IPF. SPD and VAS_cough differed significantly in patients who subsequently experienced disease progression and were associated with long-term transplant-free survival, calling for better acknowledgement of both parameters in disease management.

Physical activity monitoring-based interventions in geriatric patients: a scoping review on intervention components and clinical applicability

OBJECTIVE

To identify and analyze the components applied in interventions using physical activity (PA) monitoring in geriatric patients and determine their feasibility and applicability.

METHODS

A systematic search in six databases (PubMed, Embase, SPORTDiscus, CINAHL, Web of Science, and GeroLit) was conducted to identify studies reporting interventions that included the application of a PA monitor in adults aged ≥ 60 years with a clinical diagnosis. PA monitor interventions were analyzed regarding their feedback, goal-setting and behavior change technique (BCT) components. To determine the feasibility and applicability of interventions, the participants' adherence to the intervention, their experience as well as adverse events were analyzed.

RESULTS

Seventeen eligible studies, applying 22 interventions, were identified. Studies included a total of 827 older patients with a median age of 70.2 years. In thirteen interventions (59%), the PA monitor was embedded in a structured behavioral intervention, an indication-specific intervention or usual care. Most frequently applied intervention components were goal setting and self-monitoring (n = 18), real-time PA monitor feedback complemented by feedback from the study team (n = 12), use of further BCTs (n = 18), and regular counseling with the study team (n = 19). Comprehensive information on the participants' intervention adherence and experience were reported for 15 (68%) and 8 (36%) interventions, respectively.

CONCLUSION

The components included in PA monitoring-based interventions varied considerably especially regarding the extent, frequency, and content of feedback, goal setting and BCTs counseling. Future research should evaluate which components are most effective and clinically applicable to promote physical activity in geriatric patients. To be able to precisely analyze the effects, trials should seek to report details on intervention components, adherence and adverse events, while future reviews may use the findings of this scoping review to conduct analyses with less heterogeneity in study characteristics and intervention strategies.

Collecting health-related research data using consumer-based wireless smart scales

BACKGROUND

Serious public-health concerns such as overweight and obesity are in many cases caused by excess intake of food combined with decreases in physical activity. Smart scales with wireless data transfer can, together with smart watches and trackers, observe changes in the population's health. They can present us with a picture of our metabolism, body health, and disease risks. Combining body composition data with physical activity measurements from devices such as smart watches could contribute to building a human digital twin.

OBJECTIVE

The objectives of this study were to (1) investigate the evolution of smart scales in the last decade, (2) map status and supported sensors of smart scales, (3) get an overview of how smart scales have been used in research, and (4) identify smart scales for current and future research.

METHOD

We searched for devices through web shops and smart scale tests/reviews, extracting data from the manufacturer's official website, user manuals when available, and data from web shops. We also searched scientific literature databases for smart scale usage in scientific papers.

RESULT

We identified 165 smart scales with a wireless connection from 72 different manufacturers, released between 2009 and end of 2021. Of these devices, 49 (28%) had been discontinued by end of 2021. We found that the use of major variables such as fat and muscle mass have been as good as constant over the years, and that minor variables such as visceral fat and protein mass have increased since 2015. The main contribution is a representative overview of consumer grade smart scales between 2009 and 2021.

CONCLUSION

The last six years have seen a distinct increase of these devices in the marketplace, measuring body composition with bone mass, muscle mass, fat mass, and water mass, in addition to weight. Still, the number of research projects featuring connected smart scales are few. One reason could be the lack of professionally accurate measurements, though trend analysis might be a more feasible usage scenario.

Evaluating Gait Impairment in Parkinson's Disease from Instrumented Insole and IMU Sensor Data

Parkinson's disease (PD) is characterized by a variety of motor and non-motor symptoms, some of them pertaining to gait and balance. The use of sensors for the monitoring of patients' mobility and the extraction of gait parameters, has emerged as an objective method for assessing the efficacy of their treatment and the progression of the disease. To that end, two popular solutions are pressure insoles and body-worn IMU-based devices, which have been used for precise, continuous, remote, and passive gait assessment. In this work, insole and IMU-based solutions were evaluated for assessing gait impairment, and were subsequently compared, producing evidence to support the use of instrumentation in everyday clinical practice. The evaluation was conducted using two datasets, generated during a clinical study, in which patients with PD wore, simultaneously, a pair of instrumented insoles and a set of wearable IMU-based devices. The data from the study were used to extract and compare gait features, independently, from the two aforementioned systems. Subsequently, subsets comprised of the extracted features, were used by machine learning algorithms for gait impairment assessment. The results indicated that insole gait kinematic features were highly correlated with those extracted from IMU-based devices. Moreover, both had the capacity to train accurate machine learning models for the detection of PD gait impairment.

Measuring social desirability bias in a multi-ethnic cohort sample: its relationship with self-reported physical activity, dietary habits, and factor structure

BACKGROUND

Social desirability bias is one of the oldest forms of response bias studied in social sciences. While individuals may feel the need to fake good or bad answers in response to sensitive or intrusive questions, it remains unclear how rampant such a bias is in epidemiological research pertaining to self-reported lifestyle indicators in a multicultural Asian context. The main purpose of the current study is, therefore, to examine the sociodemographic correlates and impact of social desirability responding on self-reported physical activity and dietary habits at an epidemiological scale in a non-western multi-cultural Asian setting.

METHODS

Prior to the main analyses, confirmatory and exploratory factor analyses were conducted to determine the factorial validity of a western derived concept of social desirability. Multiple regression analyses were conducted on cross-sectional data (n = 2995) extracted from a nationwide survey conducted between 2019 and 2020.

RESULTS

A unique factor structure of social desirability was found and was therefore used for subsequent analyses. Multiple regression analyses revealed older age groups, the Indian ethnic group, those with past or present marriages, and having no income, had a significantly greater tendency to act on the bias.

CONCLUSION

The construct of social desirability bias was fundamentally different in a multicultural context than previously understood. Only a small proportion of variance of self-report lifestyle scores was explained by social desirability, thus providing support for data integrity.

Physical activity in Norwegian teenagers and young adults with haemophilia A compared to general population peers

INTRODUCTION

Limited evidence exists on objectively measured habitual physical activity (PA) of young people with haemophilia (PWH).

AIMS

To compare different outcomes of objective PA between young PWH A and controls using a commercial activity tracker.

METHODS

We enrolled males aged 13-30 years with moderate and severe haemophilia A, without inhibitors on regular prophylaxis. PA was measured with the activity tracker Fitbit Charge 3 for 12 weeks. Control group data was obtained from ≈60,000 Fitbit users, matched on age, sex and measurement period. PA variables [steps, intensities, volume, activity types, exercise frequencies and proportion meeting the World Health Organization's moderate-to-vigorous PA (MVPA) recommendations] were compared between groups descriptively and using Welch's two-sample t-test and two-sample test of proportions.

RESULTS

Forty PWH A were enrolled (mean age 19.5 years, 50% teenagers, 50% adults, three (7.5%) with moderate and 37 (92.5%) with severe haemophilia). Mean daily steps and minutes MVPA were similar between PWH and controls. PWH spent more time in light PA (mean 227 vs. 192 min/day, P = .033) and exercised more frequently (mean 5.6 vs. 3.9 exercise sessions/week, P < .001). Among teenagers, 40% PWH and 8% controls reached MVPA recommendations, compared to 95% and 100% among adults. The most common type of PA was walking.

CONCLUSION

This cohort of young PWH A on prophylactic treatment had PA levels comparable to controls. Still, a considerable proportion of teenagers did not meet the recommended weekly volume of MVPA, and we encourage clinicians to have a particular focus on promoting PA for this group.

Effectiveness of Wearable Activity Monitors on Metabolic Outcomes in Patients With Type 2 Diabetes: A Systematic Review and Meta-Analysis

OBJECTIVE

Wearable activity monitors are promising tools for improving metabolic outcomes in patients with type 2 diabetes mellitus (T2DM); however, no uniform conclusive evidence is available. This study aimed to evaluate the effects of the intervention using wearable activity monitors on blood glucose, blood pressure, blood lipid, weight, waist circumference, and body mass index (BMI) in individuals with T2DM.

METHODS

Two independent reviewers searched 4 online databases (PubMed, Cochrane Library, Web of Science, and Embase) to identify relevant studies published from January 2000 to October 2022. The primary outcome indicator was hemoglobin A1c (HbA1c), and the secondary outcome indicators included physical activity (steps per day), fasting blood glucose, triglyceride, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, total cholesterol, systolic blood pressure, diastolic blood pressure, BMI, waist circumference, and weight.

RESULTS

A total of 25 studies were included. The HbA1c level (standardized mean difference [SMD], -0.14; 95% confidence interval [CI], -0.27 to -0.02; P = .02; I² = 48%), BMI (SMD, -0.16; 95% CI, -0.26 to -0.05; P = .002; I² = 0), waist circumference (SMD, -0.21; 95% CI, -0.34 to -0.09; P < .001; I² = 0), and steps/day (SMD, 0.55; 95% CI, 0.36-0.94; P < .001; I² = 77%) significantly improved.

CONCLUSION

Wearable activity monitor-based interventions could facilitate the improvement of the HbA1c level, BMI, and waist circumference and increase in physical activity in individuals with T2DM. Wearable technology appeared to be an effective tool for the self-management of T2DM; however, there is insufficient evidence about its long-term effect.

Experience and Satisfaction with a Family-Based Physical Activity Intervention Using Activity Trackers and Apps: A Qualitative Study

Wearable activity trackers and smartphone apps have been shown to increase physical activity in children and adults. However, interventions using activity trackers and apps have rarely been tested in whole families. This study examined the experience and satisfaction with an activity tracker and app intervention (Step it Up Family) to increase physical activity in whole families. Telephone interviews were conducted with Queensland-based families (n = 19) who participated in the Step it Up Family intervention (N = 40, single-arm, pre/post feasibility study) in 2017/2018. Using commercial activity trackers combined with apps, the intervention included an introductory session, individual and family-level goal setting, self-monitoring, family step challenges, and weekly motivational text messages. Qualitative content analysis was conducted to identify themes, categories and sub-categories. In summary, parents reported that children were engaged with the activity tracker and app features to reach their daily step goals. Some technical difficulties were experienced with app navigation, syncing of activity tracker data, and tracker band discomfort. Although families liked that the weekly text messages reminded them to be active, they did not find them very motivating. Using text messages for physical activity motivation in families requires further testing. Overall, the intervention was well-received by families for increasing physical activity motivation.

Enhancing user awareness on inferences obtained from fitness trackers data

In the IoT era, sensitive and non-sensitive data are recorded and transmitted to multiple service providers and IoT platforms, aiming to improve the quality of our lives through the provision of high-quality services. However, in some cases these data may become available to interested third parties, who can analyse them with the intention to derive further knowledge and generate new insights about the users, that they can ultimately use for their own benefit. This predicament raises a crucial issue regarding the privacy of the users and their awareness on how their personal data are shared and potentially used. The immense increase in fitness trackers use has further increased the amount of user data generated, processed and possibly shared or sold to third parties, enabling the extraction of further insights about the users. In this work, we investigate if the analysis and exploitation of the data collected by fitness trackers can lead to the extraction of inferences about the owners routines, health status or other sensitive information. Based on the results, we utilise the PrivacyEnhAction privacy tool, a web application we implemented in a previous work through which the users can analyse data collected from their IoT devices, to educate the users about the possible risks and to enable them to set their user privacy preferences on their fitness trackers accordingly, contributing to the personalisation of the provided services, in respect of their personal data.

Promoting Healthy Behaviors in Older Adults to Optimize Health-Promoting Lifestyle: An Intervention Study

Introduction: Exercise intervention is the easiest and most effective way to promote human health. This study combined technology and exercise to improve the health behavior of the older adults through a physical activity intervention and to enhance a health-promoting lifestyle. Materials and methods: A quasi-experimental research method was used to openly recruit 120 healthy male and female older adults over 65 years old (average age of males: 71.6 ± 1.25 years; average age of females: 72.3 ± 1.28 years), all of whom wore smart bracelets. The participants were monitored by special personnel during the same period of walking every Monday to Friday. All participants recorded their daily steps, distance walked, and calorie consumption data for a period of 8 weeks. Results: After 8 weeks of walking, all participants showed a positive medium−high correlation of various factors between healthy behaviors and the health-promoting lifestyle scales. In the post-tests of each factor of two scales, males had the highest correlation between regular physical activity and physical activity, and females had the highest correlation between regular physical activity and social support. The variabilities in the explanatory power of the health behaviors of males and females on the health-promoting lifestyle were R2 = 70.9% (p < 0.01) and R2 = 74.1% (p < 0.01), indicating that the variables of healthy behaviors have a positive effect on health-promoting lifestyles in male and female older adults. Conclusions: Walking interventions positively affect the health behaviors of older adults and encourage health-promoting lifestyles. The value of this study is in its contribution to health promotion and public health recommendations for older adults.

Relationships between External, Wearable Sensor-Based, and Internal Parameters: A Systematic Review

Micro electro-mechanical systems (MEMS) are used to record training and match play of intermittent team sport athletes. Paired with estimates of internal responses or adaptations to exercise, practitioners gain insight into players' dose-response relationship which facilitates the prescription of the training stimuli to optimize performance, prevent injuries, and to guide rehabilitation processes. A systematic review on the relationship between external, wearable-based, and internal parameters in team sport athletes, compliant with the PRISMA guidelines, was conducted. The literature research was performed from earliest record to 1 September 2020 using the databases PubMed, Web of Science, CINAHL, and SportDISCUS. A total of 66 full-text articles were reviewed encompassing 1541 athletes. About 109 different relationships between variables have been reviewed. The most investigated relationship across sports was found between (session) rating of perceived exertion ((session-)RPE) and PlayerLoad™ (PL) with, predominantly, moderate to strong associations (r = 0.49-0.84). Relationships between internal parameters and highly dynamic, anaerobic movements were heterogenous. Relationships between average heart rate (HR), Edward's and Banister's training impulse (TRIMP) seem to be reflected in parameters of overall activity such as PL and TD for running-intensive team sports. PL may further be suitable to estimate the overall subjective perception. To identify high fine-structured loading-relative to a certain type of sport-more specific measures and devices are needed. Individualization of parameters could be helpful to enhance practicality.

Comparative effectiveness of playing golf to Nordic walking and walking on acute physiological effects on cardiometabolic markers in healthy older adults: a randomised cross-over study

Objectives

The acute effects of aerobic exercise on cardiometabolic markers are well documented in younger healthy individuals, but the same effects in older adults have not been elucidated. As such, this study compares the acute effects of three different types of age-appropriate aerobic exercises on cardiometabolic markers.

Methods

Healthy older golfers (n=25, 16 male and 9 female, 68±4 years) were enrolled in a randomised cross-over experiment. We compared the effects of three different acute aerobic exercises (18-hole golf, 6 km Nordic walk, 6 km walk) on blood pressure, blood glucose and blood lipid profile in a real-life environment.

Results

In the between-group comparison, playing golf resulted in a difference in blood glucose (golf: 0.01±1.0 mmol/L, walk: 1.3±0.9 mmol/L, p<0.001) compared with walking and triglycerides (golf: 0.13±0.2 mmol/L, Nordic walk: 0.31±0.2 mmol/L, walk: 0.23±0.2 mmol, p=0.012) and high-density lipoprotein cholesterol (golf: 0.04±0.06 mmol/L, Nordic walk: -0.02±0.06 mmol/L, walk: -0.02±0.07 mmol/L, p=0.002) compared with Nordic walking and walking. In addition, all groups had significant decreases (p<0.001) in systolic blood pressure, and Nordic walking and walking also demonstrated a decrease in diastolic blood pressure (p<0.05).

Conclusion

Acute bouts of aerobic exercise improved cardiovascular profile in healthy older adults. Despite the lower exercise intensity of golf, the longer duration and higher energy expenditure appeared to have a more positive effect on lipid profile and glucose metabolism compared with Nordic walking and walking.

Trial registration number

ISRCTN10007294.

Towards multimodal boosting of motivation for fall-preventive physical activity in seniors: An iterative development evaluation study

Background

Many seniors need to increase their physical activity (PA) and participation in fall prevention exercise. Therefore, digital systems have been developed to support fall-preventive PA. Most of them lack video coaching and PA monitoring, two functionalities that may be relevant for increasing PA.

Objective

To develop a prototype of a system to support seniors' fall-preventive PA, which includes also video coaching and PA monitoring, and to evaluate its feasibility and user experience.

Methods

A system prototype was conceived by integrating applications for step-monitoring, behavioural change support, personal calendar, video-coaching and a cloud service for data management and co-ordination. Its feasibility and user experience were evaluated in three consecutive test periods combined with technical development. In total, 11 seniors tested the system at home for four weeks with video coaching from health care professionals.

Results

Initially, the system's feasibility was non-satisfactory due to insufficient stability and usability. However, most problems could be addressed and amended. In the third (last) test period, both seniors and coaches experienced the system prototype to be fun, flexible and awareness-raising. Interestingly, the video coaching which made the system unique compared to similar systems was highly appreciated. Nonetheless, even the users in the last test period highlighted issues due to insufficient usability, stability and flexibility. Further improvements in these areas are needed.

Conclusions

Video coaching in fall-preventive PA can be valuable for both seniors and health care professionals. High reliability, usability and flexibility of systems supporting seniors are essential.

A feasibility study to evaluate a purposeful walk intervention with a distance goal using a commercially available activity monitor in elderly people post total hip replacement surgery

Introduction

Total hip replacement (THR) is performed in an increasing number of individuals around the world and while improvements in pain reduction and long-term enhancement of muscle strength are well documented, the improvement in daily activity does not follow the same trend. This study aimed to determine the feasibility of a 5-week intervention where a personalised outdoor walking distance is monitored using a commercial activity monitor (Fitbit Charge 4).

Method

Data was collected on gait and activities of daily living using patient reported outcome measures. Following the completion of the intervention period, participants took part in a semi-structured interview to voice their opinion on the use of the activity monitor, their experiences, and any challenges in order to assess the feasibility of the intervention. All quantitative data were presented descriptively, using appropriate summary statistics. Interviews were analysed using thematic analysis.

Results

Five participants who had undergone total hip replacement surgery within the postoperative period of 3 to 6 months were recruited from the local community.

Conclusion

The findings suggest that the intervention was feasible and that it encouraged all participants to increase their daily activity. Therefore, it can be concluded that a follow-up effectiveness trial is warranted.

The effectiveness of wearable activity trackers for increasing physical activity and reducing sedentary time in older adults: A systematic review and meta-analysis

Background

Traditional interventions such as education and counseling are successful in increasing physical activity (PA) participation, but are usually labor and resource intensive. Wearable activity trackers can objectively record PA and provide feedback to help users to achieve activity goals and are an increasingly popular tool among adults used to facilitate self-monitoring of PA. However, no reviews systematically explored the roles of wearable activity trackers in older populations.

Methods

We searched PubMed, Web of Science, Google Scholar, Embase, Cochrane Library, and Scopus from inception to September 10, 2022. Randomized controlled trials were included. Two reviewers independently conducted study selection, data extraction, risk of bias, and certainty of evidence assessment. A random-effects model was used to evaluate the effect size.

Results

A total of 45 studies with 7144 participants were included. A wearable activity tracker was effective in increasing daily steps (standard mean differences (SMD) = 0.59, 95% confidence interval (CI) (0.44, 0.75)), weekly moderate-to-vigorous PA (MVPA) (SMD = 0.54, 95% CI (0.36, 0.72)), and total daily PA (SMD = 0.21, 95% CI (0.01, 0.40)) and reducing sedentary time (SMD = -0.10, 95% CI (-0.19, -0.01)). Subgroup analysis showed that the effectiveness of wearable activity trackers for daily steps was not influenced by participants and intervention features. However, wearable activity trackers seemed more effective in promoting MVPA of participant's age <70 than participant's age ≥70. In addition, wearable activity trackers incorporated with traditional intervention components (e.g. telephone counseling, goal setting, and self-monitoring) could better promote MVPA than alone use. Short-term interventions potentially achieve better MVPA increase than long-term.

Conclusion

This review showed that wearable activity trackers are an effective tool to increase PA for the old population and also favor reducing sedentary time. When used together with other interventions, wearable activity trackers can achieve better MVPA increase, especially in the short term. However, how to more effectively improve the effectiveness of wearable activity trackers is an important direction of future research.