Accuracy and Precision of Energy Expenditure, Heart Rate, and Steps Measured by Combined-Sensing Fitbits Against Reference Measures: Systematic Review and Meta-analysis

Apple watch accuracy in monitoring health metrics: a systematic review and meta-analysis

Objective. Wearable technology like the Apple Watch is increasingly important for monitoring health metrics. Accurate measurement is crucial, as inaccuracies can impact health outcomes. Despite extensive research, findings on the Apple Watch's accuracy vary across different conditions. While previous reviews have summarized findings, few have utilized a meta-analytic approach. This study aims to quantitatively evaluate the accuracy of the Apple Watch in measuring health metrics. The accuracy of the Apple Watch was assessed in measuring energy expenditure (EE), heart rate (HR), and step counts (steps).Approach. We searched Embase, PubMed, Scopus, and SPORTDiscus for studies on adults using the Apple Watch compared to reference measures. The Bland-Altman framework was applied to assess mean bias and limits of agreement (LoA), with robust variance estimation to address within-study correlations. Heterogeneity was assessed across variables such as age, health status, device series, activity intensity, and activity type. Additionally, the mean absolute percentage error (MAPE) reported in the included studies was summarized by subgroups.Main results. This review included 56 studies, comprising 270 effect sizes on EE (71), HR (148), and steps (51). The meta-analysis showed a mean bias of 0.30 (LoA: -2.09-2.69) for EE (kcal min-1), -0.12 (LoA: -11.06-10.81) for HR (beats min-1), -1.83 (LoA: -9.08-5.41) for steps (steps min-1). The forest plots showed variability in LoA across subgroups. For MAPE, all subgroups for EE exceeded the 10% validity threshold, while none of the subgroups for HR exceeded this threshold. For steps, some subgroups exceeded 10%, highlighting variability in accuracy based on different conditions.Significance. This study demonstrates that while the Apple Watch generally provides accurate HR and step measurements, its accuracy for EE is limited. Although HR and step measurements showed acceptable accuracy, variability was observed across different user characteristics and measurement conditions. These findings highlight the importance of considering such factors when evaluating validity.

Reliability of Average Daily Steps Measured Through a Consumer Smartwatch in Parkinson Disease Phenotypes, Stages, and Severities: Cross-Sectional Study

Background

Average daily steps (avDS) could be a valuable indicator of real-world ambulation in people with Parkinson disease (PD), and previous studies have reported the validity and reliability of this measure. Nonetheless, no study has considered disease phenotype, stage, and severity when assessing the reliability of consumer wrist-worn devices to estimate daily step count in unsupervised, free-living conditions in PD.

Objective

This study aims to assess and compare the reliability of a consumer wrist-worn smartwatch (Garmin Vivosmart 4) in counting avDS in people with PD in unsupervised, free-living conditions among disease phenotypes, stages, and severity groups.

Methods

A total of 104 people with PD were monitored through Garmin Vivosmart 4 for 5 consecutive days. Total daily steps were recorded and avDS were calculated. Participants were dichotomized into tremor dominant (TD; n=39) or postural instability and gait disorder (PIGD; n=65), presence (n=57) or absence (n=47) of tremor, and mild (n=65) or moderate (n=39) disease severity. Based on the modified Hoehn and Yahr scale (mHY), participants were further dichotomized into earlier (mHY 1-2; n=68) or intermediate (mHY 2.5-3; n=36) disease stages. Intraclass correlation coefficient (ICC; 3,k), standard error of measurement (SEM), and minimal detectable change (MDC) were used to evaluate the reliability of avDS for each subgroup. The threshold for acceptability was set at an ICC ≥0.8 with a lower bound of 95% CI ≥0.75. The 2-tailed Student t tests for independent groups and analysis of 83.4% CI overlap were used to compare ICC between each group pair.

Results

Reliability of avDS measured through Garmin Vivosmart 4 for 5 consecutive days in unsupervised, free-living conditions was acceptable in the overall population with an ICC of 0.89 (95% CI 0.85-0.92), SEM below 10%, and an MDC of 1580 steps per day (27% of criterion). In all investigated subgroups, the reliability of avDS was also acceptable (ICC range 0.84-0.94). However, ICCs were significantly lower in participants with tremor (P=.03), with mild severity (P=.04), and earlier stage (P=.003). Moreover, SEM was below 10% in participants with PIGD phenotype, without tremor, moderate disease severity, and intermediate disease stage, with an MDC ranging from 1148 to 1687 steps per day (18%-25% of criterion). Conversely, in participants with TD phenotype, tremor, mild disease severity, and earlier disease stage, SEM was >10% of the criterion and MDC values ranged from 1401 to 2263 steps per day (30%-33% of the criterion).

Conclusions

In mild-to-moderate PD, avDS measured through a consumer smartwatch in unsupervised, free-living conditions for 5 consecutive days are reliable irrespective of disease phenotype, stage, and severity. However, in individuals with TD phenotype, tremor, mild disease severity, and earlier disease stages, reliability could be lower. These findings could facilitate a broader and informed implementation of avDS as an index of ambulatory activity in PD.

Healthy Mom Zone Adaptive Intervention With a Novel Control System and Digital Platform to Manage Gestational Weight Gain in Pregnant Women With Overweight or Obesity: Study Design and Protocol for a Randomized Controlled Trial

BACKGROUND

Regulating gestational weight gain (GWG) in pregnant women with overweight or obesity is difficult, particularly because of the narrow range of recommended GWG for optimal health outcomes. Given that many pregnant women show excessive GWG and considering the lack of a "gold standard" intervention to manage GWG, there is a timely need for effective and efficient approaches to regulate GWG. We have enhanced the Healthy Mom Zone (HMZ) 2.0 intervention with a novel digital platform, automated dosage changes, and personalized strategies to regulate GWG, and our pilot study demonstrated successful recruitment, compliance, and utility of our new control system and digital platform.

OBJECTIVE

The goal of this paper is to describe the study protocol for a randomized controlled optimization trial to examine the efficacy of the enhanced HMZ 2.0 intervention with the new automated control system and digital platform to regulate GWG and influence secondary maternal and infant outcomes while collecting implementation data to inform future scalability.

METHODS

This is an efficacy study using a randomized controlled trial design. HMZ 2.0 is a multidosage, theoretically based, and individually tailored adaptive intervention that is delivered through a novel digital platform with an automated link of participant data to a new model-based predictive control algorithm to predict GWG. Our new control system computes individual dosage changes and produces personalized physical activity (PA) and energy intake (EI) strategies to deliver just-in-time dosage change recommendations to regulate GWG. Participants are 144 pregnant women with overweight or obesity randomized to an intervention (n=72) or attention control (n=72) group, stratified by prepregnancy BMI (<29.9 vs ≥30 kg/m2), and they will participate from approximately 8 to 36 weeks of gestation. The sample size is based on GWG (primary outcome) and informed by our feasibility trial showing a 21% reduction in GWG in the intervention group compared to the control group, with 3% dropout. Secondary outcomes include PA, EI, sedentary and sleep behaviors, social cognitive determinants, adverse pregnancy and delivery outcomes, infant birth weight, and implementation outcomes. Analyses will include descriptive statistics, time series and fixed effects meta-analytic approaches, and mixed effects models.

RESULTS

Recruitment started in April 2024, and enrollment will continue through May 2027. The primary (GWG) and secondary (eg, maternal and infant health) outcome results will be analyzed, posted on ClinicalTrials.gov, and published after January 2028.

CONCLUSIONS

Examining the efficacy of the novel HMZ 2.0 intervention in terms of GWG and secondary outcomes expands the boundaries of current GWG interventions and has high clinical and public health impact. There is excellent potential to further refine HMZ 2.0 to scale-up use of the novel digital platform by clinicians as an adjunct treatment in prenatal care to regulate GWG in all pregnant women.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/66637.

Preadolescent Children Using Real-Time Heart Rate During Moderate to Vigorous Physical Activity: A Feasibility Study

BACKGROUND

Given the global burden of insufficient physical activity (PA) in children, effective behavioral interventions are needed to increase PA levels. Novel technologies can help expand the reach and accessibility of these programs. Despite the potential to use heart rate (HR) to target moderate- to vigorous-intensity PA (MVPA), most HR research to date has focused on the accuracy of HR devices or used HR for PA surveillance rather than as an intervention tool. Furthermore, most commercial HR sensors are designed for adults, and their suitability for children is unknown. Further research about the feasibility and usability of commercial HR devices is required to understand how children may use HR during PA.

OBJECTIVE

This study aimed to explore the use of a chest-worn HR sensor paired with a real-time HR display as an intervention tool among preadolescent children and the usability of a custom-designed app (Connexx) for viewing real-time HR.

METHODS

We developed Connexx, an HR information display app with an HR analytics portal to view HR tracking. Children were recruited via flyers distributed at local public schools, word of mouth, and social media posts. Eligible participants were children aged 9 to 12 years who did not have any medical contraindications to MVPA. Participants took part in a single in-person study session where they monitored their own HR using a commercial HR sensor, learned about HR, and engaged in a series of PAs while using the Connexx app to view their real-time HR. We took field note observations about participant interactions with the HR devices. Participants engaged in a semistructured interview about their experience using Connexx and HR during PA and completed the System Usability Scale (SUS) about the Connexx app. Study sessions were audio and video recorded and transcribed verbatim.

RESULTS

A total of 11 participants (n=6, 55% male; n=9, 82%, non-Hispanic White) with an average age of 10.4 (SD 1.0) years were recruited for the study. Data from observations, interviews, and SUS indicated that preadolescent children can use real-time HR information during MVPA. Observational and interview data indicated that the participants were able to understand their HR after a basic lesson and demonstrated the ability to make use of their HR information during PA. Interview and SUS responses demonstrated that the Connexx app was highly usable, despite some accessibility challenges (eg, small display font). Feedback about usability issues has been incorporated into a redesign of the Connexx app, including larger, color-coded fonts for HR information.

CONCLUSIONS

The results of this study indicate that preadolescent children understood their HR data and were able to use it in real time during PA. The findings suggest that future interventions targeting MVPA in this population should test strategies to use HR and HR monitoring as direct program targets.

Using heart rate data from wrist worn activity trackers to define thresholds for moderate to vigorous physical activity in children and young people with cystic fibrosis

BACKGROUND

Children and young people with cystic fibrosis (CYPwCF) are encouraged to do an average of 60 min of moderate-to-vigorous physical activity (MVPA) daily. However, there are no agreed heart rate (HR) thresholds for defining MVPA, so it is difficult to ascertain whether these targets are actually achieved. Wearable activity trackers enable continuous monitoring of fitness-related measures such as HR and could be used to measure duration and intensity of habitual MVPA. We aimed to define personalized and responsive MVPA thresholds from HR in CYPwCF, to determine habitual time spent in MVPA during childhood and adolescence.

METHODS

Continuous daily HR data were collected from 142 CYPwCF wearing activity trackers over 16 months. Linear mixed-effects models were used to develop personalised estimates of resting heart rate (RHR), peak heart rate (PHR) and MVPA thresholds, which were defined using the American College of Sports Medicine heart rate reserve (HRR) method.

RESULTS

309,926 days of physical activity data showed that both RHR and PHR declined with age in CYPwCF, with considerable variability within and between individuals. The HRR method produced personalised MVPA thresholds for each CYPwCF based on age, which inherently accounted for individual demographic variability and personal factors such as cardiovascular fitness or disease severity.

CONCLUSIONS

By accounting for within and between person variability in RHR and PHR, our novel method provides more accurate age-related personalised MVPA thresholds for CYPwCF than existing estimates. Our findings provide population-based estimates for RHR, PHR and MVPA thresholds at different ages in CYPwCF. This approach may help guide development of international standards for objective MVPA measurement in the era of remote HR and activity monitoring and facilitate accurate measurement of habitual physical activity in children and young people.

A randomized comparative effectiveness trial to evaluate two programs for promotion of physical activity after spinal cord injury in manual wheelchair users

Objective

The goal of this study was to determine the effectiveness of a novel whole of day activity accumulation (WODAA) physical exercise program. WODAA physical activity and physiological outcomes were compared to outcomes from individuals using a traditional planned arm crank exercise (PACE) program. Both programs included progressive exercise instruction and goal setting over a 4-month period, and utilization of a wrist-worn activity monitor (Fitbit Blaze/Versa, Fitbit Inc., San Francisco, CA).

Design

Longitudinal, randomized, comparative effectiveness trial with collaborative goal setting.

Setting

Research laboratory at a rehabilitation hospital and in participants' homes and communities.

Participants

Forty-nine manual wheelchair users with paraplegia.

Outcome measures

Physical activity measurements and cardiometabolic data were collected before, during, and after the program. The primary measures were amount of daily arm activity (Steps) and time spent in different activity and heart rate zones.

Results

Relative to baseline measures, participants in the WODAA group had significantly more daily arm movement/propulsion activity (Steps) and time spent in the Fairly and Very Active Zones and the Cardio Heart Rate Zone compared to those in the PACE group over the final month of the intervention (p < 0.05). Minutes spent in other Activity and Heart Rate Zones were similar between groups. At final evaluation, diastolic blood pressure after a 6-Minute Push Test was significantly lower in the WODAA group, while no differences were found in distance traveled, systolic, or pre-test diastolic blood pressures. Metabolic bloodwork and shoulder pain scores did not change and were similar between groups.

Conclusion

Depending on the measure used, these findings suggest that a WODAA approach to PA is comparable or more effective than a traditional PACE program in promoting physical activity in low-active manual wheelchair users with paraplegia.

Disruption in Autonomic Nervous Activity Is Associated With Central and Peripheral-Level in Dry Eye With Unstable Tear Film

Purpose

To measure autonomic nerve activity (ANA) in several eye conditions and verify whether ANA modulation is regulated by peripheral or central control in short tear film break-up time dry eye (sBUTDE).

Methods

This study included 23 eyes of 23 patients with sBUTDE (mean age 55.2 ± 16.1 years; range 21-88 years) and 24 eyes of 24 age-matched non-dry eye (DE) controls. An ANA measurement, personality questionnaire, and Ocular Surface Disease Index were administered. ANA was continuously measured for 10 minutes under three conditions: eyes closed, eyes open, and eyes open under ocular surface anesthesia.

Results

The low-frequency (LF)/high-frequency (HF) ratio (LF/HF) with eyes closed was significantly higher in the sBUTDE group than in the control group (P < 0.05). In the sBUTDE group, HF increased and LF/HF decreased with eye opening compared with those in the control group; HF with eyes open decreased with ocular surface anesthesia and reached the same level as that in the control group. Among patients where HF decreased or LF/HF increased with eye opening, 57.1% or 64.3% showed a tendency to return to the ANA state with eyes closed by ocular surface anesthesia, respectively. Factors associated with DE symptoms included break-up time, HF with eyes open, and "openness" (P < 0.05).

Conclusions

ANA modulation can be caused by peripheral, central, or mixed abnormalities in sBUTDE. Furthermore, personality traits may play a role in symptom induction. Understanding the pathogenesis of sBUTDE may aid in the treatment of cases that are refractory to conventional treatments.

The effects of weather on physical activity and sedentary behaviour in older adults

Background

Many older adults do not meet current physical activity (PA) guidelines, and this might be influenced by environmental factors (e.g., temperature). The purpose of this study was to determine how various weather variables influence light PA (LPA), moderate-vigorous PA (MVPA), and sedentary behaviour (SB), steps, and time spent walking outdoors.

Methods

Fifty community-dwelling older adults completed the 10-day assessment period, using a Fitbit fitness tracker, Global Position System (GPS), and completing self-report questionnaires. Forty participants were included in the analysis. LPA, MVPA, and SB were calculated using heart rate and multilevel models were used to assess their association with weather variables.

Results

Number of steps was positively associated with self-reported health status (0.18, p < 0.01). Increased age was associated with less time spent engaging in LPA (total and outdoors), reduced steps, increased time spent sedentary, and less time spent walking outdoors. LPA outdoors was positively associated with mean temperature. Freeze thaw cycles were associated with time spent walking outdoors. Females spent more time in total LPA and LPA indoors, and as age increased total LPA and LPA outdoors decreased.

Conclusions

Older adults located in a dry (∼690 mm precipitation annually) region with warm winters and hot summers (-5°C-30°C) seemingly choose indoor activities. Females tend to participate in indoor LPA, and as age increases the time spent in outdoor LPA decreases.

Implications

Consideration needs to be given to designing indoor PA interventions, with a focus on increasing MVPA for older adults.

Keeping Pace with Wearables: A Living Umbrella Review of Systematic Reviews Evaluating the Accuracy of Consumer Wearable Technologies in Health Measurement

BACKGROUND

Consumer wearable technologies have become ubiquitous, with clinical and non-clinical populations leveraging a variety of devices to quantify various aspects of health and wellness. However, the accuracy with which these devices measure biometric outcomes such as heart rate, sleep and physical activity remains unclear.

OBJECTIVE

To conduct a 'living' (i.e. ongoing) evaluation of the accuracy of consumer wearable technologies in measuring various physiological outcomes.

METHODS

A systematic search of the literature was conducted in the following scientific databases: MEDLINE via PubMed, Embase, Cinahl and SPORTDiscus via EBSCO. The inclusion criteria required systematic reviews or meta-analyses that evaluated the validation of consumer wearable devices against accepted reference standards. In addition to publication details, review protocol, device specifics and a summary of the authors' results, we extracted data on mean absolute percentage error (MAPE), pooled absolute bias, intraclass correlation coefficients (ICCs) and mean absolute differences.

RESULTS

Of 904 identified studies through the initial search, 24 systematic reviews met our inclusion criteria; these systematic reviews included 249 non-duplicate validation studies of consumer wearable devices involving 430,465 participants (43% female). Of the commercially available wearable devices released to date, approximately 11% have been validated for at least one biometric outcome. However, because a typical device can measure a multitude of biometric outcomes, the number of validation studies conducted represents just 3.5% of the total needed for a comprehensive evaluation of these devices. For heart rate, wearables showed a mean bias of ± 3%. In arrhythmia detection, wearables exhibited a pooled sensitivity and specificity of 100% and 95%, respectively. For aerobic capacity, wearables significantly overestimated VO2max by ± 15.24% during resting tests and ± 9.83% during exercise tests. Physical activity intensity measurements had a mean absolute error ranging from 29 to 80%, depending on the intensity of the activity being undertaken. Wearables mostly underestimated step counts (mean absolute percentage errors ranging from - 9 to  12%) and energy expenditure (mean bias =  - 3 kcal per minute, or - 3%, with error ranging from - 21.27 to 14.76%). For blood oxygen saturation, wearables showed a mean absolute difference of up to 2.0%. Sleep measurement showed a tendency to overestimate total sleep time (mean absolute percentage error typically > 10%).

CONCLUSIONS

While consumer wearables show promise in health monitoring, a conclusive assessment of their accuracy is impeded by pervasive heterogeneity in research outcomes and methodologies. There is a need for standardised validation protocols and collaborative industry partnerships to enhance the reliability and practical applicability of wearable technology assessments.

PROSPERO ID

CRD42023402703.

Digital markers of asthma exacerbations: a systematic review

Background and objective

With the increase in use of digital technologies, there is growing interest in digital markers, where technology is used to detect early markers of disease deterioration. The aim of this systematic review is to summarise the evidence relating to digital markers of asthma exacerbations.

Methods

A systematic search of the following databases was conducted, using key search terms relating to asthma, digital and exacerbations: Ovid MEDLINE, EMBASE, Psycinfo, Cochrane Database of Systematic Reviews and Cochrane Central Register of Controlled Trials. Studies that aimed to explore the relationship between any digitally measured marker and asthma exacerbations using any form of portable digital sensor technology were included.

Results

23 papers were included. The digital markers related to five key categories: environmental, physiological, medication, lung function and breath-related parameters. The most commonly studied marker was lung function, which was reported in over half (13 out of 23) of the papers. However, studies were conflicting in terms of the use of lung function parameters as a predictor of asthma exacerbations. Medication parameters were measured in over a third of the studies (10 out of 23) with a focus on short-acting β-agonist (SABA) use as a marker of exacerbations. Only four and two studies measured heart rate and cough, respectively; however, both parameters were positively associated with exacerbations in all reported studies.

Conclusion

Several digital markers are associated with asthma exacerbations. This suggests a potential role for using parameters such as heart rate, SABA use and, potentially, cough as digital markers of asthma exacerbations.

Assessment of heart rate measurements by commercial wearable fitness trackers for early identification of metabolic syndrome risk

Metabolic syndrome increases the risks of cardiovascular diseases, type 2 diabetes, and certain cancers. The early detection of metabolic syndrome is clinically relevant, as it enables timely and targeted interventions. In the current study, we aimed to investigate the association between metabolic syndrome and heart rate measured using wearable devices in a real-world setting and compare this association with that for clinical resting heart rate. Data from 564 middle-aged adults who wore wearable devices for at least 7 days with a minimum daily wear time of 20 h were analyzed. The results showed significantly elevated all-day, sleeping, minimum, and inactive heart rates in men with pre-metabolic or metabolic syndrome compared with those in normal individuals, whereas sleeping heart rate and heart rate dips were significantly increased and decreased, respectively, in women with metabolic syndrome. After adjusting for confounders, every 10-beats-per-minute increment in all-day, sleeping, minimum, and inactive heart rates in men corresponded to odds ratios of 2.80 (95% confidence interval 1.53-5.44), 3.06 (1.57-6.40), 4.21 (1.87-10.47), and 3.09 (1.64-6.29), respectively, for the presence of pre-metabolic or metabolic syndrome. In women, the association was significant only for heart rate dips (odds ratio = 0.49 [95% confidence interval 0.25-0.96] for every 10% increment). Models incorporating inactive or minimum heart rate in men and heart rate dip in women demonstrated better fits, as indicated by lower Akaike information criterion values (170.3 in men and 364.9 in women), compared with models that included clinical resting heart rate (173.4 in men and 369.1 in women). These findings suggest that the heart rate indices obtained from wearable devices may facilitate early identification of metabolic syndrome.

Evidence of spontaneous cardiac-locomotor coupling during daily activities in healthy adults

Introduction

One way to improve exercise performance and protect heart health is the extended synchronization of the stepping with the diastolic phase of the cardiac cycle. Cardiac-locomotor coupling (CLC) happens when the step rate (SR) equals the heart rate (HR). The extent of CLC in daily life is unknown. This study aims to analyze spontaneous occurrences of CLC during daily activities.

Methods

A retrospective analysis of daily life recordings from a wrist-worn sensor was undertaken (PMData, N = 16, 5 months duration). The deviation between HR and SR was used to define CLC (deviation ≤ 1%) and weak CLC (1%< deviation ≤ 10%). The occurrence and the probability of CLC during everyday life were computed from the recordings. The CLC occurrences were stratified depending on the duration and intensity of the physical activity. Finally, a Monte Carlo simulation was run to evaluate the probability of random occurrences of CLC vs. the observed recordings.

Results

Participants couple for 5% and weakly couple for 35% of the observational period. The ratio of 1:1 between HR and SR is the dominating occurrence across the study population and this overrepresentation is significant. CLC occurs mostly for long activities. The extent of CLC for various intensities of activity is subject-dependent. The results suggest that CLC is feasible for most people.

Conclusions

CLC occurs spontaneously during unsupervised daily activity in everyone in our cohort, which suggests a mechanistic interaction between the cardiac and the locomotor systems. This interaction should be investigated for medical rehabilitation and sports applications in the future.

DIGIPREDICT: physiological, behavioural and environmental predictors of asthma attacks-a prospective observational study using digital markers and artificial intelligence-study protocol

INTRODUCTION

Asthma attacks are a leading cause of morbidity and mortality but are preventable in most if detected and treated promptly. However, the changes that occur physiologically and behaviourally in the days and weeks preceding an attack are not always recognised, highlighting a potential role for technology. The aim of this study 'DIGIPREDICT' is to identify early digital markers of asthma attacks using sensors embedded in smart devices including watches and inhalers, and leverage health and environmental datasets and artificial intelligence, to develop a risk prediction model to provide an early, personalised warning of asthma attacks.

METHODS AND ANALYSIS

A prospective sample of 300 people, 12 years or older, with a history of a moderate or severe asthma attack in the last 12 months will be recruited in New Zealand. Each participant will be given a smart watch (to assess physiological measures such as heart and respiratory rate), peak flow meter, smart inhaler (to assess adherence and inhalation) and a cough monitoring application to use regularly over 6 months with fortnightly questionnaires on asthma control and well-being. Data on sociodemographics, asthma control, lung function, dietary intake, medical history and technology acceptance will be collected at baseline and at 6 months. Asthma attacks will be measured by self-report and confirmed with clinical records. The collected data, along with environmental data on weather and air quality, will be analysed using machine learning to develop a risk prediction model for asthma attacks.

ETHICS AND DISSEMINATION

Ethical approval has been obtained from the New Zealand Health and Disability Ethics Committee (2023 FULL 13541). Enrolment began in August 2023. Results will be presented at local, national and international meetings, including dissemination via community groups, and submission for publication to peer-reviewed journals.

TRIAL REGISTRATION NUMBER

Australian New Zealand Clinical Trials Registry ACTRN12623000764639; Australian New Zealand Clinical Trials Registry.

Effect of Gamification, Financial Incentives, or Both to Increase Physical Activity Among Patients at High Risk of Cardiovascular Events: The BE ACTIVE Randomized Controlled Trial

BACKGROUND

Physical activity is associated with a lower risk of major adverse cardiovascular events, but few individuals achieve guideline-recommended levels of physical activity. Strategies informed by behavioral economics increase physical activity, but their longer-term effectiveness is uncertain. We sought to determine the effect of behaviorally designed gamification, loss-framed financial incentives, or their combination on physical activity compared with attention control over 12-month intervention and 6-month postintervention follow-up periods.

METHODS

Between May 2019 and January 2024, participants with clinical atherosclerotic cardiovascular disease or a 10-year risk of myocardial infarction, stroke, or cardiovascular death of ≥7.5% by the Pooled Cohort equation were enrolled in a pragmatic randomized clinical trial. Participants received a wearable device to track daily steps, established a baseline, selected a step goal increase, and were randomly assigned to control (n=151), behaviorally designed gamification (n=304), loss-framed financial incentives (n=302), or gamification+financial incentives (n=305). The primary outcome of the trial was the change in mean daily steps from baseline through the 12-month intervention period.

RESULTS

A total of 1062 patients (mean±SD age, 67±8; 61% female; 31% non-White) were enrolled. Compared with control subjects, participants had significantly greater increases in mean daily steps from baseline during the 12-month intervention in the gamification arm (adjusted difference, 538.0 [95% CI, 186.2-889.9]; P=0.0027), financial incentives arm (adjusted difference, 491.8 [95% CI, 139.6-844.1]; P=0.0062), and gamification+financial incentives arm (adjusted difference, 868.0 [95% CI, 516.3-1219.7]; P<0.0001). During the 6-month follow-up, physical activity remained significantly greater in the gamification+financial incentives arm than in the control arm (adjusted difference, 576.2 [95% CI, 198.5-954]; P=0.0028), but it was not significantly greater in the gamification (adjusted difference, 459.8 [95% CI, 82.0-837.6]; P=0.0171) or financial incentives (adjusted difference, 327.9 [95% CI, -50.2 to 706]; P=0.09) arms after adjustment for multiple comparisons.

CONCLUSIONS

Behaviorally designed gamification, loss-framed financial incentives, and the combination of both increased physical activity compared with control over a 12-month intervention period, with the largest effect in gamification+financial incentives. These interventions could be a useful component of strategies to reduce cardiovascular risk in high-risk patients.

REGISTRATION

URL: https://clinicaltrials.gov; Unique Identifier: NCT03911141.

Wearable Sensors to Monitor Physical Activity in Heart Failure Clinical Trials: State-of-the-Art Review

BACKGROUND

Estimation of the effects that drugs or other interventions have on patients' symptoms and functions is crucial in heart failure trials. Traditional symptoms and functions clinical outcome assessments have important limitations. Actigraphy may help to overcome these limitations due to its objective nature and the potential for continuous recording of data. However, actigraphy is not currently accepted as clinically relevant by key stakeholders.

METHODS AND RESULTS

In this state-of-the-art study, the key aspects to consider when implementing actigraphy in heart failure trials are discussed. They include which actigraphy-derived measures should be considered, how to build endpoints using them, how to measure and analyze them, and how to handle the patients' and sites' logistics of integrating devices into trials. A comprehensive recommendation based on the current evidence is provided.

CONCLUSION

Actigraphy is technically feasible in clinical trials involving heart failure, but successful implementation and use to demonstrate clinically important differences in physical functioning with drug or other interventions require careful consideration of many design choices.

Net Heart Rate for Estimating Oxygen Consumption in Active Adults

The aim of this study was to verify the accuracy of predicting oxygen consumption (O2) in predominantly aerobic activities based on net heart rate (netHR), sex, and body mass index (BMI) in active adults. NetHR is the value of the difference between the resting HR (HRrest) and the average HR value obtained during a given session or period of physical activity. These activities must be continuous, submaximal, and of a stabilized intensity. The magnitude of the netHR depends mainly on the intensity of the exercise. The HR is measured in beats per minute (bpm). A total of 156 participants, 52 women and 104 men, between the ages of 18 and 81, had their netHR and net oxygen intake (netVO2) assessed. There were 79 participants in group 1 (prediction sample) (52 males and 27 females). There were 77 people in group 2 (validation sample) (52 males and 25 females). The results of the multiple linear regression showed that netVO2 (R2 = 85.2%, SEE = 3.38) could be significantly predicted by sex (p < 0.001), netHR (p < 0.001), and BMI (p < 0.001). The Bland-Altman plots satisfied the agreement requirements, and the comparison of the measured and estimated netVO2 revealed non-significant differences with a trivial effect size. We calculated the formula NetVO2 (mL/(kg·min)) = 16 + 3.67 (sex) + 0.27 (netHR) - 0.57 (BMI) to predict netVO2, where netVO2 is the amount of oxygen uptake (mL/(kg·min)) above the resting value, netHR is the heart rate (beats per minute) above the resting value measured during exercise, sex is equal to zero for women and one for men, and BMI is the body mass index. In addition, based on the knowledge of VO2, it was possible to estimate the energy expenditure from a particular training session, and to determine or prescribe the exercise intensity in MET (metabolic equivalent of task).

Feasibility Study on Menstrual Cycles With Fitbit Device (FEMFIT): Prospective Observational Cohort Study

BACKGROUND

Despite its importance to women's reproductive health and its impact on women's daily lives, the menstrual cycle, its regulation, and its impact on health remain poorly understood. As conventional clinical trials rely on infrequent in-person assessments, digital studies with wearable devices enable the collection of longitudinal subjective and objective measures.

OBJECTIVE

The study aims to explore the technical feasibility of collecting combined wearable and digital questionnaire data and its potential for gaining biological insights into the menstrual cycle.

METHODS

This prospective observational cohort study was conducted online over 12 weeks. A total of 42 cisgender women were recruited by their local gynecologist in Berlin, Germany, and given a Fitbit Inspire 2 device and access to a study app with digital questionnaires. Statistical analysis included descriptive statistics on user behavior and retention, as well as a comparative analysis of symptoms from the digital questionnaires with metrics from the sensor devices at different phases of the menstrual cycle.

RESULTS

The average time spent in the study was 63.3 (SD 33.0) days with 9 of the 42 individuals dropping out within 2 weeks of the start of the study. We collected partial data from 114 ovulatory cycles, encompassing 33 participants, and obtained complete data from a total of 50 cycles. Participants reported a total of 2468 symptoms in the daily questionnaires administered during the luteal phase and menses. Despite difficulties with data completeness, the combined questionnaire and sensor data collection was technically feasible and provided interesting biological insights. We observed an increased heart rate in the mid and end luteal phase compared with menses and participants with severe premenstrual syndrome walked substantially fewer steps (average daily steps 10,283, SD 6277) during the luteal phase and menses compared with participants with no or low premenstrual syndrome (mean 11,694, SD 6458).

CONCLUSIONS

We demonstrate the feasibility of using an app-based approach to collect combined wearable device and questionnaire data on menstrual cycles. Dropouts in the early weeks of the study indicated that engagement efforts would need to be improved for larger studies. Despite the challenges of collecting wearable data on consecutive days, the data collected provided valuable biological insights, suggesting that the use of questionnaires in conjunction with wearable data may provide a more complete understanding of the menstrual cycle and its impact on daily life. The biological findings should motivate further research into understanding the relationship between the menstrual cycle and objective physiological measurements from sensor devices.

Individually optimized estimation of energy expenditure in rescue workers using a tri-axial accelerometer and heart rate monitor

Objectives: This study aimed to provide an improved energy expenditure estimation for heavy-load physical labor using accelerometer data and heart rate (HR) measured by wearables and to support food preparation and supply management for disaster relief and rescue operations as an expedition team. Methods: To achieve an individually optimized estimation for energy expenditure, a model equation parameter was determined based on the measurements of physical activity and HR during simulated rescue operations. The metabolic equivalent of task (MET), which was measured by using a tri-axial accelerometer and individual HR, was used, where two (minimum and maximum) or three (minimum, intermediate, and maximum) representative reference points were selected for each individual model fitting. In demonstrating the applicability of our approach in a realistic situation, accelerometer-based METs and HR of 30 males were measured using the tri-axial accelerometer and wearable HR during simulated rescue operations over 2 days. Results: Data sets of 27 rescue operations (age:34.2 ± 7.5 years; body mass index (BMI):22.9 ± 1.5 kg/m2) were used for the energy expenditure estimation after excluding three rescue workers due to their activity type and insufficient HR measurement. Using the combined approach with a tri-axial accelerometer and HR, the total energy expenditure increased by 143% for two points and 133% for three points, compared with the estimated total energy expenditure using only the accelerometer-based method. Conclusion: The use of wearables provided a reasonable estimation of energy expenditure for physical workers with heavy equipment. The application of our approach to disaster relief and rescue operations can provide important insights into nutrition and healthcare management.

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.

Current Knowledge about ActiGraph GT9X Link Activity Monitor Accuracy and Validity in Measuring Steps and Energy Expenditure: A Systematic Review

Over recent decades, wearable inertial sensors have become popular means to quantify physical activity and mobility. However, research assessing measurement accuracy and precision is required, especially before using device-based measures as outcomes in trials. The GT9X Link is a recent activity monitor available from ActiGraph, recognized as a "gold standard" and previously used as a criterion measure to assess the validity of various consumer-based activity monitors. However, the validity of the ActiGraph GT9X Link is not fully elucidated. A systematic review was undertaken to synthesize the current evidence for the criterion validity of the ActiGraph GT9X Link in measuring steps and energy expenditure. This review followed the PRISMA guidelines and eight studies were included with a combined sample size of 558 participants. We found that (1) the ActiGraph GT9X Link generally underestimates steps; (2) the validity and accuracy of the device in measuring steps seem to be influenced by gait speed, device placement, filtering process, and monitoring conditions; and (3) there is a lack of evidence regarding the accuracy of step counting in free-living conditions and regarding energy expenditure estimation. Given the limited number of included studies and their heterogeneity, the present review emphasizes the need for further validation studies of the ActiGraph GT9X Link in various populations and in both controlled and free-living settings.

Accuracy of wrist-worn activity trackers for measuring steps in patients after major abdominal surgery: A validation study

Background

Wearable activity trackers provide a simple and objective measurement of postoperative mobilization. However, few have validated the accuracy of trackers in patients after major abdominal surgery.

Objective

To examine the accuracy of wrist-worn activity trackers to measure steps of patients in early mobilization after major abdominal surgery, and to explore the influence of clinical variables and gait parameters on the accuracy of trackers.

Methods

Forty-five patients after major abdominal surgery were recruited to participate in modified six-minute walk tests wearing three trackers simultaneously, the Fitbit Inspire HR, Xiaomi MI 4, and HONOR 5. The differences in displayed steps before and after the walking test were considered as the step counts measured by the trackers; the actual steps taken were determined as the average of the values manually counted by two researchers. The intraclass correlation coefficient, Bland-Altman method, mean percentage error, and mean absolute percentage error were used to assess the accuracy of trackers with reference to manual step counts.

Results

The three trackers undercounted postoperative steps by -65.5% to -23.5%. Analysis showed low-to-good agreement between step counts recorded by trackers and actual steps (ICC = 0.35-0.75); the mean absolute percentage errors ranged from 24.5% to 65.7%. For all trackers, mean absolute percentage errors correlated negatively with postoperative days (r = -0.626 to -0.744), walking speed (r = -0.714 to -0.854), step length (r = -0.466 to -0.615), and cadence (r = -0.681 to -0.790), while there were positive correlations between mean absolute percentage errors and the number of abdominal drains (r = 0.450-0.514).

Conclusions

The specific activity trackers used in this study might not be reliable tools for measuring steps counts during the walking test in the early postoperative period for patients undergoing major abdominal surgery.

Measuring Heart Rate Accurately in Patients With Parkinson Disease During Intense Exercise: Usability Study of Fitbit Charge 4

BACKGROUND

Parkinson disease (PD) is the second most common neurodegenerative disease, affecting approximately 1% of the world's population. Increasing evidence suggests that aerobic physical exercise can be beneficial in mitigating both motor and nonmotor symptoms of the disease. In a recent pilot study of the role of exercise on PD, we sought to confirm exercise intensity by monitoring heart rate (HR). For this purpose, we asked participants to wear a chest strap HR monitor (Polar Electro Oy) and the Fitbit Charge 4 (Fitbit Inc) wrist-worn HR monitor as a potential proxy due to its convenience. Polar H10 has been shown to provide highly accurate R-R interval measurements. Therefore, we treated it as the gold standard in this study. It has been shown that Fitbit Charge 4 has comparable accuracy to Polar H10 in healthy participants. It has yet to be determined if the Fitbit is as accurate as Polar H10 in patients with PD during rest and exercise.

OBJECTIVE

This study aimed to compare Fitbit Charge 4 to Polar H10 for monitoring HR in patients with PD at rest and during an intensive exercise program.

METHODS

A total of 596 exercise sessions from 11 (6 male and 5 female) participants were collected simultaneously with both devices. Patients with early-stage PD (Hoehn and Yahr ≤2) were enrolled in a 6-month exercise program designed for patients with PD. They participated in 3 one-hour exercise sessions per week. They wore both Fitbit and Polar H10 during each session. Sessions included rest, warm-up, intense exercise, and cool-down periods. We calculated the bias in the HR of the Fitbit Charge 4 at rest (5 min) and during intense exercise (20 min) by comparing the mean HR during each of the periods to the respective means measured by Polar H10 (HRFitbit - HRPolar). We also measured the sensitivity and specificity of Fitbit Charge 4 to detect average HRs that exceed the threshold for intensive exercise, defined as 70% of an individual's theoretical maximum HR. Different types of correlations between the 2 devices were investigated.

RESULTS

The mean bias was 1.68 beats per minute (bpm) at rest and 6.29 bpm during high-intensity exercise, with an overestimation by Fitbit Charge 4 in both conditions. The mean bias of the Fitbit across both rest and intensive exercise periods was 3.98 bpm. The device's sensitivity in identifying high-intensity exercise sessions was 97.14%. The correlation between the 2 devices was nonlinear, suggesting Fitbit's tendency to saturate at high values of HR.

CONCLUSIONS

The performance of Fitbit Charge 4 is comparable to Polar H10 for assessing exercise intensity in a cohort of patients with PD (mean bias 3.98 bpm). The device could be considered a reasonable surrogate for more cumbersome chest-worn devices in future studies of clinical cohorts.

Validation of Polar Grit X Pro for Estimating Energy Expenditure during Military Field Training: A Pilot Study

Wearables are lightweight, portable technology devices that are traditionally used to monitor physical activity and workload as well as basic physiological parameters such as heart rate. However recent advances in monitors have enabled better algorithms for estimation of caloric expenditure from heart rate for use in weight loss as well as sport performance. can be used for estimating energy expenditure and nutritional demand. Recently, the military has adopted the use of personal wearables for utilization in field studies for ecological validity of training. With popularity of use, the need for validation of these devices for caloric estimates is needed to assist in work-rest cycles. Thus the purpose of this effort was to evaluate the Polar Grit X for energy expenditure (EE) for use in military training exercises. Polar Grit X Pro watches were worn by active-duty elite male operators (N = 16; age: 31.7 ± 5.0 years, height: 180.1 ± 6.2 cm, weight: 91.7 ± 9.4 kg). Metrics were measured against indirect calorimetry of a metabolic cart and heart rate via a Polar heart rate monitor chest strap while exercising on a treadmill. Participants each performed five 10-minute bouts of running at a self-selected speed and incline to maintain a heart rate within one of five heart rate zones, as ordered and defined by Polar. Polar Grit X Pro watch had a good to excellent interrater reliability to indirect calorimetry at estimating energy expenditure (ICC = 0.8, 95% CI = 0.61-0.89, F (74,17.3) = 11.76, p < 0.0001) and a fair to good interrater reliability in estimating macronutrient partitioning (ICC = 0.49, 95% CI = 0.3-0.65, F (74,74.54) = 2.98, p < 0.0001). There is a strong relationship between energy expenditure as estimated from the Polar Grit X Pro and measured through indirect calorimetry. The Polar Grit X Pro watch is a suitable tool for estimating energy expenditure in free-living participants in a field setting and at a range of exercise intensities.

The use of commercial wrist-worn technology to track physiological outcomes in behavioral interventions

PURPOSE OF REVIEW

The aim of this review is to provide an overview of the use of commercial wrist-worn mobile health devices to track and monitor physiological outcomes in behavioral interventions as well as discuss considerations for selecting the optimal device.

RECENT FINDINGS

Wearable technology can enhance intervention design and implementation. The use of wrist-worn wearables provides the opportunity for tracking physiological outcomes, thus providing a unique approach for assessment and delivery of remote interventions. Recent findings support the utility, acceptability, and benefits of commercial wrist-worn wearables in interventions, and they can be used to continuously monitor outcomes, remotely administer assessments, track adherence, and personalize interventions. Wrist-worn devices show acceptable accuracy when measuring heart rate, blood pressure, step counts, and physical activity; however, accuracy is dependent on activity type, intensity, and device brand. These factors should be considered when designing behavioral interventions that utilize wearable technology.

SUMMARY

With the continuous advancement in technology and frequent product upgrades, the capabilities of commercial wrist-worn devices will continue to expand, thus increasing their potential use in intervention research. Continued research is needed to examine and validate the most recent devices on the market to better inform intervention design and implementation.

Advancing Understanding of Just-in-Time States for Supporting Physical Activity (Project JustWalk JITAI): Protocol for a System ID Study of Just-in-Time Adaptive Interventions

BACKGROUND

Just-in-time adaptive interventions (JITAIs) are designed to provide support when individuals are receptive and can respond beneficially to the prompt. The notion of a just-in-time (JIT) state is critical for JITAIs. To date, JIT states have been formulated either in a largely data-driven way or based on theory alone. There is a need for an approach that enables rigorous theory testing and optimization of the JIT state concept.

OBJECTIVE

The purpose of this system ID experiment was to investigate JIT states empirically and enable the empirical optimization of a JITAI intended to increase physical activity (steps/d).

METHODS

We recruited physically inactive English-speaking adults aged ≥25 years who owned smartphones. Participants wore a Fitbit Versa 3 and used the study app for 270 days. The JustWalk JITAI project uses system ID methods to study JIT states. Specifically, provision of support systematically varied across different theoretically plausible operationalizations of JIT states to enable a more rigorous and systematic study of the concept. We experimentally varied 2 intervention components: notifications delivered up to 4 times per day designed to increase a person's steps within the next 3 hours and suggested daily step goals. Notifications to walk were experimentally provided across varied operationalizations of JIT states accounting for need (ie, whether daily step goals were previously met or not), opportunity (ie, whether the next 3 h were a time window during which a person had previously walked), and receptivity (ie, a person previously walked after receiving notifications). Suggested daily step goals varied systematically within a range related to a person's baseline level of steps per day (eg, 4000) until they met clinically meaningful targets (eg, averaging 8000 steps/d as the lower threshold across a cycle). A series of system ID estimation approaches will be used to analyze the data and obtain control-oriented dynamical models to study JIT states. The estimated models from all approaches will be contrasted, with the ultimate goal of guiding rigorous, replicable, empirical formulation and study of JIT states to inform a future JITAI.

RESULTS

As is common in system ID, we conducted a series of simulation studies to formulate the experiment. The results of our simulation studies illustrated the plausibility of this approach for generating informative and unique data for studying JIT states. The study began enrolling participants in June 2022, with a final enrollment of 48 participants. Data collection concluded in April 2023. Upon completion of the analyses, the results of this study are expected to be submitted for publication in the fourth quarter of 2023.

CONCLUSIONS

This study will be the first empirical investigation of JIT states that uses system ID methods to inform the optimization of a scalable JITAI for physical activity.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05273437; https://clinicaltrials.gov/ct2/show/NCT05273437.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/52161.

Linking Electronic Health Records With Wearable Technology From the All of Us Research Program

OBJECTIVE

To evaluate the feasibility of using electronic health records (EHRs) and wearable data to describe patterns of longitudinal change in day-level heart rate before, during, and after pregnancy and how these patterns differ by age and body mass index.

DESIGN

Descriptive secondary analysis feasibility study using data from the National Institutes of Health All of Us Research Program.

SETTING

United States.

PARTICIPANTS

Women (N = 89) who had a birth or length of gestation code in the EHR and at least 60 days of Fitbit heart rate data during pregnancy.

METHODS

We estimated pregnancy-related episodes using EHR codes. Time consisted of five 3-month periods: before pregnancy, first trimester, second trimester, third trimester, and after birth. We analyzed data using descriptive statistics and locally estimated scatterplot smoothing.

RESULTS

An average of 330 days (SD = 112) of Fitbit heart rate data (29,392 days) were available from participants. During pregnancy, distinct peaks in heart rate occurred during the first trimester (6% increase) and third trimester (15% increase).

CONCLUSION

Future researchers can examine whether longitudinal timing and patterns of heart rate from wearable devices could be leveraged to detect health problems early in pregnancy.

Challenges of using a Fitbit smart wearable among people with dementia

OBJECTIVES

Limited research on using smart wearables such as Fitbit devices among people with dementia has shown favourable outcomes. The aim of this study was to explore the acceptability and feasibility of using a Fitbit Charge 3 among people with dementia, living in the community, who took part in the physical exercise component of the Comprehensive REsilience-building psychoSocial intervenTion pilot study.

METHODS

A mixed methods study was conducted; Quantitative data relating to wear rates for the Fitbit were recorded and qualitative data were collected by group and individual interviews with the people with dementia and their caregiver about their experience of wearing/using the Fitbit in the study.

RESULTS

Nine people with dementia and their caregiver completed the intervention. Only one participant wore the Fitbit consistently. Supporting set-up and use of the devices was time consuming and caregiver involvement was essential for day-to-day support: none of the people with dementia owned a smartphone. Few of them engaged with the Fitbit features, primarily only using it to check the time and only a minority wanted to keep the device beyond the intervention.

DISCUSSION

When designing a study using smart wearables such as a Fitbit among people with dementia, consideration should be given to the following: the possible burden on caregivers supporting the use of the device; a lack of familiarity with this technology in the target population; dealing with missing data, and the involvement of the researcher in setting up and supporting use of the device.

Are Activity Wrist-Worn Devices Accurate for Determining Heart Rate during Intense Exercise?

The market for wrist-worn devices is growing at previously unheard-of speeds. A consequence of their fast commercialization is a lack of adequate studies testing their accuracy on varied populations and pursuits. To provide an understanding of wearable sensors for sports medicine, the present study examined heart rate (HR) measurements of four popular wrist-worn devices, the (Fitbit Charge (FB), Apple Watch (AW), Tomtom runner Cardio (TT), and Samsung G2 (G2)), and compared them with gold standard measurements derived by continuous electrocardiogram examination (ECG). Eight athletes participated in a comparative study undergoing maximal stress testing on a cycle ergometer or a treadmill. We analyzed 1,286 simultaneous HR data pairs between the tested devices and the ECG. The four devices were reasonably accurate at the lowest activity level. However, at higher levels of exercise intensity the FB and G2 tended to underestimate HR values during intense physical effort, while the TT and AW devices were fairly reliable. Our results suggest that HR estimations should be considered cautiously at specific intensities. Indeed, an effective intervention is required to register accurate HR readings at high-intensity levels (above 150 bpm). It is important to consider that even though none of these devices are certified or sold as medical or safety devices, researchers must nonetheless evaluate wrist-worn wearable technology in order to fully understand how HR affects psychological and physical health, especially under conditions of more intense exercise.