Criterion-Validity of Commercially Available Physical Activity Tracker to Estimate Step Count, Covered Distance and Energy Expenditure during Sports Conditions

A Bluetooth-Enabled Device for Real-Time Detection of Sitting, Standing, and Walking: Cross-Sectional Validation Study

BACKGROUND

This study assesses the accuracy of a Bluetooth-enabled prototype activity tracker called the Sedentary behaviOR Detector (SORD) device in identifying sedentary, standing, and walking behaviors in a group of adult participants.

OBJECTIVE

The primary objective of this study was to determine the criterion and convergent validity of SORD against direct observation and activPAL.

METHODS

A total of 15 healthy adults wore SORD and activPAL devices on their thighs while engaging in activities (lying, reclining, sitting, standing, and walking). Direct observation was facilitated with cameras. Algorithms were developed using the Python programming language. The Bland-Altman method was used to assess the level of agreement.

RESULTS

Overall, 1 model generated a low level of bias and high precision for SORD. In this model, accuracy, sensitivity, and specificity were all above 0.95 for detecting sitting, reclining, standing, and walking. Bland-Altman results showed that mean biases between SORD and direct observation were 0.3% for sitting and reclining (limits of agreement [LoA]=-0.3% to 0.9%), 1.19% for standing (LoA=-1.5% to 3.42%), and -4.71% for walking (LoA=-9.26% to -0.16%). The mean biases between SORD and activPAL were -3.45% for sitting and reclining (LoA=-11.59% to 4.68%), 7.45% for standing (LoA=-5.04% to 19.95%), and -5.40% for walking (LoA=-11.44% to 0.64%).

CONCLUSIONS

Results suggest that SORD is a valid device for detecting sitting, standing, and walking, which was demonstrated by excellent accuracy compared to direct observation. SORD offers promise for future inclusion in theory-based, real-time, and adaptive interventions to encourage physical activity and reduce sedentary behavior.

COVID-19 surveillance based on consumer wearable devices

Background

Consumer wearable devices such as wristbands and smartwatches have potential application value in communicable disease surveillance.

Objective

We investigated the ability of wearable devices to monitor COVID-19 patients of varying severity.

Methods

COVID-19 patients with mobile phones supporting wearable device applications were selected from Dalian Sixth People Hospital. Physiological parameters from the wearable devices and electronic questionnaires were collected from the device wearing until 14 days post-discharge. Clinical information during hospitalization was also recorded. Based on imaging data, the patients were categorized into the milder group without pneumonia and the more severe group with pneumonia. We plotted the curves of the physiological parameters of the two groups to compare the differences and changes.

Results

Ninety-eight patients were included in the analysis. The mean age was 39.6 ± 10.5 years, including 45 males (45.9%). There were 24 asymptomatic patients, 10 mild patients, 60 moderate patients, and 4 severe patients. Compared with the milder group, the more severe group had higher heart rate-related parameters, while the heart rate variability (HRV) was the opposite. In the more severe group, the heart rate-related parameters showed a downward trend from 0 to 7 days after the fever resolution. Among them, the resting heart rate and sleep heart rate decreased on the 25th day after the onset and were close to the milder group 1 week after discharge.

Conclusions

Consumer wearable devices have the potential to monitor respiratory infections. Heart rate-related parameters obtained from these devices can be sensitive indicators of COVID-19 severity and correlate with disease evolution.

Trial registration

ClinicalTrials.gov NCT04459637.

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

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

Heart rate processing algorithms and exercise duration on reliability and validity decisions in biceps-worn Polar Verity Sense and OH1 wearables

Consumer wearable technology use is widespread and there is a need to validate measures obtained in uncontrolled settings. Because no standard exists for the treatment of heart rate data during exercise, the effect of different approaches on reliability (Coefficient of Variation [CV], Intraclass Correlation Coefficient [ICC]) and validity (Mean Absolute Percent Error [MAPE], Lin's Concordance Correlation Coefficient [CCC)] were determined in the Polar Verity Sense and OH1 during trail running. The Verity Sense met the reliability (CV < 5%, ICC > 0.7) and validity thresholds (MAPE < 5%, CCC > 0.9) in all cases. The OH1 met reliability thresholds in all cases except entire session average (ICC = 0.57). The OH1 met the validity MAPE threshold in all cases (3.3-4.1%), but not CCC (0.6-0.86). Despite various heart rate data processing methods, the approach may not affect reliability and validity interpretation provided adequate data points are obtained. It is also possible that a large volume of data will artificially inflate metrics.

Health Wearables, Gamification, and Healthful Activity

Health wearables in combination with gamification enable interventions that have the potential to increase physical activity-a key determinant of health. However, the extant literature does not provide conclusive evidence on the benefits of gamification and there are persistent concerns that competition-based gamification approaches will only benefit those who are highly active at the expense of those who are sedentary. We investigate the effect of Fitbit leaderboards on the number of steps taken by the user. Using a unique dataset of Fitbit wearable users, some of whom participate in a leaderboard, we find that leaderboards lead to a 370 (3.5%) step increase in the users' daily physical activity. However, we find that the benefits of leaderboards are highly heterogeneous. Surprisingly, we find that those who were highly active prior to adoption are hurt by leaderboards and walk 630 fewer steps daily post adoption (a 5% relative decrease). In contrast, those who were sedentary prior to adoption benefited substantially from leaderboards and walked an additional 1,300 steps daily after adoption (a 15% relative increase). We find that these effects emerge because sedentary individuals benefit even when leaderboards are small and when they do not rank first on them. In contrast, highly active individuals are harmed by smaller leaderboards and only see benefit when they rank highly on large leaderboards. We posit that this unexpected divergence in effects could be due to the underappreciated potential of non-competition dynamics (e.g., changes in expectations for exercise) to benefit sedentary users, but harm more active ones.

Relationships between overall physical activity and step counts in able-bodied adults and stroke survivors in developing countries: a cross-sectional study

PURPOSE

To investigate how step counts relate to overall physical activity (PA) in able-bodied adults and stroke survivors in developing countries.

MATERIALS AND METHODS

Sixty able-bodied adults (mean age: 48.8 ± 11.7 years old) and 60 stroke survivors (mean age: 56.7 ± 10.4 years old) were recruited in Benin (West-Africa). Step counts were collected for 7 consecutive days using the Garmin Forerunner 15 activity tracker. Then, participants completed the adapted French version of the International Physical Activity Questionnaire (IPAQ-AF) to report their PA over the same period. Spearman's rank correlation coefficients (ρ) were calculated between IPAQ-AF scores and the mean steps per day.

RESULTS

Very high correlations were observed between IPAQ-AF total scores and step counts, in able-bodied adults (ρ = 0.94; p < 0.001), and in stroke survivors (ρ = 0.91; p < 0.001). IPAQ-AF leisure-time presented negligible correlation with step counts in able-bodied adults. No activity was reported in occupation and intense domains in stroke survivors.

CONCLUSION

There is a strong relationship between overall PA and step counts in able-bodied adults and stroke survivors in Benin. Step counts appear to be an indicator of PA levels in developing countries, suggesting walking as a potential exercise to improve PA levels in stroke survivors.Implications for RehabilitationStep counts could serve as an indicator of physical activity levels in stroke survivors in developing countries.Walking may be suggested as exercise to improve physical activity levels in stroke survivors in developing countries.In Africa French speaking countries, the IPAQ-AF could be used to assess physical activity in stroke survivors and findings might guide programs to promote an active lifestyle as needed.

Using beat frequency in music to adjust running cadence in recreational runners: A randomized multiple baseline design

Running with music has been shown to acutely change cadence. However, it is unclear if the increased cadence remains long-term when running without music in an in-field situation. The aim of this 12-week study was to investigate the effect of a 4-week music running program on cadence, speed and heartrate during and after the music running program. Seven recreational runners with a cadence of <170 steps per minute were randomly assigned to a baseline and post-intervention period of different durations. During the intervention phase, the participants ran with a musical beat that was 7.5-10% higher than their mean cadence at the start of the study. Cadence, heartrate and running speed were measured twice a week during a 5-kilometer run with a watch, and were analyzed using randomization tests and visual data inspection. Two participants dropped-out due to shortage of time (n = 1) and an acute calf injury (n = 1). Cadence significantly increased during the intervention period (+8.5%), and remained elevated during the post-intervention period (+7.9% (p = .001)) in comparison with the baseline period. Heartrate and running speed did not significantly change during any period. This study among five participants shows that four weeks of running with a musical beat that is 7.5-10% higher than the preferred cadence may be an effective and feasible intervention to increase running cadence. Importantly, the increased cadence occurred without simultaneous increases in running speed and heartrate, hereby potentially reducing mechanical loading without increasing metabolic load.HighlightsRunning with a musical rhythm that is higher than the preferred cadence leads to an increased running cadence, without increasing heartrate and running speed.This cadence remains elevated for at least three to five weeks after the music intervention period.All individuals showed a practically relevant increase in cadence during and after the intervention.

Sex inequality driven by dispersal

Inequality between the sexes is pervasive both outside and inside the home. One contributing factor could be the dispersal of one sex at marriage that sets up sex-specific differences in relatedness to the group. Here we exploit the ecological diversity and different social structures found in southwest China to investigate the role of sex-biased dispersal on inequality in the sexual division of labor. We use a wearable fitness tracker and validated readings by confirming that participants' daily "steps" were positively correlated with time spent in high-energy activities, such as agriculture and animal husbandry work, and negatively correlated with low-energy activities, such as leisure and relaxation. We applied multilevel comparative approaches to examine the relative workload pattern between the sexes under different dispersal states. Our results reveal two characteristics that lead to an unfavorable division of workload: being female and dispersing at marriage. This is consistent with the hypothesis that males have increased bargaining power when remaining in their natal home, leading to inequality in workload.

The Physical Activity Level of Ophthalmologists at Work: A Pedometer-Based Study

BACKGROUND

Ophthalmology practice entails many hours of physical inactivity, a potential long-term health hazard. This study aims to perform a pedometer-based evaluation of the physical activity (PA) levels of ophthalmologists at work.

METHODS

This is a prospective observational study. Ophthalmologists from a single tertiary medical center were monitored with electronic pedometers during six morning sessions in the ophthalmology clinics. Working hours and the number of patients seen per clinic session were retrieved. The age and body mass index (BMI) of participants were documented. Step number per working hour (SPH) was calculated for all participants. Comparisons between males and females, practicing ophthalmologists (attendings) and ophthalmology residents (residents), and sub-specialties were performed. Correlations between SPH and age, BMI, and patients seen per clinic session were computed.

FINDINGS

Pedometer readings for a total of 673 working hours were analyzed for 24 ophthalmologists, 17% female, 17 attendings, mean age 44.2 years (standard deviation (SD = 9.8). The average number of SPH for all participants was 359.7 (SD = 166.7). The mean PA level of residents was significantly higher than that of attendings (410.17 SPH vs. 338.95 SPH, respectively, p = .019). Oculoplastic surgeons demonstrated significantly higher step counts per hour than cornea specialists (439.90 SPH vs. 245.55 SPH, respectively, p = .002). A negative correlation was observed between SPH and the number of patients seen per clinic session (ρ = -0.274, p = .001).

CONCLUSIONS/APPLICATIONS TO PRACTICE

Low number of SPH for ophthalmologists in this study indicates ophthalmology to be a highly sedentary medical occupation. PA levels of ophthalmologists in the workplace may indicate a personal health care challenge.

Nutrition, body composition and physical activity have differential impact on the determination of lipidemic blood profiles between young females with different blood cholesterol concentrations

INTRODUCTION

This cross-sectional study explored whether nutrition, body composition, and physical activity energy expenditure (PAΕΝ) have a differential impact on lipidemic blood profiles among young females with different blood cholesterol concentrations.

METHODS

One hundred thirty-five young female students (N = 135) were allocated into three groups according to their blood cholesterol concentrations (Chol): (A) Normal [NL; Chol: < 200 mg·dL^-1; n = 56 Age: 21.4 ± 2.6 yrs, Body Mass Index (BMI): 22.1 ± 2.0 kg·m^-2], (B) Borderline (BL; Chol: ≥200 mg·dL^-1 and <240 mg·dL^-1; n = 44 Age: 21.6 ± 2.5 yrs, BMI: 24.2 ± 3.1 kg·m^-2) and (C) High level (HL; Chol: ≥240 mg·dL^-1; n = 35 Age: 22.5 ± 2.4 yrs, BMI: 28.9 ± 2.1 kg·m^-2). Body composition [bioelectrical impedance analysis including lean body mass (LBM) and body fat mass], nutritional intake (recall questionnaire), daily physical activity energy expenditure through activity trackers and resting blood lipids concentrations were evaluated.

RESULTS

Multiple linear regression analyses revealed that in the NL group, lean mass, daily PAΕΝ and daily energy balance were the determinant parameters of blood lipidemic profiles (B: -0.815 to 0.700). In the BL group, nutrition, body composition and daily physical activity energy expenditure exhibited similar impacts (B: -0.440 to 0.478). In the HL group, nutritional intake and body fat mass determined blood lipidemic profile (B: -0.740 to 0.725).

CONCLUSION

Nutrition, body composition and daily PAΕΝ impact on blood lipids concentration is not universal among young females. In NL females, PAEN, energy expenditure and LBM are the strongest determinants of blood lipids, while in HL females, nutritional intake and body fat mass are. As PAΕΝ increases, the importance of nutrition and body fat decreases, and vice versa.

Validity of three smartwatches in estimating energy expenditure during outdoor walking and running

Commercially wrist-worn devices often present inaccurate estimations of energy expenditure (EE), with large between-device differences. We aimed to assess the validity of the Apple Watch Series 6 (AW), Garmin FENIX 6 (GF) and Huawei Watch GT 2e (HW) in estimating EE during outdoor walking and running. Twenty young normal-weight Chinese adults concurrently wore three index devices randomly positioned at both wrists during walking at 6 km/h and running at 10 km/h for 2 km on a 400- meter track. As a criterion, EE was assessed by indirect calorimetry (COSMED K5). For walking, EE from AW and GF was significantly higher than that obtained by the K5 (p < 0.001 and 0.002, respectively), but not for HW (p = 0.491). The mean absolute percentage error (MAPE) was 19.8% for AW, 32.0% for GF, and 9.9% for HW, respectively. The limits of agreement (LoA) were 44.1, 150.1 and 48.6 kcal for AW, GF, and HW respectively. The intraclass correlation coefficient (ICC) was 0.821, 0.216 and 0.760 for AW, GF, and HW, respectively. For running, EE from AW and GF were significantly higher than the K5 (p < 0.001 and 0.001, respectively), but not for HW (p = 0.946). The MAPE was 24.4%, 21.8% and 11.9% for AW, GF and HW, respectively. LoA were 62.8, 89.4 and 65.6 kcal for AW, GF and HW, respectively. The ICC was 0.741, 0.594, and 0.698 for AW, GF and HW, respectively. The results indicate that the tested smartwatches show a moderate validity in EE estimations for outdoor walking and running.

Estimation of Heart Rate and Energy Expenditure Using a Smart Bracelet during Different Exercise Intensities: A Reliability and Validity Study

Background. With wrist-worn wearables becoming increasingly available, it is important to understand their reliability and validity in different conditions. The primary objective of this study was to examine the reliability and validity of the Lexin Mio smart bracelet in measuring heart rate (HR) and energy expenditure (EE) in people with different physical activity levels exercising at different intensities. Methods. A total of 65 participants completed one maximal oxygen uptake test and two running exercise tests wearing the Mio smart bracelet, the Polar H10 HR band, and a gas-analysis system. Results. In terms of HR measurement reliability, the Mio smart bracelet showed good reliability in a left versus right test and good test−retest reliability (p > 0.05; mean absolute percentage error (MAPE) < 10%; intraclass correlation coefficient (ICC) > 0.4). For EE measurement, the Mio smart bracelet showed good reliability in a left versus right test, good test−retest reliability on the right (p > 0.05; MAPE > 10%; ICC > 0.4), and low test−retest reliability on the left (p > 0.05; MAPE > 10%; ICC < 0.4). Regarding validity, the Mio smart bracelet showed good validity for HR measurement (p > 0.05; MAPE < 10%; ICC > 0.4) and low validity for EE measurement (p < 0.05; MAPE > 10%; ICC < 0.4). Conclusion. The Lexin Mio smart bracelet showed good reliability and validity for HR measurement among people with different physical activity levels exercising at various exercise intensities in a laboratory setting. However, the smart bracelet showed good reliability and low validity for the estimation of EE.

Acute Physiological Effects of Continuous Versus Intermittent Walking During Golf in Individuals With Knee Osteoarthritis: A Pilot Study

OBJECTIVE

The aim of the study was to compare the acute effects of walking the golf course versus using a golf cart during a round of golf on biological markers of joint disease, joint pain, and cardiovascular parameters in individuals with knee osteoarthritis.

METHODS

Participants with knee OA (n = 10) older than 50 yrs were recruited for this crossover designed study in which they completed two 18-hole rounds of golf: (1) walking the course and (2) using a golf cart. Five control participants (n = 5) performed the walking condition only. Step count, heart rate, rating of perceived exertion and pain using the Numeric Pain Rating Scale were measured during the round. Serum was collected at baseline, 9th hole (halfway), and 18th hole (completion) and tested for biomarkers associated with tissue turnover (cartilage oligomeric matrix protein), inflammation (tumor necrosis factor α, interleukin 1β, interleukin 6), and degradative enzyme production (matrix metalloproteinase 3, matrix metalloproteinase 13).

RESULTS

In knee OA participants, walking the course was associated with significantly higher step count and duration of moderate/vigorous physical activity (72.2% vs. 32.6% of the round) but did lead to a significant increase in knee joint pain (P < 0.05). Both conditions caused cartilage oligomeric matrix protein and matrix metalloproteinase 13 concentration increases from baseline to completion (P < 0.05), but inflammatory markers (tumor necrosis factor α, interleukin 6, and interleukin 1β, P < 0.05) only increased when walking the course. Biomarker concentrations did not increase in control participants.

CONCLUSIONS

Walking the course optimizes the duration of moderate/vigorous activity during a round of golf, but the golf cart is a beneficial option in those with exacerbated joint pain and inflammation that would otherwise limit participation.

Wearable activity trackers-advanced technology or advanced marketing?

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

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

BACKGROUND

Although it is widely recognized that physical activity is an important determinant of health, assessing this complex behavior is a considerable challenge.

OBJECTIVE

The purpose of this systematic review and meta-analysis is to examine, quantify, and report the current state of evidence for the validity of energy expenditure, heart rate, and steps measured by recent combined-sensing Fitbits.

METHODS

We conducted a systematic review and Bland-Altman meta-analysis of validation studies of combined-sensing Fitbits against reference measures of energy expenditure, heart rate, and steps.

RESULTS

A total of 52 studies were included in the systematic review. Among the 52 studies, 41 (79%) were included in the meta-analysis, representing 203 individual comparisons between Fitbit devices and a criterion measure (ie, n=117, 57.6% for heart rate; n=49, 24.1% for energy expenditure; and n=37, 18.2% for steps). Overall, most authors of the included studies concluded that recent Fitbit models underestimate heart rate, energy expenditure, and steps compared with criterion measures. These independent conclusions aligned with the results of the pooled meta-analyses showing an average underestimation of -2.99 beats per minute (k comparison=74), -2.77 kcal per minute (k comparison=29), and -3.11 steps per minute (k comparison=19), respectively, of the Fitbit compared with the criterion measure (results obtained after removing the high risk of bias studies; population limit of agreements for heart rate, energy expenditure, and steps: -23.99 to 18.01, -12.75 to 7.41, and -13.07 to 6.86, respectively).

CONCLUSIONS

Fitbit devices are likely to underestimate heart rate, energy expenditure, and steps. The estimation of these measurements varied by the quality of the study, age of the participants, type of activities, and the model of Fitbit. The qualitative conclusions of most studies aligned with the results of the meta-analysis. Although the expected level of accuracy might vary from one context to another, this underestimation can be acceptable, on average, for steps and heart rate. However, the measurement of energy expenditure may be inaccurate for some research purposes.

Accuracy and Acceptability of Wrist-Wearable Activity-Tracking Devices: Systematic Review of the Literature

Background

Numerous wrist-wearable devices to measure physical activity are currently available, but there is a need to unify the evidence on how they compare in terms of acceptability and accuracy.

Objective

The aim of this study is to perform a systematic review of the literature to assess the accuracy and acceptability (willingness to use the device for the task it is designed to support) of wrist-wearable activity trackers.

Methods

We searched MEDLINE, Embase, the Cochrane Central Register of Controlled Trials, and SPORTDiscus for studies measuring physical activity in the general population using wrist-wearable activity trackers. We screened articles for inclusion and, for the included studies, reported data on the studies’ setting and population, outcome measured, and risk of bias.

Results

A total of 65 articles were included in our review. Accuracy was assessed for 14 different outcomes, which can be classified in the following categories: count of specific activities (including step counts), time spent being active, intensity of physical activity (including energy expenditure), heart rate, distance, and speed. Substantial clinical heterogeneity did not allow us to perform a meta-analysis of the results. The outcomes assessed most frequently were step counts, heart rate, and energy expenditure. For step counts, the Fitbit Charge (or the Fitbit Charge HR) had a mean absolute percentage error (MAPE) <25% across 20 studies. For heart rate, the Apple Watch had a MAPE <10% in 2 studies. For energy expenditure, the MAPE was >30% for all the brands, showing poor accuracy across devices. Acceptability was most frequently measured through data availability and wearing time. Data availability was ≥75% for the Fitbit Charge HR, Fitbit Flex 2, and Garmin Vivofit. The wearing time was 89% for both the GENEActiv and Nike FuelBand.

Conclusions

The Fitbit Charge and Fitbit Charge HR were consistently shown to have a good accuracy for step counts and the Apple Watch for measuring heart rate. None of the tested devices proved to be accurate in measuring energy expenditure. Efforts should be made to reduce the heterogeneity among studies.

Is the Tyme Wear Smart Shirt Reliable and Valid at Detecting Personalized Ventilatory Thresholds in Recreationally Active Individuals?

The aim of this study was to determine the extent to which the Tyme Wear smart shirt is as reliable and valid in detecting personalized ventilatory thresholds when compared to the Parvo Medics TrueOne 2400. In this validation study, 19 subjects were recruited to conduct two graded exercise test (GXT) trials. Each GXT trial was separated by 7 to 10 days of rest. During the GXT, gas exchange and heart rate data were collected by the TrueOne 2400 (TRUE) in addition to the ventilation data collected by the Tyme Wear smart shirt (S-PRED). Gas exchange data from TRUE were used to detect ventilatory threshold 1 (VT1) and ventilatory threshold 2 (VT2). TRUE and S-PRED VT1 and VT2 were compared to determine the reliability and validity of the smart shirt. Of the 19 subjects, data from 15 subjects were used during analysis. S-PRED exhibited excellent (intraclass correlation coefficient—CC > 0.90) reliability for detection of VT1 and VT2 utilizing time point and workload and moderate (0.90 > ICC > 0.75) reliability utilizing heart rate. TRUE exhibited excellent reliability for detection of VT1 and VT2 utilizing time point, workload, and heart rate. When compared to TRUE, S-PRED appears to underestimate the VT1 workload (p > 0.05) across both trials and heart rate (p < 0.05) for trial 1. However, S-PRED appears to underestimate VT2 workload (p < 0.05) and heart rate (p < 0.05) across both trials. The result from this study suggests that the Tyme Wear smart shirt is less valid but is comparable in reliability when compared to the gold standard. Moreover, despite the underestimation of S-PRED VT1 and VT2, the S-PRED-detected personalized ventilatory thresholds provide an adequate training workload for most individuals. In conclusion, the Tyme Wear smart shirt provides easily accessible testing to establish threshold-guided training zones but does not devalue the long-standing laboratory equivalent.

The female athlete triad

The female athlete triad represents the 3 interrelated components: of energy availability (EA), menstrual function and bone health. Each component exists on a spectrum ranging from optimal health to dysfunction. Screening for the triad during the annual wellness exam, the preparticipation physical evaluation (PPE) or when the athlete presents with any single component can help identify athletes at risk. A multidisciplinary team is helpful in managing the treatment of the Triad which relies on improving EA. Screening, early recognition and aggressive treatment is important, especially in adolescent athletes to optimize bone health.

What possibly affects nighttime heart rate? Conclusions from N-of-1 observational data

Background

Heart rate (HR), especially at nighttime, is an important biomarker for cardiovascular health. It is known to be influenced by overall physical fitness, as well as daily life physical or psychological stressors like exercise, insufficient sleep, excess alcohol, certain foods, socialization, or air travel causing physiological arousal of the body. However, the exact mechanisms by which these stressors affect nighttime HR are unclear and may be highly idiographic (i.e. individual-specific). A single-case or “ n-of-1” observational study (N1OS) is useful in exploring such suggested effects by examining each subject's exposure to both stressors and baseline conditions, thereby characterizing suggested effects specific to that individual.

Objective

Our objective was to test and generate individual-specific N1OS hypotheses of the suggested effects of daily life stressors on nighttime HR. As an N1OS, this study provides conclusions for each participant, thus not requiring a representative population.

Methods

We studied three healthy, nonathlete individuals, collecting the data for up to four years. Additionally, we evaluated model-twin randomization (MoTR), a novel Monte Carlo method facilitating the discovery of personalized interventions on stressors in daily life.

Results

We found that physical activity can increase the nighttime heart rate amplitude, whereas there were no strong conclusions about its suggested effect on total sleep time. Self-reported states such as exercise, yoga, and stress were associated with increased (for the first two) and decreased (last one) average nighttime heart rate.

Conclusions

This study implemented the MoTR method evaluating the suggested effects of daily stressors on nighttime heart rate, sleep time, and physical activity in an individualized way: via the N-of-1 approach. A Python implementation of MoTR is freely available.

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

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

Use of Wearable Devices to Study Physical Activity in Early Childhood Education

Physical activity recommendations for early childhood are gradually being met to a lesser extent today. The objectives of the study were: (i) to assess the degree of compliance with physical activity (PA) recommendations by gender; and (ii) to analyze the level of PA and steps in different periods over a week. This study was an observational cross-sectional study. Sixty-three young children (33 boys and 30 girls) aged two years (2.15 ± 0.35) were recruited for this study. Participants wore a “Garmin vivofit® jr.” activity tracker for seven days, collecting minutes of moderate-to-vigorous physical activity (MVPA) and step volume (Out-of-School Time and School Time). The results show a 50% compliance of the 120 min/day MVPA and 13,000 steps per day. No gender differences were detected. The findings in the analysis indicated a trend towards higher PA and steps at the Weekend. Moreover, participants reached higher PA and steps values “Out-of-School Time” than “School Time” (MVPA) (min/day). This study can provide strategies and motivational PA guidelines at school to enhance well-being at an early age. These activity trackers could stimulate more sustainable forms of urban mobility, such as walking, as the environment would accompany the child to meet daily PA recommendations.

A meta-analysis of Fitbit devices: same company, different models, different validity evidence

Fitbit devices are among the most commonly used physical activity devices used by the general public. Multiple studies have examined the validity evidence of Fitbit devices of estimating energy expenditure during physical activity compared to criterion references. However, the literature lacks objective, summary validity evidence that supports the use of various models of Fitbit devices. Therefore, this study aims (a) to examine the validity evidence among the various models of Fitbit devices and (b) to investigate the influence of several device factors on the validity evidence of Fitbit models using meta-analysis. A total of 402 articles were identified through five databases. Upon review of the articles, 29 studies were included in the meta-analysis. Seven different moderator variables, including Fitbit model, device placement, type of device, heart rate capability, release year of devices, activity types and sedentary activity, were identified and included in the meta-analysis to examine their impact on the validity evidence of Fitbit devices. The summarised validity coefficient of energy expenditure during physical activity estimated by Fitbit devices and measured by criterion references was r=.64 (k = 29, 95% CI [.59, .69], p<.001). Fitbit model was not found to be a significant factor impacting validity evidence of Fitbit devices, but heart rate capability, activity types and sedentary activity were found to be significant factors impacting validity evidence. This study found that not all Fitbit models have a similar ability in estimating energy expenditure during physical activity. Continued research is needed in examining the validity evidence of Fitbit devices, especially considering some factors may affect the validity evidence in measuring energy expenditure during physical activity.

Smart Technology and Orthopaedic Surgery: Current Concepts Regarding the Impact of Smartphones and Wearable Technology on Our Patients and Practice

PURPOSE OF REVIEW

While limited to case reports or small case series, emerging evidence advocates the inclusion of smartphone-interfacing mobile platforms and wearable technologies, consisting of internet-powered mobile and wearable devices that interface with smartphones, in the orthopaedic surgery practice. The purpose of this review is to investigate the relevance and impact of this technology in orthopaedic surgery.

RECENT FINDINGS

Smartphone-interfacing mobile platforms and wearable technologies are capable of improving the patients' quality of life as well as the extent of their therapeutic engagement, while promoting the orthopaedic surgeons' abilities and level of care. Offered advantages include improvements in diagnosis and examination, preoperative templating and planning, and intraoperative assistance, as well as postoperative monitoring and rehabilitation. Supplemental surgical exposure, through haptic feedback and realism of audio and video, may add another perspective to these innovations by simulating the operative environment and potentially adding a virtual tactile feature to the operator's visual experience. Although encouraging in the field of orthopaedic surgery, surgeons should be cautious when using smartphone-interfacing mobile platforms and wearable technologies, given the lack of a current academic governing board certification and clinical practice validation processes.

Move more - be happier? physical activity and health-related quality of life in children with congenital heart disease

OBJECTIVE

This cross-sectional study aimed to determine whether there is an association between objectively assessed physical activity (PA) and health-related quality of life (HRQoL) in children with CHD.

PATIENTS AND METHODS

From September 2017 to January 2021, 343 children with CHD (12.1 ± 3.3 years, 135 girls) provided valid PA data after a 7-day objective PA assessment. PA was evaluated as average daily steps and moderate-to-vigorous physical activity (MVPA) minutes assessed via wearable bracelet Garmin vivofit Jr. These children also completed the KINDL - a 24 Likert-scaled item questionnaires assessing HRQoL in the six dimensions physical well-being, emotional well-being, self-esteem, family, friends and everyday functioning.

RESULTS

Daily Steps (r = 0.166, P = .003) and daily MVPA minutes (r = 0.134, P = .017,) were both correlated to total KINDL score. Furthermore, both steps and MVPA were associated with the subscales physical well-being (steps: r = 0.165 p=.003; MVPA: r = 0.129, P = .022), friends (steps: r = 0.210, P < .001, MVPA: r = 0.179, P = .001), steps, and to everyday functioning (r = 0.142, P = .012). Logistic regression showed each MVPA minute increase conferred to a 1% increase in reporting better HRQoL (OR: 1.009 [95% CI: 1.002 - 1.017], P = .019).

CONCLUSIONS

PA was positively associated with HRQoL in children with CHD. Patients who move more are more likely to report better HRQoL. While the magnitude of this association needs to be further understood, continuous encouragement towards more PA seems to be crucial in a holistic approach to medical aftercare in children with CHD.

Using a GPS Watch to Characterize Life-Space Mobility in Dementia: A Dyadic Case Study

Persons with dementia (PWD) often experience difficulty navigating their environments and performing out-of-home activities. Life-space mobility (LSM) is an effective way of assessing functional levels and independence. We present a dyadic case study to explore the feasibility of using a global positioning system (GPS) watch to measure LSM of a Latino PWD. Methods included travel diary, LSM questionnaire, and qualitative interviews in addition to the GPS-based mobility characterization. GPS data indicated that the PWD made outdoor trips regularly and was active socially, with day-to-day variations. Caregiver and PWD interviews revealed contextual information about mobility patterns captured by other methods. The dyad had positive perceptions of the GPS watch for tracking health and activities. This study demonstrated a use for wearable location tracking technology to support accurate LSM assessment in dementia that can inform nursing practice, policy, and research to promote well-being and delay functional deterioration in PWD. [Journal of Gerontological Nursing, 47(10), 15-22.].

Validity, Reliability and Sensitivity to Change of Three Consumer-Grade Activity Trackers in Controlled and Free-Living Conditions among Older Adults

Wrist-worn consumer-grade activity trackers are popular devices, developed mainly for personal use. This study aimed to explore the validity, reliability and sensitivity to change of movement behaviors metrics from three activity trackers (Polar Vantage M, Garmin Vivoactive 4s and Garmin Vivosport) in controlled and free-living conditions when worn by older adults. Participants (n = 28; 74 ± 5 years) underwent a videotaped laboratory protocol while wearing all three trackers. On a separate occasion, participants (n = 17 for each of the trackers) wore one (randomly assigned) tracker and a research-grade activity monitor ActiGraph wGT3X-BT simultaneously for six consecutive days. Both Garmin trackers showed excellent performance for step counts, with a mean absolute percentage error (MAPE) below 20% and intraclass correlation coefficient (ICC_2,1) above 0.90 (p < 0.05). The MAPE for sleep time was within 10% for all the trackers tested, while it was far beyond 20% for all other movement behaviors metrics. The results suggested that all three trackers could be used for measuring sleep time with a high level of accuracy, and both Garmin trackers could also be used for step counts. All other output metrics should be used with caution. The results provided in this study could be used to guide choice on activity trackers aiming for different purposes—individual use, longitudinal monitoring or in clinical trial setting.

Association of physical activity with blood pressure in African ancestry men

This study tested the association of objectively measured physical activity with blood pressure and hypertension in African Caribbean men, an understudied population segment known to be at high-risk for cardiovascular disease (CVD) which has low levels of high-exertion physical activity. Men (N = 310) were from the Tobago Health Study and aged 50–89 years. Systolic (SBP) and diastolic (DBP) blood pressures were measured using an automated device, and hypertension was defined as SBP ≥ 140 mmHg, DBP ≥ 90 mmHg, or current use of antihypertensive medication. Physical activity was measured using the SenseWear Pro armband (SWA) and consisted of daily time engaged in sedentary behavior (SB), light physical activity (LPA), and moderate to vigorous activity (MVPA), as well as daily step count. Multiple regression analyses using the isotemporal substitution framework were used to test for associations between activity and blood pressures. Models were adjusted in stages for SWA wear time, age, antihypertensive medication use, alcohol consumption, smoking, diabetes, CVD, family history of hypertension, salt intake, and adiposity.

Replacement of SB with LPA was associated with lower SBP adjusted for wear time (β = -0.84, p < 0.05), but attenuated after adjustment for age. Replacement of SB with LPA was associated with lower DBP (β = -0.50) and lower odds of hypertension (OR = 0.88), adjusted for wear time and age (both p < 0.05). All model associations of replacement of SB with LPA were stronger when restricted to men not taking antihypertensive medications, regardless of their hypertension status.

These results support the strategy of increasing light physical activity for blood pressure management in high-risk Afro-Caribbean men.

Evaluation of a Low-Cost Commercial Actigraph and Its Potential Use in Detecting Cultural Variations in Physical Activity and Sleep

The purpose of the present study was to evaluate the performance of a low-cost commercial smartwatch, the Xiaomi Mi Band (MB), in extracting physical activity and sleep-related measures and show its potential use in addressing questions that require large-scale real-time data and/or intercultural data including low-income countries. We evaluated physical activity and sleep-related measures and discussed the potential application of such devices for large-scale step and sleep data acquisition. To that end, we conducted two separate studies. In Study 1, we evaluated the performance of MB by comparing it to the GT3X (ActiGraph, wGT3X-BT), a scientific actigraph used in research, as well as subjective sleep reports. In Study 2, we distributed the MB across four countries (Austria, Germany, Cuba, and Ukraine) and investigated physical activity and sleep among these countries. The results of Study 1 indicated that MB step counts correlated highly with the scientific GT3X device, but did display biases. In addition, the MB-derived wake-up and total-sleep-times showed high agreement with subjective reports, but partly deviated from GT3X predictions. Study 2 revealed similar MB step counts across countries, but significant later wake-up and bedtimes for Ukraine than the other countries. We hope that our studies will stimulate future large-scale sensor-based physical activity and sleep research studies, including various cultures.

Wearable technology and the association of perioperative activity level with 30-day readmission among patients undergoing major colorectal surgery

BACKGROUND

The proliferation of wearable technology presents a novel opportunity for perioperative activity monitoring; however, the association between perioperative activity level and readmission remains underexplored. This study sought to determine whether physical activity data captured by wearable technology before and after colorectal surgery can be used to predict 30-day readmission.

METHODS

In this prospective observational cohort study of adults undergoing elective major colorectal surgery (January 2018 to February 2019) at a single institution, participants wore an activity monitor 30 days before and after surgery. The primary outcome was return to baseline percentage, defined as step count on the day before discharge as a percentage of mean preoperative daily step count, among readmitted and non-readmitted patients.

RESULTS

94 patients had sufficient data available for analysis, of which 16 patients (17.0%) were readmitted within 30 days following discharge. Readmitted patients achieved a lower return to baseline percentage compared to patients who were not readmitted (median 15.1% vs. 31.8%; P = 0.004). On multivariable analysis adjusting for readmission risk and hospital length of stay, an absolute increase of 10% in return to baseline percentage was associated with a 40% decreased risk of 30-day readmission (odds ratio 0.60; P = 0.02). Analysis of the receiver operating characteristic curve identified 28.9% as an optimal return to baseline percent threshold for predicting readmission.

CONCLUSIONS

Achieving a higher percentage of an individual's preoperative baseline activity level on the day prior to discharge after major colorectal surgery is associated with decreased risk of 30-day hospital readmission.

Factors associated with validity of consumer-oriented wearable physical activity trackers: a meta-analysis

The purposes of this study were to examine (1) the strength of the criterion validity evidence of various consumer-oriented wearable physical activity trackers, (2) the influence of brands of consumer-oriented wearable physical activity on validity evidence and (3) factors that may contribute to differences in the strength of the criterion validity evidence. A total of 589 articles were identified through four databases. Pairs of researchers reviewed the articles to determine eligibility. A total of 29 studies with 96 validity coefficients were included in the meta-analysis. Five different moderators, including the brands of physical activity trackers, placement of devices, type of activities (ambulatory vs. lifestyle activities), population, and release year, were analysed to examine which factors impact the validity evidence. The summarised validity coefficient between activity trackers and energy expenditure ranged from r = .41 to r = .91. Moderator analyses revealed that the brand, placement of the device, and population significantly impact the magnitude of the validity evidence, while the type of activity and release year of the devices do not. Device brand, population, andplacement are each factor that significantly affects the validity coefficientsbetween consumer-oriented wearable physical activity trackers. Efforts should be made to improve the accuracy of these devices to maintain the credibility of the research and the trust of consumers.

Wrist-Worn Activity Trackers in Laboratory and Free-Living Settings for Patients With Chronic Pain: Criterion Validity Study

BACKGROUND

Physical activity is evidently a crucial part of the rehabilitation process for patients with chronic pain. Modern wrist-worn activity tracking devices seemingly have a great potential to provide objective feedback and assist in the adoption of healthy physical activity behavior by supplying data of energy expenditure expressed as metabolic equivalent of task units (MET). However, no studies of any wrist-worn activity tracking devices' have examined criterion validity in estimating energy expenditure, heart rate, or step count in patients with chronic pain.

OBJECTIVE

The aim was to determine the criterion validity of wrist-worn activity tracking devices for estimations of energy expenditure, heart rate, and step count in a controlled laboratory setting and free-living settings for patients with chronic pain.

METHODS

In this combined laboratory and field validation study, energy expenditure, heart rate, and step count were simultaneously estimated by a wrist-worn activity tracker (Fitbit Versa), indirect calorimetry (Jaeger Oxycon Pro), and a research-grade hip-worn accelerometer (ActiGraph GT3X) during treadmill walking at 3 speeds (3.0 km/h, 4.5 km/h, and 6.0 km/h) in the laboratory setting. Energy expenditure and step count were also estimated by the wrist-worn activity tracker in free-living settings for 72 hours. The criterion validity of each measure was determined using intraclass and Spearman correlation, Bland-Altman plots, and mean absolute percentage error. An analysis of variance was used to determine whether there were any significant systematic differences between estimations.

RESULTS

A total of 42 patients (age: 25-66 years; male: 10/42, 24%; female: 32/42, 76%), living with chronic pain (duration, in years: mean 9, SD 6.72) were included. At baseline, their mean pain intensity was 3.5 (SD 1.1) out of 6 (Multidimensional Pain Inventory, Swedish version). Results showed that the wrist-worn activity tracking device (Fitbit Versa) systematically overestimated energy expenditure when compared to the criterion standard (Jaeger Oxycon Pro) and the relative criterion standard (ActiGraph GT3X). Poor agreement and poor correlation were shown between Fitbit Versa and both Jaeger Oxycon Pro and ActiGraph GT3X for estimated energy expenditure at all treadmill speeds. Estimations of heart rate demonstrated poor to fair agreement during laboratory-based treadmill walks. For step count, the wrist-worn devices showed fair agreement and fair correlation at most treadmill speeds. In free-living settings; however, the agreement for step count between the wrist-worn device and waist-worn accelerometer was good, and the correlation was excellent.

CONCLUSIONS

The wrist-worn device systematically overestimated energy expenditure and showed poor agreement and correlation compared to the criterion standard (Jaeger Oxycon Pro) and the relative criterion standard (ActiGraph GT3X), which needs to be considered when used clinically. Step count measured with a wrist-worn device, however, seemed to be a valid estimation, suggesting that future guidelines could include such variables in this group with chronic pain.

Validity and Reliability of Physiological Data in Applied Settings Measured by Wearable Technology: A Rapid Systematic Review

The purpose of this review was to evaluate the current state of the literature and to identify the types of study designs, wearable devices, statistical tests, and exercise modes used in validation and reliability studies conducted in applied settings/outdoor environments. This was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. We identified nine articles that fit our inclusion criteria, eight of which tested for validity and one tested for reliability. The studies tested 28 different devices with exercise modalities of running, walking, cycling, and hiking. While there were no universally common analytical techniques used to measure accuracy or validity, correlative measures were used in 88% of studies, mean absolute percentage error (MAPE) in 75%, and Bland–Altman plots in 63%. Intra-class correlation was used to determine reliability. There were not any universally common thresholds to determine validity, however, of the studies that used MAPE and correlation, there were only five devices that had a MAPE of < 10% and a correlation value of > 0.7. Overall, the current review establishes the need for greater testing in applied settings when validating wearables. Researchers should seek to incorporate multiple intensities, populations, and modalities into their study designs while utilizing appropriate analytical techniques to measure and determine validity and reliability.

The Implication of Wearables and the Factors Affecting Their Usage among Recreationally Active People

Regular physical activity (PA) is associated with health and well-being. Recent findings show that PA tracking using technological devices can enhance PA behavior. Consumer devices can track many different parameters affecting PA (e.g., number of steps, distance, and heart rate). However, it remains unclear what factors affect the usage of such devices. In this study, we evaluated whether there was a change in usage behavior across the first weeks of usage. Further we investigated whether external factors such as weather and day of the week influence usage behavior. Thirty nine participants received a Fitbit Charge 2 fitness tracker for a nine-week period. All participants were asked to wear the device according to their wishes. The usage time and amount of PA were assessed, and the influencing factors, such as weather conditions and day of the week, were analyzed. The results showed that usage behavior differed largely between individuals and decreased after five weeks of usage. Moreover, the steps per worn hour did not change significantly, indicating a similar amount of activity across the nine-week period when wearing the device. Further influencing factors were the day of the week (the tracker was used less on Sundays) and the temperature (usage time was lower with temperatures >25°). Tracking peoples’ activity might have the potential to evaluate different interventions to increase PA.

Effects of an Activity Tracker and App Intervention to Increase Physical Activity in Whole Families-The Step It Up Family Feasibility Study

(1) Background: Interventions using activity trackers and smartphone apps have demonstrated their ability to increase physical activity in children and adults. However, they have not been tested in whole families. Further, few family-centered interventions have actively involved both parents and assessed physical activity effects separately for children, mothers and fathers. Objective: To examine the feasibility and short-term effects of an activity tracker and app intervention to increase physical activity in the whole family (children, mothers and fathers). (2) Methods: This was a single-arm feasibility study with pre-post intervention measures. Between 2017-2018, 40 families (58 children aged 6-10 years, 39 mothers, 33 fathers) participated in the 6-week Step it Up Family program in Queensland, Australia. Using commercial activity trackers combined with apps (Garmin Vivofit Jr for children, Vivofit 3 for adults; Garmin Australasia Pty Ltd., Sydney, Australia), the intervention included individual and family-level goal-setting, self-monitoring, performance feedback, family step challenges, family social support and modelling, weekly motivational text messages and an introductory session. Parent surveys were used to assess physical activity effects measured as pre-post intervention changes in moderate-to-vigorous physical activity (MVPA) in children, mothers and fathers. Objective Garmin activity tracker data was recorded to assess physical activity levels (steps, active minutes) during the intervention. (3) Results: Thirty-eight families completed the post intervention survey (95% retention). At post intervention, MVPA had increased in children by 58 min/day (boys: 54 min/day, girls: 62 min/day; all p < 0.001). In mothers, MVPA increased by 27 min/day (p < 0.001) and in fathers, it increased by 31 min/day (p < 0.001). The percentage of children meeting Australia's physical activity guidelines for children (≥60 MVPA min/day) increased from 34% to 89% (p < 0.001). The percentage of mothers and fathers meeting Australia's physical activity guidelines for adults (≥150 MVPA min/week) increased from 8% to 57% (p < 0.001) in mothers and from 21% to 68% (p < 0.001) in fathers. The percentage of families with 'at least one child and both parents' meeting the physical activity guidelines increased from 0% to 41% (p < 0.001). Objective activity tracker data recorded during the intervention showed that the mean (SD) number of active minutes per day in children was 82.1 (17.1). Further, the mean (SD) steps per day was 9590.7 (2425.3) in children, 7397.5 (1954.2) in mothers and 8161.7 (3370.3) in fathers. (4) Conclusions: Acknowledging the uncontrolled study design, the large pre-post changes in MVPA and rather high step counts recorded during the intervention suggest that an activity tracker and app intervention can increase physical activity in whole families. The Step it Up Family program warrants further efficacy testing in a larger, randomized controlled trial.

Reliability and Validity of Commercially Available Wearable Devices for Measuring Steps, Energy Expenditure, and Heart Rate: Systematic Review

Background

Consumer-wearable activity trackers are small electronic devices that record fitness and health-related measures.

Objective

The purpose of this systematic review was to examine the validity and reliability of commercial wearables in measuring step count, heart rate, and energy expenditure.

Methods

We identified devices to be included in the review. Database searches were conducted in PubMed, Embase, and SPORTDiscus, and only articles published in the English language up to May 2019 were considered. Studies were excluded if they did not identify the device used and if they did not examine the validity or reliability of the device. Studies involving the general population and all special populations were included. We operationalized validity as criterion validity (as compared with other measures) and construct validity (degree to which the device is measuring what it claims). Reliability measures focused on intradevice and interdevice reliability.

Results

We included 158 publications examining nine different commercial wearable device brands. Fitbit was by far the most studied brand. In laboratory-based settings, Fitbit, Apple Watch, and Samsung appeared to measure steps accurately. Heart rate measurement was more variable, with Apple Watch and Garmin being the most accurate and Fitbit tending toward underestimation. For energy expenditure, no brand was accurate. We also examined validity between devices within a specific brand.

Conclusions

Commercial wearable devices are accurate for measuring steps and heart rate in laboratory-based settings, but this varies by the manufacturer and device type. Devices are constantly being upgraded and redesigned to new models, suggesting the need for more current reviews and research.

Validation of the Severity of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome by Other Measures than History: Activity Bracelet, Cardiopulmonary Exercise Testing and a Validated Activity Questionnaire: SF-36

Introduction: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a severe and disabling chronic disease. Grading patient’s symptom and disease severity for comparison and therapeutic decision-making is necessary. Clinical grading that depends on patient self-report is subject to inter-individual variability. Having more objective measures to grade and confirm clinical grading would be desirable. Therefore, the aim of this study was to validate the clinical severity grading that has been proposed by the authors of the ME International Consensus Criteria (ICC) using more standardized measures like questionnaires, and objective measures such as physical activity tracking and cardiopulmonary exercise testing. Methods and results: The clinical database of a subspecialty ME/CFS clinic was searched for patients who had completed the SF 36 questionnaire, worn a Sensewear^TM armband for five days, and undergone a cardiopulmonary exercise test. Only patients who completed all three investigations within 3 months from each other—to improve the likelihood of stable disease—were included in the analysis. Two-hundred-eighty-nine patients were analyzed: 121 were graded as mild, 98 as moderate and 70 as having severe disease. The mean (SD) physical activity subscale of the SF-36 was 70 (11) for mild, 43 (8) for moderate and 15 (10) for severe ME/CFS patients. The mean (SD) number of steps per day was 8235 (1004) for mild, 5195 (1231) for moderate and 2031 (824) for severe disease. The mean (SD) percent predicted oxygen consumption at the ventilatory threshold was 47 (11)% for mild, 38 (7)% for moderate and 30 (7)% for severe disease. The percent peak oxygen consumption was 90 (14)% for mild, 64 (8)% for moderate and 48 (9)% for severe disease. All comparisons were p < 0.0001. Conclusion: This study confirms the validity of the ICC severity grading. Grading assigned by clinicians on the basis of patient self-report created groups that differed significantly on measures of activity using the SF-36 physical function subscale and objective measures of steps per day and exercise capacity. There was variability in function within severity grading groups, so grading based on self-report can be strengthened by the use of these supplementary measures.

Continuous 7-Month Internet of Things-Based Monitoring of Health Parameters of Pregnant and Postpartum Women: Prospective Observational Feasibility Study

BACKGROUND

Monitoring during pregnancy is vital to ensure the mother's and infant's health. Remote continuous monitoring provides health care professionals with significant opportunities to observe health-related parameters in their patients and to detect any pathological signs at an early stage of pregnancy, and may thus partially replace traditional appointments.

OBJECTIVE

This study aimed to evaluate the feasibility of continuously monitoring the health parameters (physical activity, sleep, and heart rate) of nulliparous women throughout pregnancy and until 1 month postpartum, with a smart wristband and an Internet of Things (IoT)-based monitoring system.

METHODS

This prospective observational feasibility study used a convenience sample of 20 nulliparous women from the Hospital District of Southwest Finland. Continuous monitoring of physical activity/step counts, sleep, and heart rate was performed with a smart wristband for 24 hours a day, 7 days a week over 7 months (6 months during pregnancy and 1 month postpartum). The smart wristband was connected to a cloud server. The total number of possible monitoring days during pregnancy weeks 13 to 42 was 203 days and 28 days in the postpartum period.

RESULTS

Valid physical activity data were available for a median of 144 (range 13-188) days (75% of possible monitoring days), and valid sleep data were available for a median of 137 (range 0-184) days (72% of possible monitoring days) per participant during pregnancy. During the postpartum period, a median of 15 (range 0-25) days (54% of possible monitoring days) of valid physical activity data and 16 (range 0-27) days (57% of possible monitoring days) of valid sleep data were available. Physical activity decreased from the second trimester to the third trimester by a mean of 1793 (95% CI 1039-2548) steps per day (P<.001). The decrease continued by a mean of 1339 (95% CI 474-2205) steps to the postpartum period (P=.004). Sleep during pregnancy also decreased from the second trimester to the third trimester by a mean of 20 minutes (95% CI -0.7 to 42 minutes; P=.06) and sleep time shortened an additional 1 hour (95% CI 39 minutes to 1.5 hours) after delivery (P<.001). The mean resting heart rate increased toward the third trimester and returned to the early pregnancy level during the postpartum period.

CONCLUSIONS

The smart wristband with IoT technology was a feasible system for collecting representative data on continuous variables of health parameters during pregnancy. Continuous monitoring provides real-time information between scheduled appointments and thus may help target and tailor pregnancy follow-up.

Wearable devices can predict the outcome of standardized 6-minute walk tests in heart disease

Wrist-worn devices with heart rate monitoring have become increasingly popular. Although current guidelines advise to consider clinical symptoms and exercise tolerance during decision-making in heart disease, it remains unknown to which extent wearables can help to determine such functional capacity measures. In clinical settings, the 6-minute walk test has become a standardized diagnostic and prognostic marker. We aimed to explore, whether 6-minute walk distances can be predicted by wrist-worn devices in patients with different stages of mitral and aortic valve disease. A total of n = 107 sensor datasets with 1,019,748 min of recordings were analysed. Based on heart rate recordings and literature information, activity levels were determined and compared to results from a 6-minute walk test. The percentage of time spent in moderate activity was a predictor for the achievement of gender, age and body mass index-specific 6-minute walk distances (p < 0.001; R 2 = 0.48). The uncertainty of these predictions is demonstrated.

Review of Validity and Reliability of Garmin Activity Trackers

Purpose

A systematic review to summarize the validity and reliability of steps, distance, energy expenditure, speed, elevation, heart rate, and sleep assessed by Garmin activity trackers.

Methods

Searches included studies published through December 31, 2018. Correlation coefficients (CC) were assessed as low (<0.60), moderate (0.60-<0.75), good (0.75-<0.90), or excellent (>=0.90). Mean absolute percentage errors (MAPE) were assessed as acceptable at <5% in controlled conditions and <10% for free-living.

Results

Overall, 32 studies of adults documented validity. Four of these studies also documented reliability. The sample size ranged from 1 to 95 for validity and 4 to 31 for reliability testing. Step inter- and intra-reliability was good-to-excellent and speed intra-reliability was excellent. No other features were explored for reliability. Step validity, across 16 studies, generally indicated good-to-excellent CC and acceptable MAPE. Distance validity, tested in three studies, generally indicated poor CC and MAPE that exceeded acceptable limits, with both over and underestimation. Energy expenditure validity, across 12 studies, generally indicated wide variability in CC and MAPE that exceeded acceptable limits. Heart rate validity in five studies had low-to-excellent CC and all MAPE exceeded acceptable limits. Speed, elevation, and sleep validity were assessed in only one or two studies each; for sleep, the criterion relied on self-report rather than polysomnography.

Conclusion

This systematic review of Garmin activity trackers among adults indicated higher validity of steps; few studies on speed, elevation, and sleep; and lower validity for distance, energy expenditure, and heart rate. Intra- and inter-device feature reliability needs further testing.

Low-Cost Consumer-Based Trackers to Measure Physical Activity and Sleep Duration Among Adults in Free-Living Conditions: Validation Study

Background

Wearable trackers for monitoring physical activity (PA) and total sleep time (TST) are increasingly popular. These devices are used not only by consumers to monitor their behavior but also by researchers to track the behavior of large samples and by health professionals to implement interventions aimed at health promotion and to remotely monitor patients. However, high costs and accuracy concerns may be barriers to widespread adoption.

Objective

This study aimed to investigate the concurrent validity of 6 low-cost activity trackers for measuring steps, moderate-to-vigorous physical activity (MVPA), and TST: Geonaut On Coach, iWown i5 Plus, MyKronoz ZeFit4, Nokia GO, VeryFit 2.0, and Xiaomi MiBand 2.

Methods

A free-living protocol was used in which 20 adults engaged in their usual daily activities and sleep. For 3 days and 3 nights, they simultaneously wore a low-cost tracker and a high-cost tracker (Fitbit Charge HR) on the nondominant wrist. Participants wore an ActiGraph GT3X+ accelerometer on the hip at daytime and a BodyMedia SenseWear device on the nondominant upper arm at nighttime. Validity was assessed by comparing each tracker with the ActiGraph GT3X+ and BodyMedia SenseWear using mean absolute percentage error scores, correlations, and Bland-Altman plots in IBM SPSS 24.0.

Results

Large variations were shown between trackers. Low-cost trackers showed moderate-to-strong correlations (Spearman r=0.53-0.91) and low-to-good agreement (intraclass correlation coefficient [ICC]=0.51-0.90) for measuring steps. Weak-to-moderate correlations (Spearman r=0.24-0.56) and low agreement (ICC=0.18-0.56) were shown for measuring MVPA. For measuring TST, the low-cost trackers showed weak-to-strong correlations (Spearman r=0.04-0.73) and low agreement (ICC=0.05-0.52). The Bland-Altman plot revealed a variation between overcounting and undercounting for measuring steps, MVPA, and TST, depending on the used low-cost tracker. None of the trackers, including Fitbit (a high-cost tracker), showed high validity to measure MVPA.

Conclusions

This study was the first to examine the concurrent validity of low-cost trackers. Validity was strongest for the measurement of steps; there was evidence of validity for measurement of sleep in some trackers, and validity for measurement of MVPA time was weak throughout all devices. Validity ranged between devices, with Xiaomi having the highest validity for measurement of steps and VeryFit performing relatively strong across both sleep and steps domains. Low-cost trackers hold promise for monitoring and measurement of movement and sleep behaviors, both for consumers and researchers.

Wrist-Worn Wearables for Monitoring Heart Rate and Energy Expenditure While Sitting or Performing Light-to-Vigorous Physical Activity: Validation Study

Background

Physical activity reduces the incidences of noncommunicable diseases, obesity, and mortality, but an inactive lifestyle is becoming increasingly common. Innovative approaches to monitor and promote physical activity are warranted. While individual monitoring of physical activity aids in the design of effective interventions to enhance physical activity, a basic prerequisite is that the monitoring devices exhibit high validity.

Objective

Our goal was to assess the validity of monitoring heart rate (HR) and energy expenditure (EE) while sitting or performing light-to-vigorous physical activity with 4 popular wrist-worn wearables (Apple Watch Series 4, Polar Vantage V, Garmin Fenix 5, and Fitbit Versa).

Methods

While wearing the 4 different wearables, 25 individuals performed 5 minutes each of sitting, walking, and running at different velocities (ie, 1.1 m/s, 1.9 m/s, 2.7 m/s, 3.6 m/s, and 4.1 m/s), as well as intermittent sprints. HR and EE were compared to common criterion measures: Polar-H7 chest belt for HR and indirect calorimetry for EE.

Results

While monitoring HR at different exercise intensities, the standardized typical errors of the estimates were 0.09-0.62, 0.13-0.88, 0.62-1.24, and 0.47-1.94 for the Apple Watch Series 4, Polar Vantage V, Garmin Fenix 5, and Fitbit Versa, respectively. Depending on exercise intensity, the corresponding coefficients of variation were 0.9%-4.3%, 2.2%-6.7%, 2.9%-9.2%, and 4.1%-19.1%, respectively, for the 4 wearables. While monitoring EE at different exercise intensities, the standardized typical errors of the estimates were 0.34-1.84, 0.32-1.33, 0.46-4.86, and 0.41-1.65 for the Apple Watch Series 4, Polar Vantage V, Garmin Fenix 5, and Fitbit Versa, respectively. Depending on exercise intensity, the corresponding coefficients of variation were 13.5%-27.1%, 16.3%-28.0%, 15.9%-34.5%, and 8.0%-32.3%, respectively.

Conclusions

The Apple Watch Series 4 provides the highest validity (ie, smallest error rates) when measuring HR while sitting or performing light-to-vigorous physical activity, followed by the Polar Vantage V, Garmin Fenix 5, and Fitbit Versa, in that order. The Apple Watch Series 4 and Polar Vantage V are suitable for valid HR measurements at the intensities tested, but HR data provided by the Garmin Fenix 5 and Fitbit Versa should be interpreted with caution due to higher error rates at certain intensities. None of the 4 wrist-worn wearables should be employed to monitor EE at the intensities and durations tested.

Measuring Physical Activity Using Triaxial Wrist Worn Polar Activity Trackers: A Systematic Review

Collecting objective physical activity data from research participants are increasingly done using consumer-based activity trackers. Several validation studies of Polar devices are conducted to date, but no systematic review of the current level of accuracy for these devices exist. The aim of this study is therefore to investigate the accuracy of current wrist-worn Polar devices that equips a triaxial accelerometer to measure physical activity. We conducted a systematic review by searching six databases for validation studies on modern Polar activity trackers. Studies were grouped and examined by tested outcome, i.e. energy expenditure, physical activity intensity, and steps. We summarized and reported relevant metrics from each study. The initial search resulted in 157 studies, out of which fourteen studies were included in the final review. Energy expenditure was reviewed in seven studies, physical activity intensity was reviewed in four studies, and steps was reviewed in 11 studies. There is a large difference in study protocols with conflicting results between the identified studies. However, for energy expenditure there is some indication that Polar devices perform better in free-living, compared to lab-based studies. In addition, step counting seems to have less average error compared to energy expenditure and physical activity intensity. There is large heterogeneity between the identified studies, both in terms of study protocols and results, and the accuracy of Polar devices remains unclear. More studies are needed for more recently developed devices, and future studies should take care to follow guidelines for assessment of wearable sensors designed for physical activity monitoring.

Step Count Reliability and Validity of Five Wearable Technology Devices While Walking and Jogging in both a Free Motion Setting and on a Treadmill

Wearable technology devices are used by millions of people who use daily step counts to promote healthy lifestyles. However, the accuracy of many of these devices has not been determined. The purpose was to determine reliability and validity of the Samsung Gear 2, FitBit Surge, Polar A360, Garmin Vivosmart HR+, and the Leaf Health Tracker when walking and jogging in free motion and treadmill conditions. Forty volunteers completed walking and jogging free motion and treadmill protocols of 5-minute intervals. The devices were worn simultaneously in randomized configurations. The mean of two manual steps counters was used as the criterion measure. Test-retest reliability was determined via Intraclass Correlation Coefficient (ICC). Validity was determined via a combination of Pearson's Correlation Coefficient, mean absolute percent error (MAPE: free motion ≤ 10.0%, treadmill ≤ 5.00%), and Bland-Altman analysis (device bias and limits of agreement). Significance was set at p < 0.05. The Samsung Gear 2 was deemed to be both reliable and valid for the jogging conditions, but not walking. The Fitbit Surge was reliable and valid for all conditions except for treadmill walking (deemed reliable, ICC = 0.76; but not valid). The Polar A360 was found to be reliable for one condition (treadmill jog ICC = 0.78), but not valid for any condition. The Garmin Vivosmart HR+ and Leaf Health Tracker were found to be both reliable and valid for all situations. While each device returned some level of consistency and accuracy during either free motion or treadmill exercises, the Garmin Vivosmart HR+ and the Leaf Health Tracker were deemed to be reliable and valid for all conditions tested.

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

BACKGROUND

Wearable fitness trackers are devices that can record and enhance physical activity among users. Recently, photoplethysmography (PPG) devices that use optical heart rate sensors to detect heart rate in real time have become popular and help in monitoring and controlling exercise intensity. Although the benefits of using optical heart rate monitors have been highlighted through studies, the accuracy of the readouts these commercial devices generate has not been widely assessed for different age groups, especially for the East Asian population with Fitzpatrick skin type III or IV.

OBJECTIVE

This study aimed to examine the accuracy of 2 wearable fitness trackers with PPG to monitor heart rate in real time during moderate exercise in young and older adults.

METHODS

A total of 20 young adults and 20 older adults were recruited for this study. All participants were asked to undergo a series of sedentary and moderate physical activities using indoor aerobic exercise equipment. In this study, the Polar H7 chest-strapped heart rate monitor was used as the criterion measure in 2 fitness trackers, namely Xiaomi Mi Band 2 and Garmin Vivosmart HR+. The real-time, second-by-second heart rate data obtained from both devices were recorded using the broadcast heart rate mode. To critically analyze the results, multiple statistical parameters including the mean absolute percentage error (MAPE), Lin concordance correlation coefficient (CCC), intraclass correlation coefficient, the Pearson product moment correlation coefficient, and the Bland-Altman coefficient were determined to examine the performances of the devices.

RESULTS

Both test devices exhibited acceptable overall accuracy as heart rate sensors based on several statistical tests. Notably, the MAPE values were below 10% (the designated threshold) in both devices (GarminYoung=3.77%; GarminSenior=4.73%; XiaomiYoung=7.69%; and XiaomiSenior=6.04%). The scores for reliability test of CCC for Garmin were 0.92 (Young) and 0.80 (Senior), whereas those for Xiaomi were 0.76 (Young) and 0.73 (Senior). However, the results obtained using the Bland-Altman analysis indicated that both test optical devices underestimated the average heart rate. More importantly, the study documented some unexpected outlier readings reported by these devices when used on certain participants.

CONCLUSIONS

The study reveals that commonly used optical heart rate sensors, such as the ones used herein, generally produce accurate heart rate readings irrespective of the age of the user. However, users should avoid relying entirely on these readings to indicate exercise intensities, as these devices have a tendency to produce erroneous, extreme readings, which might misinterpret the real-time exercise intensity. Future studies should therefore emphasize the occurrence rate of such errors, as this will likely benefit the development of improved models of heart rate sensors.

Effects of an intervention combining self-care and self-hypnosis on fatigue and associated symptoms in post-treatment cancer patients: A randomized-controlled trial

OBJECTIVE

Cancer has a lot of consequences such as fatigue, sleep disturbances, emotional distress, cognitive impairment and reduced physical activity. Some hypnosis-based psychological interventions showed positive effects on fatigue, sleep and emotional distress, but generally focused on breast cancer patients. Our study aimed at assessing the effects of a group intervention combining self-care and self-hypnosis on quality of life of cancer patients.

METHODS

Our longitudinal randomized-controlled trial assessed the benefits of the intervention first on fatigue and secondly on associated symptoms (sleep, emotional distress, cognitive impairment and reduced physical activity) of post-treatment cancer patients, and investigated predictors of the evolution of fatigue. All variables were measured with questionnaires and an actigraph (for sleep and physical activity).

RESULTS

Ninety five women with different cancers were included in our study. Group-by-time effects were showed for fatigue, sleep, emotional distress and cognitive functioning: symptoms have improved in the intervention group compared to wait-list control group. Three predictors of the evolution of fatigue were revealed: depression, anxiety and worry.

CONCLUSIONS

Our group intervention had benefits for post-treatment cancer patients' quality of life. Impacting emotional distress could be important in order to decrease fatigue. Further studies are needed to replicate our results. This intervention could be easily implemented to improve quality of life of cancer patients. Registration: ClinicalTrials.gov (NCT03144154). Retrospectively registered on the 1st of May, 2017.

Patient-generated health data collection using a wearable activity tracker in cancer patients-a feasibility study

PURPOSE

Incorporation of patient-generated health data (PGHD) into clinical research requires an investigation of the validity of outcomes and feasibility of implementation. This single-arm pilot trial investigated the feasibility of using a commercially available activity tracking wearable device in cancer patients to assess adherence to the device and real-time PGHD collection in a clinical research setting.

METHODS

From July to November 2017, enrolled adult patients were asked to wear a wristband-style device. Brief Fatigue Inventory (BFI) and MD Anderson Symptom Inventory (MDASI) were assessed at baseline and on day 29. Furthermore, 29-day Pittsburgh Sleep Quality Index, global impression of the devices, and NCI CTCAE v4 were evaluated.

RESULTS

Of 30 patients (mean age, 58.6 years; male, 21 [70%]), 15 (50%) and 11 (36.7%) had gastrointestinal and lung cancer, respectively, and 27 (90%, 95% CI: 0.74-0.98) were well adhered (> 70%) to the device for 28 days. The mean adherence was 84.9% (range: 41.7-95.2%). More frequent PGHD synchronization tended to show better device adherence, with moderate correlation (r = 0.62, 95% CI: 0.33-0.80, p < 000.1).

CONCLUSIONS

The feasibility of using a wearable activity tracker was confirmed in cancer patients receiving chemotherapy for a month. For future implementation in clinical trials, there is a need for further comprehensive assessment of the validity and reliability of wearable activity trackers.

TRIAL REGISTRATION

This trial was registered at the University Hospital Medical Information Network Clinical Trials Registry as UMIN: UMIN000027575.

Is Activity Tracker-Measured Ambulation an Accurate and Reliable Determinant of Postoperative Quality of Recovery? A Prospective Cohort Validation Study

BACKGROUND

Quality of recovery (QOR) instruments measure patients' ability to return to baseline health status after surgery. Whether, and the extent to which, postoperative ambulation contributes to QOR is unclear, in part due to the lack of valid tools to measure ambulation in clinical settings. This cohort study of the cesarean delivery surgical model examines the accuracy and reliability of activity trackers in quantifying early postoperative ambulation and investigates the correlation between ambulation and QOR.

METHODS

A prospective cohort of 200 parturients undergoing cesarean delivery between July 2015 and June 2017 was fitted with wrist-worn activity trackers immediately postpartum. The trackers were collected 24 hours later, along with QOR assessments (QoR-15 scale). The relationship between QOR and various covariates, including ambulation, was explored using multivariable linear regression and Spearman correlation (ρ). Forty-eight parturients fitted with 2 trackers also completed a walk exercise accompanied by a step-counting assessor, to evaluate accuracy, inter-, and intradevice reliability using interclass correlation (ICC).

RESULTS

Compared to step counting, activity trackers had high accuracy (ICC = 0.93) and excellent inter- and intradevice reliability (ICC = 0.98 and 0.96, respectively). Correlation analysis suggested that early ambulation is moderately correlated with postcesarean QoR-15 scores, with a ρ (95% confidence interval) equivalent to 0.56 (0.328-0.728). Regression analysis suggested that ambulation is a determinant of postcesarean QoR-15 scores, with an effect estimate (95% confidence interval) equivalent to 0.002 (0.001-0.003). Ambulation was also associated with all QoR-15 domains, except psychological support. The patient's acceptable symptom state (subjective threshold for good ambulation) in the first 24 hours was 287 steps.

CONCLUSIONS

This study demonstrated the accuracy and reliability of activity trackers in measuring ambulation in clinical settings and suggested that postoperative ambulation is a determinant of postoperative QOR. A hypothetical implication of our findings is that interventions that improve ambulation may also help to enhance QOR, but further research is needed to establish a causal relationship.