Evaluation of Commercial Self-Monitoring Devices for Clinical Purposes: Results from the Future Patient Trial, Phase I

Matching science to reality: how to deploy a participant-driven digital brain health platform

Introduction

Advances in digital technologies for health research enable opportunities for digital phenotyping of individuals in research and clinical settings. Beyond providing opportunities for advanced data analytics with data science and machine learning approaches, digital technologies offer solutions to several of the existing barriers in research practice that have resulted in biased samples.

Methods

A participant-driven, precision brain health monitoring digital platform has been introduced to two longitudinal cohort studies, the Boston University Alzheimer's Disease Research Center (BU ADRC) and the Bogalusa Heart Study (BHS). The platform was developed with prioritization of digital data in native format, multiple OS, validity of derived metrics, feasibility and usability. A platform including nine remote technologies and three staff-guided digital assessments has been introduced in the BU ADRC population, including a multimodal smartphone application also introduced to the BHS population. Participants select which technologies they would like to use and can manipulate their personal platform and schedule over time.

Results

Participants from the BU ADRC are using an average of 5.9 technologies to date, providing strong evidence for the usability of numerous digital technologies in older adult populations. Broad phenotyping of both cohorts is ongoing, with the collection of data spanning cognitive testing, sleep, physical activity, speech, motor activity, cardiovascular health, mood, gait, balance, and more. Several challenges in digital phenotyping implementation in the BU ADRC and the BHS have arisen, and the protocol has been revised and optimized to minimize participant burden while sustaining participant contact and support.

Discussion

The importance of digital data in its native format, near real-time data access, passive participant engagement, and availability of technologies across OS has been supported by the pattern of participant technology use and adherence across cohorts. The precision brain health monitoring platform will be iteratively adjusted and improved over time. The pragmatic study design enables multimodal digital phenotyping of distinct clinically characterized cohorts in both rural and urban U.S. settings.

The Accuracy of Commercially Available Fitness Trackers in Patients after Stroke

Background: Fitness trackers could represent an easy-to-use and cheap tool for continuous tracking of physical activity of stroke survivors during the period of their recovery at home. The aim of the study was to examine the accuracy of the Fitbit activity tracker in locomotor activity monitoring of stroke survivors with respect to gait disorders, walking speed, walking aid, and placement of the tracker on body. Methods: Twenty-four ambulatory stroke survivors (15 men and 9 women) with locomotion/gait disorder were involved in the study. Patients underwent two walking tests with the Fitbit Alta HR trackers attached on 5 different places on body. The accuracy of the trackers has been analyzed on 3 groups of patients-those walking without any walking aid, those using a single-point stick and those using a rolling walker. Results: For no-aid patients, the most accurate place was the waist. Patients with a single-point stick revealed the smallest deviations for a tracker attached to a healthy lower limb, and patients with a rolling walker revealed the smallest deviations for a tracker attached on the paretic lower limb. Conclusions: An accuracy comparable with the healthy population can be reached for all of the three groups of patients, while fulfilling the conditions for minimum speed of 2 km/h and optimal placement of the trackers with respect to a walking aid and aspect to impairment.

Mobile Health Intervention Promoting Physical Activity in Adults Post Cardiac Rehabilitation: Pilot Randomized Controlled Trial

Background

Cardiac rehabilitation (CR) is an exercise-based program prescribed after cardiac events associated with improved physical, mental, and social functioning; however, many patients return to a sedentary lifestyle leading to deteriorating functional capacity after discharge from CR. Physical activity (PA) is critical to avoid recurrence of cardiac events and mortality and maintain functional capacity. Leveraging mobile health (mHealth) strategies to increase adherence to PA is a promising approach. Based on the social cognitive theory, we sought to determine whether mHealth strategies (Movn mobile app for self-monitoring, supportive push-through messages, and wearable activity tracker) would improve PA and functional capacity over 2 months.

Objective

The objectives of this pilot randomized controlled trial were to examine preliminary effects of an mHealth intervention on group differences in PA and functional capacity and group differences in depression and self-efficacy to maintain exercise after CR.

Methods

During the final week of outpatient CR, patients were randomized 1:1 to the intervention group or usual care. The intervention group downloaded the Movn mobile app, received supportive push-through messages on motivation and educational messages related to cardiovascular disease (CVD) management 3 times per week, and wore a Charge 2 (Fitbit Inc) activity tracker to track step counts. Participants in the usual care group wore a pedometer and recorded their daily steps in a diary. Data from the 6-minute walk test (6MWT) and self-reported questionnaires were collected at baseline and 2 months.

Results

We recruited 60 patients from 2 CR sites at a community hospital in Northern California. The mean age was 68.0 (SD 9.3) years, and 23% (14/60) were female; retention rate was 85% (51/60). Our results from 51 patients who completed follow-up showed the intervention group had a statistically significant higher mean daily step count compared with the control (8860 vs 6633; P=.02). There was no difference between groups for the 6MWT, depression, or self-efficacy to maintain exercise.

Conclusions

This intervention addresses a major public health initiative to examine the potential for mobile health strategies to promote PA in patients with CVD. Our technology-based pilot mHealth intervention provides promising results on a pragmatic and contemporary approach to promote PA by increasing daily step counts after completing CR.

Trial Registration

ClinicalTrials.gov NCT03446313; https://clinicaltrials.gov/ct2/show/NCT03446313

Validity of the Polar Vantage M watch when measuring heart rate at different exercise intensities

BACKGROUND

The use of wrist worn wearable fitness trackers has been growing rapidly over the last decade. The growing popularity can be partly attributed to the improvements in technology, making activity trackers more affordable, comfortable and convenient for use in different fitness and environmental applications. Fitness trackers typically monitor activity level, track steps, distance, heart rate (HR), sleep, peripheral capillary oxygen saturation and more, as the technology continuously is advancing. In terms of measuring HR, photoplethysmography (PPG) is a relatively new technology utilised in wearables. PPG estimates HR through an optical technique that monitors changes in blood volume beneath the skin. With these new products becoming available it is important that the validity of these devices be evaluated. Therefore, the aim of this study was to assess the validity of the Polar Vantage M (PVM) watch to measure HR compared to medical grade ECG on a healthy population during a range of treadmill exercise intensities.

METHODS

A total of 30 healthy participants (n = 17 males, n = 13 females) were recruited for this study. The validity of the PVM watch to measure HR was compared against the gold standard 5-lead ECG. The study was conducted on 2 separate testing days with 24-48 h between sessions. Participants completed the Bruce Treadmill Protocol, and HR was measured every 30 s. Validation of the PVM watch in comparison to the ECG was measured with an Intraclass Correlation Coefficient (ICC) and associated 95% confidence intervals (CI) and levels of agreement were identified with Bland-Altman plots with 90% limits of agreement. Linear regression analysis was performed to calculate the value of r 2 computing the variation of HR obtained by the PVM watch and ECG.

RESULTS

In total, 30 participants completed the protocol, with data from 28 participants utilised for statistical analysis (16 males, 14 females, 26.10 ± 3.39 years, height 52.36 m ± 7.40 cm, mass 73.59 ± 11.90 kg). A strong and significant correlation was found between the PVM watch and ECG, demonstrating good criterion validity (p < 0.05, r 2 = 0.87). Good validity was seen for day 1 and day 2 for stage 0 (ICC = 0.83; 95% CI [0.63-0.92], ICC = 0.74; 95% CI [0.37-0.88]), stage 1 (ICC = 0.78; 95% CI [0.52-0.90], ICC = 0.88; 95% CI [0.74-0.95]), and stage 2 (ICC = 0.88; 95% CI [0.73-0.94], ICC = 0.80; 95% CI [0.40-0.92]). Poor validity was demonstrated on day 1 and day 2 for stages 3-5 (ICC < 0.50).

CONCLUSION

This study revealed that the PVM watch had a strong correlation with the ECG throughout the entire Bruce Protocol, however the level of agreement (LoA) becomes widely dispersed as exercise intensities increased. Due to the large LoA between the ECG and PVM watch, it is not advisable to use this device in clinical populations in which accurate HR measures are essential for patient safety; however, the watch maybe used in settings where less accurate HR is not critical to an individual's safety while exercising.

Monitoring the recovery time of children after tonsillectomy using commercial activity trackers

An observational prospective feasibility study in which children received a tracker 2 weeks before a tonsillectomy and were required to wear it until four weeks postoperatively. The parents used a diary to log the estimated steps of their child. As primary endpoint, the compliance of complete datasets was compared between the tracker and the diary. As secondary endpoints, the agreement of steps between tracker and diary, and the recovery time after tonsillectomy were analyzed.Twenty-four patients (50% male) with a median age of 6 years were recruited. The tracker had a complete dataset compliance of 91.7% in the pre-operative and 58.3% in postoperative period, whereas the diary's compliance was 62.5% in the pre-operative and 12.5% in the postoperative period. The difference of 29.2% and 45.8% in the pre-operative and postoperative periods between the tracker and the diary was significant (p < 0.005). The tracker and diary had a mean agreement difference of 1063 steps per day. Mean recovery time was 21 days after tonsillectomy.Conclusion: The results of this pilot study support the use of a tracker in terms of compliance and practicability. Consumer-level activity trackers are a viable alternative to conventional manual logging for clinical use in pediatric research.Trial registration: ClinicalTrials.gov Identifier: NCT03174496 What is known: • Consumer-level activity trackers are already used in clinical research to monitor steps and physical activity. • The use of consumer-level activity trackers in clinical studies has mostly been validated in the adult population. What is new: • This study proves the feasibility of using physical activity trackers in a pediatric population before and after a surgical intervention. • Recovery of a patient could be assessed with an activity tracker.

Patch validation: an observational study protocol for the evaluation of a multisignal wearable sensor in patients during anaesthesia and in the postanaesthesia care unit

INTRODUCTION

Except for operating rooms, postanaesthesia care units and intensive care units, where the monitoring of vital signs is continuous, intermittent care is standard practice. However, at a time when only the patients with the most serious conditions are hospitalised and only a fraction of these patients are in intensive care units, this type of monitoring is no longer sufficient. Wireless monitoring has been proposed, but it requires rigorous validation. The aim of this observational study is to compare vital signs obtained from a precordial patch sensor to those obtained with conventional monitoring.

METHODS AND ANALYSIS

This patch validation trial will be an observational, prospective, single-centre open study of 115 anaesthetised adult patients monitored with both a wireless sensor (myAngel VitalSigns, Devinnova, Montpellier, France) and a standard bedside monitor (Carescape Monitor B850, GE Healthcare, Chicago, Illinois). Both sensors will be used to record peripheral oxygen saturation, respiratory rate, heart rate, body temperature and blood pressure (systolic and diastolic). The main objective will be to assess the degree of agreement between the two systems during the patients' stay in the postanaesthesia care unit, both at the raw signal level and at the clinical parameter level. The secondary objectives will be to assess the same performance under anaesthesia, the frequency of missing data or artefacts, the diagnostic performance of the systems, the influence of patients' characteristics on agreement between the two systems, the adverse events and the acceptability of the patch to patients. Bland-Altman plots will be used in the main analysis to detect discrepancies and estimate the limits of agreement.

ETHICS AND DISSEMINATION

Ethics approval was obtained from the Ethical Committee (Toulouse, France) on 10 April 2020. We are not yet recruiting subjects for this study. The results will be submitted for publication in peer-reviewed journals.

TRIAL REGISTRATION NUMBER

NCT04344093.

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.

Wearable Activity Trackers in the Management of Rheumatic Diseases: Where Are We in 2020?

In healthcare, physical activity can be monitored in two ways: self-monitoring by the patient himself or external monitoring by health professionals. Regarding self-monitoring, wearable activity trackers allow automated passive data collection that educate and motivate patients. Wearing an activity tracker can improve walking time by around 1500 steps per day. However, there are concerns about measurement accuracy (e.g., lack of a common validation protocol or measurement discrepancies between different devices). For external monitoring, many innovative electronic tools are currently used in rheumatology to help support physician time management, to reduce the burden on clinic time, and to prioritize patients who may need further attention. In inflammatory arthritis, such as rheumatoid arthritis, regular monitoring of patients to detect disease flares improves outcomes. In a pilot study applying machine learning to activity tracker steps, we showed that physical activity was strongly linked to disease flares and that patterns of physical activity could be used to predict flares with great accuracy, with a sensitivity and specificity above 95%. Thus, automatic monitoring of steps may lead to improved disease control through potential early identification of disease flares. However, activity trackers have some limitations when applied to rheumatic patients, such as tracker adherence, lack of clarity on long-term effectiveness, or the potential multiplicity of trackers.

An Integrative Model for the Effectiveness of Biofeedback Interventions for Anxiety Regulation: Viewpoint

Biofeedback has shown to be a promising tool for the treatment of anxiety; however, several theoretical as well as practical limitations have prevented widespread adaptation until now. With current technological advances and the increasing interest in the use of self-monitoring technology to improve mental health, we argue that this is an ideal time to launch a new wave of biofeedback training. In this viewpoint paper, we reflect on the current state of biofeedback training, including the more traditional techniques and mechanisms that have been thought to explain the effectiveness of biofeedback such as the integration of operant learning and meditation techniques, and the changes in interoceptive awareness and physiology. Subsequently, we propose an integrative model that includes a set of cognitive appraisals as potential determinants of adaptive trajectories within biofeedback training such as growth mindset, self-efficacy, locus of control, and threat-challenge appraisals. Finally, we present a set of detailed guidelines based on the integration of our model with the mechanics and mechanisms offered by emerging interactive technology to encourage a new phase of research and implementation using biofeedback. There is a great deal of promise for future biofeedback interventions that harness the power of wearables and video games, and that adopt a user-centered approach to help people regulate their anxiety in a way that feels engaging, personal, and meaningful.

Efficacy of a Newly Modified Short Hydration Method for Gemcitabine and Cisplatin Combination Chemotherapy in Patients with Urothelial Carcinoma

INTRODUCTION

Conventional first-line chemotherapy for patients with metastatic urothelial carcinoma (UC) is gemcitabine and cisplatin (GC). However, cisplatin can cause renal failure, necessitating abundant fluid replacement and hospitalization during treatment. Recent evidence exists for short hydration methods in cisplatin-based chemotherapy.

OBJECTIVE

This study aims to analyze the efficacy of newly established modified short hydration GC (m-shGC) therapy in patients with UC.

METHODS

From May 2017 to March 2019, 48 patients with UC who received m-shGC therapy were treated with 1,000 mg/m2 gemcitabine on days 1, 8, and 15, and 70 mg/m2 cisplatin and 2,000 mL fluid replacement on day 1, in each 28-day cycle. We retrospectively evaluated renal function, serum electrolyte abnormalities, and adverse events (AEs) following treatment, and retrospectively compared patients under m-shGC therapy with those under conventional GC (c-GC) therapy from 2015 to 2017. In addition, from April 2019 to August 2019 in a prospective analysis, 15 patients were newly enrolled, and AE profiles and physical activity during m-shGC therapy were quantified using a wearable tracker.

RESULTS

In a retrospective analysis of 101 patients (53 c-GC and 48 m-shGC), patient characteristics were not statistically significant between the two groups. Myelosuppression, including predominant neutropenia and decreased platelets, fatigue, nausea, and constipation were the main common AEs. However, renal function and serum sodium levels in the m-shGC group remained unchanged. Grade 3-4 AEs were not more severe in the m-shGC compared with the c-GC group. Furthermore, in a prospective analysis using a wearable tracker, the amount of walking by patients on day 1 significantly declined. However, immediate recovery occurred reflecting the short hydration.

CONCLUSION

Our m-shGC therapy has an acceptable AE profile compared with conventional therapy, with UC patients showing good physical activity.

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.

Wearable devices for remote vital signs monitoring in the outpatient setting: an overview of the field

Early detection of physiological deterioration has been shown to improve patient outcomes. Due to recent improvements in technology, comprehensive outpatient vital signs monitoring is now possible. This is the first review to collate information on all wearable devices on the market for outpatient physiological monitoring.

A scoping review was undertaken. The monitors reviewed were limited to those that can function in the outpatient setting with minimal restrictions on the patient’s normal lifestyle, while measuring any or all of the vital signs: heart rate, ECG, oxygen saturation, respiration rate, blood pressure and temperature.

A total of 270 papers were included in the review. Thirty wearable monitors were examined: 6 patches, 3 clothing-based monitors, 4 chest straps, 2 upper arm bands and 15 wristbands. The monitoring of vital signs in the outpatient setting is a developing field with differing levels of evidence for each monitor. The most common clinical application was heart rate monitoring. Blood pressure and oxygen saturation measurements were the least common applications. There is a need for clinical validation studies in the outpatient setting to prove the potential of many of the monitors identified.

Research in this area is in its infancy. Future research should look at aggregating the results of validity and reliability and patient outcome studies for each monitor and between different devices. This would provide a more holistic overview of the potential for the clinical use of each device.

Variable agreement between wearable heart rate monitors during exercise in cystic fibrosis

In people with cystic fibrosis (CF), greater cardiorespiratory fitness is associated with improved survival and quality of life. Wearable activity monitors are a popular method of monitoring exercise, with measures of heart rate used to indicate exercise intensity. We assessed the agreement of heart rate recordings obtained using the Fitbit Charge HR^™, Polar® H7 heart rate sensor and Masimo SET® Rad-5v pulse oximeter with the three-lead ECG during continuous and interval exercise.

Adults with CF completed two exercise sessions, of 15-min duration per session, on a cycle ergometer while wearing the previously mentioned monitors. Firstly, participants cycled at 30% of estimated peak workload (W_peak). Secondly, participants cycled at 1-min intervals at 60% of W_peak interspersed with 2 min of unloaded cycling. Heart rate readings on all devices were recorded at minute intervals and their agreement was analysed using the Bland–Altman method.

The Polar® H7 heart rate sensor had the best agreement with three-lead ECG, with a bias of 0±1 bpm during both continuous and interval exercise. The Masimo SET® Rad-5v pulse oximeter had good agreement, with a bias of 1±7 bpm and 1±5 bpm during continuous and interval exercise, respectively. The Fitbit Charge HR^™ demonstrated less agreement, with a bias of 9±17 bpm and 5±13 bpm during continuous and interval exercise, respectively.

The Fitbit Charge HR^™ is not recommended for assessing heart rate during exercise in adults with CF. Findings support the use of the Polar® H7 for accurate heart rate monitoring.

The Fitbit Charge HR^™ does not provide accurate heart rate measurements during exercise in adults with cystic fibrosis. The Polar® H7 and Masimo SET® Rad-5v pulse oximeter do provide accurate measurements of heart rate.http://bit.ly/2KX0Yvy

Multi-Sensor-Fusion Approach for a Data-Science-Oriented Preventive Health Management System: Concept and Development of a Decentralized Data Collection Approach for Heterogeneous Data Sources

Investigations in preventive and occupational medicine are often based on the acquisition of data in the customer's daily routine. This requires convenient measurement solutions including physiological, psychological, physical, and sometimes emotional parameters. In this paper, the introduction of a decentralized multi-sensor-fusion approach for a preventive health-management system is described. The aim is the provision of a flexible mobile data-collection platform, which can be used in many different health-care related applications. Different heterogeneous data sources can be integrated and measured data are prepared and transferred to a superordinated data-science-oriented cloud-solution. The presented novel approach focuses on the integration and fusion of different mobile data sources on a mobile data collection system (mDCS). This includes directly coupled wireless sensor devices, indirectly coupled devices offering the datasets via vendor-specific cloud solutions (as e.g., Fitbit, San Francisco, USA and Nokia, Espoo, Finland) and questionnaires to acquire subjective and objective parameters. The mDCS functions as a user-specific interface adapter and data concentrator decentralized from a data-science-oriented processing cloud. A low-level data fusion in the mDCS includes the synchronization of the data sources, the individual selection of required data sets and the execution of pre-processing procedures. Thus, the mDCS increases the availability of the processing cloud and in consequence also of the higher level data-fusion procedures. The developed system can be easily adapted to changing health-care applications by using different sensor combinations. The complex processing for data analysis can be supported and intervention measures can be provided.

Quantifying Activity Levels After Sport-Related Concussion Using Actigraph and Mobile (mHealth) Technologies

CONTEXT

Interest in identifying the effects of physical and mental activity on recovery after sport-related concussion is growing. Clinical studies of concussed athletes' activities require well-validated methods for tracking their intensity and timing.

OBJECTIVE

To develop and validate a novel multimodal approach to monitoring activity postconcussion using mobile (mHealth) technologies.

DESIGN

Cohort study.

SETTING

Translational research unit.

PATIENTS OR OTHER PARTICIPANTS

A total of 40 high school and collegiate football players were evaluated at preseason and followed longitudinally after either concussion (n = 25; age = 17.88 ± 1.74 years, height = 182.07 ± 8.08 cm, mass = 98.36 ± 21.70 kg) or selection as a nonconcussed control (n = 15; age = 18.27 ± 1.83 years, height = 180.01 ± 7.19 cm, mass = 93.83 ± 24.56 kg).

MAIN OUTCOME MEASURE(S)

Participants wore a commercial actigraph and completed a daily mobile survey for 2 weeks. Analyses focused on comparisons between groups for actigraph-based physical activity and self-reported physical and mental activity during the follow-up period.

RESULTS

For the first 2 days postinjury, objective measures showed fewer daily steps in concussed (6663 ± 2667 steps) than in control (11 148 ± 3381 steps) athletes (P < .001), and both objective and self-reported measures indicated less moderate to vigorous physical activity in concussed (27.6 ± 32.6 min/d and 25.0 ± 43.6 min/d, respectively) than in control (57.3 ± 38.6 min/d and 67.5 ± 40.1 min/d, respectively) athletes (both P values < .05). Correlations between objective and self-reported measures of moderate to vigorous physical activity were moderate across select 1-week and 2-week averages. We observed no group differences in self-reported mental activities.

CONCLUSIONS

Physical activity after sport-related concussion varied widely across athletes but on average was reduced during the acute and early subacute postinjury periods for both objective and self-reported measures. The lack of differences in mental activities between groups may reflect limited change in mental exertion postconcussion or difficulty accurately measuring mental activities. Assessing concussed athletes' activities using actigraphy and self-reported scales may help monitor their compliance with activity recommendations and be useful in studies aimed at better understanding the effects of physical activity on concussion recovery.

Measuring Free-Living Physical Activity With Three Commercially Available Activity Monitors for Telemonitoring Purposes: Validation Study

Background

Remote monitoring of physical activity in patients with chronic conditions could be useful to offer care professionals real-time assessment of their patient’s daily activity pattern to adjust appropriate treatment. However, the validity of commercially available activity trackers that can be used for telemonitoring purposes is limited.

Objective

The purpose of this study was to test usability and determine the validity of 3 consumer-level activity trackers as a measure of free-living activity.

Methods

A usability evaluation (study 1) and validation study (study 2) were conducted. In study 1, 10 individuals wore one activity tracker for a period of 30 days and filled in a questionnaire on ease of use and wearability. In study 2, we validated three selected activity trackers (Apple Watch, Misfit Shine, and iHealth Edge) and a fourth pedometer (Yamax Digiwalker) against the reference standard (Actigraph GT3X) in 30 healthy participants for 72 hours. Outcome measures were 95% limits of agreement (LoA) and bias (Bland-Altman analysis). Furthermore, median absolute differences (MAD) were calculated. Correction for bias was estimated and validated using leave-one-out cross validation.

Results

Usability evaluation of study 1 showed that iHealth Edge and Apple Watch were more comfortable to wear as compared with the Misfit Flash. Therefore, the Misfit Flash was replaced by Misfit Shine in study 2. During study 2, the total number of steps of the reference standard was 21,527 (interquartile range, IQR 17,475-24,809). Bias and LoA for number of steps from the Apple Watch and iHealth Edge were 968 (IQR −5478 to 7414) and 2021 (IQR −4994 to 9036) steps. For Misfit Shine and Yamax Digiwalker, bias was −1874 and 2004, both with wide LoA of (13,869 to 10,121) and (−10,932 to 14,940) steps, respectively. The Apple Watch noted the smallest MAD of 7.7% with the Actigraph, whereas the Yamax Digiwalker noted the highest MAD (20.3%). After leave-one-out cross validation, accuracy estimates of MAD of the iHealth Edge and Misfit Shine were within acceptable limits with 10.7% and 11.3%, respectively.

Conclusions

Overall, the Apple Watch and iHealth Edge were positively evaluated after wearing. Validity varied widely between devices, with the Apple Watch being the most accurate and Yamax Digiwalker the least accurate for step count in free-living conditions. The iHealth Edge underestimates number of steps but can be considered reliable for activity monitoring after correction for bias. Misfit Shine overestimated number of steps and cannot be considered suitable for step count because of the low agreement. Future studies should focus on the added value of remotely monitoring activity patterns over time in chronic patients.

Version Reporting and Assessment Approaches for New and Updated Activity and Heart Rate Monitors

This paper addresses the significant need for improvements in device version reporting and practice across the academic and technical activity monitoring literature, and it recommends assessments for new and updated consumer sensing devices. Reproducibility and data veracity are central to good scholarship, and particularly significant in clinical and health applications. Across the literature there is an absence of device version reporting and a failure to recognize that device validity is not maintained when firmware and software updates can, and do, change device performance and parameter estimation. In this paper, we propose the use of tractable methods to assess devices at their current version and provide an example empirical approach. Experimental results for heart rate and step count acquisitions during walking and everyday living activities from Garmin Vivosmart 3 (v4.10) wristband monitors are presented and analyzed, and the reliability issues of optically-acquired heart rates, especially during periods of activity, are demonstrated and discussed. In conclusion, the paper recommends the empirical assessment of new and updated activity monitors and improvements in device version reporting across the academic and technical literature.

Objective evaluation of physical activity pattern using smart devices

Physical activity session frequency and distribution over time may play a significant role on survival after major cardiovascular events. However, the existing amount-based metrics do not account for these properties, thus the physical activity pattern is not fully evaluated. The aim of this work is to introduce a metric which accounts for the difference between the actual and uniform distribution of physical activity, thus its value depends on physical activity aggregation over time. The practical application is demonstrated on a step data from 40 participants, half of them diagnosed with chronic cardiovascular disease (CVD). The metric is capable of discriminating among different daily patterns, including going to and from work, walking in a park and being active the entire day. Moreover, the results demonstrate the tendency of CVD patients being associated with higher aggregation values, suggesting that CVD patients spend more time in a sedentary behaviour compared to healthy participants. By combining the aggregation with the intensity metric, such common weekly patterns as inactivity, regular activity and "weekend warrior" can be captured. The metric is expected to have clinical relevance since it may provide additional information on the relationship between physical activity pattern and health outcomes.

Assessment of Physical Activity by Wearable Technology During Rehabilitation After Cardiac Surgery: Explorative Prospective Monocentric Observational Cohort Study

Background

Wearable technology is finding its way into clinical practice. Physical activity describes patients’ functional status after cardiac surgery and can be monitored remotely by using dedicated trackers.

Objective

The aim of this study was to compare the progress of physical activity in cardiac rehabilitation by using wearable fitness trackers in patients undergoing coronary artery bypass surgery by either the conventional off-pump coronary artery bypass (OPCAB) or the robotically assisted minimally invasive coronary artery bypass (RA-MIDCAB). We hypothesized faster recovery of physical activity after RA-MIDCAB in the first weeks after discharge as compared to OPCAB.

Methods

Patients undergoing RA-MIDCAB or OPCAB were included in the study. Each patient received a Fitbit Charge HR (Fitbit Inc, San Francisco, CA) physical activity tracker following discharge. Rehabilitation progress was assessed by measuring the number of steps and physical activity level daily. The physical activity level was calculated as energy expenditure divided by the basic metabolic rate.

Results

A total of 10 RA-MIDCAB patients with a median age of 68 (min, 55; max, 83) years and 12 OPCAB patients with a median age of 69 (min, 50; max, 82) years were included. Baseline characteristics were comparable except for body mass index (RA-MIDCAB: 26 kg/m²; min, 22; max, 28 versus OPCAB: 29 kg/m²; min, 27; max, 33; P<.001). Intubation time (P<.05) was significantly lower in the RA-MIDCAB group. A clear trend, although not statistically significant, was observed towards a higher number of steps in RA-MIDCAB patients in the first week following discharge.

Conclusions

RA-MIDCAB patients have an advantage in recovery in the first weeks of revalidation, which is reflected by the number of steps and physical activity level measured by the Fitbit Charge HR, as compared to OPCAB patients. However, unsupervised assessment of daily physical activity varied widely and could have consequences with regard to the use of these trackers as research tools.

Listening to the patients: using participatory design in the development of a cardiac telerehabilitation web portal

BACKGROUND

Cardiovascular disease is the leading cause of all deaths worldwide. Cardiac rehabilitation is an effective approach for preventing secondary complications, but it remains a complex intervention because of the need for lifestyle changes. One solution is to employ interactive telerehabilitation or eHealth web portals. However, these have not been implemented as intended by developers. The aim of this study was to evaluate the design and usability of a cardiac telerehabilitation web portal, called the 'HeartPortal', for use among heart failure (HF) patients.

METHODS

The HeartPortal was designed using participatory design (PD). The design process involved HF patients, their relatives, healthcare professionals (HCP), healthcare company specialists and researchers. Self-determination theory (SDT) was used to enable the design to elicit intrinsic motivation within the patients. With eHealth literacy skills in mind, the goal of the HeartPortal was to successfully target the end-users. The PD process and data collection techniques included cultural probes, workshops, participant-observation, questionnaires, and problem-solving tasks.

RESULTS

The PD process helped us design an interactive web portal, the HeartPortal. Based on participants' feedback, the design incorporated features such as being able to make notes and to communicate with HCP, view data from self-tracking devices in a graphic form, and to obtain information on rehabilitation in the form of text, audio, and video. More than half of those testing the HeartPortal found that it was easy to navigate, and most of the users stated that it had an excellent structure and that using it could possibly improve their condition.

CONCLUSIONS

Overall, the HeartPortal was found to be logical and easy to navigate and will now be tested in a clinical trial within the Future Patient Telerehabilitation Program.

Patient Perspectives on Health Data Privacy and Management: "Where Is My Data and Whose Is It?"

New technologies are increasingly evaluated for use within the clinical practice to monitor patients' medical and lifestyle data. This development could contribute to a more personalized approach to patient care and potentially improve health outcomes. To date, patient perspective on this development has mostly been neglected in the literature. Hence, this study aims to shed more light on the patient perspective on health data privacy and management. Focus groups with cardiac patients were done at the Elizabeth TweeSteden Ziekenhuis (ETZ) in the Netherlands as part of the DoCHANGE project. The focus groups were conducted using a semistructured protocol which was organized around three themes: privacy regulations, data storage, and transparency and privacy management. Five focus groups with a total of 23 patients were conducted. The majority of the patients preferred to have access to their medical data; however, the knowledge on who has access to data was limited. Patients indicated that they do not want to share their medical data with health insurance companies or the pharmaceutical industry. Furthermore, most patients do not see the added value of supplementing their medical dossier with lifestyle data. Current findings showed patients prefer access to and control over own data but that the knowledge concerning data privacy and management is limited. Sharing of non-medical health data (e.g.,, physical activity) was considered unnecessary. Future studies should address patient preferences and develop infrastructure which facilitates medical data access for patients.

Wearables and the medical revolution

Wearable sensors are already impacting healthcare and medicine by enabling health monitoring outside of the clinic and prediction of health events. This paper reviews current and prospective wearable technologies and their progress toward clinical application. We describe technologies underlying common, commercially available wearable sensors and early-stage devices and outline research, when available, to support the use of these devices in healthcare. We cover applications in the following health areas: metabolic, cardiovascular and gastrointestinal monitoring; sleep, neurology, movement disorders and mental health; maternal, pre- and neo-natal care; and pulmonary health and environmental exposures. Finally, we discuss challenges associated with the adoption of wearable sensors in the current healthcare ecosystem and discuss areas for future research and development.

Reliability and validity of two fitness tracker devices in the laboratory and home environment for older community-dwelling people

Background

Two-thirds of older Australians are sedentary. Fitness trackers have been popular with younger people and may encourage older adults to become more active. Older adults may have different gait patterns and as such it is important to establish whether fitness trackers are valid and reliable for this population.

The aim of the study was to test the reliability and validity of two fitness trackers (Fitbit Flex and ChargeHR) by step count when worn by older adults. Reliability and validity were tested in two conditions: 1) in the laboratory using a two-minute-walk-test (2MWT) and 2) in a free-living environment.

Methods

Two 2MWTs were completed while wearing the fitness trackers. Participants were videoed during each test. Participants were then given one fitness tracker and a GENEactiv accelerometer to wear at home for 14-days.

Results

Thirty-one participants completed two 2MWTs and 30 completed the free-living procedure. Intra Class Correlation’s of the fitness trackers with direct observation of steps (criterion validity) was high (ICC:0.86,95%CI:0.76,0.93). However, both fitness trackers underestimated steps. Excellent test-retest reliability (ICC ≥ 0.75) was found between the two 2MWTs for each device, particularly the ChargeHR devices. Good strength of agreement was found for total distance and steps (fitness tracker) and moderate-to-vigorous physical activity (GENEactiv) for the free-living environment (Spearman Rho’s 0.78 and 0.74 respectively).

Conclusion

Reliability and validity of the Flex and ChargeHR when worn by older adults is good, however both devices underestimated step count within the laboratory environment. These fitness trackers appear suitable for consumer use and promoting physical activity for older adults.

Implementing Wearable Sensors for Continuous Assessment of Daytime Heart Rate Response in Inpatient Rehabilitation

BACKGROUND

It is unclear whether wearable heart rate (HR) sensors can be worn continuously in inpatient rehabilitation to assess cardiorespiratory training response. If feasible, these sensors offer a low-cost low-maintenance method for assessing HR response in this setting. We determined feasibility of wearable sensors for assessing HR response to daytime therapy activities in inpatient rehabilitation within a cardiorespiratory training zone equal to 55-80% of maximal HR (target HR [THR]) for at least two 10-min bouts, 3-5 days per week. Secondarily, we determined episodes of excessive HR (EHR >80% of maximal HR).

MATERIALS AND METHODS

Subjects 44-80 years of age with diagnoses of stroke, cardiac disorders, orthopedic disorders, medically complex conditions, or pulmonary disorders wore wrist-mounted HR sensors day and night throughout inpatient rehabilitation. The proportion of subjects meeting THR thresholds and experiencing EHR episodes was quantified. Multiple regression predicted THR and EHR outcomes from age, sex, length of stay, and motor function at admission and discharge.

RESULTS

Across subjects, 97,800 min of HR data were analyzed. Sixty percent of subjects met THR thresholds for cardiorespiratory benefit. Age was the single significant predictor of percent of days meeting the THR threshold (R = 0.58, p = 0.024). Forty-seven percent of subjects experienced EHR episodes on at least 1 day. No subjects experienced sensor-related adverse events, and no protocol deviations occurred from inadvertent sensor removal.

CONCLUSIONS

Most subjects experienced HR increases sufficient to obtain cardiorespiratory benefit. Likewise, most subjects had episodes of EHR. Wearable sensors were feasible for continuously assessing HR response, suggesting expanded opportunity in inpatient rehabilitation research and treatment.

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

Background

New fitness trackers and smartwatches are released to the consumer market every year. These devices are equipped with different sensors, algorithms, and accompanying mobile apps. With recent advances in mobile sensor technology, privately collected physical activity data can be used as an addition to existing methods for health data collection in research. Furthermore, data collected from these devices have possible applications in patient diagnostics and treatment. With an increasing number of diverse brands, there is a need for an overview of device sensor support, as well as device applicability in research projects.

Objective

The objective of this study was to examine the availability of wrist-worn fitness wearables and analyze availability of relevant fitness sensors from 2011 to 2017. Furthermore, the study was designed to assess brand usage in research projects, compare common brands in terms of developer access to collected health data, and features to consider when deciding which brand to use in future research.

Methods

We searched for devices and brand names in six wearable device databases. For each brand, we identified additional devices on official brand websites. The search was limited to wrist-worn fitness wearables with accelerometers, for which we mapped brand, release year, and supported sensors relevant for fitness tracking. In addition, we conducted a Medical Literature Analysis and Retrieval System Online (MEDLINE) and ClinicalTrials search to determine brand usage in research projects. Finally, we investigated developer accessibility to the health data collected by identified brands.

Results

We identified 423 unique devices from 132 different brands. Forty-seven percent of brands released only one device. Introduction of new brands peaked in 2014, and the highest number of new devices was introduced in 2015. Sensor support increased every year, and in addition to the accelerometer, a photoplethysmograph, for estimating heart rate, was the most common sensor. Out of the brands currently available, the five most often used in research projects are Fitbit, Garmin, Misfit, Apple, and Polar. Fitbit is used in twice as many validation studies as any other brands and is registered in ClinicalTrials studies 10 times as often as other brands.

Conclusions

The wearable landscape is in constant change. New devices and brands are released every year, promising improved measurements and user experience. At the same time, other brands disappear from the consumer market for various reasons. Advances in device quality offer new opportunities for research. However, only a few well-established brands are frequently used in research projects, and even less are thoroughly validated.

Validity and Reliability Evaluation of Four Commercial Activity Trackers' Step Counting Performance

INTRODUCTION

Activity trackers are useful tools for physical rehabilitation purposes. Most available activity trackers are designed for fitness and wellness use, lacking in both accuracy and precision at lower speeds. Validity and reliability at all clinically relevant speeds are crucial selection criteria for use in clinical practice. The aim of this study was to assess the validity and reliability of four consumer-based activity trackers at clinical relevant walking speeds for patient groups undergoing rehabilitation.

METHODS

The four commercial activity trackers Fitbit Surge (FS), Fitbit Charge HR (FC), Microsoft Band 2 (MB), and A&D 101NFC Activity Monitor (A&D) were evaluated at 2, 4, 4.5, and 5.5 km/h. Twenty healthy participants aged 25.6 ± 2 years walked on a treadmill at the four velocities in two trials of 100 steps each. Mean average percentage error (MAPE), intraclass correlation coefficient (ICC), and Bland-Altman 95% limits of agreement were calculated to assess validity and reliability.

RESULTS

MAPE levels were between -8% and -6% for FS, -15% and 0% for MB, 7% and 21% for FC, and -53% and 1% for AD. The biggest inaccuracies were seen at 2 km/h, where AD underestimated by 53%. The highest accuracy was predominantly found with MB and AD, which overestimated ≤2% at velocities ≥4 km/h. ICC was moderate (0.73) for FS, good (0.88) for MB, moderate (0.52) for FC, and excellent (0.98) for AD.

CONCLUSIONS

MB, FS, and AD accurately counted steps, when participants walked with velocities corresponding to a brisk walk (≥4 km/h). Walking at lower speeds (≤2 km/h) was not counted accurately. Thus, the four evaluated activity trackers are not useful for patient groups walking at lower speeds during rehabilitation, nor for counting indoor walking.

Healthy Parks Healthy People as an Upstream Stress Reduction Strategy

One of the primary goals of the Healthy Parks Healthy People (HPHP) program, located in the San Francisco Bay Area, is to offer group-based physical activities in natural settings. These activities arefor racially and ethnically diverse groups of individuals as an "upstream" strategy for improving health. This study investigated the health impact of selected two-hour HPHP Bay Area events that targeted low-income racial and ethnic minority groups using physiological and self-reported measures of stress and related variables. Study participants (N=52) in the selected HPHP Bay Area events donated saliva and filled out psychological measures of perceived stress (PSS-4; Cohen et al.) and mood state (I-PANAS-SF; Thompson, 2007) at the beginning and the end ofa two-hour guided walk in green spaces. Moreover, a measure of perceived restoration (SRRS; Han, 2007) was completed at the end ofthe walk. Study participants wore a physical activity self-monitoring device (Garmin Vivofit 2) to capture their step count and heart rate during the event. Stress, both measured by the analysis of salivary cortisol and self-reported perceived stress, significantly decreased over the course of the event (p<.0$) and there was a significant increase in positive mood (p<.05). The monitoring device also indicated that individuals were engaged in moderate levels of physical activity during the guided walks (<di>x</di> =8,990 steps, HR 95 bpm). The results encourage further development of nature-based health interventions to mitigate stress. Such interventions may be especially appropriate for low-income, urban, racial and ethnic minority groups that likely experience increased levels of stress due to social inequities and poor living conditions.

Noise Maps for Quantitative and Clinical Severity Towards Long-Term ECG Monitoring

Noise and artifacts are inherent contaminating components and are particularly present in Holter electrocardiogram (ECG) monitoring. The presence of noise is even more significant in long-term monitoring (LTM) recordings, as these are collected for several days in patients following their daily activities; hence, strong artifact components can temporarily impair the clinical measurements from the LTM recordings. Traditionally, the noise presence has been dealt with as a problem of non-desirable component removal by means of several quantitative signal metrics such as the signal-to-noise ratio (SNR), but current systems do not provide any information about the true impact of noise on the ECG clinical evaluation. As a first step towards an alternative to classical approaches, this work assesses the ECG quality under the assumption that an ECG has good quality when it is clinically interpretable. Therefore, our hypotheses are that it is possible (a) to create a clinical severity score for the effect of the noise on the ECG, (b) to characterize its consistency in terms of its temporal and statistical distribution, and (c) to use it for signal quality evaluation in LTM scenarios. For this purpose, a database of external event recorder (EER) signals is assembled and labeled from a clinical point of view for its use as the gold standard of noise severity categorization. These devices are assumed to capture those signal segments more prone to be corrupted with noise during long-term periods. Then, the ECG noise is characterized through the comparison of these clinical severity criteria with conventional quantitative metrics taken from traditional noise-removal approaches, and noise maps are proposed as a novel representation tool to achieve this comparison. Our results showed that neither of the benchmarked quantitative noise measurement criteria represent an accurate enough estimation of the clinical severity of the noise. A case study of long-term ECG is reported, showing the statistical and temporal correspondences and properties with respect to EER signals used to create the gold standard for clinical noise. The proposed noise maps, together with the statistical consistency of the characterization of the noise clinical severity, paves the way towards forthcoming systems providing us with noise maps of the noise clinical severity, allowing the user to process different ECG segments with different techniques and in terms of different measured clinical parameters.

Fitbit Charge HR Wireless Heart Rate Monitor: Validation Study Conducted Under Free-Living Conditions

Background

Many modern smart watches and activity trackers feature an optical sensor that estimates the wearer’s heart rate. Recent studies have evaluated the performance of these consumer devices in the laboratory.

Objective

The objective of our study was to examine the accuracy and sensitivity of a common wrist-worn tracker device in measuring heart rates and detecting 1-min bouts of moderate to vigorous physical activity (MVPA) under free-living conditions.

Methods

Ten healthy volunteers were recruited from a large university in Singapore to participate in a limited field test, followed by a month of continuous data collection. During the field test, each participant would wear one Fitbit Charge HR activity tracker and one Polar H6 heart rate monitor. Fitbit measures were accessed at 1-min intervals, while Polar readings were available for 10-s intervals. We derived intraclass correlation coefficients (ICCs) for individual participants comparing heart rate estimates. We applied Centers for Disease Control and Prevention heart rate zone cut-offs to ascertain the sensitivity and specificity of Fitbit in identifying 1-min epochs falling into MVPA heart rate zone.

Results

We collected paired heart rate data for 2509 1-min epochs in 10 individuals under free-living conditions of 3 to 6 hours. The overall ICC comparing 1-min Fitbit measures with average 10-s Polar H6 measures for the same epoch was .83 (95% CI .63-.91). On average, the Fitbit tracker underestimated heart rate measures by −5.96 bpm (standard error, SE=0.18). At the low intensity heart rate zone, the underestimate was smaller at −4.22 bpm (SE=0.15). This underestimate grew to −16.2 bpm (SE=0.74) in the MVPA heart rate zone. Fitbit devices detected 52.9% (192/363) of MVPA heart rate zone epochs correctly. Positive and negative predictive values were 86.1% (192/223) and 92.52% (2115/2286), respectively. During subsequent 1 month of continuous data collection (270 person-days), only 3.9% of 1-min epochs could be categorized as MVPA according to heart rate zones. This measure was affected by decreasing wear time and adherence over the period of follow-up.

Conclusions

Under free-living conditions, Fitbit trackers are affected by significant systematic errors. Improvements in tracker accuracy and sensitivity when measuring MVPA are required before they can be considered for use in the context of exercise prescription to promote better health.

Analyzing Sensor-Based Time Series Data to Track Changes in Physical Activity during Inpatient Rehabilitation

Time series data collected from sensors can be analyzed to monitor changes in physical activity as an individual makes a substantial lifestyle change, such as recovering from an injury or illness. In an inpatient rehabilitation setting, approaches to detect and explain changes in longitudinal physical activity data collected from wearable sensors can provide value as a monitoring, research, and motivating tool. We adapt and expand our Physical Activity Change Detection (PACD) approach to analyze changes in patient activity in such a setting. We use Fitbit Charge Heart Rate devices with two separate populations to continuously record data to evaluate PACD, nine participants in a hospitalized inpatient rehabilitation group and eight in a healthy control group. We apply PACD to minute-by-minute Fitbit data to quantify changes within and between the groups. The inpatient rehabilitation group exhibited greater variability in change throughout inpatient rehabilitation for both step count and heart rate, with the greatest change occurring at the end of the inpatient hospital stay, which exceeded day-to-day changes of the control group. Our additions to PACD support effective change analysis of wearable sensor data collected in an inpatient rehabilitation setting and provide insight to patients, clinicians, and researchers.

Validation of a Self-Monitoring Tool for Use in Exercise Therapy

BACKGROUND

Aerobic exercise at a subsymptom heart rate has been recommended as therapy for postconcussion syndrome. Assessing adherence with an accurate heart rate-monitoring instrument is difficult, limiting the proliferation of large-scale randomized controlled trials.

OBJECTIVE

To evaluate the validity of the Fitbit Charge HR compared with electrocardiogram (EKG) to monitor heart rate during a treadmill-based exercise protocol.

DESIGN

A methods comparison study.

SETTING

Sports medicine research center within a tertiary care institution.

PARTICIPANTS

A convenience sample of 22 healthy participants (12 female) aged 18-26 years (mean age: 22 ± 2 years).

METHODS

Fitbit Charge HR heart rate measurements were compared with EKG data concurrently collected while participants completed the Buffalo Concussion Treadmill Test.

MAIN OUTCOME MEASURES

Agreement between Fitbit Charge HR and EKG was assessed by intraclass correlation coefficients (ICC_3,1), Bland-Altman limits of agreement, and percent error.

RESULTS

We observed a strong single-measure absolute agreement between Fitbit Charge HR and EKG (intraclass correlation coefficient = 0.83; 95% confidence interval 0.67-0.90). Fitbit Charge HR underestimated heart rate compared with EKG (mean difference = -6.04 bpm; standard deviation = 10.40 bpm; Bland-Altman 95% limits of agreement = -26.42 to 14.35 bpm). A total of 69.9% of Fitbit heart rate measurements were within 10% error compared with EKG, and 91.5% of all heart rate measurements were within 20% error.

CONCLUSIONS

Although the mean bias in measuring heart rate was relatively small, the limits of agreement between the Fitbit Charge HR and EKG were broad. Thus, the Fitbit Charge HR would not be a suitable option for monitoring heart rate within a narrow range. For the purposes of postconcussion exercise therapy, the relatively inexpensive cost, easy implementation, and low maintenance make Fitbit Charge HR a viable option for assessing adherence to an exercise program when expensive clinical equipment is unavailable.

LEVEL OF EVIDENCE

II.

Wearables for independent living in older adults: Gait and falls

Solutions are needed to satisfy care demands of older adults to live independently. Wearable technology (wearables) is one approach that offers a viable means for ubiquitous, sustainable and scalable monitoring of the health of older adults in habitual free-living environments. Gait has been presented as a relevant (bio)marker in ageing and pathological studies, with objective assessment achievable by inertial-based wearables. Commercial wearables have struggled to provide accurate analytics and have been limited by non-clinically oriented gait outcomes. Moreover, some research-grade wearables also fail to provide transparent functionality due to limitations in proprietary software. Innovation within this field is often sporadic, with large heterogeneity of wearable types and algorithms for gait outcomes leading to a lack of pragmatic use. This review provides a summary of the recent literature on gait assessment through the use of wearables, focusing on the need for an algorithm fusion approach to measurement, culminating in the ability to better detect and classify falls. A brief presentation of wearables in one pathological group is presented, identifying appropriate work for researchers in other cohorts to utilise. Suggestions for how this domain needs to progress are also summarised.