Accuracy of wearable physical activity trackers in people with Parkinson's disease

A Comprehensive Review of Behavior Change Techniques in Wearables and IoT: Implications for Health and Well-Being

This research paper delves into the effectiveness and impact of behavior change techniques fostered by information technologies, particularly wearables and Internet of Things (IoT) devices, within the realms of engineering and computer science. By conducting a comprehensive review of the relevant literature sourced from the Scopus database, this study aims to elucidate the mechanisms and strategies employed by these technologies to facilitate behavior change and their potential benefits to individuals and society. Through statistical measurements and related works, our work explores the trends over a span of two decades, from 2000 to 2023, to understand the evolving landscape of behavior change techniques in wearable and IoT technologies. A specific focus is placed on a case study examining the application of behavior change techniques (BCTs) for monitoring vital signs using wearables, underscoring the relevance and urgency of further investigation in this critical intersection of technology and human behavior. The findings shed light on the promising role of wearables and IoT devices for promoting positive behavior modifications and improving individuals' overall well-being and highlighting the need for continued research and development in this area to harness the full potential of technology for societal benefit.

Validation of ActiGraph and Fitbit in the assessment of energy expenditure in Huntington's disease

BACKGROUND

Consumer and research activity monitors have become popular because of their ability to quantify energy expenditure (EE) in free-living conditions. However, the accuracy of activity trackers in determining EE in people with Huntington's Disease (HD) is unknown.

RESEARCH QUESTION

Can the ActiGraph wGT3X-B or the Fitbit Charge 4 accurately measure energy expenditure during physical activity, in people with HD compared to Indirect Calorimetry (IC) (Medisoft Ergo Card)?

METHODS

We conducted a cross-sectional, observational study with fourteen participants with mild-moderate HD (mean age 55.7 ± 11.4 years). All participants wore an ActiGraph and Fitbit during an incremental test, running on a treadmill at 3.2 km/h and 5.2 km/h for three minutes at each speed. We analysed and compared the accuracy of EE estimates obtained by Fitbit and ActiGraph against the EE estimates obtained by a metabolic cart, using with Intra-class correlation (ICC), Bland-Altman analysis and correlation tests.

RESULTS

A significant correlation and a moderate reliability was found between ActiGraph and IC for the incremental test (r = 0.667)(ICC=0.633). There was a significant correlation between Fitbit and IC during the incremental test (r = 0.701), but the reliability was poor at all tested speeds in the treadmill walk. Fitbit significantly overestimated EE, and ActiGraph underestimated EE compared to IC, but ActiGraph estimates were more accurate than Fitbit in all tests.

SIGNIFICANCE

Compared to IC, Fitbit Charge 4 and ActiGraph wGT3X-BT have reduced accuracy in estimating EE at slower walking speeds. These findings highlight the need for population-specific algorithms and validation of activity trackers.

The PRO-HOME Project. A multicomponent intervention for the protected discharge from the hospital of multimorbid and polytreated older individuals by using innovative technologies: A pilot study

BACKGROUD

Discharge planning from the hospital of frail older patients is an important step to avoid inappropriate long-stay hospitalizations and to prevent the risks related to the prolonged hospitalization. In this frame, we developed an experimental trial-'PRO-HOME', a multicomponent programme of interventions for multimorbid and polytreated hospitalized older patients.

AIM

The main aim of the study was to develop a protected discharge facility using a mini apartment equipped with advanced architectural and technological components to reduce the length of hospital stay of older participants (aged 65+ years old) admitted to the hospital for an acute event, deemed stable and dischargeable.

MATERIALS AND METHODS

This is a pilot randomized controlled study, comparing 30 hospitalized participants included in a multidimensional, transitional care programme based on information and communication technologies to 30 patients in standard usual care until hospital discharge.

RESULTS

We presented the study design of the PRO-HOME programme, including architectural and technological components, the enrolment procedures, the components of the intervention that is physical activity, cognitive training and life-style education and the evaluation method of the intervention based on the Comprehensive Geriatric Assessment to explore the changes in the individual domains that are target of the multicomponent intervention.

CONCLUSIONS

The final results will suggest whether the PRO-HOME programme represents a useful and feasible intervention to reduce the length of hospital stay of multimorbid and polytreated hospitalized older patients and improve their physical and cognitive performances and overall quality of life.

PATIENT OR PUBLIC CONTRIBUTION

Due to the characteristics of the population of interest of the PRO-HOME study, we involved in the study design and programme of the activities the participants enrolled in a previous smart home-based project named MoDiPro carried-out during a 3-year period. The elderly participants from the local population involved were asked, by means of focus groups, for feedback on their experience in MoDiPro, and their suggestions were integrated into the design phase of the current PRO-HOME project. The focus groups included open group interviews with a qualitative collection of the patients' feedback so that the participants could interact with each other.

A physiotherapy group exercise and self-management approach to improve physical activity in people with mild-moderate Parkinson's disease: a randomized controlled trial

BACKGROUND

Physical activity levels are low in people with Parkinson's disease (PD) and have proved difficult to increase with exercise programs alone. Intervention approaches that address both the capacity to engage in physical activity and self-management strategies to change and maintain exercise behaviours are needed to address this intractable issue.

METHODS

This will be an assessor-blinded, randomized controlled trial performed in Brisbane, Australia. Ninety-two people with mild-moderate PD will be randomly allocated to two groups: usual care, and a physiotherapy-led group exercise program combined with self-management strategies. In the intervention group, twelve, 80-min sessions will be conducted over 4 weeks in groups of up to 4 participants. The intervention will consist of circuit training including treadmill walking to target aerobic fitness, and activities targeting strength, balance, and gait performance. In addition, each session will also incorporate strategies focusing on self-management and behaviour change, augmented by the provision of a fitness activity tracker. Outcome measures will be collected at baseline (T1), immediately post intervention (T2) and at 6 months follow-up (T3). The primary outcome measure is free-living physical activity (average daily step count over 7 days) at pre (T1) and post (T2) intervention measured using an activPAL™ device. Secondary outcome measures captured at all time points include time spent walking, sedentary and in moderate intensity exercise over 7 days; spatiotemporal gait performance (step length, gait speed, endurance); health-related quality of life; and outcome expectations and self-efficacy for exercise.

DISCUSSION

Sustainability of gains in physical activity following exercise interventions is a challenge for most populations. Our incorporation of a chronic disease self-management approach into the exercise program including fitness tracking extends previous trials and has potential to significantly improve free-living physical activity in people with PD.

TRIAL REGISTRATION

This study has been prospectively registered in Australian and New Zealand Clinical Trial Registry (ACTRN12617001057370), registered on 19/07/2017. Available from www.anzctr.org.au/ACTRN12617001057370.aspx .

Four Days Are Enough to Provide a Reliable Daily Step Count in Mild to Moderate Parkinson's Disease through a Commercial Smartwatch

Daily steps could be a valuable indicator of real-world ambulation in Parkinson's disease (PD). Nonetheless, no study to date has investigated the minimum number of days required to reliably estimate the average daily steps through commercial smartwatches in people with PD. Fifty-six patients were monitored through a commercial smartwatch for 5 consecutive days. The total daily steps for each day was recorded and the average daily steps was calculated as well as the working and weekend days average steps. The intraclass correlation coefficient (ICC) (3,k), standard error of measurement (SEM), Bland-Altman statistics, and minimum detectable change (MDC) were used to evaluate the reliability of the step count for every combination of 2-5 days. The threshold for acceptability was set at an ICC ≥ 0.8 with a lower bound of CI 95% ≥ 0.75 and a SAM < 10%. ANOVA and Mann-Whitney tests were used to compare steps across the days and between the working and weekend days, respectively. Four days were needed to achieve an acceptable reliability (ICC range: 0.84-0.90; SAM range: 7.8-9.4%). In addition, daily steps did not significantly differ across the days and between the working and weekend days. These findings could support the use of step count as a walking activity index and could be relevant to developing monitoring, preventive, and rehabilitation strategies for people with PD.

Measurement properties of device-based physical activity instruments in ambulatory adults with physical disabilities and/or chronic diseases: a scoping review

BACKGROUND

People with physical disabilities and/or chronic diseases tend to have an inactive lifestyle. Monitoring physical activity levels is important to provide insight on how much and what types of activities people with physical disabilities and/or chronic diseases engage in. This information can be used as input for interventions to promote a physically active lifestyle. Therefore, valid and reliable physical activity measurement instruments are needed. This scoping review aims 1) to provide a critical mapping of the existing literature and 2) directions for future research on measurement properties of device-based instruments assessing physical activity behavior in ambulant adults with physical disabilities and/or chronic diseases.

METHODS

Four databases (MEDLINE, CINAHL, Web of Science, Embase) were systematically searched from 2015 to April 16th 2023 for articles investigating measurement properties of device-based instruments assessing physical activity in ambulatory adults with physical disabilities and/or chronic diseases. For the majority, screening and selection of eligible studies were done in duplicate. Extracted data were publication data, study data, study population, device, studied measurement properties and study outcome. Data were synthesized per device.

RESULTS

One hundred three of 21566 Studies were included. 55 Consumer-grade and 23 research-grade devices were studied on measurement properties, using 14 different physical activity outcomes, in 23 different physical disabilities and/or chronic diseases. ActiGraph (n = 28) and Fitbit (n = 39) devices were most frequently studied. Steps (n = 68) was the most common used physical activity outcome. 97 studies determined validity, 11 studies reliability and 6 studies responsiveness.

CONCLUSION

This scoping review shows a large variability in research on measurement properties of device-based instruments in ambulatory adults with physical disabilities and/or chronic diseases. The variability highlights a need for standardization of and consensus on research in this field. The review provides directions for future research.

Validation of Commercial Activity Trackers in Everyday Life of People with Parkinson's Disease

Maintaining physical activity is an important clinical goal for people with Parkinson's disease (PwPD). We investigated the validity of two commercial activity trackers (ATs) to measure daily step counts. We compared a wrist- and a hip-worn commercial AT against the research-grade Dynaport Movemonitor (DAM) during 14 days of daily use. Criterion validity was assessed in 28 PwPD and 30 healthy controls (HCs) by a 2 × 3 ANOVA and intraclass correlation coefficients (ICC_2,1). The ability to measure daily step fluctuations compared to the DAM was studied by a 2 × 3 ANOVA and Kendall correlations. We also explored compliance and user-friendliness. Both the ATs and the DAM measured significantly fewer steps/day in PwPD compared to HCs (p < 0.01). Step counts derived from the ATs showed good to excellent agreement with the DAM in both groups (ICC_2,1 > 0.83). Daily fluctuations were detected adequately by the ATs, showing moderate associations with DAM-rankings. While compliance was high overall, 22% of PwPD were disinclined to use the ATs after the study. Overall, we conclude that the ATs had sufficient agreement with the DAM for the purpose of promoting physical activity in mildly affected PwPD. However, further validation is needed before clinical use can be widely recommended.

Mobile health technology, exercise adherence and optimal nutrition post rehabilitation among people with Parkinson's Disease (mHEXANUT) - a randomized controlled trial protocol

BACKGROUND

Although it is well known that regular physical activity and exercise, as well as maintaining adequate nutritional status is important to delaying symptom development and maintaining physical capacity and function in people with Parkinson's Disease (PD), many are unable to follow self-management recommendations. Active interventions have shown short-term effects, but there is a need for interventions that facilitate self-management over the course of the disease. Until now, no studies have combined exercise and nutritional interventions with an individual self-management approach in PD. Thus, we aim to examine the effect of a six-month mobile health technology(m-health)-based follow-up programme, focusing on self-management in exercise and nutrition, after an in-service interdisciplinary rehabilitation programme.

METHODS

A single-blinded, two-group randomised controlled trial. Participants are Adults aged 40 or older, with idiopathic PD, Hoehn and Yahr 1-3, living at home. The intervention group receives a monthly, individualized, digital conversation with a PT, combined with use of an activity tracker. People at nutritional risk get additional digital-follow-up from a nutritional specialist. The control group receives usual care. The primary outcome is physical capacity, measured by 6-min walk test (6MWT). Secondary outcomes are nutritional status, Health related quality of life (HRQOL), physical function and exercise adherence. All measurements are performed at baseline, after 3 months and after 6 months. Sample size, based on primary outcome, is set at 100 participants randomized into the two arms, including an estimated 20% drop out.

DISCUSSION

The increasing prevalence of PD globally makes it even more important to develop evidence-based interventions that can increase motivation to stay active, promote adequate nutritional status and improve self-management in people with PD. The individually tailored digital follow-up programme, based on evidence-based practice, has the potential to promote evidence-based decision-making and to empower people with PD to implement exercise and optimal nutrition in their daily lives and, hopefully, increase adherence to exercise and nutritional recommendations.

TRIAL REGISTRATION

ClinicalTrials.gov (NCT04945876). First registration 01.03.2021.

Step-Counting Accuracy of a Commercial Smartwatch in Mild-to-Moderate PD Patients and Effect of Spatiotemporal Gait Parameters, Laterality of Symptoms, Pharmacological State, and Clinical Variables

Commercial smartwatches could be useful for step counting and monitoring ambulatory activity. However, in Parkinson's disease (PD) patients, an altered gait, pharmacological condition, and symptoms lateralization may affect their accuracy and potential usefulness in research and clinical routine. Steps were counted during a 6 min walk in 47 patients with PD and 47 healthy subjects (HS) wearing a Garmin Vivosmart 4 (GV4) on each wrist. Manual step counting was used as a reference. An inertial sensor (BTS G-Walk), placed on the lower back, was used to compute spatial-temporal gait parameters. Intraclass correlation coefficient (ICC) and mean absolute percentage error (MAPE) were used for accuracy evaluation and the Spearman test was used to assess the correlations between variables. The GV4 overestimated steps in PD patients with only a poor-to-moderate agreement. The OFF pharmacological state and wearing the device on the most-affected body side led to an unacceptable accuracy. The GV4 showed an excellent agreement and MAPE in HS at a self-selected speed, but an unacceptable performance at a slow speed. In PD patients, MAPE was not associated with gait parameters and clinical variables. The accuracy of commercial smartwatches for monitoring step counting might be reduced in PD patients and further influenced by the pharmacological condition and placement of the device.

Stressors and Destressors in Working From Home Based on Context and Physiology From Self-Reports and Smartwatch Measurements: International Observational Study Trial

Background

The COVID-19 pandemic has greatly boosted working from home as a way of working, which is likely to continue for most companies in the future, either in fully remote or in hybrid form. To manage stress levels in employees working from home, insights into the stressors and destressors in a home office first need to be studied.

Objective

We present an international remote study with employees working from home by making use of state-of-the-art technology (ie, smartwatches and questionnaires through smartphones) first to determine stressors and destressors in people working from home and second to identify smartwatch measurements that could represent these stressors and destressors.

Methods

Employees working from home from 3 regions of the world (the United States, the United Kingdom, and Hong Kong) were asked to wear a smartwatch continuously for 7 days and fill in 5 questionnaires each day and 2 additional questionnaires before and after the measurement week. The entire study was conducted remotely. Univariate statistical analyses comparing variable distributions between low and high stress levels were followed by multivariate analysis using logistic regression, considering multicollinearity by using variance inflation factor (VIF) filtering.

Results

A total of 202 people participated, with 198 (98%) participants finishing the experiment. Stressors found were other people and daily life getting in the way of work (P=.05), job intensity (P=.01), a history of burnout (P=.03), anxiety toward the pandemic (P=.04), and environmental noise (P=.01). Destressors found were access to sunlight (P=.02) and fresh air (P<.001) during the workday and going outdoors (P<.001), taking breaks (P<.001), exercising (P<.001), and having social interactions (P<.001). The smartwatch measurements positively related to stress were the number of active intensity periods (P<.001), the number of highly active intensity periods (P=.04), steps (P<.001), and the SD in the heart rate (HR; P<.001). In a multivariate setting, only a history of burnout (P<.001) and family and daily life getting in the way of work (P<.001) were positively associated with stress, while self-reports of social activities (P<.001) and going outdoors (P=.03) were negatively associated with stress. Stress prediction models based on questionnaire data had a similar performance (F1=0.51) compared to models based on automatic measurable data alone (F1=0.47).

Conclusions

The results show that there are stressors and destressors when working from home that should be considered when managing stress in employees. Some of these stressors and destressors are (in)directly measurable with unobtrusive sensors, and prediction models based on these data show promising results for the future of automatic stress detection and management.

Trial Registration

Netherlands Trial Register NL9378; https://trialsearch.who.int/Trial2.aspx?TrialID=NL9378

The association between sleep deficits and sedentary behavior in people with mild Parkinson disease

Purpose: Sleep deficits are a common nonmotor symptom of Parkinson disease (PD). People with mild PD also achieve less physical activity (PA) than healthy older adults (HOA), but the relationship between sleep and PA in PD is unclear. This study examined associations between sleep and PA in participants with PD and HOA.Materials and Methods: Secondary analysis of a prospective observational study. Participants wore a commercially available activity monitor for two weeks. Wilcoxon Rank-Sum tests compared nighttime sleep, wakenings after sleep onset, number of wakenings, naps, step count, and PA intensity between PD and HOA groups. Age-adjusted regression models calculated associations between nighttime sleep and PA.Results: Per day, participants with PD slept 75 fewer minutes (p < 0.01), took 5,792 fewer steps (p < 0.001), achieved less PA at all intensities, and had 32% more sedentary time (p < 0.001) compared to HOA. Thirty minutes more sleep was associated with 26 fewer sedentary minutes for HOA (p = 0.01) and 25 fewer sedentary minutes for the PD group (p < 0.001).Conclusions: Sleep and PA are reduced in mild PD compared to HOA. Both groups demonstrated similar associations between reduced sleep and increased sedentary behavior. Results may encourage providers to screen for sleep deficits when promoting PA.IMPLICATIONS FOR REHABILITATIONThe use of a wrist-worn commercial activity and sleep monitor was well tolerated by both healthy older adults and people with mild Parkinson Disease in this study.People with mild Parkinson Disease slept less and were less active than a group of healthy older adults.Less sleep was associated with more sedentary behavior in both groups.The relationship between poor sleep and sedentary behavior in mild Parkinson Disease suggests that rehabilitation interventions may be optimized by targeting both physical activity and sleep deficits.

Lifestyle Interventions for the Prevention of Parkinson Disease: A Recipe for Action

The prevalence of Parkinson disease (PD) is growing fast, amplifying the quest for disease-modifying therapies in early disease phases where pathology is still limited. Lifestyle interventions offer a promising avenue for preventing progression from prodromal to manifest PD. We illustrate this primarily for 1 specific lifestyle intervention, namely aerobic exercise because the case for the other main lifestyle factor (dietary interventions) to modify the course of prodromal PD is currently less persuasive. Various observations have hinted at the disease-modifying potential of exercise. First, studies in rodents with experimental parkinsonism showed that exercise elicits adaptive neuroplasticity in basal ganglia circuitries. Second, exercise is associated with a reduced risk of developing PD, suggesting a disease-modifying potential. Third, 2 large trials in persons with manifest PD indicate that exercise can help to stabilize motor parkinsonism, although this could also reflect a symptomatic effect. In addition, exercise seems to be a feasible intervention, given its minimal risk of side effects. Theoretical risks include an increase in fall incidents and cardiovascular complications, but these concerns seem to be acceptably low. Innovative approaches using gamification elements indicate that adequate long-term compliance with regular exercise programs can be achieved, although more work remains necessary to demonstrate enduring adherence for multiple years. Advances in digital technology can be used to deliver the exercise intervention in the participant's own living environment and also to measure the outcomes remotely, which will help to further boost long-term compliance. When delivering exercise to prodromal participants, outcome measures should focus not just on phenoconversion to manifest PD (which may well take many years to occur) but also on measurable intermediate outcomes, such as physical fitness or prodromal nonmotor symptoms. Taken together, there seems to be sufficient evidence to advocate the first judicious attempt of investigating exercise as a disease-modifying treatment in prodromal PD.

Physical activity and exercise outcomes in Huntington's disease (PACE-HD): results of a 12-month trial-within-cohort feasibility study of a physical activity intervention in people with Huntington's disease

INTRODUCTION

While physical activity (PA) is recognized as important in Huntington's disease (HD) disease management, there has been no long-term evaluation undertaken. We aimed to evaluate the feasibility of a nested (within cohort) randomized controlled trial (RCT) of a physical therapist-led PA intervention.

METHODS

Participants were recruited from six HD specialist centers participating in the Enroll-HD cohort study in Germany, Spain and U.S. Assessments were completed at baseline and 12 months and linked to Enroll-HD cohort data. Participants at three sites (cohort) received no contact between baseline and 12 month assessments. Participants at three additional sites (RCT) were randomized to PA intervention or control group. The intervention consisted of 18 sessions delivered over 12 months; control group participants received no intervention, however both groups completed monthly exercise/falls diaries and 6-month assessments.

RESULTS

274 participants were screened, 204 met inclusion criteria and 116 were enrolled (59 in cohort; 57 in RCT). Retention rates at 12-months were 84.7% (cohort) and 79.0% (RCT). Data completeness at baseline ranged from 42.3 to 100% and at 12-months 19.2-85.2%. In the RCT, there was 80.5% adherence, high intervention fidelity, and similar adverse events between groups. There were differences in fitness, walking endurance and self-reported PA at 12 months favoring the intervention group, with data completeness >60%. Participants in the cohort had motor and functional decline at rates comparable to previous studies.

CONCLUSION

Predefined progression criteria indicating feasibility were met. PACE-HD lays the groundwork for a future, fully-powered within cohort trial, but approaches to ensure data completeness must be considered.

CLINICALTRIALS

GOV: NCT03344601.

Accuracy of Step Count Estimations in Parkinson’s Disease Can Be Predicted Using Ambulatory Monitoring

Objectives

There are concerns regarding the accuracy of step count in Parkinson’s disease (PD) when wearable sensors are used. In this study, it was predicted that providing the normal rhythmicity of walking was maintained, the autocorrelation function used to measure step count would provide relatively low errors in step count.

Materials and Methods

A total of 21 normal walkers (10 without PD) and 27 abnormal walkers were videoed while wearing a sensor [Parkinson’s KinetiGraph (PKG)]. Median step count error rates were observed to be <3% in normal walkers but ≥3% in abnormal walkers. The simultaneous accelerometry data and data from a 6-day PKG were examined and revealed that the 5th percentile of the spectral entropy distribution, among 10-s walking epochs (obtained separately), predicted whether subjects had low error rate on step count with reference to the manual step count from the video recording. Subjects with low error rates had lower Movement Disorder Society Unified Parkinson’s Disease Rating Scale (MDS-UPDRS III) scores and UPDRS III Q10–14 scores than the high error rate counterparts who also had high freezing of gait scores (i.e., freezing of gait questionnaire).

Results

Periods when walking occurred were identified in a 6-day PKG from 190 non-PD subjects aged over 60, and 155 people with PD were examined and the 5th percentile of the spectral entropy distribution, among 10-s walking epochs, was extracted. A total of 84% of controls and 72% of people with PD had low predicted error rates. People with PD with low bradykinesia scores (measured by the PKG) had step counts similar to controls, whereas those with high bradykinesia scores had step counts similar to those with high error rates. On subsequent PKGs, step counts increased when bradykinesia was reduced by treatment and decreased when bradykinesia increased. Among both control and people with PD, low error rates were associated with those who spent considerable time making walks of more than 1-min duration.

Conclusion

Using a measure of the loss of rhythmicity in walking appears to be a useful method for detecting the likelihood of error in step count. Bradykinesia in subjects with low predicted error in their step count is related to overall step count but when the predicted error is high, the step count should be assessed with caution.

Detection of Walking Features Using Mobile Health and Deep Learning

This study identifies seven human subjects’ walking features by training a deep learning model with sensor data. Using the proposed Mobile Health Application developed for collecting sensor data from an Android device, we collected data from human subjects with a history of mild traumatic brain injury. The sensors measure acceleration in m/s2 with respect to: the X, Y, and Z directions using an accelerometer, the rate of rotation around a spatial axis with a gyroscope, and nine parameters of a rotation vector with rotation vector components along the X, Y, Z axes using a rotation vector software-based sensor. We made a deep learning model using Tensorflow and Keras to identify the walking features of the seven subjects. The data are classified into the following categories: Accelerometer (X, Y, Z); Gyroscope (X, Y, Z); Rotation (X, Y, Z); Rotation vector (nine parameters); and a combination of the preceding categories. Each dataset was then used for training and testing the accuracy of the deep learning model. According to the Keras evaluation function, the deep learning model trained with Rotation vector data shows 99.5% accuracy for classifying walking characteristics of subjects. In addition, the ability of the model to accurately classify the characteristics of subjects’ walking with all datasets combined is 99.9%.

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.

Step Monitor Accuracy During PostStroke Physical Therapy and Simulated Activities

Introduction/Purpose

The amount of stepping activity during rehabilitation post-stroke can predict walking outcomes, although the most accurate methods to evaluate stepping activity are uncertain with conflicting findings on available stepping monitors during walking assessments. Rehabilitation sessions also include non-stepping activities and the ability of activity monitors to differentiate these activities from stepping is unclear. The objective of this study was to examine the accuracy of different activity monitors worn by individuals post-stroke with variable walking speeds during clinical physical therapy (PT) and research interventions focused on walking.

Methods

In Part I, 28 participants post-stroke wore a StepWatch, ActiGraph with and without a Low Frequency Extension (LFE) filter, and Fitbit on paretic and non-paretic distal shanks at or above the ankle during clinical PT or research interventions with steps simultaneously hand counted. Mean absolute percent errors were compared between limbs and tasks performed. In Part II, 12 healthy adults completed 8 walking and 9 non-walking tasks observed during clinical PT or research. Data were descriptively analyzed and used to assist interpretation of Part I results.

Results

Part I results indicate most devices did not demonstrate an optimal limb configuration during research sessions focused on walking, with larger errors during clinical PT on the non-paretic limb. Using the limb that minimized errors for each device, the StepWatch had smaller errors than the ActiGraph and Fitbit (p<0.01), particularly in those who walked < 0.8 m/s. Conversely, errors from the ActiGraph-LFE demonstrated inconsistent differences in step counts between Fitbit and ActiGraph. Part II results indicate that errors observed during different stepping and non-stepping activities were often device-specific, with non-stepping tasks frequently detected as stepping.

Conclusions

The StepWatch and ActiGraph-LFE had smaller errors than the Fitbit or ActiGraph, with greater errors in those walking at slower speeds. Inclusion of non-stepping activities affected step counts and should be considered when measuring stepping activity in individuals post-stroke to predict locomotor outcomes following rehabilitation.

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.

Validity of mHealth devices for counting steps in individuals with Parkinson's disease

BACKGROUND

Step quantification is a good way to characterize the mobility and functional status of individuals with some functional disorder. Therefore, a validation study may lead to the feasibility of devices to stimulate an increase in the number of steps and physical activity level of individuals with Parkinson's Disease (PD).

AIM

To investigate the validity of mHealth devices to estimate the number of steps in individuals with PD and compare the estimate with a standard criterion measure.

METHOD

An observational study in a university laboratory with 34 individuals with idiopathic PD. The number of steps was measured using mHealth devices (Google Fit, Health, STEPZ, Pacer, and Fitbit INC®), and compared against a criterionstandard measure during the Two-Minute Walk Test using habitual speed.

RESULTS

Our sample was 82% men with a Hoehn and Yahr mean of 2.3 ± 1.3 and mean walking speed of 1.2 ± 0.2 m/s. Positive and statistically significant associations were found between Google Fit (r = 0.92; p < 0.01), STEPZ (r = 0.91; p < 0.01), Pacer (r = 0.77; p < 0.01), Health (r = 0.54; p < 0.01), and Fitbit Inc® (r = 0.82; p < 0.01) with the criterion-standard measure.

CONCLUSIONS

GoogleFit, STEPZ, Fitbit Inc.®, Pacer, and Health are valid instruments to measure the number of steps over a given period of time with moderate to high correlation with the criterion-standard in individuals with PD. This result shows that technology such as smartphone applications and activity monitor can be used to assess the number of steps in individuals with PD, and allows the possibility of using this technology for assessment and intervention purposes.

Effectiveness of a Long-Term, Home-Based Aerobic Exercise Intervention on Slowing the Progression of Parkinson Disease: Design of the Cyclical Lower Extremity Exercise for Parkinson Disease II (CYCLE-II) Study

OBJECTIVE

Previous short duration studies have demonstrated that high-intensity aerobic exercise improves aspects of motor and non-motor function in people with Parkinson disease (PwPD); however, the effectiveness of a long-term exercise intervention on slowing disease progression is unknown. The primary aim of this study is to determine the disease-altering effects of high-intensity aerobic exercise, administered on an upright stationary cycle, on the progression of PD. A secondary aim is to develop a prognostic model for 12-month changes in the Movement Disorder Society Unified Parkinson's Disease Rating Scale III (MDS-UPDRS III) of PwPD undergoing an aerobic exercise intervention.

METHODS

This pragmatic, multisite, single-rater blinded, randomized controlled trial will recruit PwPD from 2 large, urban, academic medical centers. Participants (N = 250 PwPD) will be randomized to (1) home-based aerobic exercise or (2) usual and customary care. Those in the aerobic exercise arm will be asked to complete in-home aerobic exercise sessions at 60% to 80% of heart rate reserve 3 times per week for 12 months utilizing a commercially available upright exercise cycle. The usual and customary care group will continue normal activity levels. Daily activity will be monitored for both groups throughout the 12-month study period. The primary outcome, both to assess disease-modifying response to aerobic exercise and for prognostic modeling in the aerobic exercise arm, is 12-month rate of change in the MDS-UPDRS III. Clinical and biomechanical measures will also be used to assess upper and lower extremity motor function as well as non-motor functions.

IMPACT

Should long-term aerobic exercise demonstrate disease-modifying capability, this study will provide evidence that "Exercise is Medicine" for PwPD. Further, the derived prognostic model will inform a patient-specific exercise prescription for PwPD and expected effects on PD progression.

Usability and Accuracy of a Smartwatch for the Assessment of Physical Activity in the Elderly Population: Observational Study

Background

Regular physical activity (PA) contributes to the primary and secondary prevention of several chronic diseases and reduces the risk of premature death. Physical inactivity is a modifiable risk factor for cardiovascular disease and a variety of chronic disorders such as diabetes, obesity, hypertension, bone and joint diseases (eg, osteoporosis and osteoarthritis), depression, and colon and breast cancer. Population aging and the related increase in chronic diseases have a major impact on the health care systems of most Western countries and will produce an even more significant effect in the future. Monitoring PA is a valuable method of determining whether people are performing enough PA so as to prevent chronic diseases or are showing early symptoms of those diseases.

Objective

The aim of this study was to estimate the accuracy of wearable devices in quantifying the PA of elderly people in a real-life setting.

Methods

Participants aged 70 to 90 years with the ability to walk safely without any walking aid for at least 300 meters, who had no walking disabilities or episodes of falling while walking in the last 12 months, were asked to walk 150 meters at their preferred pace wearing a vívoactive HR device (Garmin Ltd) and actual steps were monitored and tallied by a researcher using a hand-tally counter to assess the performance of the device at a natural speed. A Bland-Altman plot was used to analyze the difference between manually counted steps and wearable device–measured steps. The intraclass correlation coefficient (ICC) was computed (with a 95% confidence interval) between step measurements. The generalized linear mixed-model (GLMM) ICCs were estimated, providing a random effect term (random intercept) for the individual measurements (gold standard and device). Both adjusted and conditional ICCs were computed for the GLMM models considering separately the effect of age, sex, BMI, and obesity. Analyses were performed using R software (R Foundation for Statistical Computing) with the rms package.

Results

A total of 23 females and 26 males were enrolled in the study. The median age of the participants was 75 years. The Bland-Altman plot revealed that, excluding one observation, all differences across measurements were in the confidence bounds, demonstrating the substantial agreement between the step count measurements. The results were confirmed by an ICC equal to .98 (.96-.99), demonstrating excellent agreement between the two sets of measurements.

Conclusions

The level of accuracy of wearable devices in quantifying the PA of elderly people in a real-life setting that was found in this study supports the idea of considering wrist-wearable nonmedical devices (widely available in nonspecialized stores) as reliable tools. Both health care professionals and informal caregivers could monitor the level of PA of their patients.

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.

Digital Technology in Movement Disorders: Updates, Applications, and Challenges

Purpose of Review

Digital technology affords the opportunity to provide objective, frequent, and sensitive assessment of disease outside of the clinic environment. This article reviews recent literature on the application of digital technology in movement disorders, with a focus on Parkinson’s disease (PD) and Huntington’s disease.

Recent Findings

Recent research has demonstrated the ability for digital technology to discriminate between individuals with and without PD, identify those at high risk for PD, quantify specific motor features, predict clinical events in PD, inform clinical management, and generate novel insights.

Summary

Digital technology has enormous potential to transform clinical research and care in movement disorders. However, more work is needed to better validate existing digital measures, including in new populations, and to develop new more holistic digital measures that move beyond motor features.

Body-Worn Sensors for Remote Monitoring of Parkinson's Disease Motor Symptoms: Vision, State of the Art, and Challenges Ahead

The increasing prevalence of neurodegenerative conditions such as Parkinson's disease (PD) and related mobility issues places a serious burden on healthcare systems. The COVID-19 pandemic has reinforced the urgent need for better tools to manage chronic conditions remotely, as regular access to clinics may be problematic. Digital health technology in the form of remote monitoring with body-worn sensors offers significant opportunities for transforming research and revolutionizing the clinical management of PD. Significant efforts are being invested in the development and validation of digital outcomes to support diagnosis and track motor and mobility impairments "off-line". Imagine being able to remotely assess your patient, understand how well they are functioning, evaluate the impact of any recent medication/intervention, and identify the need for urgent follow-up before overt, irreparable change takes place? This could offer new pragmatic solutions for personalized care and clinical research. So the question remains: how close are we to achieving this? Here, we describe the state-of-the-art based on representative papers published between 2017 and 2020. We focus on remote (i.e., real-world, daily-living) monitoring of PD using body-worn sensors (e.g., accelerometers, inertial measurement units) for assessing motor symptoms and their complications. Despite the tremendous potential, existing challenges exist (e.g., validity, regulatory) that are preventing the widespread clinical adoption of body-worn sensors as a digital outcome. We propose a roadmap with clear recommendations for addressing these challenges and future directions to bring us closer to the implementation and widespread adoption of this important way of improving the clinical care, evaluation, and monitoring of PD.

Using Wearable Devices to Monitor Physical Activity in Patients Undergoing Aortic Valve Replacement: Protocol for a Prospective Observational Study

Background

In last few decades, several tools have been developed to measure physical function objectively; however, their use has not been well established in clinical practice.

Objective

This study aims to describe the preoperative physical function and to assess and compare 6-month postoperative changes in the physical function of patients undergoing treatment for aortic stenosis with either surgical aortic valve replacement (SAVR) or transcatheter aortic valve replacement (TAVR). The study also aims to evaluate the feasibility of wearable devices in assessing physical function in such patients.

Methods

This is a prospective observational study. The enrollment will be conducted 1 month before patients’ SAVR/TAVR. Patients will be provided with the wearable device at baseline (activity tracker device, Garmin vívoactive 3). They will be trained in the use of the device, and they will be requested to wear it on the wrist of their preferred hand until 12 months after SAVR/TAVR. After baseline assessment, they will undergo 4 follow-up assessments at 1, 3, 6, and 12 months after SAVR/TAVR. At baseline and each follow-up, they will undergo a set of standard and validated tests to assess physical function, health-related quality of life, and sleep quality.

Results

The ethics committee of Vicenza in Veneto Region in Italy approved the study (Protocol No. 943; January 4, 2019). As of October 2020, the enrollment of participants is ongoing.

Conclusions

The use of the wearable devices for real-time monitoring of physical activity of patients undergoing aortic valve replacement is a promising opportunity for improving the clinical management and consequently, the health outcomes of such patients.

Trial Registration

Clinicaltrials.gov NCT03843320; https://tinyurl.com/yyareu5y

International Registered Report Identifier (IRRID)

DERR1-10.2196/20072

Accelerometer output and its association with energy expenditure in persons with mild-to-moderate Parkinson's disease

OBJECTIVE

This study examined the association between ActiGraph accelerometer output and energy expenditure across different speeds of walking in persons with Parkinson's disease (PD), and further generated cut-points that represent a metric for quantifying time spent in moderate-to-vigorous physical activity (MVPA) among persons with PD.

METHODS

The sample included 30 persons with mild-to-moderate PD (Hoehn and Yahr stages 2-3) and 30 adults without PD matched by sex and age. All participants completed 5 minutes of quiet, seated rest and then underwent three, 6-minute bouts of walking on a treadmill at three different speeds relative to the individual's self-selected pace. Activity counts were measured using an ActiGraph accelerometer worn at the waist level on the least affected side for persons with PD and the dominant side for controls. The rate of oxygen consumption, or energy expenditure, was measured using a portable, open-circuit spirometry system.

RESULTS

Our results indicated a strong association between activity counts and energy expenditure for persons with PD (R2 = 0.87) and controls (R2 = 0.89). However, the significant difference in slopes resulted in a lower cut-point of 1,354 counts·min-1 for persons with PD than the cut-point of 2,010 counts·min-1 for controls.

CONCLUSION

Our results support the application of the disease-specific cut-point for quantifying the amount of time spent in MVPA using ActiGraph accelerometers among persons with mild-to-moderate PD. Such an application may provide accurate estimates of MVPA in this population, and better inform future research examining the possible determinants and consequences of physical activity as well as testing of interventions for changing MVPA in PD.

Implementation of Mobile Health Technologies in Clinical Trials of Movement Disorders: Underutilized Potential

Mobile health technologies (mHealth) are patient-worn or portable devices aimed at increasing the granularity and relevance of clinical measurements. The implementation of mHealth has the potential to decrease sample size, duration, and cost of clinical trials. We performed a review of the ClinicalTrials.gov database using a standardized approach to identify adoption in and usefulness of mHealth in movement disorders interventional clinical trials. Trial phase, geographical area, availability of data captured, constructs of interest, and outcome priority were collected. Eligible trials underwent quality appraisal using an ad hoc 5-point checklist to assess mHealth feasibility, acceptability, correlation with patient-centered outcome measures, and clinical meaningfulness. A total of 29% (n = 54/184) registered trials were using mHealth, mainly in Parkinson's disease and essential tremor (59.3% and 27.8%). In most cases, mHealth were used in phase 2 trials (83.3%) as secondary outcome measures (59.3%). Only five phase 3 trials, representing 9.3% of the total, used mHealth (1 as primary outcome measure, 3 as secondary, and 1 as tertiary). Only 3.7% (n = 2/54) of all trials used mHealth for measuring both motor and non-motor symptoms, and 23.1% (n = 12/52) used mHealth for unsupervised, ecologic outcomes. Our findings suggest that mHealth remain underutilized and largely relegated to phase 2 trials for secondary or tertiary outcome measures. Efforts toward greater alignment of mHealth with patient-centered outcomes and development of a universal, common-language platform to synchronize data from one or more devices will assist future efforts toward the integration of mHealth into clinical trials.

Current Perspectives on Aerobic Exercise in People with Parkinson's Disease

Parkinson's disease (PD) is a progressive neurological disorder characterized by motor and non-motor symptoms for which only symptomatic treatments exist. Exercise is a widely studied complementary treatment option. Aerobic exercise, defined as continuous movement of the body's large muscles in a rhythmic manner for a sustained period that increases caloric requirements and aims at maintaining or improving physical fitness, appears promising. We performed both a scoping review and a systematic review on the generic and disease-specific health benefits of aerobic exercise for people with PD. We support this by a meta-analysis on the effects on physical fitness (VO2max), motor symptoms (Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) motor section), and health-related quality of life (39-item Parkinson's disease Questionnaire (PDQ-39)). Aerobic exercise has generic health benefits for people with PD, including a reduced incidence of cardiovascular disease, a lower mortality, and an improved bone health. Additionally, there is level 1 evidence that aerobic exercise improves physical fitness (VO2max) and attenuates motor symptoms (MDS-UPDRS motor section) in the off-medication state, although the long-term effects (beyond 6 months) remain unclear. Dosing the exercise matters: improvements appear to be greater after training at higher intensities compared with moderate intensities. We found insufficient evidence for a beneficial effect of aerobic exercise on health-related quality of life (PDQ-39) and conflicting results regarding non-motor symptoms. Compliance to exercise regimes is challenging for PD patients but may be improved by adding exergaming elements to the training program. Aerobic exercise seems a safe intervention for people with PD, although care must be taken to avoid falls in at-risk individuals. Further studies are needed to establish the long term of aerobic exercise, including a focus on non-motor symptoms and health-related quality of life.

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.

Step-rate threshold for physical activity intensity in Parkinson's disease

OBJECTIVES

To examine the relationship between step-rate and energy expenditure during treadmill walking in persons with PD and then further develop a step-rate cut-point for moderate-to-vigorous physical activity (MVPA) for persons with PD.

MATERIALS AND METHODS

The sample consisted of 30 persons with mild-to-moderate PD and 30 controls matched by age and sex. Participants performed a 6-minute bout of over-ground walking at comfortable speed, and then completed three, 6-minute bouts of treadmill walking at 13.4 m/min slower, comfortable, and 13.4 m/min faster than comfortable speeds. The three treadmill speeds were based on the initial over-ground walking speed. The total number of steps per treadmill walking bout was recorded using a hand-tally counter, and energy expenditure was measured using a portable, indirect spirometry system.

RESULTS

The results indicated a strong association between step-rate and energy expenditure for persons with PD (R²  = .92) and controls (R²  = .92). The analyses further indicated a steeper slope of the association for persons with PD compared with controls (t(58) = -1.87, P < .05), resulting in a lower step-rate threshold (t(58) = 2.19, P < .05) for persons with PD (~80 steps·per minutes) than controls (~93 steps·per minutes).

CONCLUSION

Collectively, these results support the application of this disease-specific step-rate threshold for MVPA among persons with PD. This has important implications for physical activity promotion, prescription, and monitoring using accelerometers and pedometers for persons with PD to manage health and symptoms of PD.

Portable accelerometers for the evaluation of spatio-temporal gait parameters in people with Parkinson's disease: an integrative review

PURPOSE

The progression of Parkinson's disease causes an increase in motor dysfunctions, which makes it necessary to evaluate and monitor these changes. This integrative review aimed to gather studies - without any language restrictions - on the use, advantages and disadvantages of portable accelerometers for the evaluation of spatio-temporal gait parameters in people with Parkinson's disease published between 2014 and 2019.

METHODS

Articles were selected from the PubMed, Web of Science and Science Direct databases by combining descriptors from the Health Sciences Descriptors (DeCS) and Medical Subject Headings (MeSH) - "accelerometry", "accelerometer", "ActiGraph", "gait", "gait analysis", "gait rehabilitation", "walking inertial sensors", "Parkinson disease", "Parkinson" and "Parkinson's disease" - using OR and AND. The adapted Critical Appraisal Skill Program was used to analyze the methodological quality.

RESULTS

All the studies used portable wearable and wireless triaxial accelerometers. Among all types of accelerometers discussed, commercial wearable devices not based on smartphones and prototypes of wearable devices based and not based on smartphones can be pointed out. There was no standardization for the protocols of use, but the sensors were more often attached to the lower back (L3/L4/L5 vertebrae). The advantages included lower cost, possibility of use in outdoor environments and less complexity of data reading for non-specialized users. However, they still seem to show reduced precision and accuracy.

CONCLUSIONS

Due to the still insufficient number of articles published on the subject, we consider the need for further research, which should detail protocols of evaluation, advantages and disadvantages in stages of disease.

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.

Accuracy and Precision of Three Consumer-Grade Motion Sensors During Overground and Treadmill Walking in People With Parkinson Disease: Cross-Sectional Comparative Study

BACKGROUND

Wearable motion sensors are gaining popularity for monitoring free-living physical activity among people with Parkinson disease (PD), but more evidence supporting the accuracy and precision of motion sensors for capturing step counts is required in people with PD.

OBJECTIVE

This study aimed to examine the accuracy and precision of 3 common consumer-grade motion sensors for measuring actual steps taken during prolonged periods of overground and treadmill walking in people with PD.

METHODS

A total of 31 ambulatory participants with PD underwent 6-min bouts of overground and treadmill walking at a comfortable speed. Participants wore 3 devices (Garmin Vivosmart 3, Fitbit One, and Fitbit Charge 2 HR), and a single researcher manually counted the actual steps taken. Accuracy and precision were based on absolute and relative metrics, including intraclass correlation coefficients (ICCs) and Bland-Altman plots.

RESULTS

Participants walked 628 steps over ground based on manual counting, and Garmin Vivosmart, Fitbit One, and Fitbit Charge 2 HR devices had absolute (relative) error values of 6 (6/628, 1.0%), 8 (8/628, 1.3%), and 30 (30/628, 4.8%) steps, respectively. ICC values demonstrated excellent agreement between manually counted steps and steps counted by both Garmin Vivosmart (0.97) and Fitbit One (0.98) but poor agreement for Fitbit Charge 2 HR (0.47). The absolute (relative) precision values for Garmin Vivosmart, Fitbit One, and Fitbit Charge 2 HR were 11.1 (11.1/625, 1.8%), 14.7 (14.7/620, 2.4%), and 74.4 (74.4/598, 12.4%) steps, respectively. ICC confidence intervals demonstrated low variability for Garmin Vivosmart (0.96 to 0.99) and Fitbit One (0.93 to 0.99) but high variability for Fitbit Charge 2 HR (-0.57 to 0.74). The Fitbit One device maintained high accuracy and precision values for treadmill walking, but both Garmin Vivosmart and Fitbit Charge 2 HR (the wrist-worn devices) had worse accuracy and precision for treadmill walking.

CONCLUSIONS

The waist-worn sensor (Fitbit One) was accurate and precise in measuring steps with overground and treadmill walking. The wrist-worn sensors were accurate and precise only during overground walking. Similar research should inform the application of these devices in clinical research and practice involving patients with PD.

A Step in the Right Direction: Body Location Determines Activity Tracking Device Accuracy in Total Knee and Hip Arthroplasty Patients

INTRODUCTION

Step counts measured by activity monitoring devices (AMDs) and smartphones (SPs) can objectively measure a patient's activity levels after total hip and knee arthroplasty (total joint arthroplasty [TJA]). This study investigated the use and optimal body location of AMDs and SPs to measure step counts in the postoperative period.

METHODS

This was a two-armed, prospective, observational study of TJA inpatients (n = 24) and 2-week status after TJA (n = 25) completing a 100-ft walk. Observer-counted steps were compared with those measured by AMDs (wrist and ankle) and SPs (hip and neck). Acceptable error was defined as <30%. Error rates were treated as both dichotomous and continuous variables.

RESULTS

AMD and SP step counts had overall unacceptable error in TJA inpatients. AMDs on the contralateral ankle and SPs on the contralateral hip had error rates less than 30% at 2 weeks postoperatively. Two-week postoperative patients required lower levels of assist (11/25 walker; 4/25 no assist), and significant improvements in stride length (total hip arthroplasty 1.27 versus 1.83 ft/step; total knee arthroplasty 1.42 versus 1.83 ft/step) and cadence (total hip arthroplasty 74.6 versus 166.0 steps/min; total knee arthroplasty 73.5 versus 144.4 steps/min) were seen between inpatient and postoperative patients. Regression analysis found that increases in postoperative day and cadence led to a decrease in device error.

CONCLUSION

In inpatients with TJA, AMDs and SPs have unacceptable variability and limited utility for step counting when using a walker. As gait normalizes and the level of ambulatory assist decreases, AMDs on the contralateral ankle and SPs on the contralateral hip demonstrated low error rates. These devices offer a novel method for measurement of objective outcomes and potential for remote monitoring of patient progress after TJA.

LEVEL OF EVIDENCE

Level II, prospective, three-armed study, prognostic study.

Activity monitor use among persons with multiple sclerosis: Report on rate, pattern, and association with physical activity levels

BACKGROUND

Commercially available activity monitors are a promising approach for tracking and changing physical activity in multiple sclerosis.

OBJECTIVE

This study reports on the rate and pattern of activity monitor use in persons with multiple sclerosis, and compares self-reported physical activity levels between persons who do wear and those who do not wear activity monitors.

METHODS

Participants completed a cross-sectional survey that included a demographic and clinical characteristics scale, activity monitor use questionnaire, and Godin Leisure-Time Exercise Questionnaire (GLTEQ) for measuring total and health-promoting physical activity.

RESULTS

Of the 629 participants who completed the full survey, 249 (40%) reported using an activity monitor. The most common activity monitors were Fitbit, Apple watch, iPhone, and Garmin. There was a significant (p < 0.05), moderate difference (d = 0.5) in GLTEQ total scores between activity monitor users (36.6 ± 23.9) and non-users (25.0 ± 22.2), and in GLTEQ Health Contribution Score between activity monitor users (25.6 ± 22.3) and non-users (14.6 ± 18.9) (p < 0.05, d = 0.5). Self-reported steps from the activity monitor were significantly correlated with GLTEQ total score (ρ = 0.45; r = 0.36) and GLTEQ Health Contribution Score (ρ = 0.41; r = 0.35).

CONCLUSION

Activity monitor use is common among persons with multiple sclerosis, and activity monitor users report more total and health-promoting physical activity; this warrants further research investigating how devices may be used as a behavioral intervention tool.

Quantifying physical activity in early Parkinson disease using a commercial activity monitor

INTRODUCTION

Physical inactivity in Parkinson disease (PD) has an impact on motor and non-motor symptoms of the disease. It is unclear whether this decline in physical activity occurs early in the disease, in addition to any decline due to aging, and whether commercial activity monitors can be used to self-monitor physical activity levels in this population.

OBJECTIVE

To compare the quantity and intensity of physical activity (PA), as measured by commercial activity monitors, in people with mild PD and healthy older adults (HOA). A secondary objective was to assess adherence and user experience with wearing the activity monitoring device.

METHODS

An observational descriptive study design examined PA levels over a 14-day period using commercially-available activity monitors (Fitbit Charge HR).

RESULTS

Individuals with PD (n = 30) and HOA (n = 30) both demonstrated high adherence with wear time (PD = 13.8 [0.5] days, HOA = 13.9 [0.4] days, p = 0.55). People with PD took fewer steps per day than HOA (PD = 6416.9 (2795.5), HOA = 11441.3 (3932.1), p < 0.001). Compared to HOA, individuals with PD spent fewer minutes per day engaged in moderate to vigorous intensity activity (PD = 33.0 (22.5), HOA = 72.0(37.3), p < 0.001) and more minutes per day sedentary (PD = 803.74 (154.9), HOA = 578.26 (103.7), p < 0.001). Both groups reported that ease of use and satisfaction with the activity monitor were high.

CONCLUSIONS

People with mild PD demonstrated reduced quantity and intensity of PA compared to HOA. Both the PD and the HOA groups had good adherence wearing a commercial activity monitor that provided feedback regarding activity levels.

Engaging Older Adults With Parkinson's Disease in Physical Activity Using Technology: A Feasibility Study

Parkinson's disease (PD), a progressive neurodegenerative disorder, presents unique and daily challenges. Living with PD may limit one's physical activity and negatively affect quality of life (QOL). No studies were identified that utilized online technology to promote health in this population. The purposes of this study were to (a) assess the feasibility of an intervention that requires wearing a physical activity tracker and participating in an online support group, and (b) examine the effect of this intervention on the self-efficacy for physical activity and QOL of older adults with PD. A 12-week longitudinal pretest/posttest design was used to assess physical activity, engagement in an online support group, self-efficacy, and QOL. A postintervention questionnaire was used to capture the participants' (n = 5) experience using the physical activity tracker and an electronic tablet to engage in an online support group. The sample size of this feasibility study precluded robust quantitative analysis of QOL or self-efficacy. Findings from the open-ended questionnaire suggest technology was challenging for most participants, yet it did provide social support. Teaching effective interventions to promote self-management for increasing physical activity, and consequently improving QOL, is recommended. While technology can assist, older persons with PD may experience technological challenges.

Proof-of-Concept Testing of a Real-Time mHealth Measure to Estimate Postural Control During Walking: A Potential Application for Mild Traumatic Brain Injuries

Background: Most individuals with mild traumatic brain injury (mTBI) experience post-injury deficits in postural control. Currently available measures of postural control are lab-based or supervised, which may hinder timely symptom assessment for individuals with mTBI, including Asian populations, who do not seek initial screening post-injury. In this proof-of-concept testing study, we introduce a real-time mobile health (mHealth) system to measure postural control during walking. The proposed mHealth system can be used for home-based symptom assessment and management of mTBI.

Methods: In our proposed mHealth system, a smartwatch, a smartphone, and a cloud server communicate to measure, collect, and store body balance data in real time. Specifically, we focus on the rotation vector data that have been reported to be the most effective in terms of differentiating balance control during walking across different participants.

Results: Constant motion change in four participants (two females and two males; three healthy participants, and one individual with reduced physical mobility) was collected and analyzed. The results of our data analysis show that, compared to healthy participants, the individual was reduced physical mobility had a wider range of motion between right and left, up and down, and forward and backward while walking. We also found that female participants had narrower ranges of right-to-left and up-and-down motions than their male counterparts.

Conclusions: Our results highlight the potential of the proposed real-time mHealth system for home-based symptom assessment and management of mTBI, which may benefit Asian and other nonwhite racial minority groups that appear to be more reluctant to access post-acute rehabilitation services.