Validation of a consumer-grade activity monitor for continuous daily activity monitoring in individuals with multiple sclerosis

Block, Valerie J; Zhao, Chao; Hollenbach, Jill A.; Olgin, Jeffrey E.; Marcus, Gregory M.; Pletcher, Mark J.; Henry, Roland G.; Gelfand, Jeffrey M.; Cree, Bruce A.C.

doi:10.1177/2055217319888660

Cited by 17 publications

(15 citation statements)

References 35 publications

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“…Digital Patient Generated Health Data (PGHD), a recently introduced technology, has become available with the widespread availability of digital mobile devices, and can potentially fill the information gaps left by conventional sources of real-world data 14,15 . Wearable devices in particular that track physical activities or physiologic parameters like heart rate allow for the passive inference of behavioral activity patterns with time granularities not possible with conventional RWD [16][17][18] . Though still in the early stages of widespread clinical use, PGHD could potentially be used to gain more nuanced data on patient centered outcomes, and serve as passive health diaries with information to guide medication approaches personalized to the individual user 19 .…”

Section: Introductionmentioning

confidence: 99%

A novel digital approach to describe real world outcomes among patients with constipation

et al. 2021

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Understanding day-to-day variations in symptoms and medication management can be important in describing patient centered outcomes for people with constipation. Patient Generated Health Data (PGHD) from digital devices is a potential solution, but its utility as a tool for describing experiences of people with frequent constipation is unknown. We conducted a virtual, 16-week prospective study of individuals with frequent constipation from an online wellness platform that connects mobile consumer digital devices including wearable monitors capable of passively collecting steps, sleep, and heart rate data. Participants wore a Fitbit monitoring device for the study duration and were administered daily and monthly surveys assessing constipation symptom severity and medication usage. A set of 38 predetermined day-level behavioral activity metrics were computed from minute-level data streams for steps, sleep and heart rate. Mixed effects regression models were used to compare activity metrics between constipation status (irregular or constipated vs. regular day), medication use (medication day vs. non-medication day) and the interaction of medication day with irregular or constipation days, as well as to model likelihood to treat with constipation medications based on daily self-reported symptom severity. Correction for multiple comparisons was performed with the Benjamini–Hochberg procedure for false discovery rate. This study analyzed 1540 enrolled participants with completed daily surveys (mean age 36.6 sd 10.0, 72.8% female, 88.8% Caucasian). Of those, 1293 completed all monthly surveys and 756 had sufficient Fitbit data density for analysis of activity metrics. At a daily-level, 22 of the 38 activity metrics were significantly associated with bowel movement or medication treatment patterns for constipation. Participants were measured to have fewer steps on irregular days compared to regular days (−200 steps, 95% CI [−280, −120]), longer periods of inactivity on constipated days (9.1 min, 95% CI [5.2, 12.9]), reduced total sleep time on irregular and constipated days (−2.4 min, 95% CI [−4.3, −0.4] and −4.0 min, 95% CI [−6.5, −1.4], respectively). Participants reported greater severity of symptoms for bloating, hard stool, difficulty passing, and painful bowel movements on irregular, constipation and medication days compared to regular days with no medication. Interaction analysis of medication days with irregular or constipation days observed small increases in severity compared to non-medication days. Participants were 4.3% (95% CI 3.2, 5.3) more likely to treat with medication on constipated days versus regular. No significant increase in likelihood was observed for irregular days. Daily likelihood to treat increased for each 1-point change in symptom severity of bloating (2.4%, 95% CI [2.0, 2.7]), inability to pass (2.2%, 95% CI [1.4, 3.0]) and incomplete bowel movements (1.3%, 95% CI [0.9, 1.7]). This is the first large scale virtual prospective study describing the association between passively collected PGHD and constipation symptoms and severity at a day-to-day granularity level. Constipation status, irregular or constipated, was associated with a number of activity metrics in steps and sleep, and likelihood to treat with medication increased with increasing severity for a number of constipation symptoms. Given the small magnitude of effect, further research is needed to understand the clinical relevance of these results. PGHD may be useful as a tool for describing real world patient centered experiences for people with constipation.

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Section: Introductionmentioning

confidence: 99%

A novel digital approach to describe real world outcomes among patients with constipation

et al. 2021

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“…[ 27 ] Another study that compared average step counts per day, this time looking at Fitbit Flex and Fitbit Flex 2 estimates for people with MS to a research-grade AG GT 3 X+, found that both of the consumer WPAM overestimated steps per day. The Fitbit Flex overestimated an average of 873 steps per day while the Fitbit Flex 2 overestimated 808 steps per day with the magnitude of overestimation for both monitors increasing for individuals with higher Expanded Disability Status Scale scores [ 28 ]. This study also compared total step counts from the Fitbit Flex to directly observed hand-tallied step counts during a 2-minute walk test and found no systematic bias.…”

Section: Discussionmentioning

confidence: 99%

The Use of Consumer Wearable Physical Activity Monitors in Clinical Populations with Functional L imitations

2021

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Functionally limiting health conditions have a high rate of prevalence worldwide and incur a significant amount of economic burden. Physical activity (PA) can prevent the onset of these conditions and alleviate economic burden by reducing symptoms, but a large portion of these individuals do not engage in health enhancing PA. Consumer wearable physical activity monitors (WPAM) are tools that have become increasingly popular within the past few years and could provide a means to improve PA levels for individuals with health conditions that cause functional limitations. This review reports on the validity of PA outcomes, feasibility and utility, and intervention/promotion effectiveness for consumer WPAM in functionally limited clinical populations. 2250 records from January 2018 to July 2021 were retrieved from PubMed, Web of Science, SPORTDiscus and CINAHL with 656 records being duplicates and 23 records passing a full-text article review. Studies included within the review looked at individuals with osteoarthritis, rheumatoid arthritis, axial spondyloarthritis, multiple sclerosis, Parkinson's disease, ischemic stroke and peripheral arterial disease. The most popular brand of consumer WPAM was Fitbit. Validation studies for consumer WPAM were primarily focused on step counts showing overestimations for daily step counts and over-and under-estimations occurring within shorter time durations depending on step cadence. Wrist worn WPAM are the most feasible for functionally limited clinical populations with widespread utilization for associating clinically relevant outcomes with PA levels but they have limited validation to confirm their accuracy and precision in measurement. Interventions included used a mixture of a WPAM and other behavior change techniques to improve PA levels for clinical populations and show promising effectiveness. Future work is warranted on determining the validity of PA outcomes from WPAM determined to be feasible in select clinical populations and creating interventions looking at which features of a consumer WPAM intervention promote PA.

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“…55 Furthermore, activity trackers are normally worn on the wrist. [56][57][58] Conversely, smartphones and wearable activity trackers are not usually attached to the waist, 16 59-61 hip 62 63 and chest, 17 as was observed in several validation studies. Importantly, it has been shown that step counting error is impacted by wear location, with hip-based devices demonstrating a higher accuracy than wrist-worn devices, 64 while smartphone accuracy changes based on the device, location (waist, arm, hand or bag) and nature of the activity (running or walking).…”

Section: Index Measurementioning

confidence: 99%

Recommendations for determining the validity of consumer wearable and smartphone step count: expert statement and checklist of the INTERLIVE network

et al. 2020

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Consumer wearable and smartphone devices provide an accessible means to objectively measure physical activity (PA) through step counts. With the increasing proliferation of this technology, consumers, practitioners and researchers are interested in leveraging these devices as a means to track and facilitate PA behavioural change. However, while the acceptance of these devices is increasing, the validity of many consumer devices have not been rigorously and transparently evaluated. The Towards Intelligent Health and Well-Being Network of Physical Activity Assessment (INTERLIVE) is a joint European initiative of six universities and one industrial partner. The consortium was founded in 2019 and strives to develop best-practice recommendations for evaluating the validity of consumer wearables and smartphones. This expert statement presents a best-practice consumer wearable and smartphone step counter validation protocol. A two-step process was used to aggregate data and form a scientific foundation for the development of an optimal and feasible validation protocol: (1) a systematic literature review and (2) additional searches of the wider literature pertaining to factors that may introduce bias during the validation of these devices. The systematic literature review process identified 2897 potential articles, with 85 articles deemed eligible for the final dataset. From the synthesised data, we identified a set of six key domains to be considered during design and reporting of validation studies: target population, criterion measure, index measure, validation conditions, data processing and statistical analysis. Based on these six domains, a set of key variables of interest were identified and a ‘basic’ and ‘advanced’ multistage protocol for the validation of consumer wearable and smartphone step counters was developed. The INTERLIVE consortium recommends that the proposed protocol is used when considering the validation of any consumer wearable or smartphone step counter. Checklists have been provided to guide validation protocol development and reporting. The network also provide guidance for future research activities, highlighting the imminent need for the development of feasible alternative ‘gold-standard’ criterion measures for free-living validation. Adherence to these validation and reporting standards will help ensure methodological and reporting consistency, facilitating comparison between consumer devices. Ultimately, this will ensure that as these devices are integrated into standard medical care, consumers, practitioners, industry and researchers can use this technology safely and to its full potential.

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Validation of a consumer-grade activity monitor for continuous daily activity monitoring in individuals with multiple sclerosis

Cited by 17 publications

References 35 publications

A novel digital approach to describe real world outcomes among patients with constipation

A novel digital approach to describe real world outcomes among patients with constipation

The Use of Consumer Wearable Physical Activity Monitors in Clinical Populations with Functional L imitations

Recommendations for determining the validity of consumer wearable and smartphone step count: expert statement and checklist of the INTERLIVE network

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