Preliminary concurrent validity of the Fitbit-Zip and ActiGraph activity monitors for measuring steps in people with polymyalgia rheumatica

Chandrasekar, Anish; Hensor, Elizabeth M A; McDermott, Michael; Backhouse, Michael; Harris, Emma

doi:10.1016/j.gaitpost.2018.01.035

Cited by 17 publications

(26 citation statements)

References 38 publications

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“…Activity monitoring devices such as Fitbit provide the user with feedback about their level activity and progress, and present an opportunity to actively reinforce the patient in incremental quota-based gains tailored to each patient’s ability, thereby facilitating physical activity 20. Such devices are showing promising use in patients with chronic illness,21,22 including initial reports of effectiveness among patients with chronic pain 23,24. Our guiding hypothesis is that the most effective and efficient way to sustainably increase emotional and physical function among chronic pain patients is by 1) gradual and quota contingent increases in activity (walking) paired with re-engagement in activities of daily living; 2) monitoring and reinforcing quota contingent activity goals (number of steps) with a digital activity monitoring device (Fitbit)), and 3) teaching mind-body skills to manage pain, and target barriers to engaging in physical activity.…”

Section: Introductionmentioning

confidence: 99%

<p>Development And Early Feasibility Testing Of A Mind-Body Physical Activity Program For Patients With Heterogeneous Chronic Pain; The GetActive Study</p>

Greenberg¹,

Lin²,

Zale³

et al. 2019

JPR

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BackgroundIncreasing physical function is a challenging, yet imperative goal of pain management programs. Physical activity can improve physical function, but uptake is low due to chronic pain misconceptions, poor pain management skills, and doing too much too soon.PurposeTo increase physical function by 1) adapting an evidence-based, group, mind-body program to address the needs of patients with heterogeneous chronic pain and to facilitate individually tailored quota-based pacing with a Fitbit (GetActive with Fitbit) or without it (GetActive) (phase 1), and 2) assessing preliminary feasibility benchmarks (phase 2).MethodsWe followed evidence based frameworks for developing interventions and for early feasibility testing. In phase 1 we conducted 4 focus groups with 22 patients with heterogeneous chronic pain and adapted the mind-body program. In phase 2 we conducted a nonrandomized pilot trial of the 2 programs (N=7 and 6) with qualitative exit interviews.ResultsFocus groups showed high interest in increasing activity, a preference for walking linked to pleasurable activities, using a Fitbit to track number of steps, and learning skills to manage pain and aid with increased activity. Both programs had good to excellent feasibility markers. Participation in both programs was associated with signal of improvements in physical and emotional function, as well as intervention targets. Exit interviews confirmed high satisfaction and suggested modification.ConclusionResults informed subsequent adaptations of the 2 programs and methodology for an ongoing pilot randomized controlled trial (RCT) of the 2 programs, necessary before an efficacy RCT of the 2 programs against an education control.

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Section: Introductionmentioning

confidence: 99%

<p>Development And Early Feasibility Testing Of A Mind-Body Physical Activity Program For Patients With Heterogeneous Chronic Pain; The GetActive Study</p>

Greenberg¹,

Lin²,

Zale³

et al. 2019

JPR

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“…The Actigraph GT3X (Actigraph LLC, Penascola, FL, USA) represents the epitome of scientific accelerometers as it is unobtrusive, low-cost, and its sensitive triaxial accelerometers are capable of storing high-resolution, raw, unfiltered acceleration signals over long durations. The Actigraph monitor has been extensively studied in many situations: the validity for the evaluation of PA in healthy or pathological populations and the comparison with other AT (13–17); used as a gold standard in some studies (18, 19). Despite all these studies, the recent systematic review by Migueles et al (20) conclude that it is necessary to take a cautious approach regarding the accuracy/reliability of Actigraph in estimating the SC in real-life situations as a function of 1-the mainly used positions (wrist and hip) and 2- the age of the subjects.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Step Count Assessed Using Wrist- and Hip-Worn Actigraph GT3X in Free-Living Conditions in Young and Older Adults

et al. 2019

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Background: Walking represents a major component of physical activity (PA), and its restriction could degrade autonomy and quality of life. An important objective for preventive and/or rehabilitative strategies to improve balance and gait in normal and pathological aging conditions is to focus on physical activity. Activity monitors have recently been getting increasingly popular and represent a modern solution to measure—and communicate—PA notably in terms of steps/day. These activity monitors are well-suited for various populations as they can be worn on a variety of locations on the body, including the wrist and the hip (i.e., the two most common locations), in an undifferentiated way according to the manufacturer's instruction. The aim of this study was hence to verify potential differences in step count (SC) by comparing this parameter assessed using wrist- and hip-worn activity trackers over a 24-h period in free-living conditions in young and older adults.Methods: Young adults (n = 22) and older adults (n = 22) voluntarily participated in this study. They were required to wear two commercially-available Actigraph GT3X+ activity monitors simultaneously at two locations recommended by the manufacturer, i.e., one positioned around the wrist and one above the hip, over a 24-h period in free-living conditions. The manufacturer's software was used to obtain estimates of the SC.Results: For both groups, the wrist-worn activity tracker provided significantly higher SC than the hip-worn activity tracker did. For both placements on the body, older adults exhibited significantly lower SC than young adults. Interestingly, for both young and older participants, the difference between both measurements tended to decrease for longer distances.Conclusion: The different estimations of the step count provided by the comparison between two identical Actigraph GT3x on the wrist or the hip during the 24-h observation period in free-living conditions in young and older adults strongly suggests that caution is needed when using total step per day values as an outcome to quantify walking behavior. Probably we can suggest the same caution across implementation of different activity Tracker.

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“…[54,57,58] Chandrasekar found commercial pedometers (Fitbit-Zip and ActiGraph) to be less accurate in patients with altered gait, including lower gait velocity, reduced stride length, longer double-limb support phase and greater self-reported functional impairment, than in healthy subjects. [59] Adding the ActiGraph low-frequency extension improved the accuracy of stair step counts. Gaglani et al found the Fitbit Ultra step count to be more accurate in gaitcompromised patients than the Omron Step Counter HJ-113, the New Lifestyles 2000, or the Nike Fuelband.…”

Section: Fitness-related Indicatorsmentioning

confidence: 99%

Windows into human health through wearables data analytics

Witt

Kellogg

Snyder

et al. 2019

Current Opinion in Biomedical Engineering

119

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Background: Wearable sensors (wearables) have been commonly integrated into a wide variety of commercial products and are increasingly being used to collect and process raw physiological parameters into salient digital health information. The data collected by wearables are currently being investigated across a broad set of clinical domains and patient populations. There is significant research occurring in the domain of algorithm development, with the aim of translating raw sensor data into fitness-or health-related outcomes of interest for users, patients, and health care providers. Objectives: The aim of this review is to highlight a selected group of fitness-and health-related indicators from wearables data and to describe several algorithmic approaches used to generate these higher order indicators. Methods: A systematic search of the Pubmed database was performed with the following search terms (number of records in parentheses): Fitbit algorithm (18), Apple Watch algorithm (3), Garmin algorithm (5), Microsoft Band algorithm (8), Samsung Gear algorithm (2), Xiaomi MiBand algorithm (1), Huawei Band (Watch) algorithm (2), photoplethysmography algorithm (465), accelerometry algorithm (966), ECG algorithm (8287), continuous glucose monitor algorithm (343). The search terms chosen for this review are focused on algorithms for wearable devices that dominated the commercial wearables market between 2014-2017 and that were highly represented in the biomedical literature. A second set of search terms included categories of algorithms for fitness-related and health-related indicators that are commonly used in wearable devices (e.g. accelerometry, PPG, ECG). These papers covered the following domain areas: fitness; exercise; movement; physical activity; step count; walking; running; swimming; energy expenditure; atrial fibrillation; arrhythmia; cardiovascular; autonomic nervous system; neuropathy; heart rate variability; fall detection; trauma; behavior change; diet; eating; stress detection; serum glucose monitoring; continuous glucose monitoring; diabetes mellitus type 1; diabetes mellitus type 2. All studies uncovered through this search on commercially available device algorithms and

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Preliminary concurrent validity of the Fitbit-Zip and ActiGraph activity monitors for measuring steps in people with polymyalgia rheumatica

Cited by 17 publications

References 38 publications

<p>Development And Early Feasibility Testing Of A Mind-Body Physical Activity Program For Patients With Heterogeneous Chronic Pain; The GetActive Study</p>

<p>Development And Early Feasibility Testing Of A Mind-Body Physical Activity Program For Patients With Heterogeneous Chronic Pain; The GetActive Study</p>

Comparison of Step Count Assessed Using Wrist- and Hip-Worn Actigraph GT3X in Free-Living Conditions in Young and Older Adults

Windows into human health through wearables data analytics

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