Comparing Methods to Identify Wear-Time Intervals for Physical Activity With the Fitbit Charge 2.

There is no established method for processing data from commercially available physical activity trackers. This study aims to develop a standardized approach to defining valid wear time for use in future interventions and analyses. Sixteen African American women (mean age = 62.1 years and mean body mass index = 35.5 kg/m2) wore the Fitbit Charge 2 for 20 days. Method 1 defined a valid day as ≥10-hr wear time with heart rate data. Method 2 removed minutes without heart rate data, minutes with heart rate ≤ mean - 2 SDs below mean and ≤2 steps, and nighttime. Linear regression modeled steps per day per week change. Using Method 1 (n = 292 person-days), participants had 20.5 (SD = 4.3) hr wear time per day compared with 16.3 (SD = 2.2) hr using Method 2 (n = 282) (p < .0001). With Method 1, participants took 7,436 (SD = 3,543) steps per day compared with 7,298 (SD = 3,501) steps per day with Method 2 (p = .64). The proposed algorithm represents a novel approach to standardizing data generated by physical activity trackers. Future studies are needed to improve the accuracy of physical activity data sets.

[1]  G. Tison,et al.  Real-world heart rate norms in the Health eHeart study , 2019, npj Digital Medicine.

[2]  L. Neubeck,et al.  Data management and wearables in older adults: A systematic review. , 2019, Maturitas.

[3]  W. Kraus,et al.  Daily Step Counts for Measuring Physical Activity Exposure and Its Relation to Health , 2019, Medicine and science in sports and exercise.

[4]  Andrea Ancillao,et al.  Accuracy of consumer-level and research-grade activity trackers in ambulatory settings in older adults , 2019, PloS one.

[5]  Kaigang Li,et al.  Assessment of Accuracy of Overall Energy Expenditure Measurements for the Fitbit Charge HR 2 and Apple Watch. , 2019, American journal of health behavior.

[6]  S. Crouter,et al.  Associations between Walk Score and objective measures of physical activity in urban overweight and obese women , 2019, PloS one.

[7]  GREGORY J. WELK,et al.  Standardizing Analytic Methods and Reporting in Activity Monitor Validation Studies , 2019, Medicine and science in sports and exercise.

[8]  E. Losina,et al.  Validation of the Fitbit Charge 2 compared to the ActiGraph GT3X+ in older adults with knee osteoarthritis in free-living conditions , 2019, PloS one.

[9]  Eyal Dassau,et al.  Accuracy of Wrist-Worn Activity Monitors During Common Daily Physical Activities and Types of Structured Exercise: Evaluation Study , 2018, JMIR mHealth and uHealth.

[10]  Clayon B Hamilton,et al.  Accuracy of Fitbit Devices: Systematic Review and Narrative Syntheses of Quantitative Data , 2018, JMIR mHealth and uHealth.

[11]  James Weatherall,et al.  Sleep Tracking and Exercise in Patients With Type 2 Diabetes Mellitus (Step-D): Pilot Study to Determine Correlations Between Fitbit Data and Patient-Reported Outcomes , 2018, JMIR mHealth and uHealth.

[12]  Sheri J. Hartman,et al.  Patterns of Fitbit Use and Activity Levels Throughout a Physical Activity Intervention: Exploratory Analysis from a Randomized Controlled Trial , 2018, JMIR mHealth and uHealth.

[13]  A. LaCroix,et al.  Accelerometer-Measured Physical Activity and Sedentary Behavior in Relation to All-Cause Mortality: The Women's Health Study. , 2018, Circulation.

[14]  Chuen Seng Tan,et al.  Fitbit Charge HR Wireless Heart Rate Monitor: Validation Study Conducted Under Free-Living Conditions , 2017, JMIR mHealth and uHealth.

[15]  Peter Kerkhof,et al.  Determinants for Sustained Use of an Activity Tracker: Observational Study , 2017, JMIR mHealth and uHealth.

[16]  C. Ayers,et al.  Mobile Health Technology Can Objectively Capture Physical Activity (PA) Targets Among African-American Women Within Resource-Limited Communities—the Washington, D.C. Cardiovascular Health and Needs Assessment , 2017, Journal of Racial and Ethnic Health Disparities.

[17]  Brian T Swanson,et al.  Validity of Fitbit’s active minutes as compared with a research-grade accelerometer and self-reported measures , 2017, BMJ Open Sport & Exercise Medicine.

[18]  C. Ayers,et al.  Adherence with physical activity monitoring wearable devices in a community-based population: observations from the Washington, D.C., Cardiovascular Health and Needs Assessment , 2017, Translational behavioral medicine.

[19]  Gearóid ÓLaighin,et al.  When a Step Is Not a Step! Specificity Analysis of Five Physical Activity Monitors , 2017, PloS one.

[20]  Scott E. Crouter,et al.  Step Counting: A Review of Measurement Considerations and Health-Related Applications , 2016, Sports Medicine.

[21]  T. Hastie,et al.  Accuracy in Wrist-Worn, Sensor-Based Measurements of Heart Rate and Energy Expenditure in a Diverse Cohort , 2016, bioRxiv.

[22]  Jacqueline Kerr,et al.  "Spatial Energetics": Integrating Data From GPS, Accelerometry, and GIS to Address Obesity and Inactivity. , 2016, American journal of preventive medicine.

[23]  Diane J. Cook,et al.  Unsupervised detection and analysis of changes in everyday physical activity data , 2016, J. Biomed. Informatics.

[24]  Miao-Ju Hsu,et al.  Accuracy of Wristband Activity Monitors during Ambulation and Activities. , 2016, Medicine and science in sports and exercise.

[25]  Nia Roberts,et al.  Quantifying the Association Between Physical Activity and Cardiovascular Disease and Diabetes: A Systematic Review and Meta‐Analysis , 2016, Journal of the American Heart Association.

[26]  Mary A. Burke,et al.  You can be too thin (but not too tall): Social desirability bias in self‐reports of weight and height , 2016, Economics and human biology.

[27]  Annemarie Koster,et al.  Comparison of Sedentary Estimates between activPAL and Hip- and Wrist-Worn ActiGraph. , 2016, Medicine and science in sports and exercise.

[28]  Gregory J Welk,et al.  The Wild Wild West: A Framework to Integrate mHealth Software Applications and Wearables to Support Physical Activity Assessment, Counseling and Interventions for Cardiovascular Disease Risk Reduction. , 2016, Progress in cardiovascular diseases.

[29]  Leah R. Yingling,et al.  Community Engagement to Optimize the Use of Web-Based and Wearable Technology in a Cardiovascular Health and Needs Assessment Study: A Mixed Methods Approach , 2016, JMIR mHealth and uHealth.

[30]  R. Furberg,et al.  Systematic review of the validity and reliability of consumer-wearable activity trackers , 2015, International Journal of Behavioral Nutrition and Physical Activity.

[31]  L. Cadmus-Bertram,et al.  Use of the Fitbit to Measure Adherence to a Physical Activity Intervention Among Overweight or Obese, Postmenopausal Women: Self-Monitoring Trajectory During 16 Weeks , 2015, JMIR mHealth and uHealth.

[32]  Mark A Tully,et al.  The validation of Fibit Zip™ physical activity monitor as a measure of free-living physical activity , 2014, BMC Research Notes.

[33]  F. Sera,et al.  Quality Control Methods in Accelerometer Data Processing: Defining Minimum Wear Time , 2013, PloS one.

[34]  Leena Choi,et al.  Assessment of wear/nonwear time classification algorithms for triaxial accelerometer. , 2012, Medicine and science in sports and exercise.

[35]  C. Tudor-Locke,et al.  Characteristics of Step-Defined Physical Activity Categories in U.S. Adults , 2012, American journal of health promotion : AJHP.

[36]  J. Tucker,et al.  Physical activity in U.S.: adults compliance with the Physical Activity Guidelines for Americans. , 2011, American journal of preventive medicine.

[37]  Leena Choi,et al.  Validation of accelerometer wear and nonwear time classification algorithm. , 2011, Medicine and science in sports and exercise.

[38]  David R. Bassett,et al.  Pedometer-measured physical activity and health behaviors in U.S. adults. , 2010, Medicine and science in sports and exercise.

[39]  Charles E Matthews,et al.  The effect of social desirability and social approval on self-reports of physical activity. , 2005, American journal of epidemiology.

[40]  Matthew P Buman,et al.  Wearable Technology and Physical Activity in Chronic Disease: Opportunities and Challenges. , 2018, American journal of preventive medicine.

[41]  L. Mâsse,et al.  Physical activity in the United States measured by accelerometer. , 2008, Medicine and science in sports and exercise.