in physical activity research, and step-based physical activity goals are increasingly popularized, for example, 10,000 steps/day ( Bassett, Toth, LaMunion, & Crouter, 2017 ). The growth and adoption of wearable technologies (including research-grade accelerometers, consumer-grade wearable devices
Catrine Tudor-Locke and Elroy J. Aguiar
James W. Navalta, Jeffrey Montes, Nathaniel G. Bodell, Charli D. Aguilar, Ana Lujan, Gabriela Guzman, Brandi K. Kam, Jacob W. Manning and Mark DeBeliso
, Sattar, & Lean, 2017 ). In order for individuals to truly attain their step goals, the ability to accurately determine step count becomes important. Wearable technology was rated as the top fitness trend the past two years ( Thompson, 2015 , 2016 ), and this tendency is expected to grow as the use of
Charlotte L. Edwardson, Melanie Davies, Kamlesh Khunti, Thomas Yates and Alex V. Rowlands
Global sales of wearable technology are increasing substantially year on year, with 32 million units sold in 2014, 72 million in 2015, and over 100 million in 2016 (Statista Website [Internet], 2017a ). Health and fitness trackers make up more than one-third of this wearable technology market
Emma E. Sypes, Genevieve Newton and Zakkoyya H. Lewis
and enhanced, and in doing so, these devices contribute to the billion-dollar market of wearable technologies. 5 Given the substantial evidence concluding that EAMSs are valid tools for measuring activity levels, 6 , 7 the next step is to determine how they may influence user’s PA levels and promote
Joseph M. Stock, Ryan T. Pohlig, Matthew J. Botieri, David G. Edwards and Gregory M. Dominick
to modify existing algorithms and make changes to the measurement properties and features to any Fitbit device without warning. Thus, the rapid pace in which wearable technology is advancing, combined with a persistent lack of measurement transparency continues to hinder the ability to disseminate
Kayla J. Nuss, Joseph L. Sanford, Lucas J. Archambault, Ethan J. Schlemer, Sophie Blake, Jimikaye Beck Courtney, Nicholas A. Hulett and Kaigang Li
.A. , Navalta , J.W. , Fountaine , C.J. , & Reece , J.D. ( 2018 ). Current State of Commercial Wearable Technology in Physical Activity Monitoring 2015–2017 . Retrieved from https://digitalcommons.wku.edu/cgi/viewcontent.cgi?article=2315&context=ijes 29541338 Burke , L.E. , Wang , J. , & Sevick , M
Gregory Knell, Deborah Salvo, Kerem Shuval, Casey Durand, Harold W. Kohl III and Kelley P. Gabriel
Recent technological advances allow for field-based data collection of accelerometers in community-based studies. Mail-based administration can markedly reduce the cost and logistic challenges and burden associated with in-person data collection. It necessitates, however, other resources, such as phone calls and mailed reminder prompts, to increase protocol compliance and data recovery. Additionally, lost accelerometers can impact the study’s budget and its internal validity due to missing data. In this article, we present an applied methodological approach used to define thresholds (or cutoff points) at which pursuing unreturned accelerometers is a worthwhile versus futile pursuit. This methodological approach was designed, specifically, to maximize scalability across multiple sectors. We used data from an on-going study that administered accelerometers through the mail to illustrate and encourage investigators to replicate the approach for use in their own studies. In heterogeneous study samples, investigators might consider repeating this approach by study-relevant strata to refine thresholds and improve the return percentages of data collection instruments, minimize the potential missing data, and optimize study staff time and resources.
Alexander H.K. Montoye, John Vusich, John Mitrzyk and Matt Wiersma
Background: Consumer-based activity monitors use accelerometers to estimate Calories (kcals), but it is unknown if monitors measuring heart rate (HR) use HR in kcal prediction. Purpose: Determine if there is a difference in kcal estimations in Fitbits measuring HR compared to those not measuring HR. Methods: Participants (n = 23) wore five Fitbits and performed nine activities for five minutes each, split into four groupings (G1: sitting, standing, cycling 50–150W; G2: level (0%) and inclined (10%) walking at 1.1 m/s; G3: level (0%) and inclined (10%) walking at 1.4 m/s; G4: level (0%) and inclined (3%) jogging at 2.2–4.5 m/s) in the laboratory. Three Fitbits (Blaze, Charge HR, Alta HR) assessed steps, HR, and kcals, and two Fitbits (Alta, Flex2) assessed steps and kcals. Steps, HR, and kcals data from the Fitbits were compared to criterion measures and between Fitbits measuring HR and Fitbits without HR. Results: Fitbits with HR had significantly higher kcal predictions (10.5–23.8% higher, p < .05) during inclined compared to level activities in G2–G4, whereas Fitbits without HR had similar kcal estimates between level and inclined activities. Mean absolute percent errors for kcal predictions were similar for Fitbits measuring HR (33.7–38.3%) and Fitbits without HR (32.4–36.6%). Conclusion: Fitbits measuring HR appear to use HR when predicting kcals. However, kcal prediction accuracies were similarly poor compared to Fitbits without HR compared to criterion measures.
Sheri J. Brock, Danielle Wadsworth, Nikki Hollett and Mary E. Rudisill
The School of Kinesiology at Auburn University is using Movband Technology to support online learning in their physical activity program. Active Auburn is a 2-hr credit course that encourages students (n = 2,000/year) to become physically active through online instruction and tracking physical activity using Movband technology. Movband technology allows for uploading and monitoring group physical activity data. The implementation of this technology has allowed the School of Kinesiology to: (a) promote physical activity on our campus, (b) serve a large number of students, (c) reduce demand on classroom/physical activity space, and (d) promote our research and outreach scholarship as well, by collecting physical activity profiles for students enrolled in the course. Students report they enjoy the course and that they appreciate the “freedom to exercise” when it best fits into their schedule. This course generates considerable revenue to support course instruction and much more for the School of Kinesiology.
David R. Bassett, Patty S. Freedson and Dinesh John
( International Data Corp., 2017 ). The growth in the number of research publications about Fitbit is increasing exponentially (Figure 1 ). The global wearable-technology market, including activity trackers, is projected to grow from over $30 billion in 2016 to over $150 billion in 2026 ( CISION PR Newswire