Wearable Technology
Research-grade accelerometers have been established as good sources of data, but their price, and unintuitive setup can make them difficult to deploy. Personal activity trackers have gained popularity in the past years, and are now near-ubiquitous in physical activity contexts. Little is known about their potential for research. The PARCS lab is highly interested in harnessing consumer grade accelerometers for physical activity interventions. Our current projects include:
Asterisks (*) denote an advisory role.
Validity and Reliability of Fitbit Wearable Devices
Background and Purpose: Consumer activity trackers are a growing source of big data for physical activity (PA), and active living research.1 In particular, FitBit consumer wearable devices, are popular, cost-effective activity trackers used to monitor a variety of PA variables such as steps, heart rate, and distance.2 FitBit devices are versatile, and have the potential to longitudinally assess active living behaviors in a variety of settings. However, few studies have evaluated the reliability and validity of newer models with regards to varying activities and intensities across multiple days.
Objectives: This study explores the reliability and validity of the FitBit Blaze activity tracker as a useful tool for active living research.
Methods: Data for this study was collected in Spring 2017. Participants (n=30) were recruited via flyers, website, and word of mouth. Participants wore FitBit Blaze and Actigraph GT9X devices on a non-dominant wrist, and Polar Heart Rate chest strap monitors. Participants were asked to complete six-minute bouts of activity including: treadmill walking, incline walking, jogging, and stair stepping for a total of 24 minutes. Varying intensities were determined using Borg’s Rate of Perceived Exertion (RPE). Activity protocol was replicated across two exercise sessions several days apart. Data were aggregated to 60 second epochs and interclass correlations (ICCs) assessed criterion validity and repeated measures reliability.
Results: Participants were 50% male, had a mean age of 25.7 (SD=3.61), and a mean body mass index (BMI) of 24.5 (SD=2.83). During treadmill exercise, mean walking speed was 2.75 MPH (SD=0.69), and mean jogging speed was 5.37 MPH (SD=1.09). Preliminary results among activity sessions indicate FitBit devices demonstrated excellent reliability for steps (ICC=0.97 95% CI 0.94-0.99). Difficulty syncing FitBit heart rate data has delayed validity analysis. Full validity and reliability results by activity intensity stratified by gender and BMI will be presented at the conference.
Conclusion: This study provides valuable insight into FitBit devices as reliable and valid instruments for PA tracking. Given the popularity of wearable technology, such devices should be further tested as potential research tools for studying long-term active living behaviors.
Implications for Practice and Policy: FitBit devices have the potential to provide big data and offer ongoing insight into active living behaviors.
References
1 Wang, J. B., Cataldo, J. K., Ayala, G. X., Natarajan, L., Cadmus-Bertram, L. A., White, M. M., Pierce, J. P. (2016). Mobile and Wearable Device Features that Matter in Promoting Physical Activity. JournalMTM Journal of Mobile Technology in Medicine, 5(2), 2-11.
2 Chiauzzi, E., Rodarte, C., & Dasmahapatra, P. (2015). Patient-centered activity monitoring in the self-management of chronic health conditions. BMC Medicine, 13(1).
Yates, H.A., Winslow, D.R., Orlosky, J., Ezenwoye, O. Besenyi, G.M. (in press). The future of active living big data: Validity and reliability of wearable activity trackers. Accepted for poster presentation at the 14th Annual Active Living Research Conference, February 11 – February 14, 201, Banff, Alberta, Canada.
Qualitative Exploration of Cybersecurity and Privacy Risks of Fitbit Wearable Devices
Wearable devices for physical activity (PA) monitoring have increased drastically. Early models of wearable devices have shown high validity and reliability and a growing amount of researchers are incorporating them into technology-oriented healthy lifestyle interventions to promote PA and manage chronic conditions. Despite growing popularity, little is known about user perceptions of cyber security or data privacy for wearable devices, or how these perceptions affect device use and long-term adherence, especially within PA research.
This study qualitatively assessed cyber security and privacy concerns of wearable PA devices for research purposes. Data collection took place Spring 2017. Participants (n=30) ages 18-65 completed two educational and testing sessions consisting of device account setup, PA bouts to collect data, and review of data access on an tablet device. Small discussion groups explored perceptions of cybersecurity and privacy risk associated with wearable PA technology. Focus groups are currently being transcribed, coded, and analyzed for emerging themes.
Results will be presented at the conference. This study will advance our understanding of cyber security, privacy, and ethical concerns. Upon completion, we expect to accomplish several key outcomes: gain an in-depth understanding of user perceptions related to cyber security and privacy risk awareness and begin to outline of strategies to address or mitigate concerns for future research. This project will provide valuable information to maximize cyber security, protect confidential data, and allow users increased control for ongoing and planned PA research incorporating wearable technology for health monitoring and intervention.
Yates, H.,* Orlosky, J., Ezenwoye, O., Besenyi, G.M. (2017). Physical activity wearable technology: Assessing security and privacy risks for use in health research. Oral presentation at the American Public Health Association 145th Annual Meeting and Exposition, Nov 4-8, 2017, Atlanta, GA.
Evaluating Privacy and Security Concerns of Wearable Technology for Health Research
Background: Consumer wearable technology for physical activity (PA) monitoring has drastically increased in recent years. In particular, FitBit devices, are popular, cost-effective consumer activity trackers used to monitor a variety of PA variables. Yet, the use of FitBits in research can be challenging for those not familiar with technical aspects. FitBit user data is privatized and access to the data is restricted to the user and developers. The goal of this study is to provide detailed methodology for accessing and downloading FitBit data that enables researchers to incorporate FitBit wearable technology into PA promotion and intervention efforts.
Methods: This study occurred in Spring 2017. Trained staff helped participants create FitBit accounts and complete initial device set up. We registered as a developer with FitBit (https://dev.fitbit.com/) and obtained participant consent. Accessing FitBit’s API we authenticated participant account login information, and enrolled all study participants as Fitbit developers. Modifying publicly available JavaScript code we were able to download data for all participants for the defined study period.
Results: Access granted through the developer portal allowed researchers to download per-minute intraday data into Google Sheets via the Script Editor for the duration of the study. Variables accessed included steps, heart rate, distance, active minutes, calories burned, floors climbed, and sleep as well as user profile information (e.g., height, weight, BMI)
Conclusions: Methodology provided will allow PA researchers to integrate emerging technology into research efforts. PA data access provided through FitBit can be valuable for understanding user activity and developing and evaluating PA interventions.
Patel, S., Orlosky, J., Stewart, J., Coughlin, S.S., Besenyi, G.M. (2017). Consumer wearable devices: Accessing physical activity data for health promotion and intervention research. Oral presentation at the American Public Health Association 145th Annual Meeting and Exposition, Nov 4-8, 2017, Atlanta, GA.