Can We Use Fitbits in Our Work?
- 1. Can We Use Fitbits in Our Project Work? Presentation to the Nutrition/Obesity/Physical Activity Affinity Group Using Wearable Technologies as Data Collection Tools Ebo Dawson-Andoh • Nick Beyler February 3, 2016
- 2. 22 Outline • Lead-in: methods for measuring physical activity • Biosensors, wearables, and biosensing wearables • Benefits • Challenges and limitations • Recommendations for implementing wearable technology in data collection • On the horizon – (Sensor working group, outreach)
- 3. 33 Validity Feasibility Diaries Self-reports (or parent/teacher reports) Pedometers HR monitors Accelerometers and other wearables Direct observation Ind. Cal. DLW Methods for Measuring Physical Activity
- 4. 44 Methods for Measuring Physical Activity - Examples Indirect Calorimetry Activity Diaries Pedometers Heart Rate Monitors
- 5. 55 Project Work Involving Physical Activity • Playworks – Self-reports and teacher reports – Accelerometers – Direct observation • HCZ Healthy Harlem – Self-reports – Direct observation • HCSDB Child Health Survey – Self-reports and parent reports • Future work? – Wearables?
- 6. 66 Biosensors • Portable device that allows user to measure or monitor specific physiological parameters such as: – Heart rate – Body temperature – VO2 (oxygen consumption) • Take one-time measurements and require some voluntary action on the user’s part in order to initiate readings
- 7. 77 Biosensor Examples • Scanadu Scout: measures user vital signs (temperature, blood pressure, heart rate, blood oxygenation, etc.) • Breezing: measures and tracks metabolism • Withings Thermo: wireless thermometer
- 8. 88 Wearables • Are generally body-worn accessories that allow the user to interface with information: – Email – Notifications – Internet search – Location data • Can be worn on various parts of the body • Incorporate practical functions and features while also exchanging data with other devices • Represent a broad category of devices
- 9. 99 Wearables Examples • Smartwatches: Apple Watch, Moto 360, Pebble • Activity trackers: Fitbit, Jawbone, Misfit, Xioami • Optical: Google Glass, Oculus Rift, Samsung Gear VR
- 10. 1010 Biosensing Wearables • Integrate the features and functionality of biosensors and wearables • Provide users with continuous health measurements and/or fitness data • Serves as an umbrella for a wide array of technologies: – Activity trackers – Smartwatches – Smart clothing – Dermal patches – Contact lenses • Activity trackers are the most well-known biosensing wearables and have shown considerable adoption rates (approximately 3.3 M fitness bands and activity trackers sold between April 2013 and March 2014 according to the NPD Group)
- 11. 1111 Biosensing Wearable Examples • Under Armour, Hexoskin, Polo Tech Shirt, Gymi Smart Shirt • Google Contact Lenses • iRhythm Zio Patch
- 12. 1212 Benefits • Easier to collect physical activity data – Much more feasible than direct observation or direct/indirect calorimetry – After initial setup, little need for in-person follow-up • Bluetooth capable activity monitors may lessen data entry burden and increase compliance due to auto sync feature (Newton et al.) • Data can be instantly uploaded • Relatively low cost • Small and unobtrusive
- 13. 1313 Challenges - Validity and Reliability • Technology is relatively new but an increasing number of studies have been investigating the validity and reliability of their measurements • With the exception of Fitbit, Jawbone, and a few other research grade sensors, few have been thoroughly tested • Noah et al. found the Fitbit Tracker and Fitbit Ultra to be reliable and valid for measuring over-ground energy expenditure • Additional research will provide more data on how valid and reliable these devices are
- 14. 1414 Challenges - Data Security • Device security varies widely and depends on a number of variables: – Mobile device lock screen security (e.g., passcode, PIN, pattern, fingerprint) – Management of web portal login information – Management of hardware when not in use • Most devices upload data to an online database – This requires users to set up accounts with unique logins – Many require passwords that adhere to varying of password strength regulations – Must use the same credentials to access their data from companion apps
- 15. 1515 Challenges - Battery Life • The majority of wearable devices run on rechargeable batteries (exceptions: Misfit Shine, MoovNow) • Battery technology lags behind the tenants of Moore’s Law (Steve Brown, Intel Innovation Strategist) – Results in disproportionate advances between battery capacity and device processing power – Is a significant limiting factor for most modern technology • Many wearable devices range in battery life – Anywhere from 24 hours to 5 - 7 days (rechargeable devices) – 4 – 6 months (replaceable batteries)
- 16. 1616 Challenges - Battery Life Continued • Participants must pay attention to device battery levels – It would be very difficult for the study team know that a participant’s device died – Missing data would indicate that a participant’s device may be dead but this knowledge would not be in real time • A dead device could equal hours, if not days of lost data
- 17. 1717 Challenges - Synchronization • Devices have to be synced with a mobile device to upload data • Many devices can be set to automatically sync with a mobile device via Bluetooth • Device must be in the proximity of a mobile device • Most devices maintain a lengthy history of recorded data but regular synchronization is recommended – All Fitbit trackers store up to seven days of data – Jawbone UP stores up to nine months of data – Misfit Shine stores about a month of data
- 18. 1818 Challenges - Synchronization Continued • Auto sync functionality allows for automatic data collection around the clock – Is a good backup • It is still advised that devices be purposefully synced daily
- 19. 1919 Challenges - Accessibility • Participants must wear devices at all times to collect measurements • Likely possibility that participants could forget to wear device – Loss of data • Should also take into consideration how comfortable devices are to wear for extended periods of time
- 20. 2020 Recommendations • Validity and Reliability: – Thoroughly review the literature – Test devices in-house • Data Security: – Singer and Perry (2015) suggest clearly communicating what data are being collected and shared, consider restricting the ability to share further, clearly explaining the consequences of sharing data through a social network, explaining the parameters of aggregated data • Training for participants should include a thorough briefing on: – Data security, strong password creation, password management, device management – Establishing best practices for maintaining battery levels – Setting reminders to sync devices – Ensuring devices is worn at all times during data collection
- 21. 2121 On the Horizon • Kristen Purcell is leading sensor working group on behalf of the SIS technology group. – Investigating the use of these technologies across our current work and think about opportunities to build research functionality around – Including sensor technology as part of a broader data collection tool or platform that links it to other key data – Interested individuals can reach out to Kristen about joining • Other thoughts and suggestions? – What other metrics would be useful indicators? – What data collection needs aren’t being met by tools and platforms? • Outreach to new and existing clients – Foundations – State and Federal agencies
- 22. 2222 For More Information • Ebo Dawson-Andoh – EDawson-Andoh@mathematica-mpr.com • Nick Beyler – NBeyler@mathematica-mpr.com
- 23. 2323 References • Bai, Y., Welk, G. J., Nam, Y. H., Lee, J. A., Lee, J. M., Kim, Y., & Dixon, P. M. (2015). Comparison of Consumer and Research Monitors under Semistructured Settings. Medicine and Science in Sports and Exercise. In press. • Beyler, N., Bleeker, M., James-Burdumy, S., Fortson, J., & Benjamin, M. (2014). The Impact of Playworks on Students’ Physical Activity During Recess: Findings from a Randomized Controlled Trial. Preventive Medicine, 69, S20-S26. • Dannecker, K. L., Sazonova, N. A., Melanson, E. L., Sazonov, E. S., & Browning, R. C. (2013). A comparison of energy expenditure estimation of several physical activity monitors. Medicine and Science in Sports and Exercise, 45(11), 2105-2112. • Evenson, K.R., Goto, M. M., & Furberg, R. D. (2015). Systematic review of the validity and reliability of consumer-wearable activity trackers. International Journal of Behavioral Nutrition and Physical Activity, 12, 159. • Ferguson, T., Rowlands, A. V., Olds, T., & Maher, C. (2015). The Validity of Consumer-Level, Activity Monitors in Healthy Adults Worn in Free-Living Conditions: A Cross-Sectional Study. International Journal of Behavioral Nutrition and Physical Activity, 12, 42. • Granado-Font, E., Flores-Mateo, G., Sorli-Aguilar, M., Montana-Carreras, X., Ferre-Grau, C., Barrera-Uriarte, M., Oriol-Colominas, E., Rey-Renones, C., Caules, L., & Satue-Gracia, E. (2015). Effectiveness of a Smartphone Application and Wearable Device for Weight Loss in Overweight or Obese Primary Care Patients: Protocol for a Randomised Controlled Trial. BMC Public Health, 15(1), 531.
- 24. 2424 References Continued • Howard, C. (2015). Widespread Use of Wearable Technology. Military & Aerospace Electronics, retrieved from: http://www.militaryaerospace.com/articles/print/volume- 26/issue-9/technology-focus/widespread-use-of-wearable-technology.html • Huberty, J., Ehlers, D. K., Kurka, J., Ainsworth, B., & Buman, M. (2015). Feasibility of Three Wearable Sensors for 24 Hour Monitoring in Middle-Aged Women. BMC Women’s Health, 15(1), 1. • Lee, V. R., Drake, J., & Williamson, K. (2015). Let’s Get Physical: K-12 Students Using Wearable Devices to Obtain and Learn About Data from Physical Activities. TechTrends, 59(4), 46-53. • Miller, J. D., Najafi, B., & Armstrong, D. G. (2015). Clinically-Oriented Wearables for the DM Population. Retrieved from http://www.podiatrym.com/pdf/2015/11/Miller1115web.pdf. • Newton Jr, R. L., Marker, A. M., Allen, H. R., Machtmes, R., Han, H., Johnson, W. D., Schuna, J. M., Broyles, S. T., Tudor-Locke, C., & Church, T. S. (2014). Parent-Targeted Mobile Phone Intervention to Increase Physical Activity in Sedentary Children: Randomized Pilot Trial. JMIR mHealth and uHealth, 2(4), e48. • Noah, J. A., Spierer, D. K., Gu, J., & Bronner, S. (2013). Comparison of steps and energy expenditure assessment in adults of Fitbit Tracker and Ultra to the Actical and indirect calorimetry. Journal of Medical Engineering & Technology, 37(7), 456-462. Looks a bit strange with the big space between the text and web link.
- 25. 2525 References Continued • Singer, R. W., & Perry, A. J. (2015). Wearables: The Well-Dressed Privacy Policy. Intellectual Property & Technology Law Journal, 27(7), 24-27. • Sirard, J. R., & Pate, R. R. (2001). Physical Activity Assessment in Children and Adolescents. Sports Medicine, 31(6), 439-454. • Spierer, D. K., Hagins, M., Rundle, A., & Pappas, E. (2011). A comparison of energy expenditure from the Actiheart and Actical physical activity monitors during low intensity activities, walking, and jogging. European Journal of Applied Physiology, 111(4), 659-667. • Vanhelst, J., Hurdiel, R., Mikulovic, J., Bui-Xuan, G., Fardy, P., Theunynck, Beghin, L. (2012). Validation of the Vivago Wrist-Worn Accelerometer in the Assessment of Physical Activity. BMC Public Health, 12(1), 690.