can we use fitbits in our work?
TRANSCRIPT
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
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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)
33Validity
Fe
as
ibilit
y
DiariesSelf-reports (or
parent/teacher reports)
Pedometers
HR monitors
Accelerometers and
other wearables
Direct observation
Ind. Cal.
DLW
Methods for Measuring Physical Activity
44
Methods for Measuring Physical Activity - Examples
Indirect Calorimetry Activity Diaries
Pedometers
Heart Rate Monitors
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?
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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
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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
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Wearables
• Are generally body-worn accessories that allow the
user to interface with information:
– 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
99
Wearables Examples
• Smartwatches: Apple Watch, Moto 360, Pebble
• Activity trackers: Fitbit, Jawbone, Misfit, Xioami
• Optical: Google Glass, Oculus Rift, Samsung Gear VR
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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)
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Biosensing Wearable Examples
• Under Armour, Hexoskin, Polo Tech Shirt, Gymi
Smart Shirt
• Google Contact Lenses
• iRhythm Zio Patch
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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
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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
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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
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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)
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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
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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
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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
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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
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
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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
2222
For More Information
• Ebo Dawson-Andoh
• Nick Beyler
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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.
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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.
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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.