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

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)

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?

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

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

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

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

– EDawson-Andoh@mathematica-mpr.com

• Nick Beyler

– NBeyler@mathematica-mpr.com

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.

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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.