TY - GEN
T1 - ROAMM
T2 - 18th IEEE International Conference on e-Health Networking, Applications and Services, Healthcom 2016
AU - Nair, Sanjay
AU - Kheirkhahan, Matin
AU - Davoudi, Anis
AU - Rashidi, Parisa
AU - Wanigatunga, Amal A.
AU - Corbett, Duane B.
AU - Manini, Todd M.
AU - Ranka, Sanjay
N1 - Funding Information:
The Metabolic Costs of Daily Activity in Older Adults Study is funded by the National Institutes of Health (NIH) /National Institute on Aging (NIA) (R01AG042525). The research is partially supported by the Claude D. Pepper Older Americans Independence Centers at the University of Florida (1P30AG028740) and University of Florida Informatics Institute.
Publisher Copyright:
© 2016 IEEE.
PY - 2016/11/18
Y1 - 2016/11/18
N2 - Mobile health (mHealth) based on smartphone and smartwatch technology is changing the landscape for how patients and research participants communicate about their health in real time. Flexible control of the different interconnected and frequently communicating mobile devices can provide a rich set of health care applications that can adapt dynamically to their environment. In this paper, we propose a real-time online activity and mobility monitoring (ROAMM) framework consisting of a smart-watch application for data collection, a server for data storage and retrieval as well as online monitoring and administrative tasks. We evaluated this framework to collect actigraphy data on the wrist and used it for feature detection and classification of different tasks of daily living conducted by participants. The information retrieved from the smartwatches yielded high accuracy for sedentary behavior prediction (accuracy = 97.44%) and acceptable performance for activity intensity level estimation (rMSE = 0.67 and R2 = 0.52).
AB - Mobile health (mHealth) based on smartphone and smartwatch technology is changing the landscape for how patients and research participants communicate about their health in real time. Flexible control of the different interconnected and frequently communicating mobile devices can provide a rich set of health care applications that can adapt dynamically to their environment. In this paper, we propose a real-time online activity and mobility monitoring (ROAMM) framework consisting of a smart-watch application for data collection, a server for data storage and retrieval as well as online monitoring and administrative tasks. We evaluated this framework to collect actigraphy data on the wrist and used it for feature detection and classification of different tasks of daily living conducted by participants. The information retrieved from the smartwatches yielded high accuracy for sedentary behavior prediction (accuracy = 97.44%) and acceptable performance for activity intensity level estimation (rMSE = 0.67 and R2 = 0.52).
UR - http://www.scopus.com/inward/record.url?scp=85006515539&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85006515539&partnerID=8YFLogxK
U2 - 10.1109/HealthCom.2016.7749479
DO - 10.1109/HealthCom.2016.7749479
M3 - Conference contribution
AN - SCOPUS:85006515539
T3 - 2016 IEEE 18th International Conference on e-Health Networking, Applications and Services, Healthcom 2016
BT - 2016 IEEE 18th International Conference on e-Health Networking, Applications and Services, Healthcom 2016
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 14 September 2016 through 17 September 2016
ER -