mHealth and Aging

mHealth and Aging

mHealth and Aging

With aging comes increased burden of chronic disease. A successful transition to a sustainable health care system would require older adults and their caregivers to carry out routine care at home or in the community. This much needed patient/caregiver empowerment, as well as seamless integration with health care providers when needed, can be facilitated by data technologies. Mobile health, or more commonly known as mHealth, leverages mobile devices and sensors to collect health data from everyday lives outside of hospitals and clinics. When integrated with machine learning and artificial intelligence, mHealth can be an ideal solution for continuous health monitoring in older adults as well as supporting aging-in-place. Toward these goals, we are developing machine learning models based on wearable data that can track and predict frailty and fall risk.


Related Publications

mHealth

M. Sultana, M. Al-Jefri, and J. Lee. Using machine learning and smartphone and smartwatch data to detect emotional states and transitions: an exploratory study. JMIR mHealth and uHealth, 8(9):e17818, September 2020.

Aging

Data for Healthy Aging (D4HA) Working Group. Mobile technology and data-informed approaches for healthy aging and aging-in-place, [Position Paper], October 2020.

Aging
Pub1

B. Y. Kim, A. Sharafoddini, N. Tran, E. Y. Wen, and J. Lee. Consumer mobile apps for potential drug-drug interaction check: systematic review and content analysis using the mobile app rating scale (MARS). JMIR mHealth and uHealth, 6(3):e74, March 2018.

Pub3

B. Kim and J. Lee. Smart devices for older adults managing chronic disease: a scoping review. JMIR mHealth and uHealth, 5(5):e69, May 2017.

Pub2

A. Puri, B. Kim, O. Nguyen, P. Stolee, J. Tung, and J. Lee. User acceptance of wrist-worn activity trackers among community-dwelling older adults: mixed method study. JMIR mHealth and uHealth, 5(11):e173, November 2017.


Funded By

AgeWell