TY - JOUR
T1 - Methodology for establishing a community-wide life laboratory for capturing unobtrusive and continuous remote activity and health data
AU - Kaye, Jeffrey
AU - Reynolds, Christina
AU - Bowman, Molly
AU - Sharma, Nicole
AU - Riley, Thomas
AU - Golonka, Ona
AU - Lee, Jonathan
AU - Quinn, Charlie
AU - Beattie, Zachary
AU - Austin, Johanna
AU - Seelye, Adriana
AU - Wild, Katherine
AU - Mattek, Nora
N1 - Funding Information:
The research described here was supported by grants from the National Institutes of Health, National Institute on Aging (U2CAG054397, P30 AG024978, P30 AG008017, R01 AG042191, R01 AG024059), Intel, the Foundation for the National Institutes of Health and the Robert Wood Johnson Foundation.
Publisher Copyright:
© 2018 Journal of Visualized Experiments.
PY - 2018/7/27
Y1 - 2018/7/27
N2 - An end-to-end suite of technologies has been established for the unobtrusive and continuous monitoring of health and activity changes occurring in the daily life of older adults over extended periods of time. The technology is aggregated into a system that incorporates the principles of being minimally obtrusive, while generating secure, privacy protected, continuous objective data in real-world (home-based) settings for months to years. The system includes passive infrared presence sensors placed throughout the home, door contact sensors installed on exterior doors, connected physiological monitoring devices (such as scales), medication boxes, and wearable actigraphs. Driving sensors are also installed in participants' cars and computer (PC, tablet or smartphone) use is tracked. Data is annotated via frequent online self-report options that provide vital information with regard to the data that is difficult to infer via sensors such as internal states (e.g., pain, mood, loneliness), as well as data referent to activity pattern interpretation (e.g., visitors, rearranged furniture). Algorithms have been developed using the data obtained to identify functional domains key to health or disease activity monitoring, including mobility (e.g., room transitions, steps, gait speed), physiologic function (e.g., weight, body mass index, pulse), sleep behaviors (e.g., sleep time, trips to the bathroom at night), medication adherence (e.g., missed doses), social engagement (e.g., time spent out of home, time couples spend together), and cognitive function (e.g., time on computer, mouse movements, characteristics of online form completion, driving ability). Change detection of these functions provides a sensitive marker for the application in health surveillance of acute illnesses (e.g., viral epidemic) to the early detection of prodromal dementia syndromes. The system is particularly suitable for monitoring the efficacy of clinical interventions in natural history studies of geriatric syndromes and in clinical trials.
AB - An end-to-end suite of technologies has been established for the unobtrusive and continuous monitoring of health and activity changes occurring in the daily life of older adults over extended periods of time. The technology is aggregated into a system that incorporates the principles of being minimally obtrusive, while generating secure, privacy protected, continuous objective data in real-world (home-based) settings for months to years. The system includes passive infrared presence sensors placed throughout the home, door contact sensors installed on exterior doors, connected physiological monitoring devices (such as scales), medication boxes, and wearable actigraphs. Driving sensors are also installed in participants' cars and computer (PC, tablet or smartphone) use is tracked. Data is annotated via frequent online self-report options that provide vital information with regard to the data that is difficult to infer via sensors such as internal states (e.g., pain, mood, loneliness), as well as data referent to activity pattern interpretation (e.g., visitors, rearranged furniture). Algorithms have been developed using the data obtained to identify functional domains key to health or disease activity monitoring, including mobility (e.g., room transitions, steps, gait speed), physiologic function (e.g., weight, body mass index, pulse), sleep behaviors (e.g., sleep time, trips to the bathroom at night), medication adherence (e.g., missed doses), social engagement (e.g., time spent out of home, time couples spend together), and cognitive function (e.g., time on computer, mouse movements, characteristics of online form completion, driving ability). Change detection of these functions provides a sensitive marker for the application in health surveillance of acute illnesses (e.g., viral epidemic) to the early detection of prodromal dementia syndromes. The system is particularly suitable for monitoring the efficacy of clinical interventions in natural history studies of geriatric syndromes and in clinical trials.
KW - Aging
KW - Aging in place
KW - Independent living
KW - Pervasive computing
KW - Smart home
KW - Technology
KW - Unobtrusive monitoring
UR - http://www.scopus.com/inward/record.url?scp=85054311322&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85054311322&partnerID=8YFLogxK
U2 - 10.3791/56942
DO - 10.3791/56942
M3 - Article
C2 - 30102277
AN - SCOPUS:85054311322
SN - 1940-087X
VL - 2018
JO - Journal of Visualized Experiments
JF - Journal of Visualized Experiments
IS - 137
M1 - e56942
ER -