BibTeX for papers by David Kotz; for complete/updated list see https://www.cs.dartmouth.edu/~kotz/research/papers.html @InProceedings{boateng:geriactive, author = {George Boateng and John A. Batsis and Patrick Proctor and Ryan Halter and David Kotz}, title = {{GeriActive: Wearable App for Monitoring and Encouraging Physical Activity among Older Adults}}, booktitle = {{Proceedings of the IEEE Conference on Body Sensor Networks (BSN)}}, year = 2018, month = {March}, pages = {46--49}, publisher = {IEEE}, copyright = {IEEE}, DOI = {10.1109/BSN.2018.8329655}, URL = {https://www.cs.dartmouth.edu/~kotz/research/boateng-geriactive/index.html}, abstract = {The ability to monitor a person's level of daily activity can inform self-management of physical activity and assist in augmenting behavioral interventions. For older adults, the importance of regular physical activity is critical to reduce the risk of long-term disability. In this work, we present GeriActive, an application on the Amulet wrist-worn device that monitors in real time older adults' daily activity levels (low, moderate and vigorous), which we categorized using metabolic equivalents (METs). The app implements an activity-level detection model we developed using a linear Support Vector Machine (SVM). We trained our model using data from volunteer subjects (n{$=$}29) who performed common physical activities (sit, stand, lay down, walk and run) and obtained an accuracy of 94.3\% with leave-one-subject-out (LOSO) cross-validation. We ran a week-long field study to evaluate the usability and battery life of the GeriActive system where 5 older adults wore the Amulet as it monitored their activity level. Their feedback showed that our system has the potential to be usable and useful. Our evaluation further revealed a battery life of at least 1 week. The results are promising, indicating that the app may be used for activity-level monitoring by individuals or researchers for health delivery interventions that could improve the health of older adults.}, }