CHI '08 Extended Abstracts on Human Factors in Computing Systems
Accurate activity recognition in a home setting
UbiComp '08 Proceedings of the 10th international conference on Ubiquitous computing
AndWellness: an open mobile system for activity and experience sampling
WH '10 Wireless Health 2010
Monitoring body positions and movements during sleep using WISPs
WH '10 Wireless Health 2010
Using a live-in laboratory for ubiquitous computing research
PERVASIVE'06 Proceedings of the 4th international conference on Pervasive Computing
Power constrained sensor sample selection for improved form factor and lifetime in localized BANs
Proceedings of the conference on Wireless Health
A comparison of mobile patient monitoring systems
HIS'13 Proceedings of the second international conference on Health Information Science
Occupancy Detection from Electricity Consumption Data
Proceedings of the 5th ACM Workshop on Embedded Systems For Energy-Efficient Buildings
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Depression is a major health issue affecting over 21 million American adults that often goes untreated, and even when undergoing treatment it is hard to monitor the effectiveness of the treatment. To address these issues, we have created a real-time depression monitoring system for the home. This system runs 24/7 and can potentially detect the early signs of a depression episode, as well track progress managing a depressive illness. A cohesive set of integrated wireless sensors, a touch screen station, mobile device, and associated software deliver the above capabilities. The data collected are multi-modal, spanning a number of different behavioral domains including sleep, weight, activities of daily living, and speech prosody. The reports generated by this aggregated data across multiple behavioral domains are aimed to provide caregivers with more accurate and thorough information about the client's current functioning, thus helping in their diagnostic assessment and therapeutic treatment planning as well for patients in the management and tracking of their symptoms. We present data of a case study showing the value of the system, deployed over a period of two weeks in a home during a depressive episode. Larger scale studies are planned for the future.