Specific Aims. Development and Acceptability of an Ambient In-Home Activity Assessment Tool for Stroke Stroke is the leading cause of serious, long-term disability in the United States . Every year, approximately 800,000 people experience a new or recurrent stroke . Due to advances in acute neurological care, nearly 85% survive and many live with the […]
Sensing technologies hold enormous potential for early detection of health changes that can dramatically affect the aging experience. Embedded health assessment can enable functional independence, improve self-management of chronic or acute conditions, and thus, improve quality of life
Sensing technologies hold enormous potential for detecting and tracking health changes that can dramatically affect the aging experience. Embedded health assessment can improve management of chronic or acute conditions, and thus, improve quality of life. Problems in chronic disease management are often the cause of losing independence for aging Americans.
Extracting information from the sensors installed in the homes of elderly pose a unique set of challenges. Add to it the short amount of time the clinicians and nurses have to analyze this data, and the problem becomes more complicated. The ongoing work in this project focuses on development of algorithms to glean information from in-home sensor data and then presenting it in the form of textual summaries using Natural Language Generation techniques.