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WMCSA
2008
IEEE

HealthSense: classification of health-related sensor data through user-assisted machine learning

9 years 21 days ago
HealthSense: classification of health-related sensor data through user-assisted machine learning
Remote patient monitoring generates much more data than healthcare professionals are able to manually interpret. Automated detection of events of interest is therefore critical so that these points in the data can be marked for later review. However, for some important chronic health conditions, such as pain and depression, automated detection is only partially achievable. To assist with this problem we developed HealthSense, a framework for real-time tagging of health-related sensor data. HealthSense transmits sensor data from the patient to a server for analysis via machine learning techniques. The system uses patient input to assist with classification of interesting events (e.g., pain or itching). Due to variations between patients, sensors, and condition types, we presume that our initial classification is imperfect and accommodate this by incorporating user feedback into the machine learning process. This is done by occasionally asking the patient whether they are experiencing t...
Erich P. Stuntebeck, John S. Davis II, Gregory D.
Added 01 Jun 2010
Updated 01 Jun 2010
Type Conference
Year 2008
Where WMCSA
Authors Erich P. Stuntebeck, John S. Davis II, Gregory D. Abowd, Marion Blount
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