Using wearable sensors to measure motor abilities following stroke

Proceedings - BSN 2006: International Workshop on Wearable and Implantable Body Sensor Networks

Volumn 2006, Issue , 2006, Pages 5-8

  Hester, Todd ^a   Hughes, Richard ^a   Sherrill, Delsey M ^a   Knorr, Bethany ^b   Akay, Metin ^c   Stein, Joel ^a   Bonato, Paolo ^a,d  

^a and Red Sox Foundation and Massachusetts General Hospital Home Base Program   (United States)

^b DARTMOUTH COLLEGE   (United States)

^c ARIZONA STATE UNIVERSITY   (United States)

^d HARVARD MIT DIVISION OF HEALTH SCIENCES AND TECHNOLOGY   (United States)

Author keywords

Clinical assessment; Stroke; Wearable sensors

Indexed keywords

CLINICAL ASSESSMENT; STROKE REHABILITATION; WEARABLE SENSORS;

BIOELECTRIC PHENOMENA; BIOSENSORS; BRAIN; MATHEMATICAL MODELS; MEDICAL PROBLEMS; SENSOR DATA FUSION;

NEUROMUSCULAR REHABILITATION;

EID: 33750811624     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/BSN.2006.57     Document Type: Conference Paper

References (6)

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2. National Institute of Neurological Disorders and Stroke (NINDS), Stroke: Hope Through Research, NINDS, Washington, DC, 2004.
3. Center for Disease Control, Morbidity and Mortality Weekly Report, CDC, Atlanta, GA, 2001.
4. V. Pomeroy, A. Pramanik, L. Sykes, J. Richards, and E. Hill, "Agreement between physiotherapists on quality of movement rated via videotape", Clinical Rehabilitation, May 2003, pp. 264-272.
5. IH Witten and E. Frank, Data Mining: Practical machine learning tools and techniques. Morgan Kaufman, San Francisco, 2005.
6. H Akaike, "A New Look at Statistical Model Identification." IEEE Transactions on Automatic Control, IEEE, 1974, pp. 716-722.