Quantitative falls risk estimation through multi-sensor assessment of standing balance

Physiological Measurement

Volumn 33, Issue 12, 2012, Pages 2049-2063

  Greene, Barry R ^a,b   McGrath, Denise ^a,c   Walsh, Lorcan ^a   Doheny, Emer P ^a,b   McKeown, David ^a   Garattini, Chiara ^a   Cunningham, Clodagh ^a,d   Crosby, Lisa ^a,d   Caulfield, Brian ^a,e   Kenny, Rose A ^a,d  

^a Technology Research for Independent Living (TRIL)   (Ireland)

^b Intel Research Cambridge Lab   (United Kingdom)

^c UNIVERSITY OF ULSTER   (United Kingdom)

^d ST JAMES S HOSPITAL   (Ireland)

^e UNIVERSITY COLLEGE DUBLIN   (Ireland)

Author keywords

balance; Falls; falls risk estimation; inertial sensor; pressure sensor; support vector machine (SVM)

Indexed keywords

CLASSIFICATION (OF INFORMATION); INERTIAL NAVIGATION SYSTEMS; RISK ASSESSMENT; RISK PERCEPTION; WEARABLE SENSORS;

CLASSIFICATION ACCURACY; FALL; FALL RISK; FALL RISK ESTIMATION; INERTIAL SENSOR; MEAN CLASSIFICATION; OLDER ADULTS; RISK ESTIMATION; SUPPORT VECTOR MACHINE; SUPPORT VECTORS MACHINE;

SUPPORT VECTOR MACHINES;

EID: 84869166963     PISSN: 09673334     EISSN: 13616579     Source Type: Journal    
DOI: 10.1088/0967-3334/33/12/2049     Document Type: Article

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