Triaxial accelerometer-based fall detection method using a self-constructing cascade-AdaBoost-SVM classifier

IEEE Journal of Biomedical and Health Informatics

Volumn 17, Issue 2, 2013, Pages 411-419

  Cheng, Wen Chang ^a   Jhan, Ding Mao ^a  

^a CHAOYANG UNIVERSITY OF TECHNOLOGY   (Taiwan)

Author keywords

Feature selection; Signal magnitude area (SMA); Signal magnitude vector (SMV); Sliding window; Weak classifier

Indexed keywords

ACCELEROMETERS; CLASSIFICATION (OF INFORMATION); FEATURE EXTRACTION; SUPPORT VECTOR MACHINES; VECTORS;

ACCELERATION SIGNALS; ADA BOOST CLASSIFIERS; ADABOOST ALGORITHM; SIGNAL MAGNITUDE; SLIDING WINDOW; STRONG CLASSIFIERS; TRIAXIAL ACCELEROMETER; WEAK CLASSIFIERS;

ADAPTIVE BOOSTING;

ACCELEROMETRY; AMBULATORY MONITORING; DEVICES; FALLING; HUMAN; PROCEDURES; SIGNAL PROCESSING; SUPPORT VECTOR MACHINE; ARTICLE; EQUIPMENT; METHODOLOGY;

ACCELEROMETRY; ACCIDENTAL FALLS; HUMANS; MONITORING, AMBULATORY; SIGNAL PROCESSING, COMPUTER-ASSISTED; SUPPORT VECTOR MACHINES;

EID: 84883609061     PISSN: 21682194     EISSN: None     Source Type: Journal    
DOI: 10.1109/JBHI.2012.2237034     Document Type: Article

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