Human fall detection on embedded platform using depth maps and wireless accelerometer

Computer Methods and Programs in Biomedicine

Volumn 117, Issue 3, 2014, Pages 489-501

  Kwolek, Bogdan ^a   Kepski, Michal ^b  

^a AGH UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Poland)

^b UNIVERSITY OF RZESZÓW   (Poland)

Author keywords

Assistive technology; Depth image analysis; Fall detection; Sensor technology for smart homes

Indexed keywords

ALARM SYSTEMS; AUTOMATION; COSTS; ERRORS; INTELLIGENT BUILDINGS;

ASSISTIVE TECHNOLOGY; DEPTH IMAGE; DESIGN AND IMPLEMENTS; FALL DETECTION; SMART HOMES; SVM-BASED CLASSIFIERS; TRIAXIAL ACCELEROMETER; WIRELESS ACCELEROMETERS;

ACCELEROMETERS;

ACCELERATION; ACCELEROMETER; ACCELEROMETRY; ADULT; AGED; ALARM MONITORING; ALGORITHM; ARTICLE; ASSISTIVE TECHNOLOGY; BODY MOVEMENT; CLASSIFIER; CLINICAL ARTICLE; DAILY LIFE ACTIVITY; FALL DETECTION SYSTEM; FALLING; HUMAN; IMAGE ANALYSIS; KINECT SENSOR; MATHEMATICAL MODEL; MOTION; MOTION ANALYSIS SYSTEM; MOTION SENSING DEVICE; PHYSICAL ACTIVITY; PREDICTIVE VALUE; PRIVACY; SENSOR; SIGNAL PROCESSING; SUNLIGHT; SUPPORT VECTOR MACHINE; VIDEORECORDING; AMBULATORY MONITORING; CONSTRUCTION WORK AND ARCHITECTURAL PHENOMENA; DEVICES; MIDDLE AGED; MOVEMENT (PHYSIOLOGY); PREVENTION AND CONTROL; PROCEDURES; REPRODUCIBILITY;

ACCELEROMETRY; ACCIDENTAL FALLS; ACTIVITIES OF DAILY LIVING; ADULT; FACILITY DESIGN AND CONSTRUCTION; HUMANS; MIDDLE AGED; MONITORING, AMBULATORY; MOVEMENT; REPRODUCIBILITY OF RESULTS; SUPPORT VECTOR MACHINES;

EID: 84909641818     PISSN: 01692607     EISSN: 18727565     Source Type: Journal    
DOI: 10.1016/j.cmpb.2014.09.005     Document Type: Article

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