Activity identification using body-mounted sensors - A review of classification techniques

Physiological Measurement

Volumn 30, Issue 4, 2009, Pages

  Preece, Stephen J ^a   Goulermas, John Y ^b   Kenney, Laurence P J ^a   Howard, Dave ^a   Meijer, Kenneth ^c   Crompton, Robin ^b  

^a UNIVERSITY OF SALFORD   (United Kingdom)

^b UNIVERSITY OF LIVERPOOL   (United Kingdom)

^c MAASTRICHT UNIVERSITY   (Netherlands)

Author keywords

Activity monitoring; Classification; Fall detection; Machine learning

Indexed keywords

CLASSIFICATION (OF INFORMATION); CONTINUOUS TIME SYSTEMS; FALL DETECTION; LEARNING SYSTEMS;

ACTIVITY MONITORING; ACTIVITY PROFILING; BODY MOUNTED SENSORS; BODY-WORN SENSORS; CLASSIFICATION TECHNIQUE; FALL DETECTION; HUMAN MOVEMENTS; PROFILING SYSTEMS; SENSING TECHNOLOGY; SENSORS DATA;

WEARABLE SENSORS;

ARTIFICIAL NEURAL NETWORK; AUTOMATION; BAYES THEOREM; BIOMEDICAL ENGINEERING; CLASSIFICATION; DECISION TREE; FREQUENCY ANALYSIS; FUZZY LOGIC; MACHINE LEARNING; MEDICAL TECHNOLOGY; MONITORING; NORMAL DISTRIBUTION; PRIORITY JOURNAL; PROBABILITY; REVIEW; SENSOR; SUPPORT VECTOR MACHINE;

EID: 65249157400     PISSN: 09673334     EISSN: 13616579     Source Type: Journal    
DOI: 10.1088/0967-3334/30/4/R01     Document Type: Review

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