Wearable pendant device monitoring using new wavelet-based methods shows daily life and laboratory gaits are different

Medical and Biological Engineering and Computing

Volumn 54, Issue 4, 2016, Pages 663-674

  Brodie, Matthew A D ^a   Coppens, Milou J M ^a   Lord, Stephen R ^a   Lovell, Nigel H ^a   Gschwind, Yves J ^a   Redmond, Stephen J ^a   Del Rosario, Michael Benjamin ^a   Wang, Kejia ^a   Sturnieks, Daina L ^a   Persiani, Michela ^a   Delbaere, Kim ^a  

^a UNIVERSITY OF NEW SOUTH WALES   (Australia)

Author keywords

Falls; Gait analysis; Remote; Wavelet; Wearable devices

Indexed keywords

GAIT ANALYSIS; LABORATORIES; WALKING AIDS; WAVELET ANALYSIS; WEARABLE SENSORS;

FALLS; REMOTE; SPECIFIC LOCATION; TRAINING AND TESTING; WAVELET; WAVELET TRANSFORMATIONS; WAVELET-BASED METHODS; WEARABLE DEVICES;

WEARABLE TECHNOLOGY;

ACCELEROMETER; ADULT; AGED; ARTICLE; DAILY LIFE ACTIVITY; FEMALE; GAIT; GAIT ORTHOSIS; HUMAN; MALE; MORBIDITY; PRIORITY JOURNAL; STANDING; WALKING; WALKING SPEED; WEARABLE PENDANT DEVICE; ACCELERATION; ALGORITHM; AMBULATORY MONITORING; DECISION TREE; DEVICES; PHYSIOLOGY; VERY ELDERLY; WAVELET ANALYSIS;

ACCELERATION; ACTIVITIES OF DAILY LIVING; AGED; AGED, 80 AND OVER; ALGORITHMS; DECISION TREES; FEMALE; GAIT; HUMANS; MALE; MONITORING, AMBULATORY; WAVELET ANALYSIS;

EID: 84938704134     PISSN: 01400118     EISSN: 17410444     Source Type: Journal    
DOI: 10.1007/s11517-015-1357-9     Document Type: Article

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