Gait parameter estimation from a miniaturized ear-worn sensor using singular spectrum analysis and longest common subsequence

IEEE Transactions on Biomedical Engineering

Volumn 61, Issue 4, 2014, Pages 1261-1273

  Jarchi, Delaram ^a   Wong, Charence ^a   Kwasnicki, Richard Mark ^a   Heller, Ben ^b   Tew, Garry A ^c   Yang, Guang Zhong ^a  

^a IMPERIAL COLLEGE LONDON   (United Kingdom)

^b SHEFFIELD HALLAM UNIVERSITY   (United Kingdom)

^c UNIVERSITY OF YORK   (United Kingdom)

Author keywords

Body sensor networks; e AR sensor; gait; longest common subsequence (LCSS); singular spectrum analysis (SSA)

Indexed keywords

ACCELEROMETERS; BODY SENSOR NETWORKS; GAIT ANALYSIS; PARAMETER ESTIMATION; PARAMETER EXTRACTION; SPECTRUM ANALYSIS; SPORTING GOODS;

ABSOLUTE ERROR; CONFIDENCE INTERVAL; GAIT; LOCAL FEATURE; LONGEST COMMON SUBSEQUENCES; NEW APPROACHES; SINGULAR SPECTRUM ANALYSIS; TRIAXIAL ACCELEROMETER;

SENSORS;

ACCELERATION; ACCELEROMETER; ACCELEROMETRY; ACCURACY; ADULT; ARTICLE; CAMERA; EAR WORN SENSOR; GAIT; HEEL; HUMAN; HUMAN EXPERIMENT; NORMAL HUMAN; SENSOR; SPECTROSCOPY; STANDING; TOE; TREADMILL; WALKING;

ADULT; ALGORITHMS; EAR; GAIT; HUMANS; MINIATURIZATION; REMOTE SENSING TECHNOLOGY; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 84897135245     PISSN: 00189294     EISSN: 15582531     Source Type: Journal    
DOI: 10.1109/TBME.2014.2299772     Document Type: Article

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