Analyzing human gait and posture by combining feature selection and kernel methods

Neurocomputing

Volumn 74, Issue 16, 2011, Pages 2665-2674

  Samà, Albert ^a,b   Angulo, Cecilio ^a,c   Pardo, Diego ^a,b   Català, Andreu ^a,c   Cabestany, Joan ^a,c  

^a CETpD Technical Research Center for Dependency Care and Autonomous Living   (Spain)

^b FHCSAA Sant Antoni Abat Hospital   (Spain)

^c UNIVERSITAT POLITÈCNICA DE CATALUNYA   (Spain)

Author keywords

Human gait and posture detection; Inertial body sensor; Kernel methods application; Time series analysis

Indexed keywords

ACTIVITY MONITORING; AUTOMATIC ESTIMATION; COMMON STRUCTURES; COMPUTATIONAL ALGORITHM; DAILY LIVING; HUMAN GAIT; HUMAN POSTURES; INERTIAL BODY SENSOR; KERNEL METHODS; KERNEL METHODS APPLICATION; KINEMATIC INFORMATION; POSTURE DETECTION; PRINCIPAL COMPONENTS ANALYSIS; RECONSTRUCTION SPACES; SENSOR INFORMATIONS; SINGLE SENSOR; SPATIO-TEMPORAL PROPERTIES; SPATIOTEMPORAL PARAMETERS; STEP LENGTH; SUPPORT VECTOR REGRESSIONS; USER MOTION;

DYNAMICAL SYSTEMS; PRINCIPAL COMPONENT ANALYSIS; SENSORS; TIME SERIES; TIME SERIES ANALYSIS; VECTOR SPACES;

FEATURE EXTRACTION;

ACCELERATION; ACCELEROMETRY; ARTICLE; BIOMECHANICS; BODY MOVEMENT; BODY POSTURE; COMPUTER ANALYSIS; COMPUTER PROGRAM; CONTROLLED STUDY; DAILY LIFE ACTIVITY; FEATURE SELECTION; GAIT; KERNEL METHOD; KINEMATICS; LEG MOVEMENT; MACHINE LEARNING; PREDICTION; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; SENSOR; SIGNAL PROCESSING; SITTING; STANDING; SUPPORT VECTOR MACHINE; WALKING SPEED;

EID: 80051587272     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2011.03.028     Document Type: Article

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