A novel HMM distributed classifier for the detection of gait phases by means of a wearable inertial sensor network

Sensors (Switzerland)

Volumn 14, Issue 9, 2014, Pages 16212-16234

  Taborri, Juri ^a   Rossi, Stefano ^b   Palermo, Eduardo ^a   Patanè, Fabrizio ^c   Cappa, Paolo ^a,d  

^a SAPIENZA UNIVERSITY OF ROME   (Italy)

^b UNIVERSITY OF TUSCIA   (Italy)

^c NICCOLÒ CUSANO UNIVERSITY   (Italy)

^d Neurorehabilitation Division   (Italy)

Author keywords

Distributed classifier; Gait detection; Gyroscopes; Hidden Markov Models; Hierarchical decision; Wearable sensor network

Indexed keywords

ANGULAR VELOCITY; GYROSCOPES; HIDDEN MARKOV MODELS; PATIENT REHABILITATION; SENSOR NETWORKS; UNITS OF MEASUREMENT;

BETTER PERFORMANCE; COEFFICIENT OF VARIATION; COMPUTATIONAL LOADS; GAIT DETECTION; HIERARCHICAL DECISIONS; INERTIAL MEASUREMENT UNIT; REAL-TIME APPLICATION; WEARABLE SENSOR NETWORKS;

PATTERN RECOGNITION;

ACCELEROMETRY; AMBULATORY MONITORING; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER NETWORK; COMPUTER SIMULATION; DEVICE FAILURE ANALYSIS; DEVICES; EQUIPMENT DESIGN; FEMALE; GAIT; HUMAN; MALE; PHYSIOLOGY; PROBABILITY; PROCEDURES; STATISTICAL MODEL; TRANSDUCER; YOUNG ADULT;

ACCELEROMETRY; ARTIFICIAL INTELLIGENCE; COMPUTER COMMUNICATION NETWORKS; COMPUTER SIMULATION; EQUIPMENT DESIGN; EQUIPMENT FAILURE ANALYSIS; FEMALE; GAIT; HUMANS; INSTRUMENTATION; MALE; MARKOV CHAINS; METHODS; MODELS, STATISTICAL; MONITORING, AMBULATORY; PATTERN RECOGNITION, AUTOMATED; PHYSIOLOGY; TRANSDUCERS; YOUNG ADULT;

EID: 84907483910     PISSN: 14248220     EISSN: None     Source Type: Journal    
DOI: 10.3390/s140916212     Document Type: Article

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