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A Hybrid HMM/Kalman Filter for Tracking Hip Angle in Gait Cycle Liang DONG Jiankang WU Xiaoming BAO Publication IEICE TRANSACTIONS on Information and Systems Vol.E89-D No.7 pp.2319-2323 Publication Date: 2006/07/01 Online ISSN: 1745-1361 DOI: 10.1093/ietisy/e89-d.7.2319 Print ISSN: 0916-8532 Type of Manuscript: LETTER Category: Biological Engineering Keyword: hidden Markov model, Kalman filter, hip angle, gait analysis, Full Text: PDF(501.1KB)>>
Summary: Movement of the thighs is an important factor for studying gait cycle. In this paper, a hybrid hidden Markov model (HMM)/Kalman filter (KF) scheme is proposed to track the hip angle during gait cycles. Within such a framework, HMM and KF work in parallel to estimate the hip angle and detect major gait events. This approach has been applied to study gait features of different subjects and compared with video based approach. Experimental results indicate that 1.) the swing angle of the hip can be detected with simple hardware configuration using biaxial accelerometers and 2.) the hip angle can be tracked for different subjects within the error range of -5°  +5°. | ||||||||||
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