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Bae, Joonbum
Bio-Robotics and Control (BiRC) Lab
Research Interests
  • Design and control of physical human-robot interaction systems

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Gait phase analysis based on a Hidden Markov Model

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Title
Gait phase analysis based on a Hidden Markov Model
Author
Bae, JoonbumTomizuka, Masayoshi
Keywords
Gait abnormalities; Gait motions; Gait phase analysis; Gait phasis; Gait rehabilitation; Ground contacts; Observed data; Posterior probability
Issue Date
201109
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
Citation
MECHATRONICS, v.21, no.6, pp.961 - 970
Abstract
For effective gait rehabilitation treatments, the status of a patient's gait needs to be analyzed precisely. Since the gait motions are cyclic with several gait phases, the gait motions can be analyzed by gait phases. In this paper, a Hidden Markov Model (HMM) is applied to analyze the gait phases in the gait motions. Smart Shoes are utilized to obtain the ground reaction forces (GRFs) as observed data in the HMM. The posterior probabilities from the HMM are used to infer the gait phases, and the abnormal transition between gait phases are checked by the transition matrix. The proposed gait phase analysis methods have been applied to actual gait data, and the results show that the proposed methods have the potential of tools for diagnosing the status of a patient and evaluating a rehabilitation treatment.
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DOI
http://dx.doi.org/10.1016/j.mechatronics.2011.03.003
ISSN
0957-4158
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