Determination of human gait phase using fuzzy inference

Chad MacDonald; Darla Smith; Richard Brower; Martine Ceberio; Thompson Sarkodie-Gyan

doi:10.1109/ICORR.2007.4428495

Determination of human gait phase using fuzzy inference

Chad MacDonald, Darla Smith, Richard Brower, Martine Ceberio, Thompson Sarkodie-Gyan

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

17 Scopus citations

Abstract

This paper discusses the design and implementation of a fuzzy inference system for the recognition of human gait phases. In particular, this work focuses on using the angles of the joints of lower limb to determine the current stage of a subject's gait cycle. The fuzzy rule-based system was developed using typical joint angle trajectories over a single gait cycle. The behavior of each joint was examined to determine appropriate rules for differentiating between gait phases. The completed system was then tested using joint angle trajectories measured from healthy human test subjects and shown to be capable of reproducing the gait phase transitions found by a human expert.

Original language	English
Title of host publication	2007 IEEE 10th International Conference on Rehabilitation Robotics, ICORR'07
Pages	661-665
Number of pages	5
DOIs	https://doi.org/10.1109/ICORR.2007.4428495
State	Published - 2007
Event	2007 IEEE 10th International Conference on Rehabilitation Robotics, ICORR'07 - Noordwijk, Netherlands Duration: Jun 12 2007 → Jun 15 2007

Publication series

Name	2007 IEEE 10th International Conference on Rehabilitation Robotics, ICORR'07

Conference

Conference	2007 IEEE 10th International Conference on Rehabilitation Robotics, ICORR'07
Country/Territory	Netherlands
City	Noordwijk
Period	06/12/07 → 06/15/07

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10.1109/ICORR.2007.4428495

Cite this

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title = "Determination of human gait phase using fuzzy inference",

abstract = "This paper discusses the design and implementation of a fuzzy inference system for the recognition of human gait phases. In particular, this work focuses on using the angles of the joints of lower limb to determine the current stage of a subject's gait cycle. The fuzzy rule-based system was developed using typical joint angle trajectories over a single gait cycle. The behavior of each joint was examined to determine appropriate rules for differentiating between gait phases. The completed system was then tested using joint angle trajectories measured from healthy human test subjects and shown to be capable of reproducing the gait phase transitions found by a human expert.",

author = "Chad MacDonald and Darla Smith and Richard Brower and Martine Ceberio and Thompson Sarkodie-Gyan",

year = "2007",

doi = "10.1109/ICORR.2007.4428495",

language = "English",

isbn = "1424413206",

series = "2007 IEEE 10th International Conference on Rehabilitation Robotics, ICORR'07",

pages = "661--665",

booktitle = "2007 IEEE 10th International Conference on Rehabilitation Robotics, ICORR'07",

note = "2007 IEEE 10th International Conference on Rehabilitation Robotics, ICORR'07 ; Conference date: 12-06-2007 Through 15-06-2007",

}

MacDonald, C, Smith, D, Brower, R, Ceberio, M & Sarkodie-Gyan, T 2007, Determination of human gait phase using fuzzy inference. in 2007 IEEE 10th International Conference on Rehabilitation Robotics, ICORR'07., 4428495, 2007 IEEE 10th International Conference on Rehabilitation Robotics, ICORR'07, pp. 661-665, 2007 IEEE 10th International Conference on Rehabilitation Robotics, ICORR'07, Noordwijk, Netherlands, 06/12/07. https://doi.org/10.1109/ICORR.2007.4428495

Determination of human gait phase using fuzzy inference. / MacDonald, Chad; Smith, Darla; Brower, Richard et al.
2007 IEEE 10th International Conference on Rehabilitation Robotics, ICORR'07. 2007. p. 661-665 4428495 (2007 IEEE 10th International Conference on Rehabilitation Robotics, ICORR'07).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - This paper discusses the design and implementation of a fuzzy inference system for the recognition of human gait phases. In particular, this work focuses on using the angles of the joints of lower limb to determine the current stage of a subject's gait cycle. The fuzzy rule-based system was developed using typical joint angle trajectories over a single gait cycle. The behavior of each joint was examined to determine appropriate rules for differentiating between gait phases. The completed system was then tested using joint angle trajectories measured from healthy human test subjects and shown to be capable of reproducing the gait phase transitions found by a human expert.

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Y2 - 12 June 2007 through 15 June 2007

ER -

Determination of human gait phase using fuzzy inference

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