Distinct feature extraction for video-based gait phase classification

Ye, Minxiang and Yang, Cheng and Stankovic, Vladimir and Stankovic, Lina and Cheng, Samuel (2020) Distinct feature extraction for video-based gait phase classification. IEEE Transactions on Multimedia, 22 (5). pp. 1113-1125. ISSN 1520-9210 (https://doi.org/10.1109/TMM.2019.2942479)

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Abstract

Recent advances in image acquisition and analysis have resulted in disruptive innovation in physical rehabilitation systems facilitating cost-effective, portable, video-based gait assessment. While these inexpensive motion capture systems, suitable for home rehabilitation, do not generally provide accurate kinematics measurements on their own, image processing algorithms ensure gait analysis that is accurate enough for rehabilitation programs. This paper proposes high-accuracy classification of gait phases and muscle actions, using readings from low-cost motion capture systems. First, 12 gait parameters, drawn from the medical literature, are defined to characterize gait patterns. These proposed parameters are then used as input to our proposed multi-channel time-series classification and gait phase reconstruction methods. Proposed methods fully utilize temporal information of gait parameters, thus improving the final classification accuracy. The validation, conducted using 126 experiments, with 6 healthy volunteers and 9 stroke survivors with manually-labelled gait phases, achieves state-of-art classification accuracy of gait phase with lower computational complexity compared to previous solutions

ORCID iDs

Ye, Minxiang ORCID logoORCID: https://orcid.org/0000-0003-0083-7145, Yang, Cheng, Stankovic, Vladimir ORCID logoORCID: https://orcid.org/0000-0002-1075-2420, Stankovic, Lina ORCID logoORCID: https://orcid.org/0000-0002-8112-1976 and Cheng, Samuel;
  • Item type:Article
    ID code:69683
    Dates:
    Date
    Event
    31 May 2020
    Published
    19 September 2019
    Published Online
    2 September 2019
    Accepted
    Notes:© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
    Subjects:Technology > Electrical engineering. Electronics Nuclear engineering
    Department:Faculty of Engineering > Electronic and Electrical Engineering
    Depositing user: Pure Administrator
    Date deposited:06 Sep 2019 14:16
    Last modified:11 Nov 2024 12:25
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/69683
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