A method for predicting personalized pelvic motion based on body meta-features for gait rehabilitation robot

Sung Yul Shin, Jisoo Hong, Changmook Chun, Seung Jong Kim, Chang Hwan Kim

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    3 Citations (Scopus)

    Abstract

    Training for balancing, which is governed by the motion of pelvis and thorax, is a key for gait rehabilitation. COWALK, which is a gait rehabilitation robot under development in our institute, is capable of pelvic motion training. In this paper, we describe a statistical method to generate pelvic motion which is considered to fit each person, i.e., personalized pelvic motion. We measured 14 anthropometric features of human and captured gait motion using an optical motion capture system from 113 healthy subjects. We setup a database of gait motion and body measurements; we define a 4 dimensional compact vector representation of pelvic motion, and body meta-feature, which is a weighted linear combination of the anthropometric measurements, to maximize statistical correlation between the former and the latter. To synthesize a personalized pelvic motion for a new subject, we search for k nearest neighbors in the space of body meta-feature (k-NN algorithm), and average the pelvic motions of them. We validate the algorithm using the database of 113 subjects by excluding each person, synthesizing a personalized pelvic motion for the subject, and comparing it with actual motion of the subject.

    Original languageEnglish
    Title of host publicationIROS 2014 Conference Digest - IEEE/RSJ International Conference on Intelligent Robots and Systems
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages2063-2068
    Number of pages6
    ISBN (Electronic)9781479969340
    DOIs
    Publication statusPublished - 2014 Oct 31
    Event2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2014 - Chicago, United States
    Duration: 2014 Sept 142014 Sept 18

    Publication series

    NameIEEE International Conference on Intelligent Robots and Systems
    ISSN (Print)2153-0858
    ISSN (Electronic)2153-0866

    Other

    Other2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2014
    Country/TerritoryUnited States
    CityChicago
    Period14/9/1414/9/18

    Bibliographical note

    Publisher Copyright:
    © 2014 IEEE.

    ASJC Scopus subject areas

    • Control and Systems Engineering
    • Software
    • Computer Vision and Pattern Recognition
    • Computer Science Applications

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