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
Externally publishedYes
Event2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2014 - Chicago, United States
Duration: 2014 Sep 142014 Sep 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
CountryUnited States
CityChicago
Period14/9/1414/9/18

ASJC Scopus subject areas

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

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    Shin, S. Y., Hong, J., Chun, C., Kim, S-J., & Kim, C. H. (2014). A method for predicting personalized pelvic motion based on body meta-features for gait rehabilitation robot. In IROS 2014 Conference Digest - IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 2063-2068). [6942838] (IEEE International Conference on Intelligent Robots and Systems). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IROS.2014.6942838