A novel approach for generalising walking gaits across embodiments and behaviours

Hsiu-Chin Lin, M. Howard, S. Vijayakumar

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

Abstract / Description of output

Our goal is to introduce a more appropriate method of generalising walking gaits across different subjects and behaviours. Walking gaits are a result of complex factors that include variations resulting from embodiments and tasks, making techniques that use average template frameworks suboptimal for systematic analysis. The proposed work aims to devise methodologies for being able to represent gaits and gait transitions such that optimal policies may be recovered. The problem is formalised using a walking phase model, and the nullspace learning method is used to generalise a consistent policy. This policy can serve as reference guideline to quantify and identify pathological gaits. We have demonstrated robustness of our method with motion-capture data with induced gait abnormality. Future work will extend this to kinetic features and higher dimensional features.
Original languageEnglish
Title of host publicationBiomedical Robotics and Biomechatronics (2014 5th IEEE RAS EMBS International Conference on
PublisherInstitute of Electrical and Electronics Engineers
Pages1009-1015
Number of pages7
ISBN (Print)978-1-4799-3126-2
DOIs
Publication statusPublished - 1 Aug 2014

Keywords / Materials (for Non-textual outputs)

  • biology computing
  • gait analysis
  • learning (artificial intelligence)
  • gait abnormality
  • motion-capture data
  • nullspace learning method
  • pathological gaits
  • walking gait generalisation
  • walking phase model
  • Educational institutions
  • Foot
  • Kinematics
  • Knee
  • Legged locomotion
  • Pathology

Fingerprint

Dive into the research topics of 'A novel approach for generalising walking gaits across embodiments and behaviours'. Together they form a unique fingerprint.

Cite this