Comparison of gait event detection from shanks and feet in single-task and multi-task walking of healthy older adults

W. Kong, J. Lin, L. Waaning, S. Sessa, Sarah Cosentino, D. Magistro, M. Zecca, R. Kawashima, Atsuo Takanishi

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

4 Citations (Scopus)

Abstract

Automatic and objective detection algorithms for gait events from MEMS Inertial Measurement Units data have been developed to overcome subjective inaccuracy in traditional visual observation. Their accuracy and sensitivity have been verified with healthy older adults, Parkinson's disease and spinal injured patients, using single-task gait exercises, where events are precise as the subject is focusing only on walking. Multi-task walking instead simulates a more realistic and challenging scenario where subjects perform secondary cognitive task while walking, so it is a better benchmark. In this paper, we test two algorithms based on shank and foot angular velocity data in single-task, dual-task and multi-task walking. Results show that both algorithms fail when the subject slows extremely down or pauses due to high cognitive and attentional load, and, in particular, the first stride detection error rate of the foot-based algorithm increases. Stride time is accurate with both algorithms regardless of walking types, but the shank-based algorithm leads to an overestimation on the proportion of swing phase in one gait cycle. Increasing the number of cognitive tasks also causes this error with both algorithms.

Original languageEnglish
Title of host publication2016 IEEE International Conference on Robotics and Biomimetics, ROBIO 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2063-2068
Number of pages6
ISBN (Electronic)9781509043644
DOIs
Publication statusPublished - 2017 Feb 27
Event2016 IEEE International Conference on Robotics and Biomimetics, ROBIO 2016 - Qingdao, China
Duration: 2016 Dec 32016 Dec 7

Other

Other2016 IEEE International Conference on Robotics and Biomimetics, ROBIO 2016
CountryChina
CityQingdao
Period16/12/316/12/7

ASJC Scopus subject areas

  • Hardware and Architecture
  • Artificial Intelligence
  • Control and Systems Engineering

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    Kong, W., Lin, J., Waaning, L., Sessa, S., Cosentino, S., Magistro, D., Zecca, M., Kawashima, R., & Takanishi, A. (2017). Comparison of gait event detection from shanks and feet in single-task and multi-task walking of healthy older adults. In 2016 IEEE International Conference on Robotics and Biomimetics, ROBIO 2016 (pp. 2063-2068). [7866633] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ROBIO.2016.7866633