A Novel Method for Bilateral Gait Segmentation Using a Single Thigh-Mounted Depth Sensor and IMU

Blair H. Hu*, Nili E. Krausz, Levi J Hargrove

*Corresponding author for this work

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

4 Scopus citations

Abstract

Lower limb assistive devices have shown potential to restore mobility to millions of individuals with walking impairments; however, their success depends on whether they can be controlled safely, reliably, and intuitively with user-friendly sensors. To assist the user's walking patterns, many devices implement finite-state controllers which rely on accurate estimation of the current gait phase (e.g. Stance, swing) of one or both legs. Bilateral gait segmentation is especially important for restoring natural interlimb coordination, which contributes to device safety and efficiency. Most existing techniques for gait segmentation use ground contact, device-embedded, or body-worn sensors with threshold or machine learning-based algorithms. They have been effective at identifying the state of the ipsilateral (i.e. Sensor-side) leg but can become inconvenient for bilateral gait segmentation because they often require many sensors and are more sensitive to sensor placement. Therefore, we present a proof of concept for a novel approach to bilateral gait segmentation using a thigh-mounted inertial measurement unit (IMU) and depth sensor with the contralateral leg in its field of view. We extracted two features, ground and shank angle, from the depth data and developed a sensor fusion strategy to predict contralateral heel contact and ipsilateral toe off with accuracy approaching that of a setup with bilateral thigh and shank IMUs. By using computer vision to estimate the state of both legs, we introduce a new technique for bilateral gait segmentation which could make assistive devices more user-friendly, safe, and functional.

Original languageEnglish (US)
Title of host publicationBIOROB 2018 - 7th IEEE International Conference on Biomedical Robotics and Biomechatronics
PublisherIEEE Computer Society
Pages807-812
Number of pages6
ISBN (Electronic)9781538681831
DOIs
StatePublished - Oct 9 2018
Event7th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics, BIOROB 2018 - Enschede, Netherlands
Duration: Aug 26 2018Aug 29 2018

Publication series

NameProceedings of the IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics
Volume2018-August
ISSN (Print)2155-1774

Other

Other7th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics, BIOROB 2018
CountryNetherlands
CityEnschede
Period8/26/188/29/18

ASJC Scopus subject areas

  • Artificial Intelligence
  • Biomedical Engineering
  • Mechanical Engineering

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    Hu, B. H., Krausz, N. E., & Hargrove, L. J. (2018). A Novel Method for Bilateral Gait Segmentation Using a Single Thigh-Mounted Depth Sensor and IMU. In BIOROB 2018 - 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (pp. 807-812). [8487806] (Proceedings of the IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics; Vol. 2018-August). IEEE Computer Society. https://doi.org/10.1109/BIOROB.2018.8487806