Comparative assessment of heel rise detection for consistent gait phase separation

Mikko Salminen, Jarmo Perttunen, Janne Avela, Antti Vehkaoja

Research output: Contribution to journalArticleScientificpeer-review

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Abstract

Background: Accurate identification of gait events is crucial to reliable gait analysis. Heel rise, a key event marking the transition from mid-stance to terminal stance, poses challenges in precise detection due to its gradual nature. This leads to variability in accuracy across studies utilizing diverse measuring techniques. Research question: How do different HR detection methods compare when assessed against the underlying heel motion pattern and visual detection across varying speed, footwear conditions, and individuals? Methods: Leveraging data from over 10,000 strides in diverse scenarios with 15 healthy subjects, we evaluated methods based on measurements from optical motion capture (OMC), force plates, and shank-mounted inertial measurement units (IMUs). The evaluation of these methods included an assessment of their precision and consistency with the heel marker's motion pattern and agreement with visually detected heel rise. Results: OMC-based heel rise detection methods, utilizing the heel marker's vertical acceleration and jerk, consistently identified the same point in the heel motion pattern, outperforming velocity-based methods and our new position-based method resembling traditional footswitch-based heel rise detection. Variability in velocity and position-based methods derives from subtle heel rise variations after mid-stance, exhibiting individual differences. Our proposed IMU-based methods show promise by closely matching OMC-based accuracy. Significance: The results have significant implications for gait analysis, providing insights into heel rise event detection's complexities. Accurate HR identification is crucial for gait phase separation, and our findings, especially with the robust heel marker's jerk-based method, enhance precision and consistency across walking conditions. Moreover, our successful development and validation of IMU-based algorithm offer cost-effective and mobile alternative for HR detection, expanding their potential use in comprehensive gait analysis.

Original languageEnglish
Article numbere33546
Number of pages11
JournalHeliyon
Volume10
Issue number13
DOIs
Publication statusPublished - 15 Jul 2024
Publication typeA1 Journal article-refereed

Keywords

  • Event detection
  • Gait analysis
  • Heel-off
  • Inertial measurement unit (IMU)
  • Optical motion capture
  • Shank angular velocity

Publication forum classification

  • Publication forum level 1

ASJC Scopus subject areas

  • General

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