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Related Experiment Video

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Unrestricted stride detection during stair climbing using IMUs.

Hannah Lena Siebers1, Nad Siroros1, Waleed Alrawashdeh1

  • 1Department of Orthopaedic Surgery, RWTH Aachen University Hospital, Aachen, Germany.

Medical Engineering & Physics
|June 25, 2021
PubMed
Summary

A new stride detection algorithm accurately identifies initial (IC) and terminal contact (TC) gait events during walking and stair climbing. This robust method achieved 100% detection accuracy, outperforming existing algorithms in complex movements.

Keywords:
Gait analysisIMUKinematicStep detection

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Area of Science:

  • Biomechanics
  • Human Movement Analysis
  • Wearable Sensor Technology

Background:

  • Stride detection (initial contact and terminal contact) is crucial for gait analysis but challenging using only kinematic data from Inertial Measurement Units (IMUs).
  • Existing algorithms often fail with diverse movement patterns like stair climbing and vary significantly in sensor placement, filtering, and signal analysis, limiting their applicability.
  • The need for a robust, universally applicable stride detection algorithm for various locomotion tasks is evident.

Purpose of the Study:

  • To develop and validate a novel, robust algorithm for automatic stride detection (initial contact and terminal contact).
  • To assess the algorithm's performance across different movement types, specifically walking and stair climbing.
  • To compare the new algorithm's efficacy against existing stride detection methods.

Main Methods:

  • Kinematic motion data were collected from 35 healthy participants using the MyoMotion IMU system during walking and stair climbing.
  • A new stride detection algorithm was developed based on an analysis of existing methods for initial contact (IC) and terminal contact (TC) detection.
  • The newly developed algorithm was validated against two other established algorithms.

Main Results:

  • The novel algorithm demonstrated 100% accuracy in detecting gait events during both walking and stair climbing (ascending/descending).
  • In contrast, existing algorithms showed significantly lower detection rates during stair climbing, with only 44% and 91% of gait events detected.
  • The developed algorithm proved successful in automatic stride detection across varied locomotion tasks.

Conclusions:

  • The newly developed stride detection algorithm offers a robust and highly accurate solution for gait analysis, particularly in complex activities like stair climbing.
  • This algorithm overcomes limitations of previous methods, providing reliable detection of initial and terminal contact events regardless of movement type.
  • The findings suggest this algorithm can enhance the precision and applicability of IMU-based gait analysis in diverse research and clinical settings.