Foot angular kinematics measured with inertial measurement units: A reliable criterion for real-time gait event detection

J Biomech. 2022 Jan:130:110880. doi: 10.1016/j.jbiomech.2021.110880. Epub 2021 Nov 27.

Abstract

Accurate and reliable real-time detection of gait events using inertial measurement units (IMUs) is crucial for (1) developing clinically meaningful gait parameters to differentiate normal and impaired gait or (2) creating patient-tailored gait rehabilitation strategies or control of prosthetic devices using feedback from gait phases. However, most previous studies focused only on algorithms with high temporal accuracy and neglected the importance of (1) high reliability, i.e., detecting only and all true gait events, and (2) real-time implementation. Thus, in this study, we presented a novel approach for initial contact (IC) and terminal contact (TC) detection in real-time based on the measurement of the foot orientation. Unlike foot/shank angular velocity and acceleration, foot orientation provides physiologically meaningful kinematic features corresponding to our observational recognition of IC and TC, regardless of the walking modality. We conducted an experimental study to validate our algorithm, including seven participants performing four walking/running activities. By analyzing 5,555 ICs/TCs recorded during the tests, only our algorithm achieved a sensitivity and precision of 100%. Our obtained temporal accuracy (mean ± standard deviation of errors ranging from 0 ± 3 to 6 ± 5 time samples; sampling frequency: 100 Hz) was better than or comparable to those reported in the literature. Our algorithm's performance does not depend on thresholds and gait speed/modality, and it can be used for feedback-based therapeutic gait training or real-time control of assistive or prosthetic technologies. Nevertheless, its performance for pathological gait must be validated in the future. Finally, we shared the codes and sample data on https://www.ncbl.ualberta.ca/codes.

Keywords: Gait analysis; Inertial measurement units; Pressure insoles; Temporal gait events; Wearable sensors.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Biomechanical Phenomena
  • Foot*
  • Gait*
  • Humans
  • Reproducibility of Results
  • Walking