Citation

Choi S, Ko C, Kong K. Sensors (Basel) 2023; 23(19).

Copyright

(Copyright © 2023, MDPI: Multidisciplinary Digital Publishing Institute)

DOI

10.3390/s23198276

PMID

37837106

PMCID

PMC10575403

Abstract

This paper introduces a Gait Phase Estimation Module (GPEM) and its real-time algorithm designed to estimate gait phases continuously and monotonically across a range of walking speeds and accelerations/decelerations. To address the challenges of real-world applications, we propose a speed-adaptive online gait phase estimation algorithm, which enables precise estimation of gait phases during both constant speed locomotion and dynamic speed changes. Experimental verification demonstrates that the proposed method offers smooth, continuous, and repetitive gait phase estimation when compared to conventional approaches such as the phase portrait method and time-based estimation. The proposed method achieved a 48% reduction in gait phase deviation compared to time-based estimation and a 48.29% reduction compared to the phase portrait method. The proposed algorithm is integrated within the GPEM, allowing for its versatile application in controlling gait assistive robots without incurring additional computational burden. The results of this study contribute to the development of robust and efficient gait phase estimation techniques for various robotic applications.

Language: en

Keywords

inertial measurement unit; gait phase estimation; wearable robots