Adaptive Gait Phase Segmentation Based on the Time-Varying Identification of the Ankle Dynamics: Technique and Simulation Results

Author(s)

Perez-Ibarra, Juan C. ; Siqueira, Adriano A. G. ; Krebs, Hermano, I ; IEEE

• Document type: Journal article
• Source: 2020 8TH IEEE RAS/EMBS INTERNATIONAL CONFERENCE FOR BIOMEDICAL ROBOTICS AND BIOMECHATRONICS (BIOROB); v. N/A, p. 6-pg., 2020-01-01.

Abstract

Gait abnormalities introduce undesired patterns that limit stability, efficiency, and finally, walker independence. Most of the current algorithms for the identification of gait events using kinematic and inertial data have obtained high performance in healthy subjects. However, most of them showed limited performance when tested with impaired subjects. We hypothesize that to improve gait event detection one must take into consideration the differences between the dynamics of each phase. In this paper, we developed and evaluated a novel methodology for adaptation of a set of parameters for gait event detection using mechanical perturbations. Our proposal employs an ensemble-based procedure for the characterization of the ankle dynamics. We based our proposal on a hybrid model of the human dynamics during gait where the parameters of the dynamics model are abruptly changed according to a Markov chain. In this document, we described the adaptive algorithm and presented preliminary results on a gait simulator. We demonstrated the ability of the algorithm to adapt the parameters according to the changes in human walking. (AU)

• FAPESP's process: 13/14756-0 - Adaptive variable impedance applied to robotic rehabilitation of walking
• Grantee: Adriano Almeida Gonçalves Siqueira
• Support Opportunities: Regular Research Grants
• FAPESP's process: 11/10369-6 - Robotic rehabilitation of walking: new strategies based on natural characteristics
• Grantee: Adriano Almeida Gonçalves Siqueira
• Support Opportunities: Scholarships abroad - Research