Hybrid Simulated Annealing and Genetic Algorithm for Optimization of a Rule-based Algorithm for Detection of Gait Events in Impaired Subjects

Author(s)

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

• Document type: Journal article
• Source: 2020 IEEE/ASME INTERNATIONAL CONFERENCE ON ADVANCED INTELLIGENT MECHATRONICS (AIM); v. N/A, p. 5-pg., 2020-01-01.

Abstract

Accurate identification of gait phases is a necessary step for control of robotic devices during gait therapy or automatic diagnosis of gait impairments. Most of the existing algorithms use a rule-based approach that takes advantage of the consistency of the gait cycle among healthy subjects. Since impaired gait patterns lack of that inter-subject consistency, most of those algorithms have limited performance when detecting phases in impaired subjects. In this paper, we propose a new algorithm for real-time detection of four gait events (heel-strike, toe-strike, heel-off and toe-off). The proposed algorithm uses a set of threshold-based rules and to compute the adequate values for the thresholds, maximizing the performance of the algorithm, we use a hybrid meta-heuristic approach that integrates Simulated Annealing and a Genetic Algorithm. Using data collected during overground and treadmill walking trials with a wearable device equipped with an inertial sensor, we report experimental results for three subjects: one healthy, one hemiparetic, and one myelopathic. F-1-scores for the three subjects were 0.98, 0.99, and 0.91, respectively. (AU)

• 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
• 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