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

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...

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Published in:IEEE/ASME International Conference on Advanced Intelligent Mechatronics pp. 1167 - 1171
Main Authors: Perez-Ibarra, Juan C., Siqueira, Adriano A. G., Terra, Marco H., Krebs, Hermano I.
Format: Conference Proceeding
Language:English
Published: IEEE 01.07.2020
Subjects:
Angular velocity
Artificial Intelligence
Foot
Gait Analysis
Genetic algorithms
Intelligent Sensors
Legged locomotion
Optimization
Performance evaluation
Protocols
Rehabilitation Robots
Wearable Sensors
ISSN:2159-6255
Online Access:Get full text
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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.
AbstractList 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.
Author Siqueira, Adriano A. G.
Krebs, Hermano I.
Perez-Ibarra, Juan C.
Terra, Marco H.
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  givenname: Juan C.
  surname: Perez-Ibarra
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  organization: University of São Paulo,Departments of Mechanical Engineering and Electrical Engineering,São Carlos,Brazil
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  givenname: Adriano A. G.
  surname: Siqueira
  fullname: Siqueira, Adriano A. G.
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  givenname: Marco H.
  surname: Terra
  fullname: Terra, Marco H.
  organization: University of São Paulo,Department of Electrical Engineering,São Carlos,Brazil
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  givenname: Hermano I.
  surname: Krebs
  fullname: Krebs, Hermano I.
  organization: Massachusetts Institute of Technology,Dept. of Mechanical Engineering,Cambridge,MA,USA
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Snippet Accurate identification of gait phases is a necessary step for control of robotic devices during gait therapy or automatic diagnosis of gait impairments. Most...
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SubjectTerms Angular velocity
Artificial Intelligence
Foot
Gait Analysis
Genetic algorithms
Intelligent Sensors
Legged locomotion
Optimization
Performance evaluation
Protocols
Rehabilitation Robots
Wearable Sensors
Title Hybrid Simulated Annealing and Genetic Algorithm for Optimization of a Rule-based Algorithm for Detection of Gait Events in Impaired Subjects
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