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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| Vydané v: | IEEE/ASME International Conference on Advanced Intelligent Mechatronics s. 1167 - 1171 |
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| Hlavní autori: | , , , |
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01.07.2020
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| ISSN: | 2159-6255 |
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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. |
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| 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. |
| Author_xml | – sequence: 1 givenname: Juan C. surname: Perez-Ibarra fullname: Perez-Ibarra, Juan C. organization: University of São Paulo,Departments of Mechanical Engineering and Electrical Engineering,São Carlos,Brazil – sequence: 2 givenname: Adriano A. G. surname: Siqueira fullname: Siqueira, Adriano A. G. organization: University of São Paulo,Dept. of Mechanical Engineering,São Carlos,Brazil – sequence: 3 givenname: Marco H. surname: Terra fullname: Terra, Marco H. organization: University of São Paulo,Department of Electrical Engineering,São Carlos,Brazil – sequence: 4 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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| StartPage | 1167 |
| 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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