Evaluation of sEMG-Based Feature Extraction and Effective Classification Method for Gait Phase Detection

Fang Peng, Wei Peng, Cheng Zhang

研究成果: Conference contribution

抄録

Gait phase detection is an essential procedure for amputated person with an artificial leg to walk naturally. However, a high-performance gait phase detection system is challenging due to (1) the complexity of surface electromyography (sEMG) and redundancy among the numerous features; (2) a robust recognition algorithm which can satisfy the real-time and high accuracy requirement of the system. This paper presents a gait phase detection method based on feature selection and ensemble learning. Four kinds of features extraction methods of sEMG, including time, frequency, time/frequency domain and entropy, are quantitatively analyzed by statistical analysis and calculation complexity to select the best features set. Furthermore, a multiclass classifier using Light Gradient Boosting Machine (LightGBM) is first introduced in gait recognition for discriminating six different gait phases with an average accuracy (94.1%) in a reasonable calculation time (85 ms), and the average accuracy is 5%, which is better than the traditional multiple classifiers decision fusion model. The proposed robust algorithm can effectively reduce the effect of speed on the result, which make it a perfect choice for gait phase detection.

元の言語English
ホスト出版物のタイトルCognitive Systems and Signal Processing - 4th International Conference, ICCSIP 2018, Revised Selected Papers
編集者Dewen Hu, Fuchun Sun, Huaping Liu
出版者Springer-Verlag
ページ138-149
ページ数12
ISBN(印刷物)9789811379857
DOI
出版物ステータスPublished - 2019 1 1
イベント4th International Conference on Cognitive Systems and Information Processing, ICCSIP 2018 - Beijing, China
継続期間: 2018 11 292018 12 1

出版物シリーズ

名前Communications in Computer and Information Science
1006
ISSN(印刷物)1865-0929

Conference

Conference4th International Conference on Cognitive Systems and Information Processing, ICCSIP 2018
China
Beijing
期間18/11/2918/12/1

Fingerprint

Electromyography
Gait
Feature Extraction
Feature extraction
Classifiers
Evaluation
Robust Algorithm
Redundancy
Statistical methods
Entropy
Fusion reactions
Classifier Fusion
Gait Recognition
Decision Fusion
Multiple Classifiers
Ensemble Learning
Recognition Algorithm
Multi-class
Boosting
Walk

ASJC Scopus subject areas

  • Computer Science(all)
  • Mathematics(all)

これを引用

Peng, F., Peng, W., & Zhang, C. (2019). Evaluation of sEMG-Based Feature Extraction and Effective Classification Method for Gait Phase Detection. : D. Hu, F. Sun, & H. Liu (版), Cognitive Systems and Signal Processing - 4th International Conference, ICCSIP 2018, Revised Selected Papers (pp. 138-149). (Communications in Computer and Information Science; 巻数 1006). Springer-Verlag. https://doi.org/10.1007/978-981-13-7986-4_13

Evaluation of sEMG-Based Feature Extraction and Effective Classification Method for Gait Phase Detection. / Peng, Fang; Peng, Wei; Zhang, Cheng.

Cognitive Systems and Signal Processing - 4th International Conference, ICCSIP 2018, Revised Selected Papers. 版 / Dewen Hu; Fuchun Sun; Huaping Liu. Springer-Verlag, 2019. p. 138-149 (Communications in Computer and Information Science; 巻 1006).

研究成果: Conference contribution

Peng, F, Peng, W & Zhang, C 2019, Evaluation of sEMG-Based Feature Extraction and Effective Classification Method for Gait Phase Detection. : D Hu, F Sun & H Liu (版), Cognitive Systems and Signal Processing - 4th International Conference, ICCSIP 2018, Revised Selected Papers. Communications in Computer and Information Science, 巻. 1006, Springer-Verlag, pp. 138-149, 4th International Conference on Cognitive Systems and Information Processing, ICCSIP 2018, Beijing, China, 18/11/29. https://doi.org/10.1007/978-981-13-7986-4_13
Peng F, Peng W, Zhang C. Evaluation of sEMG-Based Feature Extraction and Effective Classification Method for Gait Phase Detection. : Hu D, Sun F, Liu H, 編集者, Cognitive Systems and Signal Processing - 4th International Conference, ICCSIP 2018, Revised Selected Papers. Springer-Verlag. 2019. p. 138-149. (Communications in Computer and Information Science). https://doi.org/10.1007/978-981-13-7986-4_13
Peng, Fang ; Peng, Wei ; Zhang, Cheng. / Evaluation of sEMG-Based Feature Extraction and Effective Classification Method for Gait Phase Detection. Cognitive Systems and Signal Processing - 4th International Conference, ICCSIP 2018, Revised Selected Papers. 編集者 / Dewen Hu ; Fuchun Sun ; Huaping Liu. Springer-Verlag, 2019. pp. 138-149 (Communications in Computer and Information Science).
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