Robust EMG pattern recognition to muscular fatigue effect for powered wheelchair control

Author:

Song Jae-Hoon1,Jung Jin-Woo2,Lee Sang-Wan3,Bien Zeungnam3

Affiliation:

1. Air Navigation and Traffic System Department, Korea Aerospace Research Institute, 45 Eoeun-dong, Yuseong-gu, Daejeon 305-333, Korea

2. Department of Computer Engineering, Dongguk University, 3-26 Pil-dong, Chung-gu, Seoul 100-715, Korea

3. Department of Electrical Engineering and Computer Science, Korea Advanced Institute of Science and Technology, 373-1 Guseong-dong, Yuseong-gu, Daejeon 305-701, Korea

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

Cited by 23 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. PSD Information Based Fatigue Invariant Hand Gesture Recognition Using sEMG;2024 International Conference on Signal Processing and Communications (SPCOM);2024-07-01

2. Fuzzy min–max neural networks: a bibliometric and social network analysis;Neural Computing and Applications;2023-01-30

3. A Muscle Fiber Conduction Velocity Estimator Using Surface Electromyography Signals Acquired From Vastus Lateralis;2022 IEEE 19th India Council International Conference (INDICON);2022-11-24

4. ANALYSIS OF INDUCED ISOMETRIC FATIGUING CONTRACTIONS IN BICEPS BRACHII MUSCLES USING MYOTONOMETRY AND SURFACE ELECTROMYOGRAPHIC MEASUREMENTS;Journal of Mechanics in Medicine and Biology;2022-05-05

5. SeNic: An Open Source Dataset for sEMG-Based Gesture Recognition in Non-Ideal Conditions;IEEE Transactions on Neural Systems and Rehabilitation Engineering;2022

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