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31 ta ish

Ish: EMG-Based Recognition of Lower Limb Movements in Athletes: A Comparative Study of Classification Techniques

  1. Classification Of Some Sensitive Motion Of Fingers To Create Modern Biointerface

    Kudratjon Zohirov

    MaqolaMuscle activation and electromyography studies20229 iqtibos
    ABI

  2. A New Approach to Determining the Active Potential Limit of an Electromyography Signal

    Kudratjon Zohirov

    MaqolaMuscle activation and electromyography studies20238 iqtibos
    ABI

  3. An EMG Signal Based Approach for Assessing the Physical Condition of Athletes in Wrestling

    Kudratjon Zohirov, Rashid Nasimov, Sardor Boykobilov +3

    MaqolaMuscle activation and electromyography studies20242 iqtibos
    ABI

  4. EMG Wrist-hand Motion Recognition System for Real-time Embedded Platform

    Sumit A. Raurale, John McAllister, Jesús Martínez del Rincón

    Maqola20192 iqtibos
    ABI

  5. Support Vector Machine-Based Classification Scheme for Myoelectric Control Applied to Upper Limb

    Mohammadreza Asghari Oskoei, Huosheng Hu

    Maqola20082 iqtibos
    ABI

  6. Development of Surface EMG Game Control Interface for Persons with Upper Limb Functional Impairments

    Joseph Muguro, Pringgo Widyo Laksono, Wahyu Rahmaniar +7

    Maqola20212 iqtibos
    ABI

  7. Development of an Integrated System of sEMG Signal Acquisition, Processing, and Analysis with AI Techniques

    Filippo Laganà, Danilo Pratticò, Giovanni Angiulli +4

    Maqola20242 iqtibos
    ABI

  8. A Bimodal EMG/FMG System Using Machine Learning Techniques for Gesture Recognition Optimization

    Nuno D. Pires, Milton P. Macedo

    Maqola20252 iqtibos
    ABI

  9. FPGA implementation of fast FIR low pass filter for EMG removal from ECG signal

    Rakesh Chand, Pawan Tripathi, Abhishek Mathur +1

    Maqola20102 iqtibos
    ABI

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