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  • Open Access

    ARTICLE

    An Efficient Method for Identifying Lower Limb Behavior Intentions Based on Surface Electromyography

    Liuyi Ling1,2,3, Yiwen Wang1,*, Fan Ding4, Li Jin1, Bin Feng3, Weixiao Li3, Chengjun Wang1, Xianhua Li1

    CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 2771-2790, 2023, DOI:10.32604/cmc.2023.043383 - 26 December 2023

    Abstract Surface electromyography (sEMG) is widely used for analyzing and controlling lower limb assisted exoskeleton robots. Behavior intention recognition based on sEMG is of great significance for achieving intelligent prosthetic and exoskeleton control. Achieving highly efficient recognition while improving performance has always been a significant challenge. To address this, we propose an sEMG-based method called Enhanced Residual Gate Network (ERGN) for lower-limb behavioral intention recognition. The proposed network combines an attention mechanism and a hard threshold function, while combining the advantages of residual structure, which maps sEMG of multiple acquisition channels to the lower limb motion More >

  • Open Access

    ARTICLE

    Automatic Detection of Outliers in Multi-Channel EMG Signals Using MFCC and SVM

    Muhammad Irfan1, Khalil Ullah2, Fazal Muhammad3,*, Salman Khan3, Faisal Althobiani4, Muhammad Usman5, Mohammed Alshareef4, Shadi Alghaffari4, Saifur Rahman1

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 169-181, 2023, DOI:10.32604/iasc.2023.032337 - 29 September 2022

    Abstract The automatic detection of noisy channels in surface Electromyogram (sEMG) signals, at the time of recording, is very critical in making a noise-free EMG dataset. If an EMG signal contaminated by high-level noise is recorded, then it will be useless and can’t be used for any healthcare application. In this research work, a new machine learning-based paradigm is proposed to automate the detection of low-level and high-level noises occurring in different channels of high density and multi-channel sEMG signals. A modified version of mel frequency cepstral coefficients (mMFCC) is proposed for the extraction of features… More >

  • Open Access

    ARTICLE

    Characteristics of Surface Electromyography of Forehand Smash of Badminton Players

    Chen Zhang*

    Molecular & Cellular Biomechanics, Vol.18, No.1, pp. 33-40, 2021, DOI:10.32604/mcb.2021.014352 - 26 January 2021

    Abstract To understand the characteristics of the forehand smash of badminton player and improve their performance, this study took eight badminton players as the subject, obtained the kinematics data through the Qualisys infrared high-speed camera, obtained the electromyography (EMG) data through the ME-6000 surface EMG test system, and compared and analyzed their forehand smash action. The results showed that the greater the angle and speed of different joints in the forehand smash was, the greater the speed and strength of hitting the ball was; the discharge amount of biceps brachii (BB) was the smallest, followed by More >

  • Open Access

    ARTICLE

    The Kinematics and Surface Electromyography Characteristics of Round Kick of Martial Arts Athletes

    Xin Wang*

    Molecular & Cellular Biomechanics, Vol.17, No.4, pp. 189-198, 2020, DOI:10.32604/mcb.2020.011236 - 20 October 2020

    Abstract In order to improve the level of athletes, modern scientific and technological means can be used to understand the characteristics and rules of movement. This study mainly analyzed the whip leg technique of Sanda athletes. Taking ten athletes as an example, the kinematics and surface electromyography (sEMG) data of them were measured, calculated and sorted out when they were doing the action of round kick. The results showed that the movement completion time of the first-level athletes was shorter, 0.34 ± 0.33 s. In the stage of turning hip and hitting, the angle of hip… More >

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