Liuyi Ling^1,2,3, Yiwen Wang^1,*, 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 >

C. S. S. Anupama¹, Rafina Zakieva², Afanasiy Sergin³, E. Laxmi Lydia⁴, Seifedine Kadry^5,6,7, Chomyong Kim⁸, Yunyoung Nam^8,*

Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1453-1468, 2023, DOI:10.32604/iasc.2023.038321 - 21 June 2023

Abstract Gait is a biological typical that defines the method by that people walk. Walking is the most significant performance which keeps our day-to-day life and physical condition. Surface electromyography (sEMG) is a weak bioelectric signal that portrays the functional state between the human muscles and nervous system to any extent. Gait classifiers dependent upon sEMG signals are extremely utilized in analysing muscle diseases and as a guide path for recovery treatment. Several approaches are established in the works for gait recognition utilizing conventional and deep learning (DL) approaches. This study designs an Enhanced Artificial Algae… More >

Muhammad Irfan¹, Khalil Ullah², Fazal Muhammad^3,*, 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 >

Narathip Chaobankoh¹, Tallit Jumphoo¹, Monthippa Uthansakul¹, Khomdet Phapatanaburi², Bura Sindthupakorn³, Supakit Rooppakhun⁴, Peerapong Uthansakul^1,*

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1269-1282, 2022, DOI:10.32604/cmc.2022.027474 - 18 May 2022

Abstract Recently, the Muscle-Computer Interface (MCI) has been extensively popular for employing Electromyography (EMG) signals to help the development of various assistive devices. However, few studies have focused on ankle foot movement classification considering EMG signals at limb position. This work proposes a new framework considering two EMG signals at a lower-limb position to classify the ankle movement characteristics based on normal walking cycles. For this purpose, we introduce a human ankle-foot movement classification method using a two-dimensional-convolutional neural network (2D-CNN) with low-cost EMG sensors based on lower-limb motion. The time-domain signals of EMG obtained from… More >

R. Joshua Samuel Raj^1,*, J. Prince Antony Joel², Salem Alelyani³, Mohammed Saleh Alsaqer³, C. Anand Deva Durai⁴

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1171-1188, 2022, DOI:10.32604/cmc.2022.021667 - 03 November 2021

Abstract Human Adaptive Mechatronics (HAM) includes human and computer system in a closed loop. Elderly person with disabilities, normally carry out their daily routines with some assistance to move their limbs. With the short fall of human care takers, mechatronics devices are used with the likes of exoskeleton and exosuits to assist them. The rehabilitation and occupational therapy equipments utilize the electromyography (EMG) signals to measure the muscle activity potential. This paper focuses on optimizing the HAM model in prediction of intended motion of upper limb with high accuracy and to increase the response time of… More >

Hassan Ashraf¹, Asim Waris^1,*, Syed Omer Gilani¹, Muhammad Umair Tariq¹, Hani Alquhayz²

Intelligent Automation & Soft Computing, Vol.27, No.3, pp. 799-815, 2021, DOI:10.32604/iasc.2021.014765 - 01 March 2021

Abstract Empirical Mode Decomposition (EMD) is a data-driven and fully adaptive signal decomposition technique to decompose a signal into its Intrinsic Mode Functions (IMF). EMD has attained great attention due to its capabilities to process a signal in the frequency-time domain without altering the signal into the frequency domain. EMD-based signal denoising techniques have shown great potential to denoise nonlinear and nonstationary signals without compromising the signal’s characteristics. The denoising procedure comprises three steps, i.e., signal decomposition, IMF thresholding, and signal reconstruction. Thresholding is performed to assess which IMFs contain noise. In this study, Interval Thresholding… More >

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 >

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 >

Hsiang-Wen Huang¹, Ting-Wei Kuo¹, Chi-Long Lee¹, Yan-Ting Lin¹, Yan-Ying Ju², Chih-Hsiu Cheng^1,*

Molecular & Cellular Biomechanics, Vol.16, Suppl.2, pp. 113-115, 2019, DOI:10.32604/mcb.2019.07509

Abstract Wheelchair basketball is mainly designed for people who are physically challenged with permanent lower body disabilities. Free throw execution is one of the basic skills and could represent the preferred shooting mechanics so as to examine the overall shooting mechanics in basketball players. It requires the body to act as a kinetic chain to summate energy from the wheelchair to the upper extremity for the coordinated movements. Researchers have shown that the kinetic chain of the wheelchair basketball athletes could be affected by the kinematic parameters such as the release velocity and shooting angle [1-3].… More >