AIMC Topic: Electromyography

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EMG-based Multi-User Hand Gesture Classification via Unsupervised Transfer Learning Using Unknown Calibration Gestures.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Mar 12, 2024
The poor generalization performance and heavy training burden of the gesture classification model contribute as two main barriers that hinder the commercialization of sEMG-based human-machine interaction (HMI) systems. To overcome these challenges, e...
Electromyography Machine Learning Humans Calibration Algorithms Neural Networks, Computer Gestures
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A Physics-Informed Low-Shot Adversarial Learning for sEMG-Based Estimation of Muscle Force and Joint Kinematics.

IEEE journal of biomedical and health informatics Mar 6, 2024
Muscle force and joint kinematics estimation from surface electromyography (sEMG) are essential for real-time biomechanical analysis of the dynamic interplay among neural muscle stimulation, muscle dynamics, and kinetics. Recent advances in deep neur...
Humans Biomechanical Phenomena Upper Extremity Neural Networks, Computer Electromyography Muscles
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Hip contact forces can be predicted with a neural network using only synthesised key points and electromyography in people with hip osteoarthritis.

Osteoarthritis and cartilage Mar 3, 2024
OBJECTIVE: To develop and validate a neural network to estimate hip contact forces (HCF), and lower body kinematics and kinetics during walking in individuals with hip osteoarthritis (OA) using synthesised anatomical key points and electromyography. ...
Female Aged Biomechanical Phenomena Humans Neural Networks, Computer Gait Hip Joint Muscle, Skeletal Osteoarthritis, Hip Weight-Bearing Electromyography Male Middle Aged Walking
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Specific Instructions Are Important: A Cross-sectional Study on Device Parameters and Instruction Types While Walking With a Robot in Children and Adolescents.

American journal of physical medicine & rehabilitation Feb 29, 2024
OBJECTIVE: The aim of the study is to evaluate how gait kinematics and muscle activity during robot-assisted gait training are affected by different combinations of parameter settings and a number of instruction types, ranging from no instructions to...
Adolescent Child Muscle, Skeletal Robotics Electromyography Walking Cross-Sectional Studies Biomechanical Phenomena Male Humans Female Gait Disorders, Neurologic Gait Exercise Therapy
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Deep learning approach to improve the recognition of hand gesture with multi force variation using electromyography signal from amputees.

Medical engineering & physics Feb 28, 2024
Variations in muscular contraction are known to significantly impact the quality of the generated EMG signal and the output decision of a proposed classifier. This is an issue when the classifier is further implemented in prosthetic hand design. Ther...
Humans Gestures Neural Networks, Computer Electromyography Algorithms Amputees Deep Learning
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Classification of Action Potentials With High Variability Using Convolutional Neural Network for Motor Unit Tracking.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Feb 26, 2024
The reliable classification of motor unit action potentials (MUAPs) provides the possibility of tracking motor unit (MU) activities. However, the variation of MUAP profiles caused by multiple factors in realistic conditions challenges the accurate cl...
Electromyography Humans Motor Neurons Neural Networks, Computer Action Potentials Algorithms Muscle, Skeletal
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Teleoperation of an Anthropomorphic Robot Hand with a Metamorphic Palm and Tunable-Stiffness Soft Fingers.

Soft robotics Feb 21, 2024
Teleoperation in soft robotics can endow soft robots with the ability to perform complex tasks through human-robot interaction. In this study, we propose a teleoperated anthropomorphic soft robot hand with variable degrees of freedom (DOFs) and a met...
Electromyography Fingers Equipment Design Hand Humans Hand Strength Robotics
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Deep learning and predictive modelling for generating normalised muscle function parameters from signal images of mandibular electromyography.

Medical & biological engineering & computing Feb 20, 2024
Challenges arise in accessing archived signal outputs due to proprietary software limitations. There is a notable lack of exploration in open-source mandibular EMG signal conversion for continuous access and analysis, hindering tasks such as pattern ...
Electromyography Temporomandibular Joint Masseter Muscle Mandible Signal Processing, Computer-Assisted Mastication Female Young Adult Adult Male Deep Learning Humans
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The Impact of Feature Extraction on Classification Accuracy Examined by Employing a Signal Transformer to Classify Hand Gestures Using Surface Electromyography Signals.

Sensors (Basel, Switzerland) Feb 16, 2024
Interest in developing techniques for acquiring and decoding biological signals is on the rise in the research community. This interest spans various applications, with a particular focus on prosthetic control and rehabilitation, where achieving prec...
Gestures Neural Networks, Computer Signal Processing, Computer-Assisted Algorithms Electromyography
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Classification of EMG signals with CNN features and voting ensemble classifier.

Computer methods in biomechanics and biomedical engineering Feb 5, 2024
Electromyography (EMG) signals are primarily used to control prosthetic hands. Classifying hand gestures efficiently with EMG signals presents numerous challenges. In addition to overcoming these challenges, a successful combination of feature extrac...
Humans Hand Electromyography Voting Neural Networks, Computer Algorithms Signal Processing, Computer-Assisted
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