AIMC Topic: Electromyography
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Generalizing Upper Limb Force Modeling With Transfer Learning: A Multimodal Approach Using EMG and IMU for New Users and Conditions.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Jan 19, 2024
In the field of EMG-based force modeling, the ability to generalize models across individuals could play a significant role in its adoption across a range of applications, including assistive devices, robotic and rehabilitation devices. However, curr...
Deep Learning-Based Identification Algorithm for Transitions Between Walking Environments Using Electromyography Signals Only.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Jan 19, 2024
Although studies on terrain identification algorithms to control walking assistive devices have been conducted using sensor fusion, studies on transition classification using only electromyography (EMG) signals have yet to be conducted. Therefore, th...
Integrated block-wise neural network with auto-learning search framework for finger gesture recognition using sEMG signals.
Artificial intelligence in medicine
Jan 17, 2024
Accurate finger gesture recognition with surface electromyography (sEMG) is essential and long-challenge in the muscle-computer interface, and many high-performance deep learning models have been developed to predict gestures. For these models, probl...
User identification system based on 2D CQT spectrogram of EMG with adaptive frequency resolution adjustment.
Scientific reports
Jan 16, 2024
User identification systems based on electromyogram (EMG) signals, generated inside the body in different signal patterns and exhibiting individual characteristics based on muscle development and activity, are being actively researched. However, nonl...
From Forearm to Wrist: Deep Learning for Surface Electromyography-Based Gesture Recognition.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Jan 15, 2024
Though the forearm is the focus of the prostheses, myoelectric control with the electrodes on the wrist is more comfortable for general consumers because of its unobtrusiveness and incorporation with the existing wrist-based wearables. Recently, deep...
Factors Affecting Workers' Mental Stress in Handover Activities During Human-Robot Collaboration.
Human factors
Jan 12, 2024
OBJECTIVE: This study investigated the effects of different approach directions, movement speeds, and trajectories of a co-robot's end-effector on workers' mental stress during handover tasks.
Cross-User Electromyography Pattern Recognition Based on a Novel Spatial-Temporal Graph Convolutional Network.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Jan 12, 2024
With the goal of promoting the development of myoelectric control technology, this paper focuses on exploring graph neural network (GNN) based robust electromyography (EMG) pattern recognition solutions. Given that high-density surface EMG (HD-sEMG) ...
Exploring the impact of human-robot interaction on workers' mental stress in collaborative assembly tasks.
Applied ergonomics
Jan 5, 2024
Advances in robotics have contributed to the prevalence of human-robot collaboration (HRC). However, working and interacting with collaborative robots in close proximity can be psychologically stressful. Therefore, understanding the impacts of human-...
Artificial intelligence for automatic classification of needle EMG signals: A scoping review.
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
Jan 3, 2024
OBJECTIVE: This scoping review provides an overview of artificial intelligence (AI), including machine and deep learning techniques, in the interpretation of clinical needle electromyography (nEMG) signals.
The role of artificial intelligence in electrodiagnostic and neuromuscular medicine: Current state and future directions.
Muscle & nerve
Dec 27, 2023
The rapid advancements in artificial intelligence (AI), including machine learning (ML), and deep learning (DL) have ushered in a new era of technological breakthroughs in healthcare. These technologies are revolutionizing the way we utilize medical ...
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