AIMC Topic: Electromyography
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Lower Limb Motion Recognition Based on sEMG and CNN-TL Fusion Model.
Sensors (Basel, Switzerland)
Nov 4, 2024
To enhance the classification accuracy of lower limb movements, a fusion recognition model integrating a surface electromyography (sEMG)-based convolutional neural network, transformer encoder, and long short-term memory network (CNN-Transformer-LSTM...
Multilevel attention mechanism for motion fatigue recognition based on sEMG and ACC signal fusion.
PloS one
Nov 4, 2024
This study aims to develop a cost-effective and reliable motion monitoring device capable of comprehensive fatigue analysis. It achieves this objective by integrating surface electromyography (sEMG) and accelerometer (ACC) signals through a feature f...
Novel multimodal sensing and machine learning strategies to classify cognitive workload in laparoscopic surgery.
European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
Oct 15, 2024
BACKGROUND: Surgeons can experience elevated cognitive workload (CWL) during surgery due to various factors including operative technicalities and the environmental demands of the operating theatre. This can result in poorer outcomes and have a detri...
Identification of Spared and Proportionally Controllable Hand Motor Dimensions in Motor Complete Spinal Cord Injuries Using Latent Manifold Analysis.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Oct 9, 2024
The loss of bilateral hand function is a debilitating challenge for millions of individuals that suffered a motor-complete spinal cord injury (SCI). We have recently demonstrated in eight tetraplegic individuals the presence of highly functional spar...
From Simulation to Reality: Predicting Torque With Fatigue Onset via Transfer Learning.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Oct 7, 2024
Muscle fatigue impacts upper extremity function but is often overlooked in biomechanical models. The present work leveraged a transfer learning approach to improve torque predictions during fatiguing upper extremity movements. We developed two artifi...
Muscle Tone Assessment by Machine Learning Using Surface Electromyography.
Sensors (Basel, Switzerland)
Sep 30, 2024
Muscle tone is defined as the resistance to passive stretch, but this definition is often criticized for its ambiguity since some suggest it is related to a state of preparation for movement. Muscle tone is primarily regulated by the central nervous ...
Hand gesture recognition using sEMG signals with a multi-stream time-varying feature enhancement approach.
Scientific reports
Sep 27, 2024
Hand gesture recognition based on sparse multichannel surface electromyography (sEMG) still poses a significant challenge to deployment as a muscle-computer interface. Many researchers have been working to develop an sEMG-based hand gesture recogniti...
Recurrent Neural Network Enabled Continuous Motion Estimation of Lower Limb Joints From Incomplete sEMG Signals.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Sep 27, 2024
Decoding continuous human motion from surface electromyography (sEMG) in advance is crucial for improving the intelligence of exoskeleton robots. However, incomplete sEMG signals are prevalent on account of unstable data transmission, sensor malfunct...
Performance of a Novel Muscle Synergy Approach for Continuous Motion Estimation on Untrained Motion.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Sep 25, 2024
When applying continuous motion estimation (CME) model based on sEMG to human-robot system, it is inevitable to encounter scenarios in which the motions performed by the user are different from the motions in the training stage of the model. It has b...
An enzyme-inspired specificity in deep learning model for sleep stage classification using multi-channel PSG signals input: Separating training approach and its performance on cross-dataset validation for generalizability.
Computers in biology and medicine
Sep 20, 2024
Numerous automatic sleep stage classification systems have been developed, but none have become effective assistive tools for sleep technicians due to issues with generalization. Four key factors hinder the generalization of these models are instrume...
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