AIMC Topic: Electromyography

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Explainable Deep Learning Model for EMG-Based Finger Angle Estimation Using Attention.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Jul 15, 2022
Electromyography (EMG) is one of the most common methods to detect muscle activities and intentions. However, it has been difficult to estimate accurate hand motions represented by the finger joint angles using EMG signals. We propose an encoder-deco...
Fingers Muscle, Skeletal Humans Electromyography Movement Deep Learning
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Beyond Efficiency: Surface Electromyography Enables Further Insights into the Surgical Movements of Urologists.

Journal of endourology Jul 12, 2022
Surgical skill evaluation while performing minimally invasive surgeries is a highly complex task. It is important to objectively assess an individual's technical skills throughout surgical training to monitor progress and to intervene when skills ar...
Humans Electromyography Internship and Residency Clinical Competence Urologists Robotics
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Evaluation of surgical skill using machine learning with optimal wearable sensor locations.

PloS one Jun 3, 2022
Evaluation of surgical skills during minimally invasive surgeries is needed when recruiting new surgeons. Although surgeons' differentiation by skill level is highly complex, performance in specific clinical tasks such as pegboard transfer and knot t...
Muscle, Skeletal Bayes Theorem Electromyography Machine Learning Wearable Electronic Devices
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Deep Learning-Based Surface Nerve Electromyography Data of E-Health Electroacupuncture in Treatment of Peripheral Facial Paralysis.

Computational and mathematical methods in medicine May 31, 2022
This study was aimed at exploring the application value of electroacupuncture in the treatment of peripheral facial palsy using surface nerve electromyogram (EMG) image data based on deep learning. The surface nerve EMG recognition model was construc...
Facial Paralysis Electroacupuncture Humans Electromyography Deep Learning Telemedicine
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Soft, Lightweight Wearable Robots to Support the Upper Limb in Activities of Daily Living: A Feasibility Study on Chronic Stroke Patients.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society May 30, 2022
Stroke can be a devastating condition that impairs the upper limb and reduces mobility. Wearable robots can aid impaired users by supporting performance of Activities of Daily Living (ADLs). In the past decade, soft devices have become popular due to...
Electromyography Stroke Feasibility Studies Activities of Daily Living Muscle, Skeletal Robotics Humans Wearable Electronic Devices Upper Extremity
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Decoding neural activity preceding balance loss during standing with a lower-limb exoskeleton using an interpretable deep learning model.

Journal of neural engineering May 26, 2022
Falls are a leading cause of death in adults 65 and older. Recent efforts to restore lower-limb function in these populations have seen an increase in the use of wearable robotic systems; however, fall prevention measures in these systems require ear...
Deep Learning Electroencephalography Humans Adult Exoskeleton Device Electromyography Brain-Computer Interfaces
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Estimating muscle activation from EMG using deep learning-based dynamical systems models.

Journal of neural engineering May 19, 2022
. To study the neural control of movement, it is often necessary to estimate how muscles are activated across a variety of behavioral conditions. One approach is to try extracting the underlying neural command signal to muscles by applying latent var...
Animals Deep Learning Locomotion Bayes Theorem Electromyography Rats Muscle, Skeletal
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CSAC-Net: Fast Adaptive sEMG Recognition through Attention Convolution Network and Model-Agnostic Meta-Learning.

Sensors (Basel, Switzerland) May 11, 2022
Gesture recognition through surface electromyography (sEMG) provides a new method for the control algorithm of bionic limbs, which is a promising technology in the field of human-computer interaction. However, subject specificity of sEMG along with t...
Learning Gestures Electromyography Humans Neural Networks, Computer Algorithms
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A Systematic Study on Electromyography-Based Hand Gesture Recognition for Assistive Robots Using Deep Learning and Machine Learning Models.

Sensors (Basel, Switzerland) May 11, 2022
Upper limb amputation severely affects the quality of life and the activities of daily living of a person. In the last decade, many robotic hand prostheses have been developed which are controlled by using various sensing technologies such as artific...
Electromyography Artificial Limbs Activities of Daily Living Upper Extremity Gestures Robotics Quality of Life Deep Learning Humans Machine Learning
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Improved and Secured Electromyography in the Internet of Health Things.

IEEE journal of biomedical and health informatics May 5, 2022
Physiological signals are of great importance for clinical analysis but are prone to diverse interferences. To enable practical applications, biosignal quality issues, especially contaminants, need to be dealt with automated processes. For example, a...
Electromyography Signal Processing, Computer-Assisted Internet Humans Neural Networks, Computer Algorithms
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