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Electromyography

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Artificial intelligence for automatic classification of needle EMG signals: A scoping review.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
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
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 ...

ExoMechHand prototype development and testing with EMG signals for hand rehabilitation.

Medical engineering & physics
Rehabilitation is a major requirement to improve the quality of life and mobility of patients with disabilities. The use of rehabilitative devices without continuous supervision of medical experts is increasing manifold, mainly due to prolonged thera...

High-Performance Hydrogel Sensors Enabled Multimodal and Accurate Human-Machine Interaction System for Active Rehabilitation.

Advanced materials (Deerfield Beach, Fla.)
Human-machine interaction (HMI) technology shows an important application prospect in rehabilitation medicine, but it is greatly limited by the unsatisfactory recognition accuracy and wearing comfort. Here, this work develops a fully flexible, confor...

LSTM-MSA: A Novel Deep Learning Model With Dual-Stage Attention Mechanisms Forearm EMG-Based Hand Gesture Recognition.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
This paper introduces the Long Short-Term Memory with Dual-Stage Attention (LSTM-MSA) model, an approach for analyzing electromyography (EMG) signals. EMG signals are crucial in applications like prosthetic control, rehabilitation, and human-computer...

A wearable system to assist impaired-neck patients: Design and evaluation.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
Patients with neurological disorders, such as amyotrophic lateral sclerosis, Parkinson's disease, and cerebral palsy, often face challenges due to head-neck immobility. The conventional treatment approach involves using a neck collar to maintain an u...

A Multimodal Multilevel Converged Attention Network for Hand Gesture Recognition With Hybrid sEMG and A-Mode Ultrasound Sensing.

IEEE transactions on cybernetics
Gesture recognition based on surface electromyography (sEMG) has been widely used in the field of human-machine interaction (HMI). However, sEMG has limitations, such as low signal-to-noise ratio and insensitivity to fine finger movements, so we cons...

Novel Wearable HD-EMG Sensor With Shift-Robust Gesture Recognition Using Deep Learning.

IEEE transactions on biomedical circuits and systems
In this work, we present a hardware-software solution to improve the robustness of hand gesture recognition to confounding factors in myoelectric control. The solution includes a novel, full-circumference, flexible, 64-channel high-density electromyo...

Artificial intelligence-based classification of motor unit action potentials in real-world needle EMG recordings.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: To develop an artificial neural network (ANN) for classification of motor unit action potential (MUAP) duration in real-word, unselected and uncleaned needle electromyography (n-EMG) recordings.

Design and Analysis of an Upper Limb Rehabilitation Robot Based on Multimodal Control.

Sensors (Basel, Switzerland)
To address the rehabilitation needs of upper limb hemiplegic patients in various stages of recovery, streamline the workload of rehabilitation professionals, and provide data visualization, our research team designed a six-degree-of-freedom upper lim...