AIMC Topic: Electromyography

Clear Filters Showing 211 to 220 of 659 articles

sEMG-Based Gain-Tuned Compliance Control for the Lower Limb Rehabilitation Robot during Passive Training.

Sensors (Basel, Switzerland) Oct 17, 2022
The lower limb rehabilitation robot is a typical man-machine coupling system. Aiming at the problems of insufficient physiological information and unsatisfactory safety performance in the compliance control strategy for the lower limb rehabilitation ...
Electromyography Electric Impedance Humans Lower Extremity Robotics
View on PubMed DOI

Ultrathin crystalline-silicon-based strain gauges with deep learning algorithms for silent speech interfaces.

Nature communications Oct 3, 2022
A wearable silent speech interface (SSI) is a promising platform that enables verbal communication without vocalization. The most widely studied methodology for SSI focuses on surface electromyography (sEMG). However, sEMG suffers from low scalabilit...
Algorithms Reproducibility of Results Electromyography Silicon Deep Learning Speech
View on PubMed DOI

Using Deep Learning for Task and Tremor Type Classification in People with Parkinson's Disease.

Sensors (Basel, Switzerland) Sep 27, 2022
Hand tremor is one of the dominating symptoms of Parkinson's disease (PD), which significantly limits activities of daily living. Along with medications, wearable devices have been proposed to suppress tremor. However, suppressing tremor without inte...
Parkinson Disease Electromyography Activities of Daily Living Tremor Humans Deep Learning
View on PubMed DOI

sEMG-Based Gesture Recognition Using Deep Learning From Noisy Labels.

IEEE journal of biomedical and health informatics Sep 9, 2022
Gesture recognition for myoelectric prosthesis control utilizing sparse multichannel surface Electromyography (sEMG) is a challenging task, and from a Muscle-Computer Interface (MCI) standpoint, the performance is still far from optimal. However, the...
Neural Networks, Computer Algorithms Humans Electromyography Gestures Hand Deep Learning
View on PubMed DOI

Individual Identification by Late Information Fusion of EmgCNN and EmgLSTM from Electromyogram Signals.

Sensors (Basel, Switzerland) Sep 7, 2022
This paper is concerned with individual identification by late fusion of two-stream deep networks from Electromyogram (EMG) signals. EMG signal has more advantages on security compared to other biosignals exposed visually, such as the face, iris, and...
Neural Networks, Computer Databases, Factual Humans Electromyography
View on PubMed DOI

Residual one-dimensional convolutional neural network for neuromuscular disorder classification from needle electromyography signals with explainability.

Computer methods and programs in biomedicine Aug 24, 2022
BACKGROUND AND OBJECTIVE: Neuromuscular disorders are diseases that damage our ability to control body movements. Needle electromyography (nEMG) is often used to diagnose neuromuscular disorders, which is an electrophysiological test measuring electr...
Movement Humans Electromyography Neural Networks, Computer Algorithms
View on PubMed DOI

A Systematic Review of Sensor Fusion Methods Using Peripheral Bio-Signals for Human Intention Decoding.

Sensors (Basel, Switzerland) Aug 23, 2022
Humans learn about the environment by interacting with it. With an increasing use of computer and virtual applications as well as robotic and prosthetic devices, there is a need for intuitive interfaces that allow the user to have an embodied interac...
Humans Intention Robotics Myography Upper Extremity Electromyography
View on PubMed DOI

A Home-based Tele-rehabilitation System With Enhanced Therapist-patient Remote Interaction: A Feasibility Study.

IEEE journal of biomedical and health informatics Aug 11, 2022
As a promising alternative to hospital-based manual therapy, robot-assisted tele-rehabilitation therapy has shown significant benefits in reducing the therapist's workload and accelerating the patient's recovery process. However, existing telerobotic...
Telerehabilitation Electromyography Humans Feasibility Studies Robotics Movement
View on PubMed DOI

Toward Robust, Adaptiveand Reliable Upper-Limb Motion Estimation Using Machine Learning and Deep Learning-A Survey in Myoelectric Control.

IEEE journal of biomedical and health informatics Aug 11, 2022
To develop multi-functionalhuman-machine interfaces that can help disabled people reconstruct lost functions of upper-limbs, machine learning (ML) and deep learning (DL) techniques have been widely implemented to decode human movement intentions from...
Upper Extremity Deep Learning Electromyography Machine Learning Humans Artificial Limbs Reproducibility of Results Movement
View on PubMed DOI

A novel sEMG data augmentation based on WGAN-GP.

Computer methods in biomechanics and biomedical engineering Jul 21, 2022
The classification of sEMG signals is fundamental in applications that use mechanical prostheses, making it necessary to work with generalist databases that improve the accuracy of those classifications. Therefore, synthetic signal generation can be ...
Movement Electromyography Artificial Limbs Neural Networks, Computer
View on PubMed DOI
Popular Topics
Recent Journals