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Electromyography

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A Perifacial EMG Acquisition System for Facial-Muscle-Movement Recognition.

Sensors (Basel, Switzerland)
This paper proposes a portable wireless transmission system for the multi-channel acquisition of surface electromyography (EMG) signals. Because EMG signals have great application value in psychotherapy and human-computer interaction, this system is ...

Feature recognition in multiple CNNs using sEMG images from a prototype comfort test.

Computer methods and programs in biomedicine
OBJECTIVE: Deep learning-based CNN networks have recently been investigated to solve the problem of body posture recognition based on surface electromyographic signals (sEMG). Influenced by these studies, to develop a combined approach of sEMG and CN...

Cybersecurity in neural interfaces: Survey and future trends.

Computers in biology and medicine
With the joint advancement in areas such as pervasive neural data sensing, neural computing, neuromodulation and artificial intelligence, neural interface has become a promising technology facilitating both the closed-loop neurorehabilitation for neu...

Active Human-Following Control of an Exoskeleton Robot With Body Weight Support.

IEEE transactions on cybernetics
This article presents an active human-following control of the lower limb exoskeleton for gait training. First, to improve safety, considering the human balance, the OpenPose-based visual feedback is used to estimate the individual's pose, then, the ...

3DSleepNet: A Multi-Channel Bio-Signal Based Sleep Stages Classification Method Using Deep Learning.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
A novel multi-channel-based 3D convolutional neural network (3D-CNN) is proposed in this paper to classify sleep stages. Time domain features, frequency domain features, and time-frequency domain features are extracted from electroencephalography (EE...

Combining electromyographic and electrical impedance data sets through machine learning: A study in D2-mdx and wild-type mice.

Muscle & nerve
INTRODUCTION/AIMS: Needle impedance-electromyography (iEMG) assesses the active and passive electrical properties of muscles concurrently by using a novel needle with six electrodes, two for EMG and four for electrical impedance myography (EIM). Here...

A Novel Event-Driven Spiking Convolutional Neural Network for Electromyography Pattern Recognition.

IEEE transactions on bio-medical engineering
Electromyography (EMG) pattern recognition is an important technology for prosthesis control and human-computer interaction etc. However, the practical application of EMG pattern recognition is hampered by poor accuracy and robustness due to electrod...

Customization of a passive surgical support robot to specifications for ophthalmic surgery and preliminary evaluation.

Japanese journal of ophthalmology
PURPOSE: To customize a passive surgery support robot for ophthalmic surgery and preliminarily evaluate its performance.

A Novel Approach to Detecting Muscle Fatigue Based on sEMG by Using Neural Architecture Search Framework.

IEEE transactions on neural networks and learning systems
Muscle fatigue detection is of great significance to human physiological activities, but many complex factors increase the difficulty of this task. In this article, we integrate several effective techniques to distinguish muscle states under fatigue ...

Transfer Learning on Electromyography (EMG) Tasks: Approaches and Beyond.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Machine learning on electromyography (EMG) has recently achieved remarkable success on various tasks, while such success relies heavily on the assumption that the training and future data must be of the same data distribution. However, this assumptio...