AIMC Topic: Electromyography
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Human arm weight compensation in rehabilitation robotics: efficacy of three distinct methods.
Journal of neuroengineering and rehabilitation
Feb 5, 2020
BACKGROUND: Arm weight compensation with rehabilitation robots for stroke patients has been successfully used to increase the active range of motion and reduce the effects of pathological muscle synergies. However, the differences in structure, perfo...
Estimation of absolute states of human skeletal muscle via standard B-mode ultrasound imaging and deep convolutional neural networks.
Journal of the Royal Society, Interface
Jan 29, 2020
The objective is to test automated estimation of active and passive skeletal muscle states using ultrasonic imaging. Current technology (electromyography, dynamometry, shear wave imaging) provides no general, non-invasive method for online estimatio...
Hand Gesture Recognition Using Compact CNN Via Surface Electromyography Signals.
Sensors (Basel, Switzerland)
Jan 26, 2020
By training the deep neural network model, the hidden features in Surface Electromyography(sEMG) signals can be extracted. The motion intention of the human can be predicted by analysis of sEMG. However, the models recently proposed by researchers of...
Design of a deep learning model for automatic scoring of periodic and non-periodic leg movements during sleep validated against multiple human experts.
Sleep medicine
Jan 23, 2020
OBJECTIVE: Currently, manual scoring is the gold standard of leg movement scoring (LMs) and periodic LMs (PLMS) in overnight polysomnography (PSG) studies, which is subject to inter-scorer variability. The objective of this study is to design and val...
An Optimal Electrical Impedance Tomography Drive Pattern for Human-Computer Interaction Applications.
IEEE transactions on biomedical circuits and systems
Jan 20, 2020
In this article, we presented an optimal Electrical Impedance Tomography (EIT) drive pattern based on feature selection and model explanation, and proposed a portable EIT system for applications in human-computer interaction for gesture recognition a...
Competitive Learning in a Spiking Neural Network: Towards an Intelligent Pattern Classifier.
Sensors (Basel, Switzerland)
Jan 16, 2020
One of the modern trends in the design of human-machine interfaces (HMI) is to involve the so called spiking neuron networks (SNNs) in signal processing. The SNNs can be trained by simple and efficient biologically inspired algorithms. In particular,...
Robotic-assisted hand therapy for improvement of hand function in children with cerebral palsy: a case series study.
European journal of physical and rehabilitation medicine
Jan 14, 2020
BACKGROUND: Most types of robot-assisted training (RT) have been used in Cerebral Palsy (CP) patients only focus on proximal upper extremity. Few of study investigated the effect of distal upper extremity training.
Fatigue Evaluation through Machine Learning and a Global Fatigue Descriptor.
Journal of healthcare engineering
Jan 7, 2020
Research in physiology and sports science has shown that fatigue, a complex psychophysiological phenomenon, has a relevant impact in performance and in the correct functioning of our motricity system, potentially being a cause of damage to the human ...
A Deep Transfer Learning Approach to Reducing the Effect of Electrode Shift in EMG Pattern Recognition-Based Control.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Dec 25, 2019
An important barrier to commercialization of pattern recognition myoelectric control of prostheses is the lack of robustness to confounding factors such as electrode shift, skin impedance variations, and learning effects. To overcome this challenge, ...
The Interaction Between Feedback Type and Learning in Routine Grasping With Myoelectric Prostheses.
IEEE transactions on haptics
Dec 23, 2019
While prosthetic fitting after upper-limb loss allows for restoration of motor functions, it deprives the amputee of tactile sensations that are essential for grasp control in able-bodied subjects. Therefore, it is commonly assumed that restoring the...
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