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Electromyography

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Myoelectric digit action decoding with multi-output, multi-class classification: an offline analysis.

Scientific reports
The ultimate goal of machine learning-based myoelectric control is simultaneous and independent control of multiple degrees of freedom (DOFs), including wrist and digit artificial joints. For prosthetic finger control, regression-based methods are ty...

Robotic Rehabilitation in Spinal Cord Injury: A Pilot Study on End-Effectors and Neurophysiological Outcomes.

Annals of biomedical engineering
Robot-aided gait training (RAGT) has been implemented to provide patients with spinal cord injury (SCI) with a physiological limb activation during gait, cognitive engagement, and an appropriate stimulation of peripheral receptors, which are essentia...

Continuous Estimation of Knee Joint Angle Based on Surface Electromyography Using a Long Short-Term Memory Neural Network and Time-Advanced Feature.

Sensors (Basel, Switzerland)
Continuous joint angle estimation based on a surface electromyography (sEMG) signal can be used to improve the man-machine coordination performance of the exoskeleton. In this study, we proposed a time-advanced feature and utilized long short-term me...

Exploring augmented grasping capabilities in a multi-synergistic soft bionic hand.

Journal of neuroengineering and rehabilitation
BACKGROUND: State-of-the-art bionic hands incorporate hi-tech devices which try to overcome limitations of conventional single grip systems. Unfortunately, their complexity often limits mechanical robustness and intuitive prosthesis control. Recently...

Multi-Segmentation Parallel CNN Model for Estimating Assembly Torque Using Surface Electromyography Signals.

Sensors (Basel, Switzerland)
The precise application of tightening torque is one of the important measures to ensure accurate bolt connection and improvement in product assembly quality. Currently, due to the limited assembly space and efficiency, a wrench without the function o...

Intra-subject approach for gait-event prediction by neural network interpretation of EMG signals.

Biomedical engineering online
BACKGROUND: Machine learning models were satisfactorily implemented for estimating gait events from surface electromyographic (sEMG) signals during walking. Most of them are based on inter-subject approaches for data preparation. Aim of the study is ...

Computer Vision-Based Grasp Pattern Recognition With Application to Myoelectric Control of Dexterous Hand Prosthesis.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Artificial intelligence provides new feasibilities to the control of dexterous prostheses. To achieve suitable grasps over various objects, a novel computer vision-based classification method assorting objects into different grasp patterns is propose...

High accurate lightweight deep learning method for gesture recognition based on surface electromyography.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Surface Electromyography (sEMG) is used mostly for neuromuscular diagnosis, assistive technology, physical rehabilitation, and human-computer interactions. Achieving a precise and lightweight method along with low latency f...

Comparison study of classification methods of intramuscular electromyography data for non-human primate model of traumatic spinal cord injury.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
Traumatic spinal cord injury is a serious neurological disorder. Patients experience a plethora of symptoms that can be attributed to the nerve fiber tracts that are compromised. This includes limb weakness, sensory impairment, and truncal instabilit...

Characterizing forearm muscle activity in young adults during dynamic wrist flexion-extension movement using a wrist robot.

Journal of biomechanics
Current research suggests that the wrist extensor muscles function as the primary stabilizers of the wrist-joint complex. However, most investigations have utilized isometric study designs, with little consideration for wrist dynamics or changes in p...