AI Medical Compendium Topic:
Electromyography

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Functional Tasks Performed by People with Severe Muscular Atrophy Using an sEMG Controlled Robotic Manipulator.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
For paralyzed people activities of daily living like eating or drinking are impossible without external assistance. Robotic assistance systems can give these people a part of their independence back. Especially if the operation with a joystick is not...

A sEMG Classification Framework with Less Training Data.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Supervised machine learning algorithms, such as Artificial Neural Network (ANN), have been applied to surface electromyograph (sEMG) to classify user's muscular states. This paper introduces a novel framework to design a binary sEMG classifier to dis...

Interactive Sleep Stage Labelling Tool For Diagnosing Sleep Disorder Using Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Traditional manual scoring of the entire sleep for diagnosis of sleep disorders is highly time-consuming and dependent to experts experience. Thus, automatic methods based on electrooculography (EOG) analysis have been increasingly attracted attentio...

Multichannel Sleep Stage Classification and Transfer Learning using Convolutional Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Current sleep medicine relies on the supervised analysis of polysomnographic measurements, comprising amongst others electroencephalogram (EEG), electromyogram (EMG), and electrooculogram (EOG) signals. Convolutional neural networks (CNN) provide an ...

Gated Recurrent Neural Networks for EMG-Based Hand Gesture Classification. A Comparative Study.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Electromyographic activities (EMG) generated during contraction of upper limb muscles can be mapped to distinct hand gestures and movements, posing them as a promising modality for prosthetic and cybernetic applications. This paper presents a compara...

An Optimal Method of Training the Specific Lower Limb Muscle Group Using an Exoskeletal Robot.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
This paper suggests a novel method of strengthening specific muscle groups in the lower limb during a functional movement. When the foot of an user wearing an exoskeletal robot follows a given path, the contribution of each muscle group to generate t...

A Deep Learning Architecture for Temporal Sleep Stage Classification Using Multivariate and Multimodal Time Series.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Sleep stage classification constitutes an important preliminary exam in the diagnosis of sleep disorders. It is traditionally performed by a sleep expert who assigns to each 30 s of the signal of a sleep stage, based on the visual inspection of signa...

Self-powered robots to reduce motor slacking during upper-extremity rehabilitation: a proof of concept study.

Restorative neurology and neuroscience
BACKGROUND: Robotic rehabilitation is a highly promising approach to recover lost functions after stroke or other neurological disorders. Unfortunately, robotic rehabilitation currently suffers from "motor slacking", a phenomenon in which the human m...

Finger language recognition based on ensemble artificial neural network learning using armband EMG sensors.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Deaf people use sign or finger languages for communication, but these methods of communication are very specialized. For this reason, the deaf can suffer from social inequalities and financial losses due to their communication restriction...

A wearable resistive robot facilitates locomotor adaptations during gait.

Restorative neurology and neuroscience
BACKGROUND: Robotic-resisted treadmill walking is a form of task-specific training that has been used to improve gait function in individuals with neurological injury, such as stroke, spinal cord injury, or cerebral palsy. Traditionally, these device...