Biology subjects

Menhaj, M. B.

Publications and source records attributed to Menhaj, M. B..

3 recordsLinked to original sources

bioRxiv2025

Design and Implementation of a Decision Making System for Controlling a Hand Exoskeleton Based on EEG/EMG Signals

This paper presents an approach of combining Electroencephalography (EEG) and Electromyography (EMG) signals to create a hybrid Brain Interface Computer (BCI) device for controlling a hand exoskeleton through classifying the flexion attempt and resting states of the subjects. We analyzed data of 51 healthy and patients with brain lesions that involved the motor cortex and different hand movement disorders. Their EMG and EEG activity were recorded while the subjects attempted to move their index finger. The signals are analyzed through deep neural network, restricted Boltzmann machine and LDA classifier methods to access a reliable accuracy. Further, to evaluate the proposed approach, we designed and implemented a robotic system for rehabilitation of the hand movement to show that it is able to derive assistive control, by detecting flexion movement from the signals as a command and send it to robot. The system is combined with control signals that determine the information of flexion according to measured EMG signals.

neuroscience↗

bioRxiv2023

EEG Signal Processing to Control a Finger Rehabilitation System

This study aims to provide a comprehensive comparison for classification of Electroencephalography (EEG) signal based motor imagery, in time domain and time-frequency domain with different classifiers. We used EEG signals recorded while the subjects were imagining the movement of individual fingers, and analyzed the signals in time domain as well as using wavelet transform and Wigner transform. Our main goal is to compare different methods of feature extraction and classification as the important steps in the process of EEG signals for the Brain-Computer Interface (BCI) system. The experimental results indicate that the Support Vector Machine (SVM) method provides a better classification performance compared with other classification methods. Also, Linear Discriminative Analysis (LDA) performs as well as the SVM, after applying PCA for dimension reduction. The proposed scheme can be applied successfully to BCI systems where the amount of large data.

bioinformatics↗

bioRxiv2018

Spatiotemporal Analysis of Category and Target-related Information Processing in the Brain during Object Detection

To recognize a target object, the brain implements strategies which involve a combination of externally sensory-driven and internally task-driven mechanisms. While several studies have suggested a role for frontal brain areas in enhancing task-related representations in visual cortices, especially the lateral-occipital cortex, they remained silent about the type of information transferred to visual areas. However, the recently developed method of representational causality analysis, allowed us to track the movement of different types of information in the brain. Accordingly, we designed an EEG object detection experiment and evaluated the spatiotemporal dynamics of category- and target-related information across the brain using. Results showed that the prefrontal area initiated the processing of target-related information. This information was then transferred to posterior brain areas during stimulus presentation to facilitate object detection and to direct the decision-making procedure. We also observed that, as compared to category-related information, the target-related information could predict the behavioral detection performance more accurately, suggesting the dominant representation of internal compared to external information in brain signals. These results provided new evidence about the role of prefrontal cortices in the processing of task-related information the brain during object detection.

neuroscience↗