EEG sensor driven assistive device for elbow and finger rehabilitation using deep learning

P Mukherjee, AH Roy - Expert Systems with Applications, 2024 - Elsevier
In today's world, a large number of people suffer from motor impairment-related challenges.
Rehabilitation is the main method used to overcome these difficulties. The goal of the paper …

Development of a novel machine learning-based approach for brain function assessment and integrated software solution

J Qu, L Cui, W Guo, L Bu, Z Wang - Advanced Engineering Informatics, 2024 - Elsevier
Abstract Industry 5.0 emphasizes human-centered solutions. However, bridging the gap
between human conditions and engineering systems remains a challenge in this era …

Printed multi-EMG electrodes on the 3D surface of an orthosis for rehabilitation: A feasibility study

E Cantu, T Fapanni, G Giorgi, C Narduzzi… - IEEE Sensors …, 2021 - ieeexplore.ieee.org
The article proposes the development of an innovative prototype of smart orthosis with a fully
integrated multi-electrodes matrix for electromyography (EMG), to improve non-invasive …

Use of force feedback device in a hybrid brain-computer interface based on SSVEP, EOG and eye tracking for sorting items

A Kubacki - Sensors, 2021 - mdpi.com
Research focused on signals derived from the human organism is becoming increasingly
popular. In this field, a special role is played by brain-computer interfaces based on …

[HTML][HTML] A comprehensive study of EEG-based control of artificial arms

AS Ihab - Vojnotehnički glasnik, 2023 - cyberleninka.ru
Introduction/purpose: The electroencephalography (EEG) signal has a great impact on the
development of prosthetic arm control technology. EEG signals are used as the main tool in …

[PDF][PDF] Safety and Security Aspects of Implanted Brain-Computer Interface (BCI) for Human-Robot Interaction

IA Satam - International Journal of Multidisciplinary Research and …, 2023 - ijmrap.com
The study of brain-computer interfaces (BCIs) has great potential in a variety of fields. Both
invasive and non-invasive monitoring technologies can interpret brain activity, opening the …

Online Hand Movement Recognition System with EEG-EMG Fusion Using One-Dimensional Convolutional Neural Network

H Wang, H Jia, Z Sun, F Duan - 2024 IEEE/RSJ International …, 2024 - ieeexplore.ieee.org
Upper limb amputees face significant challenges in their daily lives due to the loss of hand
or arm functionality. Researchers have developed upper limb prostheses to restore normal …

Biological Signals for the Control of Robotic Devices in Rehabilitation: An Innovative Review

D Huamanchahua, LA Huamán-Lévano… - … IOT, Electronics and …, 2022 - ieeexplore.ieee.org
Biological signals have been extensively studied for disease diagnosis, treatment, and
biomedical research to know the patient's health status; however, the potential of these …

Evaluating EEG–EMG Fusion-Based Classification as a Method for Improving Control of Wearable Robotic Devices for Upper-Limb Rehabilitation

JG Tryon - 2023 - search.proquest.com
Musculoskeletal disorders are the biggest cause of disability worldwide, and wearable
mechatronic rehabilitation devices have been proposed for treatment. However, before …

Аналіз та особливості методу керування біонічним протезом за допомогою електроенцефалографії (аналітичний огляд)

РІ Білий, ВВ Левицький - Оптико-електроннi iнформацiйно …, 2024 - oeipt.vntu.edu.ua
Анотація Ця стаття надає огляд сучасних досліджень у напрямку методу керування
біонічним протезом за допомогою електроенцефалографії (ЕЕГ), який є важливою та …