IoT-driven augmented reality and virtual reality systems in neurological sciences

M Sahu, R Gupta, RK Ambasta, P Kumar - Internet of Things, 2024 - Elsevier
Research in augmented and virtual reality in congregation with the Internet of Things has
opened many avenues in diagnosing and treating neurological disorders. Augmented reality …

[HTML][HTML] Teleoperated robotic arm movement using electromyography signal with wearable Myo armband

HF Hassan, SJ Abou-Loukh, IK Ibraheem - Journal of King Saud University …, 2020 - Elsevier
The primary purpose of this research is to move a 5-DoF Aideepen ROT3U robotic arm in
real-time based on the surface Electromyography (sEMG) signal obtained from a wireless …

Fuzzy inference system (FIS)-long short-term memory (LSTM) network for electromyography (EMG) signal analysis

R Suppiah, N Kim, A Sharma… - Biomedical physics & …, 2022 - iopscience.iop.org
A wide range of application domains, s such as remote robotic control, rehabilitation, and
remote surgery, require capturing neuromuscular activities. The reliability of the application …

Intramuscular EMG feature extraction and evaluation at different arm positions and hand postures based on a statistical criterion method

A Asghar, SJ Khan, F Azim… - Proceedings of the …, 2023 - journals.sagepub.com
Prostheses control using electromyography signals have shown promising aspects in
various fields including rehabilitation sciences and assistive technology controlled devices …

BIO‐inspired fuzzy inference system—For physiological signal analysis

R Suppiah, N Kim, K Abidi… - IET Cyber‐Systems and …, 2023 - Wiley Online Library
When a person's neuromuscular system is affected by an injury or disease, Activities‐for‐
Daily‐Living (ADL), such as gripping, turning, and walking, are impaired …

A novel neuroevolution model for emg-based hand gesture classification

Y Dweiri, Y Hajjar, O Hatahet - Neural Computing and Applications, 2023 - Springer
Classification of hand gestures from multichannel surface electromyography (sEMG) has
been widely explored for the control of robotic prostheses. Several deep-learning algorithms …

Analysing the effect of robotic gait on lower extremity muscles and classification by using deep learning

İ Çalıkuşu, E Uzunhisarcıklı, U Fidan… - Computer Methods in …, 2022 - Taylor & Francis
Robotic gait training helps the nervous system recover and strengthen weak muscle groups.
Many studies in the literature show that applying robotic gait rehabilitation to patients with …

High precision activity tracker based on the correlation of accelerometer and EMG data

P Faragό, R Groza, S Hintea - 2019 42nd International …, 2019 - ieeexplore.ieee.org
Wearable biomedical electronics are a road opener for ubiquitous healthcare. In this context,
correlation of biomedical data acquired from different wearable sensors enable remote …

Design of an intelligent controller for myoelectric prostheses based on multilayer perceptron neural network

MN Raheema, JS Hussain… - IOP Conference Series …, 2020 - iopscience.iop.org
Myoelectric prostheses have been researched widely, and some cases have been
implemented to be used by amputees in real life. However, natural control of an active …

[PDF][PDF] A decision-making mechanism based on EMG signals and adaptive neural fuzzy inference system (ANFIS) for hand gesture prediction

DH Kısa, MA Özdemir, O Güren… - Journal of the Faculty of …, 2023 - researchgate.net
Purpose: The aim is to automatically predict 7 hand gestures using fuzzy logic (FL) and EMG
signals. Theory and Methods: EMG data were collected from 30 participants while they …