[HTML][HTML] A systematic review on surface electromyography-based classification system for identifying hand and finger movements

A Sultana, F Ahmed, MS Alam - Healthcare Analytics, 2023 - Elsevier
The developments in engineering fields have extended the use of electromyography (EMG)
beyond traditional diagnostic applications to multifarious areas like movement analysis …

Sign language recognition using the electromyographic signal: a systematic literature review

A Ben Haj Amor, O El Ghoul, M Jemni - Sensors, 2023 - mdpi.com
The analysis and recognition of sign languages are currently active fields of research
focused on sign recognition. Various approaches differ in terms of analysis methods and the …

An intelligent neuromarketing system for predicting consumers' future choice from electroencephalography signals

FR Mashrur, KM Rahman, MTI Miya… - Physiology & …, 2022 - Elsevier
Abstract Neuromarketing utilizes Brain-Computer Interface (BCI) technologies to provide
insight into consumers responses on marketing stimuli. In order to achieve insight …

BCI-based consumers' choice prediction from EEG signals: an intelligent neuromarketing framework

FR Mashrur, KM Rahman, MTI Miya… - Frontiers in human …, 2022 - frontiersin.org
Neuromarketing relies on Brain Computer Interface (BCI) technology to gain insight into how
customers react to marketing stimuli. Marketers spend about $750 billion annually on …

A novel methodology for classifying EMG movements based on SVM and genetic algorithms

M Aviles, LM Sánchez-Reyes, RQ Fuentes-Aguilar… - Micromachines, 2022 - mdpi.com
Electromyography (EMG) processing is a fundamental part of medical research. It offers the
possibility of developing new devices and techniques for the diagnosis, treatment, care, and …

Comparative analysis of SVM and Naive Bayes classifier for the SEMG signal classification

Y Narayan - Materials Today: Proceedings, 2021 - Elsevier
The surface electromyography (sEMG) signals are the human muscle signals which are
employed in various biomedical and engineering applications. Classification of sEMG …

SEMG signal classification using KNN classifier with FD and TFD features

Y Narayan - Materials Today: Proceedings, 2021 - Elsevier
For developing thebio-engineering inspired human–machine interface, surface
electromyography (SEMG) signals have been widely exploited in the last decade. Movement …

Lightweight neural network for COVID-19 detection from chest X-ray images implemented on an embedded system

T Sanida, A Sideris, D Tsiktsiris, M Dasygenis - Technologies, 2022 - mdpi.com
At the end of 2019, a severe public health threat named coronavirus disease (COVID-19)
spread rapidly worldwide. After two years, this coronavirus still spreads at a fast rate. Due to …

SEMG-based upper limb movement classifier: Current scenario and upcoming challenges

MC Tosin, JC Machado, A Balbinot - Journal of Artificial Intelligence …, 2022 - jair.org
Despite achieving accuracies higher than 90% on recognizing upper-limb movements
through sEMG (surface Electromyography) signal with the state of art classifiers in the …

A home-based bilateral rehabilitation system with sEMG-based real-time variable stiffness

Y Liu, S Guo, Z Yang, H Hirata… - IEEE Journal of …, 2020 - ieeexplore.ieee.org
Bilateral rehabilitation allows patients with hemiparesis to exploit the cooperative
capabilities of both arms to promote the recovery process. Although various approaches …