A transfer learning framework based on motor imagery rehabilitation for stroke

F Xu, Y Miao, Y Sun, D Guo, J Xu, Y Wang, J Li, H Li… - Scientific Reports, 2021 - nature.com
Deep learning networks have been successfully applied to transfer functions so that the
models can be adapted from the source domain to different target domains. This study uses …

Feature extraction and classification in brain-computer interfacing: Future research issues and challenges

DD Chakladar, S Chakraborty - Natural computing for unsupervised …, 2019 - Springer
Brain-computer interfacing (BCI) is a communication bridge between human brain and
computer. BCI system consisted of four sections (signal acquisition, signal processing …

Classification of eeg-p300 signals extracted from brain activities in bci systems using ν-svm and blda algorithms

A Momennezhad, M Shamsi… - Applied Medical …, 2014 - ami.info.umfcluj.ro
In this paper, a linear predictive coding (LPC) model is used to improve classification
accuracy, convergent speed to maximum accuracy, and maximum bitrates in brain computer …

EEG subspace analysis and classification using principal angles for brain-computer interfaces

RB Ashari - 2015 - search.proquest.com
Abstract Brain-Computer Interfaces (BCIs) help paralyzed people who have lost some or all
of their ability to communicate and control the outside environment from loss of voluntary …

Data Classification Through Cognitive Computing

S Chakraborty, L Dey - Computing for Data Analysis: Theory and Practices, 2023 - Springer
A brain–computer interface (BCI) is a direct link between the human brain and an external
system. Computer–brain interfaces are used to send sensory information from the brain or to …

[PDF][PDF] DEPARTAMENTO DE ENGENHARIA ELÉTRICA

RM Duarte - 2015 - researchgate.net
Neste trabalho, foram inferidos os principais desafios envolvidos no projeto, implementação
e teste de um sistema de interface cérebro máquina utilizando um amplificador EEG portátil …