A comprehensive review on critical issues and possible solutions of motor imagery based electroencephalography brain-computer interface

A Singh, AA Hussain, S Lal, HW Guesgen - Sensors, 2021 - mdpi.com
Motor imagery (MI) based brain–computer interface (BCI) aims to provide a means of
communication through the utilization of neural activity generated due to kinesthetic …

Passive brain-computer interfaces for enhanced human-robot interaction

M Alimardani, K Hiraki - Frontiers in Robotics and AI, 2020 - frontiersin.org
Brain-computer interfaces (BCIs) have long been seen as control interfaces that translate
changes in brain activity, produced either by means of a volitional modulation or in response …

Development of a ternary hybrid fNIRS-EEG brain–computer interface based on imagined speech

A Rezazadeh Sereshkeh, R Yousefi… - Brain-Computer …, 2019 - Taylor & Francis
There is increasing interest in developing intuitive brain-computer interfaces (BCIs) to
differentiate intuitive mental tasks such as imagined speech. Both electroencephalography …

A hybrid method fusing frequency recognition with attention detection to enhance an asynchronous brain-computer interface

J Zhao, Y Shi, W Liu, T Zhou, Z Li… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Objective: One critical problem in controlling an asynchronous brain-computer interface
(BCI) system is to discriminate between control and idle states. This paper proposes a hybrid …

Hybrid brain-computer interface with motor imagery and error-related brain activity

M Mousavi, LR Krol, VR de Sa - Journal of Neural Engineering, 2020 - iopscience.iop.org
Objective. Brain-computer interface (BCI) systems read and interpret brain activity directly
from the brain. They can provide a means of communication or locomotion for patients …

State-based decoding of force signals from multi-channel local field potentials

A Ahmadi, A Khorasani, V Shalchyan, MR Daliri - IEEE Access, 2020 - ieeexplore.ieee.org
The functional use of brain-machine interfaces (BMIs) in everyday tasks requires the
accurate decoding of both movement and force information. In real-word tasks such as reach …

Detection of error-related potentials in stroke patients from EEG using an artificial neural network

N Usama, IK Niazi, K Dremstrup, M Jochumsen - Sensors, 2021 - mdpi.com
Error-related potentials (ErrPs) have been proposed as a means for improving brain–
computer interface (BCI) performance by either correcting an incorrect action performed by …

[HTML][HTML] 基于言语想象的脑机交互关键技术

艳鹏刘, 安民龚, 鹏丁, 磊赵, 谦钱… - Sheng Wu Yi Xue …, 2022 - ncbi.nlm.nih.gov
言语表达是一种人类重要的高级认知行为, 该行为的实现与人的大脑活动密切相关,
真实的言语表达和言语想象都能够激活部分相同的脑区, 因此言语想象成为一种脑机交互的 …

Decoding Subject-Driven Cognitive States from EEG Signals for Cognitive Brain–Computer Interface

D Huang, Y Wang, L Fan, Y Yu, Z Zhao, P Zeng… - Brain Sciences, 2024 - mdpi.com
In this study, we investigated the feasibility of using electroencephalogram (EEG) signals to
differentiate between four distinct subject-driven cognitive states: resting state, narrative …

Online adaptive classification system for brain–computer interface based on error-related potentials and neurofeedback

X Haotian, G Anmin, L Jiangong, W Fan, D Peng… - … Signal Processing and …, 2023 - Elsevier
The electroencephalogram (EEG)-based brain–computer interface (EEG-BCI) is used in
many fields, and can provide a more convenient way of life for patients with or without …