Brain-computer interface: Advancement and challenges

MF Mridha, SC Das, MM Kabir, AA Lima, MR Islam… - Sensors, 2021 - mdpi.com
Brain-Computer Interface (BCI) is an advanced and multidisciplinary active research domain
based on neuroscience, signal processing, biomedical sensors, hardware, etc. Since the …

EEG-based BCIs on motor imagery paradigm using wearable technologies: a systematic review

A Saibene, M Caglioni, S Corchs, F Gasparini - Sensors, 2023 - mdpi.com
In recent decades, the automatic recognition and interpretation of brain waves acquired by
electroencephalographic (EEG) technologies have undergone remarkable growth, leading …

Enhancing cross-subject motor imagery classification in EEG-based brain–computer interfaces by using multi-branch CNN

RR Chowdhury, Y Muhammad, U Adeel - Sensors, 2023 - mdpi.com
A brain–computer interface (BCI) is a computer-based system that allows for communication
between the brain and the outer world, enabling users to interact with computers using …

Recent trends in EEG based Motor Imagery Signal Analysis and Recognition: A comprehensive review.

N Sharma, M Sharma, A Singhal, R Vyas, H Malik… - IEEE …, 2023 - ieeexplore.ieee.org
The electroencephalogram (EEG) motor imagery (MI) signals are the widespread paradigms
in the brain-computer interface (BCI). Its significant applications in the gaming, robotics, and …

An EEG motor imagery dataset for brain computer interface in acute stroke patients

H Liu, P Wei, H Wang, X Lv, W Duan, M Li, Y Zhao… - Scientific Data, 2024 - nature.com
The brain-computer interface (BCI) is a technology that involves direct communication with
parts of the brain and has evolved rapidly in recent years; it has begun to be used in clinical …

Comparison of automated machine learning (AutoML) tools for epileptic seizure detection using electroencephalograms (EEG)

S Lenkala, R Marry, SR Gopovaram, TC Akinci… - Computers, 2023 - mdpi.com
Epilepsy is a neurological disease characterized by recurrent seizures caused by abnormal
electrical activity in the brain. One of the methods used to diagnose epilepsy is through …

Toward a diagnostic CART model for Ischemic heart disease and idiopathic dilated cardiomyopathy based on heart rate total variability

A Accardo, L Restivo, M Ajčević, A Miladinović… - Medical & Biological …, 2022 - Springer
Diagnosis of etiology in early-stage ischemic heart disease (IHD) and dilated
cardiomyopathy (DCM) patients may be challenging. We aimed at investigating, by means of …

A data-driven machine learning approach for brain-computer interfaces targeting lower limb neuroprosthetics

A Dillen, E Lathouwers, A Miladinović… - Frontiers in human …, 2022 - frontiersin.org
Prosthetic devices that replace a lost limb have become increasingly performant in recent
years. Recent advances in both software and hardware allow for the decoding of …

Selection of the minimum number of EEG sensors to guarantee biometric identification of individuals

J Ortega-Rodríguez, JF Gómez-González, E Pereda - Sensors, 2023 - mdpi.com
Biometric identification uses person recognition techniques based on the extraction of some
of their physical or biological properties, which make it possible to characterize and …

Motor imagery classification based on EEG sensing with visual and vibrotactile guidance

L Batistić, D Sušanj, D Pinčić, S Ljubic - Sensors, 2023 - mdpi.com
Motor imagery (MI) is a technique of imagining the performance of a motor task without
actually using the muscles. When employed in a brain–computer interface (BCI) supported …