Towards Bridging the Gap Between Computational Intelligence and Neuroscience in Brain-Computer Interfaces With a Common Description of Systems and Data

This paper focuses on electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) comparison to help the rehabilitation patients. Both methods have unique techniques and placement of electrodes. Usage of signals are different in application based on the economic conditions. This study helps in choosing the signal for the betterment of analysis. Ten healthy subject datasets of EEG & FNIRS are taken and applied to plot topography separately. Accuracy, Sensitivity, peaks, integral areas, etc are compared and plotted. The main advantages of this study are to prompt their necessities in the analysis of rehabilitation devices to manage their life as a typical individual.

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Barriers and solutions for translating brain-computer interfaces for augmentative and alternative communication from research into practice

10.32873/unl.dc.oth.006 ◽

2020 ◽

Author(s):

Kevin Pitt

Keyword(s):

Augmentative And Alternative Communication ◽

Brain Computer Interfaces ◽

Alternative Communication ◽

Computer Interfaces

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Automated System for Epileptic Seizures Prediction based on Multi-Channel Recordings of Electrical Brain Activity

Information and Control Systems ◽

10.31799/1684-8853-2018-4-115-122 ◽

2018 ◽

pp. 115-122 ◽

Cited By ~ 1

Author(s):

V. A. Maksimenko ◽

A. A. Harchenko ◽

A. Lüttjohann

Keyword(s):

Epileptic Seizure ◽

Brain Activity ◽

Epileptic Seizures ◽

Automated System ◽

Brain Computer Interfaces ◽

Electrical Brain Activity ◽

Computer Interfaces ◽

Prediction And Prevention ◽

The Brain

Introduction: Now the great interest in studying the brain activity based on detection of oscillatory patterns on the recorded data of electrical neuronal activity (electroencephalograms) is associated with the possibility of developing brain-computer interfaces. Braincomputer interfaces are based on the real-time detection of characteristic patterns on electroencephalograms and their transformation into commands for controlling external devices. One of the important areas of the brain-computer interfaces application is the control of the pathological activity of the brain. This is in demand for epilepsy patients, who do not respond to drug treatment.Purpose: A technique for detecting the characteristic patterns of neural activity preceding the occurrence of epileptic seizures.Results:Using multi-channel electroencephalograms, we consider the dynamics of thalamo-cortical brain network, preceded the occurrence of an epileptic seizure. We have developed technique which allows to predict the occurrence of an epileptic seizure. The technique has been implemented in a brain-computer interface, which has been tested in-vivo on the animal model of absence epilepsy.Practical relevance:The results of our study demonstrate the possibility of epileptic seizures prediction based on multichannel electroencephalograms. The obtained results can be used in the development of neurointerfaces for the prediction and prevention of seizures of various types of epilepsy in humans.

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Privacy and brain-computer interfaces

ACM SIGCAS Computers and Society ◽

10.1145/2908216.2908223 ◽

2016 ◽

Vol 46 (1) ◽

pp. 41-53 ◽

Cited By ~ 2

Author(s):

Kirsten Wahlstrom ◽

N. Ben Fairweather ◽

Helen Ashman

Keyword(s):

Brain Computer Interfaces ◽

Computer Interfaces

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Learning Invariant Patterns Based on a Convolutional Neural Network and Big Electroencephalography Data for Subject-Independent P300 Brain-Computer Interfaces

IEEE Transactions on Neural Systems and Rehabilitation Engineering ◽

10.1109/tnsre.2021.3083548 ◽

2021 ◽

pp. 1-1

Author(s):

Wei Gao ◽

Tianyou Yu ◽

Jin-Gang Yu ◽

Zhenghui Gu ◽

Kendi Li ◽

...

Keyword(s):

Neural Network ◽

Convolutional Neural Network ◽

Brain Computer Interfaces ◽

Computer Interfaces

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Universal neurophysiological interpretation of EEG brain-computer interfaces

2021 9th International Winter Conference on Brain-Computer Interface (BCI) ◽

10.1109/bci51272.2021.9385350 ◽

2021 ◽

Author(s):

James D. Bennett ◽

Sam E. John ◽

David B. Grayden ◽

Anthony N. Burkitt

Keyword(s):

Brain Computer Interfaces ◽

Computer Interfaces

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An Introductory Tutorial on Brain–Computer Interfaces and Their Applications

Electronics ◽

10.3390/electronics10050560 ◽

2021 ◽

Vol 10 (5) ◽

pp. 560

Author(s):

Andrea Bonci ◽

Simone Fiori ◽

Hiroshi Higashi ◽

Toshihisa Tanaka ◽

Federica Verdini

Keyword(s):

Biomedical Engineering ◽

Data Privacy ◽

Lie Detection ◽

Human Cognition ◽

Brain Computer Interfaces ◽

Computer Interfaces ◽

Brain Signals ◽

Ethical And Legal Issues ◽

And Performance ◽

Brain Computer Interfacing

The prospect and potentiality of interfacing minds with machines has long captured human imagination. Recent advances in biomedical engineering, computer science, and neuroscience are making brain–computer interfaces a reality, paving the way to restoring and potentially augmenting human physical and mental capabilities. Applications of brain–computer interfaces are being explored in applications as diverse as security, lie detection, alertness monitoring, gaming, education, art, and human cognition augmentation. The present tutorial aims to survey the principal features and challenges of brain–computer interfaces (such as reliable acquisition of brain signals, filtering and processing of the acquired brainwaves, ethical and legal issues related to brain–computer interface (BCI), data privacy, and performance assessment) with special emphasis to biomedical engineering and automation engineering applications. The content of this paper is aimed at students, researchers, and practitioners to glimpse the multifaceted world of brain–computer interfacing.

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