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In this study, we illustrate the progress of BCI research and present scores of unveiled contemporary approaches. First, we explore a decoding natural speech approach that is designed to decode human speech directly from the human brain…

Signal Processing · Electrical Eng. & Systems 2022-07-15 Md Jobair Hossain Faruk , Maria Valero , Hossain Shahriar

For several decades, electroencephalography (EEG) has featured as one of the most commonly used tools in emotional state recognition via monitoring of distinctive brain activities. An array of datasets have been generated with the use of…

The analysis of brain connectivity aims to understand the emergence of functional networks into the brain. This information can be used in the process of electroencephalographic (EEG) signal analysis and classification for a braincomputer…

Neurons and Cognition · Quantitative Biology 2020-07-28 J. A. Gaxiola-Tirado

To handle the scarcity and heterogeneity of electroencephalography (EEG) data for Brain-Computer Interface (BCI) tasks, and to harness the power of large publicly available data sets, we propose Neuro-GPT, a foundation model consisting of…

Machine Learning · Computer Science 2024-03-05 Wenhui Cui , Woojae Jeong , Philipp Thölke , Takfarinas Medani , Karim Jerbi , Anand A. Joshi , Richard M. Leahy

The application of psychophysiology in human-computer interaction is a growing field with significant potential for future smart personalised systems. Working in this emerging field requires comprehension of an array of physiological…

Human-Computer Interaction · Computer Science 2016-09-06 Lauri Ahonen , Benjamin Cowley

Brain-Computer Interface (BCI) is an essential mechanism that interprets the human brain signal. It provides an assistive technology that enables persons with motor disabilities to communicate with the world and also empowers them to lead…

Signal Processing · Electrical Eng. & Systems 2020-09-22 Srihari Maruthachalam

A brain-computer interface (BCI) based on the motor imagery (MI) paradigm translates one's motor intention into a control signal by classifying the Electroencephalogram (EEG) signal of different tasks. However, most existing systems either…

Data Structures and Algorithms · Computer Science 2020-07-27 Eitan Netzer , Alex Frid , Dan Feldman

Brain-computer interfaces (BCIs) offer transformative potential, but decoding neural signals presents significant challenges. The core premise of this paper is built around demonstrating methods to elucidate the underlying low-dimensional…

Machine Learning · Computer Science 2025-02-28 Benjamin J. Choi

This document describes a technical study of the electroencephalographic (EEG) headset OpenBCI (New York, US). In comparison to research grade EEG, the OpenBCI headset is affordable thus suitable for the general public use. In this study we…

Human-Computer Interaction · Computer Science 2019-04-11 Maxime Chabance , Grégoire Cattan , Bastien Maureille

Brain computer interface (BCI) research, as well as increasing portions of the field of neuroscience, have found success deploying large-scale artificial intelligence (AI) pre-training methods in conjunction with vast public repositories of…

Neurons and Cognition · Quantitative Biology 2025-06-03 Mattson Ogg , Rahul Hingorani , Diego Luna , Griffin W. Milsap , William G. Coon , Clara A. Scholl

Deficit of attention, anxiety, sleep disorders are some of the problems which affect many persons. As these issues can evolve into severe conditions, more factors should be taken into consideration. The paper proposes a conception which…

Measuring brain activity with electroencephalography (EEG) is mature enough to assess mental states. Combined with existing methods, such tool can be used to strengthen the understanding of user experience. We contribute a set of methods to…

Human-Computer Interaction · Computer Science 2016-01-13 Jérémy Frey , Maxime Daniel , Julien Castet , Martin Hachet , Fabien Lotte

Evaluating human-computer interaction is essential as a broadening population uses machines, sometimes in sensitive contexts. However, traditional evaluation methods may fail to combine real-time measures, an "objective" approach and data…

Human-Computer Interaction · Computer Science 2013-11-12 Jérémy Frey , Christian Mühl , Fabien Lotte , Martin Hachet

Brain-computer interfaces have many algorithms based on the P300 component of ERP. Modern industry has started to produce consumer grade EEG equipment which is handy and not too expensive. This gives us an opportunity to use BCI in everyday…

Neurons and Cognition · Quantitative Biology 2016-11-02 S. N. Agapov , V. A Bulanov , A. V. Zakharov , M. S. Sergeeva

Brain-computer interfaces (BCIs) allow users to control computer applications by modulating their brain activity. Since BCIs rely solely on brain activity, they have enormous potential as an alternative access method for engaging children…

Human-Computer Interaction · Computer Science 2021-05-27 Javad Rahimipour Anaraki , Chelsea Anne Rauh , Jason Leung , Tom Chau

We present a new large-scale electroencephalography (EEG) dataset as part of the THINGS initiative, comprising over 1.6 million visual stimulus trials collected from 20 participants, and totaling more than twice the size of the most popular…

Neurons and Cognition · Quantitative Biology 2025-08-28 Jonathan Xu , Ugo Bruzadin Nunes , Wangshu Jiang , Samuel Ryther , Jordan Pringle , Paul S. Scotti , Arnaud Delorme , Reese Kneeland

The devices that can read Electroencephalography (EEG) signals have been widely used for Brain-Computer Interfaces (BCIs). Popularity in the field of BCIs has increased in recent years with the development of several consumer-grade EEG…

Human-Computer Interaction · Computer Science 2022-04-25 Cameron Aume , Shantanu Pal , Subhas Mukhopadhyay

Deciphering the intricacies of the human brain has captivated curiosity for centuries. Recent strides in Brain-Computer Interface (BCI) technology, particularly using motor imagery, have restored motor functions such as reaching, grasping,…

Computation and Language · Computer Science 2024-05-06 Hanwen Liu , Daniel Hajialigol , Benny Antony , Aiguo Han , Xuan Wang

Electroencephalography (EEG) monitors ---by either intrusive or noninvasive electrodes--- time and frequency variations and spectral content of voltage fluctuations or waves, known as brain rhythms, which in some way uncover activity during…

Neurons and Cognition · Quantitative Biology 2019-03-13 Javier A. Galadí , Joaquín J. Torres , J. Marro

Electroencephalogram (EEG) provides noninvasive measures of brain activity and is found to be valuable for diagnosis of some chronic disorders. Specifically, pre-treatment EEG signals in alpha and theta frequency bands have demonstrated…

Applications · Statistics 2023-05-24 Bin Yang , Xingche Guo , Ji Meng Loh , Qinxia Wang , Yuanjia Wang
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