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Brain Computer Interface

A Brain-Computer Interface (BCI), also known as a Brain-Machine Interface (BMI), is a technology that enables direct communication between the brain and an external device, such as a computer or a machine, without the need for any muscular or peripheral nerve activity. Essentially, BCIs establish a direct pathway between the brain and an external device, allowing for bidirectional communication.

BCIs typically work by detecting and interpreting brain signals, which are then translated into commands that control external devices or provide feedback to the user. These brain signals can be detected through various methods, including electroencephalography (EEG), which measures electrical activity in the brain through electrodes placed on the scalp, or invasive techniques such as implanted electrodes.

Papers

Showing 251275 of 466 papers

TitleStatusHype
Automatic Control of Reactive Brain Computer Interfaces0
Student Teaching and Research Laboratory Focusing on Brain-computer Interface Paradigms - A Creative Environment for Computer Science Students -0
Subject-independent trajectory prediction using pre-movement EEG during grasp and lift task0
Subject-Independent Brain-Computer Interface for Decoding High-Level Visual Imagery Tasks0
Subject-Independent Brain-Computer Interfaces with Open-Set Subject Recognition0
Subject-Independent Classification of Brain Signals using Skip Connections0
Subject-Independent Deep Architecture for EEG-based Motor Imagery Classification0
Sub-Scalp Brain-Computer Interface Device Design and Fabrication0
Sub-Scalp EEG for Sensorimotor Brain-Computer Interface0
Switching EEG Headsets Made Easy: Reducing Offline Calibration Effort Using Active Weighted Adaptation Regularization0
Target-centered Subject Transfer Framework for EEG Data Augmentation0
The feasibility of combining communication BCIs with FES for individuals with locked-in syndrome0
The "Sound of Silence" in EEG -- Cognitive voice activity detection0
The Study of Human Preference Based on Integrated Analysis of N1 and LPP Components0
Time delay multi-feature correlation analysis to extract subtle dependencies from EEG signals0
Topological Data Analysis (TDA) Techniques Enhance Hand Pose Classification from ECoG Neural Recordings0
To Root Artificial Intelligence Deeply in Basic Science for a New Generation of AI0
Toward BCI-enabled Metaverse: A Joint Learning and Resource Allocation Approach0
Towards a Fast Steady-State Visual Evoked Potentials (SSVEP) Brain-Computer Interface (BCI)0
Towards Asynchronous Motor Imagery-Based Brain-Computer Interfaces: a joint training scheme using deep learning0
Towards Brain-Computer Interfaces for Drone Swarm Control0
Towards Personalized Brain-Computer Interface Application Based on Endogenous EEG Paradigms0
Towards personalized human AI interaction - adapting the behavior of AI agents using neural signatures of subjective interest0
Towards Probabilistic Inference of Human Motor Intentions by Assistive Mobile Robots Controlled via a Brain-Computer Interface0
Towards the bio-personalization of music recommendation systems: A single-sensor EEG biomarker of subjective music preference0
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