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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 191200 of 466 papers

TitleStatusHype
Unidirectional brain-computer interface: Artificial neural network encoding natural images to fMRI response in the visual cortexCode0
Phase Synchrony Component Self-Organization in Brain Computer Interface0
A Dynamic Domain Adaptation Deep Learning Network for EEG-based Motor Imagery Classification0
Brief Architectural Survey of Biopotential Recording Front-Ends since the 1970s0
Bootstrapping Adaptive Human-Machine Interfaces with Offline Reinforcement Learning0
Pseudo-online framework for BCI evaluation: A MOABB perspective0
Advancing Brain-Computer Interface System Performance in Hand Trajectory Estimation with NeuroKinect0
Aggregating Intrinsic Information to Enhance BCI Performance through Federated LearningCode0
A Brain-Computer Interface Augmented Reality Framework with Auto-Adaptive SSVEP Recognition0
Deep Learning Architecture for Motor Imaged Words0
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