Device Interaction with Non-Invasive BCI

Abstract - This review focuses on Non-invasive Brain–Computer Interfaces (BCIs), which are systems designed to establish a direct link between the brain and external devices without the need for physical movement. These EEG-based BCIs are applicable in assistive and interactive contexts. A significant emphasis is on BCI-based spellers, which facilitate communication through brain signals. The review examines three main types: P300, Motor Imagery (MI), and Steady-State Visual Evoked Potentials (SSVEP). P300 spellers utilize event-related potentials for high precision; MI spellers depend on imagined movements but demand extensive training; and SSVEP spellers provide rapid performance using flickering visual stimuli. This review details various EEG signal processing techniques, BCI system architecture, and contemporary classification methods for EEG-based BCI. Key Words: Electroencephalography (EEG), Brain-Computer Interface, Speller, P300, Motor Imagery (MI), Steady State Visual Evoked Potential (SSVEP)

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Publication Details

Journal
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Published
2025-04-22
DOI
https://doi.org/10.55041/ijsrem44819
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
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article

Device Interaction with Non-Invasive BCI

Meher Bhawnani
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
EEG and Brain-Computer Interfaces
article

Device Interaction with Non-Invasive BCI

Meher Bhawnani
article en

Abstract

Abstract - This review focuses on Non-invasive Brain–Computer Interfaces (BCIs), which are systems designed to establish a direct link between the brain and external devices without the need for physical movement. These EEG-based BCIs are applicable in assistive and interactive contexts. A significant emphasis is on BCI-based spellers, which facilitate communication through brain signals. The review examines three main types: P300, Motor Imagery (MI), and Steady-State Visual Evoked Potentials (SSVEP). P300 spellers utilize event-related potentials for high precision; MI spellers depend on imagined movements but demand extensive training; and SSVEP spellers provide rapid performance using flickering visual stimuli. This review details various EEG signal processing techniques, BCI system architecture, and contemporary classification methods for EEG-based BCI. Key Words: Electroencephalography (EEG), Brain-Computer Interface, Speller, P300, Motor Imagery (MI), Steady State Visual Evoked Potential (SSVEP)

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENTVol. 09(04)
Openalex Percentile: Top 92%
EEG and Brain-Computer Interfaces
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