BRAIN-COMPUTER INTERFACE WITH ADAPTATIONS FOR HIGH-SPEED, ACCURATE, AND INTUITIVE USER INTERACTIONS

Smart overview of the Invention

The described technology focuses on a brain-computer interface (BCI) designed for high-speed and accurate user interactions. This system integrates brain activity tracking with eye and head movement sensors to enhance user experience. It is hardware agnostic, allowing it to work with various devices by interpreting neural signals to control external machines and devices.

Background

BCIs traditionally serve as assistive technologies, enabling individuals with severe disabilities to communicate and interact with machines using brain signals. These systems have evolved from basic implementations, like the Farwell-Donchin speller, which allows users to select characters by focusing on them, to more complex systems that aim to provide intuitive interaction without conventional input devices like keyboards or mice.

System Overview

The proposed BCI system combines eye movement and neural signal tracking to facilitate real-time user interaction. It features three main components: a pointing control feature analogous to a mouse pointer, an action control feature similar to a mouse click or keystroke, and a user interface/user experience (UI/UX) feature that supports these controls. This design aims to improve the speed and accuracy of BCIs, making them suitable for real-world applications.

Technical Implementation

Figures in the application illustrate various components and processes of the BCI system. These include schematics of the hybrid interfacing system, examples of UI/UX during operation, and flowcharts detailing signal processing and decision-making methods. The system analyzes brain and eye-tracking data to determine user intent, enabling precise control over connected devices.

Applications and Benefits

This BCI technology aims to enhance the usability of BCIs beyond laboratory settings by improving information transfer rates and reducing error rates. It seeks to make BCIs more intuitive for users, thus broadening their applicability from assistive technologies for disabled individuals to general use in controlling computers and other devices. The advancements promise more natural interaction paradigms suitable for everyday tasks.