Brainwave Control Platform with Extensible EEG Interpretation Plugins
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Solution Overview
Problem
Existing brain-computer interface (BCI) technologies lack a unified platform that allows for easy expansion and compatibility with various EEG devices and object control plugins, requiring developers to have deep knowledge of brain data interpretation and complex coding, limiting large-scale development.
Innovation Solution
A BCI software platform with an extensible architecture that allows developers to program in their chosen language using plugins for EEG signal extraction and control, enabling seamless integration of different EEG devices and object control plugins without requiring specialized knowledge of brain data interpretation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If proprietary software is used for specific BCI hardware devices, then device compatibility is achieved, but developer flexibility and general hardware support are limited
Solution Approach 1:
The system segments the BCI software into modular components: a hardware abstraction layer that interfaces with specific EEG devices, an interpretation layer that processes brain data, and an application layer that developers can program. This segmentation allows each layer to be independently developed and replaced, enabling both device compatibility and developer flexibility.
Solution Approach 2:
The patent implements a universal software platform that can interface with multiple types of BCI hardware devices through standardized protocols. The hardware abstraction layer provides universal support for different EEG devices while maintaining the ability to interpret and process various types of brain data, making the system multi-functional across different hardware configurations.
2Adaptability or versatility
If open source software with general hardware support is used, then developer flexibility is improved, but compatibility with proprietary BCI devices is reduced
Solution Approach 1:
The patent introduces a hardware abstraction layer as an intermediary between the open source software platform and proprietary BCI devices. This mediator translates device-specific protocols into standardized interfaces that the open source software can handle, maintaining both device compatibility and developer flexibility.
3Reliability
If complex coding interfaces and GUI coding environments are used, then BCI functionality is achieved, but ease of development is reduced
Solution Approach 1:
The system provides self-service through automated brain data interpretation and pre-configured processing pipelines. The interpretation layer automatically analyzes EEG signals and translates them into actionable commands, eliminating the need for developers to manually program complex brain data processing algorithms and reducing development complexity.
4Measurement precision
If deep knowledge of brain data interpretation is required, then processing accuracy is improved, but accessibility to developers is reduced
Solution Approach 1:
The patent extracts the complex brain data interpretation logic into a separate, pre-configured interpretation layer that operates independently from the application development process. This extracted layer handles all the sophisticated signal processing and translation of EEG data into commands, allowing developers to focus on application logic without needing to understand the underlying brain data processing.
Data Source
AI summary
Embodiments of a system for controlling an object using brainwaves are disclosed. The system includes a set of EEG electrodes configured to be positioned on a head of a user and to collect EEG signals. The system further includes one or more computer readable storage mediums storing a framework configured to execute an extensible architecture through which EEG signals are interpreted for control of the object. The framework includes an EEG device plugin associated with the set of EEG electrodes and configured to extract the EEG signals from the set of EEG electrodes. The framework also includes an interpreter plugin configured to convert the EEG signals extracted by the EEG device plugin into a command. Further, the framework includes an object control plugin configured to access the command through an extension point of the interpreter plugin and to execute the command to control the object.