Visual Stimuli Control for Brain-Computer Interface EEG Accuracy
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Solution Overview
Problem
Existing brain-computer interfaces face challenges in accurately controlling visual stimuli due to process scheduling issues, which affect the accuracy of EEG signal patterns recognition.
Innovation Solution
A software system comprising a generator, actuator, and controller, where the generator creates image sequences based on experimenter input, the actuator runs on the GPU to ensure asynchronous and unscheduled visual stimulus display, and the controller manages the actuator and electroencephalograph instrument interactions to maintain accurate and synchronized visual stimuli.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the visual stimuli process runs on the CPU with standard process scheduling, then the system is easy to control and manage, but the accuracy and timing precision of visual stimuli cannot be guaranteed due to process dispatching interruptions
Solution Approach 1:
The system is divided into three independent modules: generator (CPU-based, creates image sequences), actuator (GPU-based, displays visual stimuli), and controller (CPU-based, coordinates operations). This segmentation allows the actuator to run independently on the GPU, isolating it from CPU process scheduling interruptions and ensuring timing accuracy, while the generator and controller remain on the CPU for ease of management.
Solution Approach 2:
The controller acts as an intermediary between the generator and the actuator. It receives generation tasks from the generator, processes them, and sends control commands to the actuator. This intermediary role allows the system to maintain complex timing requirements while keeping the overall system manageable through centralized coordination.
2Productivity
If the actuator uses synchronous calls for start and stop operations, then the control flow is simple to implement, but the system responsiveness and real-time performance are reduced due to blocking calls
Solution Approach 1:
The actuator interfaces are designed to support both synchronous and asynchronous calling modes. This dynamic flexibility allows the system to adapt to different operational requirements: synchronous calls for simple sequential operations and asynchronous calls for time-critical operations where the controller cannot afford to be blocked, thereby improving overall system responsiveness.
Solution Approach 2:
The calling mode parameter of the actuator interfaces can be changed between synchronous and asynchronous based on the specific operational context. This parameter change allows the system to optimize performance for different tasks without requiring fundamentally different control mechanisms.
Data Source
AI summary
Disclosed is an accurate control method of visual stimuli for a brain-computer interface. It is a common approach for brain-computer interfaces to evoke specific EEG signal patterns by visual stimuli and recognize the EEG signal patterns in real time. However, due to the influence of process scheduling, a process showing the visual stimuli may sometimes be dispatched out of a CPU, leading to the difficulty in guaranteeing the accuracy of the visual stimuli and the recognition effect of the EEG signal patterns. The invention designs a control method to support accurate visual stimuli of a brain-computer interface. A software system implementing the method comprises a generator, an actuator and a controller. The generator automatically generates an image sequence according to test requirements. The actuator is a module running on a GPU. At the beginning of a trail, the controller asynchronously calls an interface of the actuator to start the actuator, and the actuator accurately shows the image sequence generated by the generator. At the end of the trail, the controller asynchronously calls an interface of the actuator to stop showing visual stimuli.