CereBridge: An Efficient, FPGA-based Real-Time Processing Platform for True Mobile Brain-Computer Interfaces.

Area of Science:

• Biomedical Engineering
• Neuroscience
• Computer Engineering

Background:

• Modern mobile Brain-Computer Interfaces (BCIs) often use separate, stationary processing units, limiting mobility and introducing latency.
• Wireless transmission between BCI components can be a bottleneck for real-time applications.

Purpose of the Study:

• To design and implement a novel, entirely mobile FPGA-based platform for BCIs.
• To overcome the limitations of current BCI systems regarding mobility and latency.

Main Methods:

• Developed a miniaturized, ultra-low power Flash-based FPGA platform.
• Integrated signal acquisition and digital signal processing into a single, stackable system.
• Utilized a single Li-ion battery for power and incorporated an optional Bluetooth Low Energy extension.

Main Results:

• The platform can acquire and fully process up to 32 EEG channels with 24-bit precision and a sampling rate of 250-16k samples/second.
• The system is credit-card sized, weighs less than 60g, and offers high adaptability and flexibility.
• Achieved a significant reduction in latency and a substantial increase in mobility compared to traditional BCIs.

Conclusions:

• The developed FPGA-based platform offers a highly mobile, flexible, and efficient solution for real-world BCI applications.
• This integrated system minimizes latency and enhances user mobility, paving the way for advanced BCI use cases.
• The platform's design supports diverse application scenarios and can be extended wirelessly if needed.