A Wireless EEG Acquisition System Capable of Real-Time BCI Applications

Electroencephalography (EEG), known for its high temporal resolution and non-invasive characteristics, is widely used in brain-computer interface（BCI） research and clinical diagnosis. However, most current studies rely on commercial EEG systems, which typically feature highly integrated hardware architectures and closed software platforms, limiting access to raw data and restricting functional expansion. To address these issues, we propose a portable wireless multi-channel EEG acquisition system that integrates analog-to-digital conversion (ADC) conversion, wireless communication, and signal processing software platforms. The system is capable of simultaneously acquiring 16-channel EEG signals at a maximum sampling rate of 1000 Sa/s and transmitting the data to the user interface via Wi-Fi. The hardware integrates modules such as ADC, power management and microcontroller (MCU). On the software side, a multithreading mechanism is employed to divide tasks, while real-time data acquisition, buffering, processing, and transmission are achieved using signal-slot mechanisms. To validate the system, we first conducted electrical tests, which demonstrated an input noise level below 2.1 μV and a common-mode rejection ratio (CMRR) exceeding 105 dB. Then the acquisition experiments of spontaneous EEG and evoked EEG were carried out using the paradigm presentation module integrated in this system. Finally, we conducted real-time BCI control experiments using a steady-state visual evoked (SSVEP) paradigm to validate the system’s feasibility and practicality in closed-loop BCI applications. A custom-designed feeding robot was used as the controlled device, forming a closed-loop workflow from EEG acquisition to device control. The results validate our EEG system’s reliability for cognitive neuroscience research and highlight its potential in clinical diagnostics, human-computer interaction, and real-time BCI applications.