Design and implementation of high sampling rate and multichannel wireless recorder for EEG monitoring and SSVEP response detection

Ruikai Li; Yixing Zhang; Guangwei Fan; Ziteng Li; Jun Li; Shiyong Fan; Cunguang Lou; Xiuling Liu

doi:10.3389/fnins.2023.1193950

Design and implementation of high sampling rate and multichannel wireless recorder for EEG monitoring and SSVEP response detection

Front Neurosci. 2023 Jun 29:17:1193950. doi: 10.3389/fnins.2023.1193950. eCollection 2023.

Authors

Ruikai Li^#^{1

2}, Yixing Zhang^#¹, Guangwei Fan¹, Ziteng Li¹, Jun Li¹, Shiyong Fan¹, Cunguang Lou¹, Xiuling Liu¹

Affiliations

¹ The College of Electronic Information Engineering and the Hebei Key Laboratory of Digital Medical Engineering, Hebei University, Baoding, China.
² Information Center, The Affiliated Hospital of Hebei University, Baoding, China.

^# Contributed equally.

Abstract

Introduction: The collection and process of human brain activity signals play an essential role in developing brain-computer interface (BCI) systems. A portable electroencephalogram (EEG) device has become an important tool for monitoring brain activity and diagnosing mental diseases. However, the miniaturization, portability, and scalability of EEG recorder are the current bottleneck in the research and application of BCI.

Methods: For scalp EEG and other applications, the current study designs a 32-channel EEG recorder with a sampling rate up to 30 kHz and 16-bit accuracy, which can meet both the demands of scalp and intracranial EEG signal recording. A fully integrated electrophysiology microchip RHS2116 controlled by FPGA is employed to build the EEG recorder, and the design meets the requirements of high sampling rate, high transmission rate and channel extensive.

Results: The experimental results show that the developed EEG recorder provides a maximum 30 kHz sampling rate and 58 Mbps wireless transmission rate. The electrophysiological experiments were performed on scalp and intracranial EEG collection. An inflatable helmet with adjustable contact impedance was designed, and the pressurization can improve the SNR by approximately 4 times, the average accuracy of steady-state visual evoked potential (SSVEP) was 93.12%. Animal experiments were also performed on rats, and spike activity was captured successfully.

Conclusion: The designed multichannel wireless EEG collection system is simple and comfort, the helmet-EEG recorder can capture the bioelectric signals without noticeable interference, and it has high measurement performance and great potential for practical application in BCI systems.

Keywords: BCI; EEG; RHS2116; SSVEP; electroencephalography; inflatable helmet.

Grants and funding

This study was supported by the National Natural Science Foundation of China (U20A20224), the Natural Science Foundation of Hebei Province under (Grant No. F2021201005), the Key Projects of the Education Department of Hebei Province under (Grant Nos. ZD2022072 and ZD2020146), and Hebei Science and Technology Plan Project No. 22321701D.