| Title |
A Cost-efficient Low-noise Real-time EEG Recording System |
| Authors |
박수민(Su-Min Park) ; 이광호(Gwang-Ho Lee) ; 이제원(Je-Won Lee) ; 정상우(Sang-Woo Jeong) ; 박건욱(Gun-Wook Park) ; 최정호(Jung-Ho Choi) ; 박재준(Jae-Jun Park) ; 박성윤(Sung-Yun Park) |
| DOI |
https://doi.org/10.5573/ieie.2025.62.10.65 |
| Keywords |
EEG; Neural recording; Analog amplification; Cost-efficient; Real-time interface |
| Abstract |
The recording and analysis of electroencephalographic (EEG) signals have emerged as essential technologies for the early detection of neurological disorders such as dementia, stroke, and anxiety disorders. However, the widespread adoption of EEG measurement systems has been limited by the high cost of commercially available devices and sensing modules, underscoring the need for low-cost, high-efficiency alternatives. In this study, a cost-effective EEG acquisition system was developed to reliably capture microvolt-level signals by employing a low-noise analog amplifier while optimizing the ADC resolution to reduce expenses without compromising signal integrity. The EEG data are transmitted wireless in real time to a personal computer via a Bluetooth Low Energy interface implemented on an NRF52840 module. Additionally, a Python-based live-streaming graphical user interface was developed to enable intuitive visualization and analysis of the recorded signals. A digital notch filter was incorporated to effectively suppress 60 Hz power line interference. The proposed system, realized through both breadboard prototyping and PCB fabrication, achieved a voltage gain of 58 dB and a common-mode rejection ratio of 80 dB. Comparative evaluation against the OpenBCI Ganglion board demonstrated that the total production cost could be reduced by approximately 30%, from \36,900 to \22,400. |