Development of electroencephalography (EEG) data acquisition system based on FPGA PYNQ

Rizki Arif, Sastra Kusuma Wijaya, Prawito Prajitno, Hendra Saputra Gani

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

This study proposed a novel Field Programmable Gate Array (FPGA)-based 32-channel data acquisition system to acquire and process Electroencephalography (EEG) signal. The data acquisition system utilized PYNQ-Z1 board, which was equipped with a Xilinx ZYNQ XC7Z020-1CLG400C All Programmable System-on-Chip (APSoCs) that offered high performance embedded system because of the combination between the flexibility and versatility of the programmable logic (PL) and the high-speed embedded processor or programmable system (PS). As the core of the data acquisition system, the FPGA collected, processed, and stored the data based on Front-End Analog to Digital Converter (ADC) ADS1299EEG-FE. The communication protocol used in the data acquisition system was Serial Peripheral Interface (SPI) with daisy-chain configuration. For the signal processing part, a 5th-order Butterworth bandpass filter and Fast Fourier Transform (FFT) has been implemented directly on the PYNQ's Overlay. The overlay was configurable FPGA design that extend the system from the PS of the ZYNQ to the PL, enabling us to control directly the hardware platform using Python running in the PS. The mean accuracy error obtained from validation result of the developed system was 1.34% and the Total Harmonic Distortion (THD) performance criterion resulting in 0.0091%, both of them validated with NETECH MiniSIM EEG Simulator 330. The comparison between the developed system and Neurostyle NS-EEG-D1 System acquiring the same EEG data shows correlation parameter gradient of 0.9818, y-intercept with -0.1803, and R squared of 0.9742 based on the least square analysis. The parameter above indicated that the developed system was adequate enough, if not on a par, with the commercialized, medical grade EEG data acquisition system Neurostyle NS-EEG-D1 as the system assured and maintained accuracy with higher sampling frequency.

Original languageEnglish
Title of host publication3rd Biomedical Engineering''s Recent Progress in Biomaterials, Drugs Development, and Medical Devices
Subtitle of host publicationProceedings of the International Symposium of Biomedical Engineering, ISBE 2018
EditorsPraswasti P.D.K. Wulan, Misri Gozan, Sotya Astutiningsih, Ghiska Ramahdita, Radon Dhelika, Prasetyanugraheni Kreshanti
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735418226
DOIs
Publication statusPublished - 9 Apr 2019
Event3rd International Symposium of Biomedical Engineering''s Recent Progress in Biomaterials, Drugs Development, and Medical Devices, ISBE 2018 - Jakarta, Indonesia
Duration: 6 Aug 20188 Aug 2018

Publication series

NameAIP Conference Proceedings
Volume2092
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference3rd International Symposium of Biomedical Engineering''s Recent Progress in Biomaterials, Drugs Development, and Medical Devices, ISBE 2018
CountryIndonesia
CityJakarta
Period6/08/188/08/18

Keywords

  • ADS1299EEG-FE
  • data acquisition system
  • electroencephalography
  • FPGA
  • PYNQ-Z1

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