EEG data acquisition system 32 channels based on Raspberry Pi with relative power ratio and brain symmetry index features

Henry Hendarwin, Sastra Kusuma Wijaya, Prawito Prajitno, Nurhadi Ibrahim, Hendra Saputra Gani, Wahyu Apriadi

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

Abstract

An inhouse Electroencephalography (EEG) data acquisition system based on Raspberry Pi and Analog Front End (AFE) ADS1299 EEGFE-PDK has been developed. The system displayed a relative power ratio (RPR) and brain symmetry index (BSI) in real-time. The features of the AFE are simultaneous sampling for eight channels, 24 bits resolution, low power, and low noise of < 5 mW and < 1 μV, respectively. The system consists of 4 units AFE in daisy chain configuration. The communication between AFE and Raspberry Pi is programmable using registers of RDATA format accessed via a serial peripheral interface (SPI) and programmed using C. The data acquired were processed using MATLAB. These data were transferred using Local Area Networking (LAN) filtered based on 5th order Butterworth and processed in a personal computer (PC). The RPR was calculated using Fast Fourier Transforms (FFT) and Power Spectral Density (PSD). The BSI was calculated using Welch method. The acquired and processed data would be sent to High Definition Multiple Interface (HDMI) if needed by users. This system has been evaluated using EEG simulator (NETECH MiniSim EEG), which is generate sinusoidal electrical signal with frequency 2 Hz, 5 Hz, and voltage amplitude 30, 50 μV, with error average less than 6%.

Original languageEnglish
Title of host publication4th Biomedical Engineering''s Recent Progress in Biomaterials, Drugs Development, Health, and Medical Devices
Subtitle of host publicationProceedings of the International Symposium of Biomedical Engineering, ISBE 2019
EditorsKenny Lischer, Tomy Abuzairi, Siti Fauziyah Rahman, Misri Gozan
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735419445
DOIs
Publication statusPublished - 10 Dec 2019
Event4th International Symposium of Biomedical Engineering�s Recent Progress in Biomaterials, Drugs Development, Health, and Medical Devices, ISBE 2019 - Padang, West Sumatera, Indonesia
Duration: 22 Jul 201924 Jul 2019

Publication series

NameAIP Conference Proceedings
Volume2193
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference4th International Symposium of Biomedical Engineering�s Recent Progress in Biomaterials, Drugs Development, Health, and Medical Devices, ISBE 2019
CountryIndonesia
CityPadang, West Sumatera
Period22/07/1924/07/19

Keywords

  • ADS1299
  • BSI
  • Daisy Chain
  • EEG
  • Raspberry Pi
  • RPR

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