Open source eeg platform with reconfigurable features for multiple-scenarios

Juan M. López, Fabián González, Juan C. Bohórquez, Jorge Bohorquez, Mario A. Valderrama, Fredy Segura-Quijano

Research output: Contribution to journalArticle

Abstract

Electroencephalogram (EEG) acquisition systems are widely used as diagnostic and research tools. This document shows the implementation of a reconfigurable family of three affordable 8-channels, 24 bits of resolution, EEG acquisition systems intended for a wide variety of research purposes. The three devices offer a modular design and upgradability, permitting changes in the firmware and software. Due to the nature of the Analog Front-End (AFE) used, no high-pass analog filters were implemented, allowing the capture of very low frequency components. Two systems of the family, called “RF-Brain” and “Bluetooth-Brain”, were designed to be light and wireless, planned for experimentation where movement of the subject cannot be restricted. The sample rate in these systems can be configured up to 2000 samples per second (SPS) for the RF-Brain and 250 SPS for the Bluetooth-Brain when the 8 channels are used. If fewer channels are required, the sampling frequency can be higher (up to 4 kSPS or 2 kSPS for 1 channel for RF-Brain and Bluetooth-Brain respectively). The third system, named “USB-Brain”, is a wired device designed for purposes requiring high sampling frequency acquisition and general purpose ports, with sampling rates up to 4 kSPS.

Original languageEnglish (US)
Pages (from-to)253~264
JournalIndonesian Journal of Electrical Engineering and Informatics
Volume6
Issue number3
DOIs
StatePublished - Jan 1 2018

Fingerprint

Open Source
Brain
Scenarios
Bluetooth
Sampling
Electroencephalography
Analogue
Modular Design
Firmware
Experimentation
Low Frequency
Diagnostics
Filter
Software
Acquisition

Keywords

  • Biofeedback brain-computer interface (bci) electroencephalography (eeg) neurophysiology portable instruments

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Control and Systems Engineering
  • Information Systems
  • Hardware and Architecture
  • Computer Networks and Communications
  • Control and Optimization
  • Artificial Intelligence
  • Electrical and Electronic Engineering

Cite this

Open source eeg platform with reconfigurable features for multiple-scenarios. / López, Juan M.; González, Fabián; Bohórquez, Juan C.; Bohorquez, Jorge; Valderrama, Mario A.; Segura-Quijano, Fredy.

In: Indonesian Journal of Electrical Engineering and Informatics, Vol. 6, No. 3, 01.01.2018, p. 253~264.

Research output: Contribution to journalArticle

López, Juan M. ; González, Fabián ; Bohórquez, Juan C. ; Bohorquez, Jorge ; Valderrama, Mario A. ; Segura-Quijano, Fredy. / Open source eeg platform with reconfigurable features for multiple-scenarios. In: Indonesian Journal of Electrical Engineering and Informatics. 2018 ; Vol. 6, No. 3. pp. 253~264.
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