Open Source EEG Platform with Reconfigurable Features for Multiple-Scenarios

dc.contributor.authorJuan Manuel López
dc.contributor.authorFabián Andrés González
dc.contributor.authorJuan Carlos Bohórquez
dc.contributor.authorJorge Bohórquez
dc.contributor.authorMario Valderrama
dc.contributor.authorFredy Segura-Quijano
dc.coverage.spatialBolivia
dc.date.accessioned2026-03-22T16:34:42Z
dc.date.available2026-03-22T16:34:42Z
dc.date.issued2018
dc.descriptionCitaciones: 1
dc.description.abstractElectroencephalogram (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.
dc.identifier.doi10.11591/ijeei.v6i3.556
dc.identifier.urihttps://doi.org/10.11591/ijeei.v6i3.556
dc.identifier.urihttps://andeanlibrary.org/handle/123456789/59068
dc.language.isoen
dc.publisherInstitute of Advanced Engineering and Science (IAES)
dc.relation.ispartofIndonesian Journal of Electrical Engineering and Informatics (IJEEI)
dc.sourceUniversity of Miami
dc.subjectFirmware
dc.subjectBluetooth
dc.subjectModular design
dc.subjectComputer science
dc.subjectSampling (signal processing)
dc.subjectUSB
dc.subjectComputer hardware
dc.subjectElectroencephalography
dc.subjectChannel (broadcasting)
dc.subjectWireless
dc.titleOpen Source EEG Platform with Reconfigurable Features for Multiple-Scenarios
dc.typearticle

Files