CereBridge

An Efficient, FPGA-based Real-Time Processing Platform for True Mobile Brain-Computer Interfaces

verfasst von

Marc-Nils Wahalla, Guillermo Paya Vaya, Holger Blume

Abstract

In general, the signal chain in modern mobile Brain-Computer Interfaces (BCIs) is subdivided into at least two blocks. These are usually wirelessly connected with digital signal processing part implemented separately and often stationary. This causes a limited mobility and results in an additional, although avoidable, latency due to the wireless transmission channel. Therefore, a novel, entirely mobile FPGA-based platform for BCIs has been designed and implemented. While featuring highly efficient adaptability to targeted algorithms due to the ultra low power Flash-based FPGA, the stackable system design and the configurable hardware ensure flexibility for the use in different application scenarios. Powered through a single Li-ion battery, the miniaturized system area of half the size of a credit card leads to high mobility and thus allow for real-world scenario applicability. A Bluetooth Low Energy extension can be connected without any significant area cost, if a wireless data or control signal transmission channel is required. The resulting system is capable of acquiring and fully processing of up to 32 EEG channels with 24 bit precision each and a sampling rate of 250-16k samples per second with a total weight less than 60 g.

Organisationseinheit(en)

Fachgebiet Architekturen und Systeme

Typ

Aufsatz in Konferenzband

Seiten

4046-4050

Anzahl der Seiten

5

Publikationsdatum

2020

Publikationsstatus

Veröffentlicht

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Signalverarbeitung, Gesundheitsinformatik, Maschinelles Sehen und Mustererkennung, Biomedizintechnik

Elektronische Version(en)

https://doi.org/10.1109/embc44109.2020.9175623 (Zugang: Geschlossen)