Characterization of a Raspberry Pi as the core for a low-cost multimodal EEG-fNIRS platform

Freddy del Ángel Arrieta, Michelle Rojas Cisneros, Jesús Joel Rivas, Luis R. Castrejón, Luis Enrique Sucar, Javier Pérez-Andreu, Felipe Orihuela-Espina

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abstract

Poor understanding of brain recovery after injury, sparsity of evaluations and limited availability of healthcare services hinders the success of neurorehabilitation programs in rural communities. The availability of neuroimaging ca-pacities in remote communities can alleviate this scenario supporting neurorehabilitation programs in remote settings. This research aims at building a multimodal EEG-fNIRS neuroimaging platform deployable to rural communities to support neurorehabilitation efforts. A Raspberry Pi 4 is chosen as the CPU for the platform responsible for presenting the neurorehabilitation stimuli, acquiring, processing and storing concurrent neuroimaging records as well as the proper synchronization between the neuroimaging streams. We present here two experiments to assess the feasibility and characterization of the Raspberry Pi as the core for a multimodal EEG-fNIRS neuroimaging platform; one over controlled conditions using a combination of synthetic and real data, and another from a full test during resting state. CPU usage, RAM usage and operation temperature were measured during the tests with mean operational records below 40% for CPU cores, 13.6% for memory and 58.85 ° C for temperatures. Package loss was inexistent on synthetic data and negligible on experimental data. Current consumption can be satisfied with a 1000 mAh 5V battery. The Raspberry Pi 4 was able to cope with the required workload in conditions of operation similar to those needed to support a neurorehabilitation evaluation.

Original languageEnglish
Title of host publication43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2021)
PublisherIEEE
Pages1288-1291
Number of pages4
ISBN (Electronic)9781728111797, 9781728111780 (USB)
ISBN (Print)9781728111803 (PoD)
DOIs
Publication statusPublished - 9 Dec 2021
Event43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Virtual
Duration: 1 Nov 20215 Nov 2021

Publication series

NameAnnual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society.
ISSN (Print)2375-7477
ISSN (Electronic)2694-0604

Conference

Conference43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Abbreviated titleEMBC '21
Period1/11/215/11/21

Keywords

  • Neuroimaging
  • Temperature measurement
  • Protocols
  • Random access memory
  • Medical services
  • Virtual machining
  • Software

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