Brain Monitoring Devices for Neuroscience: A Review of Current Technologies

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Authors: Claudio Salvalaio, eduardo maciel, Felipe Correa Bitencourt, Eduarda A. Tessari, Isadora Nascimento, Daniela Pohren, Aline Souza Pagnussat, Isabel Cristina Siqueira da Silva, Alcyr Oliveira
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References: 34

Abstract

This scoping review presents a device-level characterization of 98 commercially available wireless brain monitoring systems, focusing on electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) applications in neuroscience and neurorehabilitation. A structured literature search was conducted in accordance with PRISMA guidelines and registered in the Open Science Framework. Searches were performed across five databases (IEEE Xplore, Scopus, PubMed/MEDLINE,Web of Science, and Embase) between March and August 2025. From 5,069 retrieved records, 3,748 remained after duplicate removal. After consolidation of studies reporting multiple devices, 3,164 unique articles were screened, of which 2,100 reported the use of identifiable brain monitoring devices, corresponding to an inclusion rate of 66.37%. Based on these studies and complementary manufacturer documentation, a dataset comprising 98 commercially available devices was compiled and analyzed in terms of acquisition-level characteristics, research adoption, and application-oriented readiness. Research adoption was quantified using DOI-indexed publication counts, revealing a highly skewed distribution in which the five most frequently used devices accounted for 59.10% of all studies. Regression analysis controlling for device age showed that open access to raw data and software interfaces was the only factor significantly associated with higher research adoption. A TOPSIS-based multi-criteria decision analysis was applied to compare devices according to acquisition-level suitability. The results indicate a shift toward portable and software-accessible neurotechnology, alongside persistent differences between consumer- and research-grade systems in data access, synchronization, and real-time capability. This review provides a reproducible framework to support informed device selection in neuroscience and neurorehabilitation.

Fields of Study & Subjects

EEG and Brain-Computer Interfaces Optical Imaging and Spectroscopy Techniques Neuroscience and Neural Engineering

Publication details

Journal / source
IEEE Access
Volume
14
Pages
23907–23920
Publication date
1 January 2026
Language
EN