Prototype of a Multimodal and Multichannel Electro-Physiological and General-Purpose Signal Capture System: Evaluation in Sleep-Research-like Scenario

The simultaneous analysis of electrophysiological signals from various physiological systems, such as the brain, skeletal muscles, and cardiac muscles, has become increasingly necessary in both clinical and research settings. However, acquiring multiple modalities of electrophysiological data often necessitates the use of diverse, specialized technological tools, which can complicate the establishment of a comprehensive multimodal experimental setup. This paper introduces a prototype system, named the Multimodal-Multichannel Acquisition Module-MADQ, designed for the simultaneous acquisition of multimodal and multichannel electrophysiological and general-purpose signals. The MADQ comprises three distinct capturing blocks, each equipped with separate reference circuits, supporting a total of up to 40 electrophysiological input channels, alongside 4 channels of analog input and 4 channels of digital input signal. The system is capable of sampling frequencies up to 16 kHz. Key features of the MADQ include individually configurable bipolar recording, lead-off detection capability, and real-time online filtering. The system's functional performance was characterized through metrics such as Input-Referred Noise (IRN), Noise-Free Bits (NFB), and Effective Number of Bits (ENOB) across varying gain and sampling frequencies. Preliminary experiments, conducted in a setup emulating a sleep study with auditory evoked potential detection, demonstrate the system's potential for integration into multimodal experimental scenarios.

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Publication Details

Journal
Sensors
Published
2025-04-30
DOI
https://doi.org/10.3390/s25092816
Citations
1
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
1.43

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article

Prototype of a Multimodal and Multichannel Electro-Physiological and General-Purpose Signal Capture System: Evaluation in Sleep-Research-like Scenario

Aluizio d’Affonsêca Netto, J. Castillo-G, Pablo Cevallos-Larrea, Carlos Júlio Tierra-Criollo et al.
1 citations
Sensors
EEG and Brain-Computer Interfaces
1.43
article

Prototype of a Multimodal and Multichannel Electro-Physiological and General-Purpose Signal Capture System: Evaluation in Sleep-Research-like Scenario

Aluizio d’Affonsêca Netto, J. Castillo-G, Pablo Cevallos-Larrea, Carlos Júlio Tierra-Criollo, D. A. Molina-Vidal, Leimer Guambaña-Calle
article en
1 citations

Abstract

The simultaneous analysis of electrophysiological signals from various physiological systems, such as the brain, skeletal muscles, and cardiac muscles, has become increasingly necessary in both clinical and research settings. However, acquiring multiple modalities of electrophysiological data often necessitates the use of diverse, specialized technological tools, which can complicate the establishment of a comprehensive multimodal experimental setup. This paper introduces a prototype system, named the Multimodal-Multichannel Acquisition Module-MADQ, designed for the simultaneous acquisition of multimodal and multichannel electrophysiological and general-purpose signals. The MADQ comprises three distinct capturing blocks, each equipped with separate reference circuits, supporting a total of up to 40 electrophysiological input channels, alongside 4 channels of analog input and 4 channels of digital input signal. The system is capable of sampling frequencies up to 16 kHz. Key features of the MADQ include individually configurable bipolar recording, lead-off detection capability, and real-time online filtering. The system's functional performance was characterized through metrics such as Input-Referred Noise (IRN), Noise-Free Bits (NFB), and Effective Number of Bits (ENOB) across varying gain and sampling frequencies. Preliminary experiments, conducted in a setup emulating a sleep study with auditory evoked potential detection, demonstrate the system's potential for integration into multimodal experimental scenarios.

SensorsVol. 25(9)
Universidade Federal do Rio de Janeiro (BR), Politecnica Salesiana University (EC)
Universidad Politécnica Salesiana del Ecuador, Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Conselho Nacional de Desenvolvimento Científico e Tecnológico, Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro, Financiadora de Estudos e Projetos
Openalex Percentile: Top 20%
EEG and Brain-Computer Interfaces
1.43
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