AD8232 to Biopotentials Sensors: Open Source Project and Benchmark

Author:

Mendes Junior José Jair Alves1ORCID,Campos Daniel Prado2ORCID,Biassio Lorenzo Coelho de Andrade Villela De1,Passos Pedro Carlin1,Júnior Paulo Broniera3ORCID,Lazzaretti André Eugênio1ORCID,Krueger Eddy4ORCID

Affiliation:

1. Graduate Program in Electrical Engineering and Industrial Informatics (CPGEI), Federal University of Technology—Paraná (UTFPR), Sete de Setembro, 3165, Curitiba 80230-901, Brazil

2. Graduate Program in Biomedical Engineering (PPGEB), Federal University of Technology—Paraná (UTFPR), Marcílio Dias, 635, Apucarana 86812-460, Brazil

3. Senai Institute of Information and Communication Technology (ISTIC), Electronic System Laboratory—Embedded and Power Electronics, IoT and 4.0 Manufacturing, Rua Belém 844, Londrina 86026-040, Brazil

4. Anatomy Department, Neural and Rehabilitation Engineering Laboratory, State University of Londrina, Rodovia Celso Garcia Cid-Pr 445, Km 380, Londrina 86057-970, Brazil

Abstract

Acquiring biopotentials with fidelity using low-cost circuits is a significant challenge in biomedical instrumentation. In this perspective, our goal is to investigate the characteristics of the widely applied AD8232®, an analog front-end for biopotential acquisition. We designed and evaluated circuits to acquire the most common biosignals: electrocardiogram (ECG), electromyogram (EMG), and electroencephalogram (EEG). Our findings show that the circuit is suitable for ECG and EMG instrumentation, although it has limitations for EEG signals, particularly concerning the gain. The entire project of the boards is also a contribution of this work as we intend to corroborate open-source do-it-yourself biomedical instrumentation.

Funder

Federal University of Technology—Paraná

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering

Reference55 articles.

1. Simini, F., and Bertemes-Filho, P. (2022). Medicine-Based Informatics and Engineering, Springer International Publishing.

2. Biopotential Amplifiers;Nagel;Biomedical Engineering Handbook,2000

3. Low-cost electromyography—Validation against a commercial system using both manual and automated activation timing thresholds;Heywood;J. Electromyogr. Kinesiol.,2018

4. Palumbo, A., Vizza, P., Calabrese, B., and Ielpo, N. (2021). Biopotential Signal Monitoring Systems in Rehabilitation: A Review. Sensors, 21.

5. Plácido da Silva, H., Guerreiro, J., Lourenco, A., Fred, A., and Martins, R. (2014, January 7–9). BITalino: A Novel Hardware Framework for Physiological Computing. Proceedings of the International Conference on Physiological Computing Systems, Lisbon, Portugal.

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