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Volume 20
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10.3390/s20236765
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Article

Bioimpedance Sensor and Methodology for Acute Pain Monitoring

by
Mihaela Ghita
1,2,*,
Martine Neckebroek
3,
Jasper Juchem
1,2,
Dana Copot
1,2,
Cristina I. Muresan
4 and
Clara M. Ionescu
1,2,4
1
Research Group of Dynamical Systems and Control, Ghent University, Tech Lane Science Park 125, 9052 Ghent, Belgium
2
EEDT—Core Lab on Decision and Control, Flanders Make Consortium, Tech Lane Science Park 131, 9052 Ghent, Belgium
3
Department of Anesthesia, Ghent University Hospital, C. Heymanslaan 10, 9000 Gent, Belgium
4
Department of Automation, Technical University of Cluj-Napoca, Memorandumului 28, 400114 Cluj-Napoca, Romania
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(23), 6765; https://doi.org/10.3390/s20236765
Submission received: 3 November 2020 / Revised: 21 November 2020 / Accepted: 23 November 2020 / Published: 26 November 2020
(This article belongs to the Special Issue Sensors and Biomedical Signal Processing for Patient Monitoring)
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Abstract

The paper aims to revive the interest in bioimpedance analysis for pain studies in communicating and non-communicating (anesthetized) individuals for monitoring purpose. The plea for exploitation of full potential offered by the complex (bio)impedance measurement is emphasized through theoretical and experimental analysis. A non-invasive, low-cost reliable sensor to measure skin impedance is designed with off-the-shelf components. This is a second generation prototype for pain detection, quantification, and modeling, with the objective to be used in fully anesthetized patients undergoing surgery. The 2D and 3D time–frequency, multi-frequency evaluation of impedance data is based on broadly available signal processing tools. Furthermore, fractional-order impedance models are implied to provide an indication of change in tissue dynamics correlated with absence/presence of nociceptor stimulation. The unique features of the proposed sensor enhancements are described and illustrated here based on mechanical and thermal tests and further reinforced with previous studies from our first generation prototype.
Keywords: noninvasive pain sensor; electrical impedance spectroscopy; time–frequency analysis; model identification; fractional-order impedance model; nociceptive stimulation noninvasive pain sensor; electrical impedance spectroscopy; time–frequency analysis; model identification; fractional-order impedance model; nociceptive stimulation

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MDPI and ACS Style

Ghita, M.; Neckebroek, M.; Juchem, J.; Copot, D.; Muresan, C.I.; Ionescu, C.M. Bioimpedance Sensor and Methodology for Acute Pain Monitoring. Sensors 2020, 20, 6765. https://doi.org/10.3390/s20236765

AMA Style

Ghita M, Neckebroek M, Juchem J, Copot D, Muresan CI, Ionescu CM. Bioimpedance Sensor and Methodology for Acute Pain Monitoring. Sensors. 2020; 20(23):6765. https://doi.org/10.3390/s20236765

Chicago/Turabian Style

Ghita, Mihaela, Martine Neckebroek, Jasper Juchem, Dana Copot, Cristina I. Muresan, and Clara M. Ionescu. 2020. "Bioimpedance Sensor and Methodology for Acute Pain Monitoring" Sensors 20, no. 23: 6765. https://doi.org/10.3390/s20236765

APA Style

Ghita, M., Neckebroek, M., Juchem, J., Copot, D., Muresan, C. I., & Ionescu, C. M. (2020). Bioimpedance Sensor and Methodology for Acute Pain Monitoring. Sensors, 20(23), 6765. https://doi.org/10.3390/s20236765

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