Abstract
This paper presents the design of an analog front-end of an electrochemical conductivity sensor. This forms part of a multi-parameter sensing device for use in the detection and diagnosis of urolithiasis in its preliminary stages. The proposed conductivity bio-sensor is used for measuring the concentration of total dissolved salts in urine. It will be combined with FET-based potentiometric sensors for measuring Ca2+ and pH, and an amperometric sensor for measuring uric acid into an integrated lab-on-a-chip point-of-care device.
Furthermore, measured data are collected and stored in a database for future use in an AI (Artificial Intelligence) diagnosis system. Such a multi-parameter approach caters for a more effective stone-risk indexing.
The conductivity sensor readout circuit works on the principle of electrochemical impedance spectroscopy. The sample under test (urine) is subjected to a constant sinusoidal current which causes it to develop a potential difference. The sample interface is via four-point gold coated flat electrodes. The true RMS (root mean square) value of current and voltage is measured and impedance magnitude is calculated by dividing voltage to current.
Measurement is iterated for several frequencies in the range between 1.5 kHz and 3.3 kHz. The frequency is selected from prime numbers to avoid harmonics distortion.
The proposed system has been tested in an on-board platform and the results of the measurement are correlated to a commercial conductivity meter device. The developed conductivity sensor and its readout circuitry have potential usage in point-of-care test device for urolithiasis prognosis and screening.
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Acknowledgment
The authors would like to express their deep gratitude to Ten-Chen Hospital Group, Chung-Li for medical issue consulting, Holtek Semiconductor Inc for providing support of digital hardware and Dr. Angelito Silverio for his great help of paper editing.
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Ramezani, R.F. et al. (2020). Development of Urine Conductivity Sensing System for Measurement and Data Collection. In: Lin, KP., Magjarevic, R., de Carvalho, P. (eds) Future Trends in Biomedical and Health Informatics and Cybersecurity in Medical Devices. ICBHI 2019. IFMBE Proceedings, vol 74. Springer, Cham. https://doi.org/10.1007/978-3-030-30636-6_22
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DOI: https://doi.org/10.1007/978-3-030-30636-6_22
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