Abstract
Ion-sensors play a major role in physiology and healthcare monitoring since they are capable of continuously collecting biological data from body fluids. Nevertheless, ion interference from background electrolytes present in the sample is a paramount challenge for a precise multi-ion-monitoring. In this work, we propose the first system combining a battery-powered portable multi-channel electronic front-end, and an embedded Multi-output Support Vector Regressor (M-SVR), that supplies an accurate, continuous, and real-time monitoring of sodium, potassium, ammonium, and calcium ions. These are typical analytes tracked during physical exercise. The front-end interface was characterized through a sensor array built with screen-printed electrodes. Nernstian sensitivity and limit of detection comparable to a bulky laboratory potentiometer were achieved in both water and artificial sweat. The multivariate calibration model was deployed on a Raspberry Pi where the activity of the target ions were locally computed. The M-SVR model was trained, optimized, and tested on an experimental dataset acquired following a design of experiments. We demonstrate that the proposed multivariate regressor is a compact, low-complexity, accurate, and unbiased estimator of sodium and potassium ions activity. A global normalized root mean-squared error improvement of 6.97%, and global mean relative error improvement of 10.26%, were achieved with respect to a standard Multiple Linear Regressor (MLR). Within a real-time multi-ion-monitoring task, the overall system enabled the continuous monitoring and accurate determination of the four target ions activity, with an average accuracy improvement of 27.73% compared to a simple MLR, and a prediction latency of [Formula: see text].
Highlights
INTRODUCTIONI ON-SENSING technology is increasingly receiving interest due to its ability to provide a non-invasive and continuous
I ON-SENSING technology is increasingly receiving interest due to its ability to provide a non-invasive and continuousManuscript received June 9, 2021; revised August 24, 2021 and October 3, 2021; accepted October 4, 2021
We propose a complete electronic tongue system coupling: a multi-ion-sensor array, an electronic front-end interface, and the Multi-output Support Vector Regressor (M-SVR) calibration model deployed on an edge device, enabling an accurate, continuous, and real-time determination of sodium, potassium, ammonium, and calcium ions in artificial sweat, for physiology applications
Summary
I ON-SENSING technology is increasingly receiving interest due to its ability to provide a non-invasive and continuous. We have recently presented in [24], a Multi-output Support Vector Regressor (M-SVR), that has been demonstrated to be a compact, accurate, robust, and low-complexity multivariate calibration model for sodium, potassium, lithium, and lead ions monitoring, in various healthcare applications. We propose a complete electronic tongue system coupling: a multi-ion-sensor array, an electronic front-end interface, and the M-SVR calibration model deployed on an edge device, enabling an accurate, continuous, and real-time determination of sodium, potassium, ammonium, and calcium ions in artificial sweat, for physiology applications (see Fig. 1).
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