Validation of an mHealth System for Monitoring Fundamental Physiological Parameters in the Clinical Setting

Abstract

The aim of this work was to validate the measurements of three physiological parameters, namely, body temperature, heart rate, and peripheral oxygen saturation, captured with an out-of-the-lab device using measurements taken with clinically proven devices. The out-of-the-lab specialized device was integrated into a customized mHealth application, e-CoVig, developed within the AIM Health project. To perform the analysis, single consecutive measurements of the three vital parameters obtained with e-CoVig and with the standard devices from patients in an intensive care unit were collected, preprocessed, and then analyzed through classical agreement analysis, where we used Lin’s concordance coefficient to assess the agreement correlation and Bland–Altman plots with exact confidence intervals for the limits of agreement to analyze the paired data readings. The existence of possible systematic errors was also addressed, where we found the presence of additive errors, which were corrected, and weak proportional biases. We obtained the mean overall agreement between the measurements taken with the novel e-CoVig device and the reference devices for the measured quantities. Although some limitations in this study were encountered, we present more advanced methods for their further assessment.