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

## TL;DR

This study validates an mHealth system for measuring body temperature, heart rate, and oxygen saturation against clinical devices in an ICU setting.

## Contribution

The study introduces a novel mHealth device integrated into the e-CoVig app and validates its accuracy using clinical standards.

## Key findings

- The e-CoVig device showed overall agreement with standard devices for measuring vital signs.
- Additive errors were identified and corrected, with weak proportional biases observed.
- Advanced methods for further assessment of the device's accuracy were proposed.

## 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.