VERIFICATION OF THE MODEL AND METHOD FUNCTIONALITY FOR REMOTE HEALTH MONITORING ILLUSTRATED BY THE DEVIATIONS IN HUMAN BODY TEMPERATURE INDICATORS
Abstract
The rapid development of telemedicine in the healthcare sector facilitates the active implementation of various methods and models for remote monitoring of human health indicators. In this regard, significant attention is paid to the development of mobile applications capable of providing accurate and timely monitoring of key health indicators in real-time. The aim of this research is to evaluate the applicability of the proposed method and model for remote monitoring of human health indicators, and to analyze the effectiveness of the developed mobile application HelpMeTracker in identifying deviations in human body temperature indicators. To assess the functionality of the proposed health monitoring method, a comprehensive experiment was conducted, which included participants from different age categories and social groups. During the experiment, the application was to analyze and track the dynamics of changes in human body temperature indicators using sensors integrated into smartwatches or fitness trackers, and timely notify about detected anomalies for the possibility of rapid response to changes in health status. The results obtained during the conducted research demonstrate that the proposed model and method for remote monitoring of human health indicators have a high degree of effectiveness for observing the current health status. During the experiment, the HelpMeTracker application reliably detected all deviations in body temperature indicators obtained from sensors of wearable devices and successfully informed all participants of the process. Based on the obtained results, it can be concluded that the application of the proposed approach for remote monitoring is sufficient to capture deviations in body temperature indicators, track the dynamics of changes, and form a substantiated comprehensive assessment of human health based on the information received from the device sensors.
