Exploring the Synchrony Between Body Temperature and HR, RR, and Aortic Blood Pressure in Viral/Bacterial Disease Onsets with Signal Dynamics

TL;DR

This study analyzes the dynamic relationships between body temperature, heart rate, respiration, and blood pressure to improve early illness detection using signal processing, potentially enabling pre-symptomatic intervention.

Contribution

It introduces a signal dynamics analysis approach to predict vital sign changes, enhancing early detection of viral and bacterial disease onsets beyond traditional methods.

Findings

Heart rate and respiration follow temperature changes.

Aortic blood pressure follows heart rate and respiration.

Vital sign trends can be predicted from each other.

Abstract

Signal-based early detection of illnesses has been a key topic in research and hospital settings; it reduces technological costs and paves the way for quick and effective patient-care operations. Elementary machine learning and signal processing algorithms have proven to be sufficient in classifying the onset of viral and bacterial conditions before clinical symptoms are shown. Inspired by these recent developments, this project employs signal dynamics analysis to infer changes in vital signs (temperature, respiration, and heart rate). The results demonstrate that the trends of one vital function can be predicted from that of another. In particular, it is shown that heart rate and respiration typically change shortly after body temperature, and aortic blood pressure follows. This is not an etiologically specific approach, but if advanced further, it can enable patients and wearable system users to tame these changes and prevent immediate symptoms.