Minimally Invasive and Non-Invasive Sensor Technologies for Predicting Heart Failure an Overview

Abstract

This chapter explains the non-invasive and minimally invasive sensor technologies and techniques employed for heart failure (HF) diagnosis. It summarizes landmark studies and clinical trials which prove the potential of non-invasive monitoring of HF patients. The methods for identifying worsening HF can be listed as body weight measurements, electrocardiography (ECG), bioimpedance monitoring, activity tracking, implanted pressure sensors, lung ultrasound monitoring, measurements with sound and Doppler sensors, seismocardiography, ballistocardiography, photoplethysmography, and measurement of natriuretic peptides levels in circulating blood. It is necessary to elucidate the effect of remote monitoring modalities for HF prediction on large-scale randomized control trials. A relative increase in thoracic bioimpedance provides better prediction of HF-related congestion. ECG is among the under-investigated techniques for HF remote monitoring. The positive results of clinical trials with large numbers of patients show the high potential of non-invasive sensors for diagnosing HF.