A Novel Broadband Forcecardiography Sensor for Simultaneous Monitoring of Respiration, Infrasonic Cardiac Vibrations and Heart Sounds.

Emilio Andreozzi,Paolo Bifulco,Daniele Esposito,Gaetano D Gargiulo

doi:10.3389/fphys.2021.725716

Emilio Andreozzi, Paolo Bifulco + Show 2 more

Open Access

https://doi.org/10.3389/fphys.2021.725716

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Abstract

The precordial mechanical vibrations generated by cardiac contractions have a rich frequency spectrum. While the lowest frequencies can be palpated, the higher infrasonic frequencies are usually captured by the seismocardiogram (SCG) signal and the audible ones correspond to heart sounds. Forcecardiography (FCG) is a non-invasive technique that measures these vibrations via force sensing resistors (FSR). This study presents a new piezoelectric sensor able to record all heart vibrations simultaneously, as well as a respiration signal. The new sensor was compared to the FSR-based one to assess its suitability for FCG. An electrocardiogram (ECG) lead and a signal from an electro-resistive respiration band (ERB) were synchronously acquired as references on six healthy volunteers (4 males, 2 females) at rest. The raw signals from the piezoelectric and the FSR-based sensors turned out to be very similar. The raw signals were divided into four components: Forcerespirogram (FRG), Low-Frequency FCG (LF-FCG), High-Frequency FCG (HF-FCG) and heart sounds (HS-FCG). A beat-by-beat comparison of FCG and ECG signals was carried out by means of regression, correlation and Bland–Altman analyses, and similarly for respiration signals (FRG and ERB). The results showed that the infrasonic FCG components are strongly related to the cardiac cycle (R2 > 0.999, null bias and Limits of Agreement (LoA) of ± 4.9 ms for HF-FCG; R2 > 0.99, null bias and LoA of ± 26.9 ms for LF-FCG) and the FRG inter-breath intervals are consistent with ERB ones (R2 > 0.99, non-significant bias and LoA of ± 0.46 s). Furthermore, the piezoelectric sensor was tested against an accelerometer and an electronic stethoscope: synchronous acquisitions were performed to quantify the similarity between the signals. ECG-triggered ensemble averages (synchronized with R-peaks) of HF-FCG and SCG showed a correlation greater than 0.81, while those of HS-FCG and PCG scored a correlation greater than 0.85. The piezoelectric sensor demonstrated superior performances as compared to the FSR, providing more accurate, beat-by-beat measurements. This is the first time that a single piezoelectric sensor demonstrated the ability to simultaneously capture respiration, heart sounds, an SCG-like signal (i.e., HF-FCG) and the LF-FCG signal, which may provide information on ventricular emptying and filling events. According to these preliminary results the novel piezoelectric FCG sensor stands as a promising device for accurate, unobtrusive, long-term monitoring of cardiorespiratory functions and paves the way for a wide range of potential applications, both in the research and clinical fields. However, these results should be confirmed by further analyses on a larger cohort of subjects, possibly including also pathological patients.

Highlights

Cardiac monitoring has always been a critical task in medicine, all the more so if one considers the current burden of cardiovascular diseases (Gersh et al, 2010; Benjamin et al, 2018)
To prove that the novel piezoelectric lead-zirconatetitanate (PZT) sensor is suitable for FCG, the similarity of the ECG-triggered ensemble averages of the two FCG signals obtained from the force sensitive resistors (FSR)-based and PZT sensors was assessed by evaluating their correlation
As shown by the much lower limits of agreement (LoA) of the highfrequency FCG (HF-FCG)-derived interbeat intervals provided by the PZT sensor as compared to those provided by the FSR-based sensor, the PZT sensor provides more precise and stable measurements and proved capable of acquiring SCG-like (HF-FCG) and heart sounds components with a very high signal-to-noise ratio (SNR), without the need for ensemble averaging, which is commonly required for SCG signal processing

Summary

Introduction

Cardiac monitoring has always been a critical task in medicine, all the more so if one considers the current burden of cardiovascular diseases (Gersh et al, 2010; Benjamin et al, 2018). From the end of the XIX century, scientific researchers have investigated several objective methods to gain further insights into the mechanical events that occur within the cardiac cycle, both in healthy and pathological subjects (Knoop, 1965; Luisada et al, 1985; Zanetti and Salerno, 1990) These methods were based on various kinds of mechanical sensors and well-known examples are Phonocardiography (PCG) (Rappaport and Sprague, 1942; Ismail et al, 2018), Kinetocardiography (Eddleman et al, 1953), Apexcardiography (Marey, 1878; Benchimol and Dimond, 1962), Dynamocardiography (Komarov, 1958; Babskiy and Karpman, 1964), Ballistocardiography (BCG) (Gordon, 1877; Burger and Noordergraaf, 1956; Starr, 1958; Knoop, 1965; Sadek et al, 2019), and Seismocardiography (SCG) (Zanetti and Salerno, 1990; Inan et al, 2015; Taebi et al, 2019). Due to the cumbersome instrumentation involved and the uneasiness of signals interpretation, these techniques lost their appeal for both research and clinical purposes (Zanetti and Salerno, 1990)

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