A Comparison of Heart Pulsations Provided by Forcecardiography and Double Integration of Seismocardiogram

Abstract

Seismocardiography (SCG) is largely regarded as the state-of-the-art technique for continuous, long-term monitoring of cardiac mechanical activity in wearable applications. SCG signals are acquired via small, lightweight accelerometers fixed on the chest. They provide timings of important cardiac events, such as heart valves openings and closures, thus allowing the estimation of cardiac time intervals of clinical relevance. Forcecardiography (FCG) is a novel technique that records the cardiac-induced vibrations of the chest wall by means of specific force sensors, which proved capable of monitoring respiration, heart sounds and infrasonic cardiac vibrations, simultaneously from a single contact point on the chest. A specific infrasonic component captures the heart walls displacements and looks very similar to the Apexcardiogram. This low-frequency component is not visible in SCG recordings, nor it can be extracted by simple filtering. In this study, a feasible way to extract this information from SCG signals is presented. The proposed approach is based on double integration of SCG. Numerical double integration is usually very prone to large errors, therefore a specific numerical procedure was devised. This procedure yields a new displacement signal (DSCG) that features a low-frequency component (LF-DSCG) very similar to that of the FCG (LF-FCG). Experimental tests were carried out using an FCG sensor and an off-the-shelf accelerometer firmly attached to each other and placed onto the precordial region. Simultaneous recordings were acquired from both sensors, together with an electrocardiogram lead (used as a reference). Quantitative morphological comparison confirmed the high similarity between LF-FCG and LF-DSCG (normalized cross-correlation index >0.9). Statistical analyses suggested that LF-DSCG, although achieving a fair sensitivity in heartbeat detection (about 90%), has not a very high consistency within the cardiac cycle, leading to inaccuracies in inter-beat intervals estimation. Future experiments with high-performance accelerometers and improved processing methods are envisioned to investigate the potential enhancement of the accuracy and reliability of the proposed method.

Keywords: Forcecardiography; Seismocardiography; accelerometer; cardiac monitoring; heart vibrations; piezoelectric sensor.

Figure 1

(a) Lateral view of sensors assembly applied on the chest of a subject; (b) frontal view of sensors positioning area on the chest (green dashed line).

Figure 2

LF-FCG, LF-DSCG and ECG signals acquired during apneas (subject #2).

Figure 3

FRG, LF-FCG, LF-DSCG and ECG signals acquired during quiet breathing (subject #2).

Figure 4

Statistical analyses on inter-beat intervals extracted from LF-FCG and LF-DSCG signals during apneas. (a) Results of regression and correlation analyses of LF-FCG vs. ECG; (b) results of Bland-Altman analysis of LF-FCG vs. ECG; (c) results of regression and correlation analyses of LF-DSCG vs. ECG; (d) results of Bland-Altman analysis of LF-DSCG vs. ECG.

Figure 5

Statistical analyses on inter-beat intervals extracted from LF-FCG and LF-DSCG signals during respiration. (a) Results of regression and correlation analyses of LF-FCG vs. ECG; (b) results of Bland-Altman analysis of LF-FCG vs. ECG; (c) results of regression and correlation analyses of LF-DSCG vs. ECG; (d) results of Bland-Altman analysis of LF-DSCG vs. ECG.