Andreozzi Emilio, Centracchio Jessica, Esposito Daniele, Bifulco Paolo
Department of Electrical Engineering and Information Technologies, University of Naples Federico II, Via Claudio, 21, 80125 Napoli, Italy.
Bioengineering (Basel). 2022 Apr 9;9(4):167. doi: 10.3390/bioengineering9040167.
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.
地震心动图(SCG)在很大程度上被视为可穿戴应用中连续、长期监测心脏机械活动的先进技术。SCG信号通过固定在胸部的小型、轻型加速度计获取。它们提供重要心脏事件的时间,如心脏瓣膜的开闭,从而能够估计具有临床相关性的心脏时间间隔。力心动图(FCG)是一种新技术,通过特定的力传感器记录心脏引起的胸壁振动,该传感器已证明能够从胸部的单个接触点同时监测呼吸、心音和次声心脏振动。一个特定的次声成分捕捉心脏壁的位移,看起来与心尖心动图非常相似。这个低频成分在SCG记录中不可见,也不能通过简单滤波提取。在本研究中,提出了一种从SCG信号中提取此信息的可行方法。所提出的方法基于SCG的双重积分。数值双重积分通常非常容易产生大误差,因此设计了一种特定的数值程序。该程序产生一个新的位移信号(DSCG),其具有一个与FCG(LF-FCG)非常相似的低频成分(LF-DSCG)。使用一个FCG传感器和一个现成的加速度计进行实验测试,它们牢固地相互连接并放置在前胸区域。从两个传感器同时采集记录,并采集一份心电图导联(用作参考)。定量形态学比较证实了LF-FCG和LF-DSCG之间的高度相似性(归一化互相关指数>0.9)。统计分析表明,LF-DSCG虽然在心跳检测中具有相当的灵敏度(约90%),但在心动周期内的一致性不是很高,导致心跳间期估计不准确。设想未来使用高性能加速度计和改进的处理方法进行实验,以研究所提出方法的准确性和可靠性的潜在提高。