合成地震心电图和心电图发生器幻影

M. Nikbakht, D. Lin, Asim H. Gazi, O. Inan
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引用次数: 3

摘要

地震心动图(SCG)和心电图(ECG)信号是两种源自心血管的信号,包含心脏健康评估的重要特征。有效地利用这些信号要求记录具有可接受的信噪比。研究外部因素(如振动)对这些信号的影响,以及随后的伪影去除算法设计,仍然是一个挑战,因为缺乏对地面真值标签的访问和人类参与者的安全问题。在这项工作中,提出了一种合成SCG和ECG发生器系统,该系统可以在可能对人类参与者不安全或不方便的环境中收集数据,并提供地面真实值标签以及模拟记录。该系统使用真人SCG和心电信号进行了验证,SCG和心电信号在时间和频域分别显示>90%和>98%的输入输出相关性。因此,该系统能够产生具有临床相关振幅的真实SCG和ECG信号,有利于在相关环境中收集无参与者的数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Synthetic Seismocardiogram and Electrocardiogram Generator Phantom
The seismocardiogram (SCG) and electrocardio-gram (ECG) signals are two signals of cardiovascular origin containing important features for cardiac health assessment. Effective use of these signals requires recordings with acceptable signal to noise ratio. Studying the effects of external factors such as vibrations on these signals, and subsequent artifact removal algorithm design, remains a challenge due to lack of access to ground truth labels and human participant safety concerns. In this work, a synthetic SCG and ECG generator system is presented that enables data collection in environments that may be unsafe or inconvenient for human participants and offers ground truth labels along with the simulated recordings. The system was validated using real human SCG and ECG signals and showed >90%, and >98% input output correlations in both time and frequency domains for SCG and ECG signals respectively. Thus, the system is able to generate realistic SCG and ECG signals with clinically relevant amplitudes favorable for participant-free data collection in relevant environments.
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