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首页> 外文会议>Sensing and analysis technologies for biomedical and cognitive applications 2016 >Remote Heartbeat Signal Detection from Visible Spectrum Recordings Based on Blind Deconvolution
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Remote Heartbeat Signal Detection from Visible Spectrum Recordings Based on Blind Deconvolution

机译：基于盲反卷积的可见光谱记录远程心跳信号检测

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摘要

While recent advances have shown that it is possible to acquire a signal equivalent to the heartbeat from visual spectrum video recordings of the human skin, extracting the heartbeat's exact timing information from it, for the purpose of heart rate variability analysis, remains a challenge. In this paper, we explore two novel methods to estimate the remote cardiac signal peak positions, aiming at a close representation of the R-peaks of the ECG signal. The first method is based on curve fitting (CF) using a modified filtered least mean square (LMS) optimization and the second method is based on system estimation using blind deconvolution (BDC). To prove the efficacy of the developed algorithms, we compared results obtained with the ground truth (ECG) signal. Both methods achieved a low relative error between the peaks of the two signals. This work, performed under an IRB approved protocol, provides initial proof that blind deconvolution techniques can be used to estimate timing information of the cardiac signal closely correlated to the one obtained by traditional ECG. The results show promise for further development of a remote sensing of cardiac signals for the purpose of remote vital sign and stress detection for medical, security, military and civilian applications.
机译：尽管最近的进展表明，有可能从人皮肤的可视频谱视频记录中获取与心跳等效的信号，但从中提取心跳的准确定时信息以进行心率变异性分析仍然是一个挑战。在本文中，我们探索了两种新颖的方法来估计远程心脏信号峰值位置，旨在对ECG信号的R峰进行精确表示。第一种方法基于使用改进的滤波最小均方（LMS）优化的曲线拟合（CF），第二种方法基于使用盲反卷积（BDC）的系统估计。为了证明所开发算法的有效性，我们将获得的结果与地面真实情况（ECG）信号进行了比较。两种方法均在两个信号的峰值之间实现了较低的相对误差。这项工作是在IRB批准的协议下进行的，提供了初步证明，即可以使用盲解卷积技术来估计与传统ECG获得的心脏信号密切相关的心脏信号的时序信息。结果表明，有望进一步开发用于远程生命体征和压力检测的心脏信号遥感技术，以用于医疗，安全，军事和民用领域。

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