论文标题
ECG和PPG相关分析的运行时监视和统计方法
Runtime Monitoring and Statistical Approaches for Correlation Analysis of ECG and PPG
论文作者
论文摘要
生物物理信号（例如心电图（ECG）和光摄像机图（PPG））是感知福祉重要参数的关键。巧合的是，ECG和PPG是信号，它为相同现象（即心脏周期）提供了一个“不同的窗口”。虽然它们是单独使用的，但尚无关于不同心电图和PPG事件的确切校正的研究。例如，使用较便宜的传感器以及使用多个信号来增强鲁棒性的攻击检测和缓解方法，在许多方面（例如传感器融合）将有助于提高精度。考虑到这一点，我们提出了正式建立ECG和PPG信号之间的关键关系的第一种方法。我们将正式的运行时间监控与统计分析和回归分析相结合，以获得我们的结果。
Biophysical signals such as Electrocardiogram (ECG) and Photoplethysmogram (PPG) are key to the sensing of vital parameters for wellbeing. Coincidentally, ECG and PPG are signals, which provide a "different window" into the same phenomena, namely the cardiac cycle. While they are used separately, there are no studies regarding the exact correction of the different ECG and PPG events. Such correlation would be helpful in many fronts such as sensor fusion for improved accuracy using cheaper sensors and attack detection and mitigation methods using multiple signals to enhance the robustness, for example. Considering this, we present the first approach in formally establishing the key relationships between ECG and PPG signals. We combine formal run-time monitoring with statistical analysis and regression analysis for our results.
