Performance Analysis of Gyroscope and Accelerometer Sensors for Seismocardiography-Based Wearable Pre-Ejection Period Estimation
Performance Analysis of Gyroscope and Accelerometer Sensors for Seismocardiography-Based Wearable Pre-Ejection Period Estimation
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DOI：
10.1109/jbhi.2019.2895775
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发表时间：
2019-11-01
影响因子：
7.7
通讯作者：
Inan, Omer T.
中科院分区：
文献类型：
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作者：
Shandhi, Md Mobashir Hasan;Semiz, Beren;Inan, Omer T.
目的：收缩时间间隔，例如射血前期（PEP），是用于评估心脏收缩力的重要参数，其可以使用心震图（SCG）非侵入性地测量。最近的研究表明，基于加速度计和陀螺仪的SCG信号上的特定点可用于PEP估计。然而，SCG信号的复杂形态和受试者间变化可能使该假设非常具有挑战性，并且当这些技术用于开发全局模型时会增加均方根误差（RMSE）。研究方法：在这项研究中，我们比较了基于陀螺仪和加速度计的SCG信号，单独和组合，以估计PEP，以显示这些传感器在捕获有关心血管健康的有价值信息方面的功效。我们从这些传感器的所有轴提取一般时域特征，并使用各种回归技术开发全局模型。结果如下：在陀螺仪和加速度计的单轴比较中，来自陀螺仪的头到脚轴周围的角速度信号在所有受试者中提供了最低的RMSE，为12.63 ± 0.49 ms。PEP的最佳估计，在所有科目的RMSE为11.46 - 0.32毫秒，实现了从陀螺仪和加速度计的功能相结合。与最近文献中使用的算法相比，我们的全球模型显示RMSE低30。结论：与位于胸骨中部的加速度计相比，陀螺仪可以提供更好的PEP估计。全局PEP估计模型可以通过组合来自两个传感器的一般时域特征来改进。重要性：这项工作可用于开发低成本的可穿戴心脏监测设备，并使用单传感器或多传感器融合来生成心脏收缩时间间隔的通用估计模型。
Objective: Systolic time intervals, such as the pre-ejection period (PEP), are important parameters for assessing cardiac contractility that can be measured non-invasively using seismocardiography (SCG). Recent studies have shown that specific points on accelerometer- and gyroscope-based SCG signals can be used for PEP estimation. However, the complex morphology and inter-subject variation of the SCG signal can make this assumption very challenging and increase the root mean squared error (RMSE) when these techniques are used to develop a global model. Methods: In this study, we compared gyroscope- and accelerometer-based SCG signals, individually and in combination, for estimating PEP to show the efficacy of these sensors in capturing valuable information regarding cardiovascular health. We extracted general time-domain features from all the axes of these sensors and developed global models using various regression techniques. Results: In single-axis comparison of gyroscope and accelerometer, angular velocity signal around head to foot axis from the gyroscope provided the lowest RMSE of 12.63 0.49 ms across all subjects. The best estimate of PEP, with a RMSE of 11.46 0.32 ms across all subjects, was achieved by combining features from the gyroscope and accelerometer. Our global model showed 30 lower RMSE when compared to algorithms used in recent literature. Conclusion: Gyroscopes can provide better PEP estimation compared to accelerometers located on the mid-sternum. Global PEP estimation models can be improved by combining general time domain features from both sensors. Significance: This work can be used to develop a low-cost wearable heart-monitoring device and to generate a universal estimation model for systolic time intervals using a single- or multiple-sensor fusion.