School of Electronic Engineering, Soongsil University, Seoul 06978, Korea.
Department of Industrial and Information Systems Engineering, Soongsil University, Seoul 06978, Korea.
Sensors (Basel). 2017 Aug 14;17(8):1872. doi: 10.3390/s17081872.
Accelerometers are applied to various applications to collect information about movements of other sensors deployed at diverse fields ranging from underwater area to human body. In this study, we try to characterize the nonlinear relationship between motion artifact and acceleration data. The cross bicoherence test and the Volterra filter are used as the approaches to detection and modeling. We use the cross bicoherence test to directly detect in the frequency domain and we indirectly identify the nonlinear relationship by improving the performance of eliminating motion artifact in heartbeat rate estimation using a nonlinear filter, the second-order Volterra filter. In the experiments, significant bicoherence values are observed through the cross bicoherence test between the photoplethysmogram (PPG) signal contaminated with motion artifact and the acceleration sensor data. It is observed that for each dataset, the heartbeat rate estimation based on the Volterra filter is superior to that of the linear filter in terms of average absolute error. Furthermore, the leave one out cross-validation (LOOCV) is employed to develop an optimal structure of the Volterra filter for the total datasets. Due to lack of data, the developed Volterra filter does not demonstrate significant difference from the optimal linear filter in terms of t-test. Through this study, it can be concluded that motion artifact may have a quadaratical relationship with acceleration data in terms of bicoherence and more experimental data are required for developing a robust and efficient model for the relationship.
加速度计应用于各种应用中，以收集从水下区域到人体等不同领域部署的其他传感器的运动信息。在这项研究中，我们试图描述运动伪影与加速度数据之间的非线性关系。采用双谱相干检验和 Volterra 滤波器作为检测和建模的方法。我们使用双谱相干检验直接在频域中进行检测，并通过改进使用非线性滤波器（二阶 Volterra 滤波器）消除心率估计中运动伪影的性能，间接地识别非线性关系。在实验中，通过带运动伪影的光电容积脉搏波（PPG）信号与加速度传感器数据之间的交叉双谱相干检验观察到显著的双谱相干值。观察到对于每个数据集，基于 Volterra 滤波器的心率估计在平均绝对误差方面优于线性滤波器。此外，采用留一法交叉验证（LOOCV）为总数据集开发 Volterra 滤波器的最优结构。由于数据不足，开发的 Volterra 滤波器在 t 检验方面与最优线性滤波器没有显著差异。通过这项研究，可以得出结论，双谱相干表明运动伪影与加速度数据之间可能存在二次关系，并且需要更多的实验数据来开发用于该关系的稳健有效的模型。
