Du Peng, Qiao Wenlian, O'Grady Greg, Egbuji John U, Lammers Wim, Cheng Leo K, Pullan Andrew J
Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand.
Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:2527-30. doi: 10.1109/IEMBS.2009.5334822.
High-resolution (HR; multi-electrode) recordings have led to detailed spatiotemporal descriptions of gastric slow wave activity. The large amount of data conveyed by the HR recordings demands an automated way of extracting the key measures such as activation times. In this study, a derivative-based method of identifying slow wave events was proposed. The raw signal was filtered using a second order Butterworth filter (low-pass; 10 Hz). The signal in each channel was differentiated and a threshold was taken as the 4.5x of the average of the negative first derivatives. An active event was defined where the first derivatives of the signal were more negative than the threshold. The accuracy of the method was validated against manually marked times, with a positive predictive value of 0.71. The detected activation times were interpolated using a second-order polynomial, the coefficients of which were evaluated using a previously developed least-square fitting method. The velocity fields were calculated, showing detailed spatiotemporal profile of slow wave propagation. The average of slow wave propagation velocity was 5.86 +/- 0.07 mms(-1).
高分辨率（HR；多电极）记录已实现对胃慢波活动的详细时空描述。HR记录所传达的大量数据需要一种自动提取诸如激活时间等关键指标的方法。在本研究中，提出了一种基于导数识别慢波事件的方法。原始信号使用二阶巴特沃斯滤波器（低通；10 Hz）进行滤波。对每个通道的信号求导，并将阈值设为负一阶导数平均值的4.5倍。当信号的一阶导数比阈值更负时，定义为一个活跃事件。该方法的准确性通过与手动标记时间进行验证，阳性预测值为0.71。使用二阶多项式对检测到的激活时间进行插值，其系数使用先前开发的最小二乘法拟合方法进行评估。计算了速度场，展示了慢波传播的详细时空轮廓。慢波传播速度的平均值为5.86 +/- 0.07 mm s⁻¹。
