Malarvili M B, Mesbah Mostefa, Boashash Boualem
Signal Processing Research Laboratory, Queensland University of Technology, Brisbane, Australia.
Australas Phys Eng Sci Med. 2006 Mar;29(1):67-72.
The ECG has been much neglected in automatic seizure detection in the newborn. Changes in heart rate and ECG rhythm are often found in animal and adult patients with seizure. However, little is known about heart rate variability (HRV) changes in human neonate during seizure. Results of ongoing time-frequency research are presented here with the aim to compare the performance of various time-frequency distributions (TFDs) when applied to HRV time series for non-seizure and seizure newborns. The TFDs studied are the Wigner-Ville (WVD), the Spectrogram (SP), the Choi-Williams (CWD) and the Modified B (MBD) distributions. Based on our preliminary results, our current conclusion is MBD outperforms other TFDs in terms of time-frequency resolution, cross-terms suppression and to represent the newborn HRV signals of non-seizure and seizure which are closely-spaced components in the time-frequency domain.
在新生儿自动癫痫检测中,心电图(ECG)一直被严重忽视。在患有癫痫的动物和成年患者中,经常会发现心率和心电图节律的变化。然而,对于癫痫发作期间人类新生儿的心率变异性(HRV)变化却知之甚少。本文展示了正在进行的时频研究结果,目的是比较各种时频分布(TFD)应用于非癫痫和癫痫新生儿的HRV时间序列时的性能。所研究的TFD包括维格纳-威利(WVD)分布、频谱图(SP)、崔-威廉姆斯(CWD)分布和修正B(MBD)分布。基于我们的初步结果,我们目前的结论是,在时频分辨率、交叉项抑制以及表示非癫痫和癫痫新生儿HRV信号方面,MBD在时频域中优于其他TFD,这些信号是紧密间隔的成分。