Touch Lab, Biomedical Engineering Group, Department of Applied Mechanics, Indian Institute of Technology Madras, Chennai, 600036, Tamilnadu, India.
Med Biol Eng Comput. 2011 Nov;49(11):1241-7. doi: 10.1007/s11517-011-0796-1. Epub 2011 Jul 12.
Extraction of extra-cardiac information from photoplethysmography (PPG) signal is a challenging research problem with significant clinical applications. In this study, radial basis function neural network (RBFNN) is used to reconstruct the gastric myoelectric activity (GMA) slow wave from finger PPG signal. Finger PPG and GMA (measured using Electrogastrogram, EGG) signals were acquired simultaneously at the sampling rate of 100 Hz from ten healthy subjects. Discrete wavelet transform (DWT) was used to extract slow wave (0-0.1953 Hz) component from the finger PPG signal; this slow wave PPG was used to reconstruct EGG. A RBFNN is trained on signals obtained from six subjects in both fasting and postprandial conditions. The trained network is tested on data obtained from the remaining four subjects. In the earlier study, we have shown the presence of GMA information in finger PPG signal using DWT and cross-correlation method. In this study, we explicitly reconstruct gastric slow wave from finger PPG signal by the proposed RBFNN-based method. It was found that the network-reconstructed slow wave provided significantly higher (P < 0.0001) correlation (≥ 0.9) with the subject's EGG slow wave than the correlation obtained (≈0.7) between the PPG slow wave from DWT and the EEG slow wave. Our results showed that a simple finger PPG signal can be used to reconstruct gastric slow wave using RBFNN method.
从光体积脉搏波（PPG）信号中提取心脏外信息是一个具有重要临床应用的具有挑战性的研究问题。在这项研究中，径向基函数神经网络（RBFNN）用于从手指 PPG 信号重建胃肌电活动（GMA）慢波。同时从十个健康受试者以 100 Hz 的采样率采集手指 PPG 和 GMA（使用胃电图（EGG）测量）信号。离散小波变换（DWT）用于从手指 PPG 信号中提取慢波（0-0.1953 Hz）分量；使用此慢波 PPG 重建 EGG。RBFNN 基于在空腹和餐后条件下从六个受试者获得的信号进行训练。训练后的网络在其余四个受试者获得的数据上进行测试。在早期的研究中，我们已经使用 DWT 和互相关方法证明了 GMA 信息存在于手指 PPG 信号中。在这项研究中，我们通过提出的基于 RBFNN 的方法，明确地从手指 PPG 信号重建胃慢波。研究发现，与 DWT 获得的 PPG 慢波与 EEG 慢波之间的相关性（约为 0.7）相比，网络重建的慢波与受试者的 EGG 慢波具有更高的相关性（P <0.0001，≥0.9）。我们的结果表明，简单的手指 PPG 信号可以使用 RBFNN 方法来重建胃慢波。
