Extraction of gastric slow waves from electrogastrog rams: combining independent component analysis and adaptive signal enhancement
The electrogastrogram (EGG), a cutaneous measurement of gastric electrical activity, is a mixture of gastric slow waves and noise. To detect the propagation of gastric slow waves, it is desired to obtain gastric slow waves in each of multichannel EGGs. Recently, independent component analysis (ICA) has shown its efficiency in separating the gastric slow wave from noisy multichannel EGGs. However, this method is not able to recover gastric slow waves in each of the multichannel EGGs. In this paper, a two-stage combined method was proposed for extracting gastric slow waves. First, ICA was performed to separate the gastric slow wave component from noisy multichannel EGGs. Second, adaptive signal enhancement with a reference input derived by the ICA in the first stage was employed to extract gastric slow waves in each channel. Quantitative analysis showed that, with the proposed method, the maximum root-mean-square error between the estimated time lag and its theoretical value in the simulations was only 0.65. The results from real EGG data demonstrated that the combined method was able to extract gastric slow waves from individual channels of EGGs which are important to identify the slow wave propagation. Therefore, the proposed method can be used to detect propagation of gastric slow waves from multichannel EGGs.
independent component analysis electrogastrogram blind source separation adaptive filter hilbert transform