Novel adaptive filtering technique for the processing of electrogastrogram

摘要

The electrogastrogram measured cutaneously by attaching electrodes to the abdominal skin contains considerable noise. An attempt is made to develop an efficient adaptive filtering technique suitable for real time processing of electrogastrogram. A novel technique combining both adaptive noise cancellation and adaptive signal enhancement in a single recurrent neural network is proposed. To compare its performance, adaptive noise cancellation and cascaded connection of adaptive noise cancellation and adaptive signal enhancement are employed. Recurrent neural networks using Real Time Recurrent Learning (RTRL) algorithm are employed for implementing the all the above systems. An attempt is made to alleviate the computational burden imposed by RTRL algorithm by employing pruning of weights.