Intracranial pressure signals forecasting with wavelet trasform and neuro-fuzzy network

In this paper, we propose a novel approach to forecast the time evolution of the intracranial pressure (ICP) signal acquired by means of optical fiber catheters in patients with neurological pathologies. The proposed processing system uses wavelet transform and neuro-fuzzy network (NFN) to make the forecast. It is noteworthy to underline that a forecasting approach based only on NFN would provide information limited to a few samples. The advantage of this method is that it turns to account both the wavelet ability to focus information in few parameters and the NFN performance to expand the forecasting to a larger set, improving the agreement between the experimental data and the predicted ones.