A preliminary study for investigating idiopatic normal pressure hydrocephalus by means of statistical parameters classification of intracranial pressure recordings.

The objective of this study is to investigate Id-iopatic Normal Pressure Hydrocephalus (INPH) through a multidimensional and multiparameter analysis of statistical data obtained from accurate analysis of Intracranial Pressure (ICP) recordings. Such a study could permit to detect new factors, correlated with therapeutic response, which are able to validate a predicting significance for infusion test. The algorithm developed by the authors computes 13 ICP parameter trends on each of the recording, afterward 9 statistical information from each trend is determined. All data are transferred to the datamining software WEKA. According to the exploited feature-selection techniques, the WEKA has revealed that the most significant statistical parameter is the maximum of Single-Wave-Amplitude: setting a 27 mmHg threshold leads to over 90% of correct classification.