The development of statistical methods for the diagnosis of neurological diseases based on multiparameter analysis of brain activity

Abstract

The application of data science for the analysis of biomedical data presented as time series allows using new methods of analysis of living systems. Therefore, using these methods it could be possible to discover new diagnostic criteria for neurological diseases. In this paper, in the framework of Memory Functions Formalism, one of the approaches of statistical physics, we analyze recordings of signals of the human brain cortex in the sleep state of 19 patients with nocturnal frontal lobe epilepsy and 8 healthy subjects. We observe alterations of dynamic parameter behavior at the pathology and in healthy subjects. Furthermore, we reveal significant alterations in brain rhythms manifestations at statistical memory functions power spectra of patients with epilepsy and healthy subject. As a result, we show that the application of the statistical analysis of electroencephalogram recordings, after appropriate verification, can be helpful in the search of diagnostic criteria of nocturnal frontal lobe epilepsy.