Time series analysis of Parkinson's disease, Huntington's disease and Amyotrophic Lateral Sclerosis

Abstract

The aim of this paper is to study the (clinical) time-series data of three diseases with complex dynamics: Parkinson's disease, Huntington's disease and Amyotrophic Lateral Sclerosis. For this purpose, first all of the time series data are embedded in a vector space of suitable dimension and then the correlation dimension of the above mentioned diseases is estimated. The results are also compared with healthy control subjects. At the next step, existence of chaos in these diseases is investigated by means of the so-called 0-1 test. The simulations show that none of the above mentioned diseases are chaotic.