Time Series Prediction for Biomedical Measurements using Fuzzy Logic

Abstract- In this paper is proposed an algorithm of prediction fuzzy for chaotic time series. This approach has been select because, in presence of specific pathologies, biomedical data may be represented as a chaotic time series [1]. In particular, we are interested in monitoring the intracranial pressure (IP) of some patients in a state of coma who were suffering from intracranial hypertension syndrome. In these particular cases, prediction is necessary (from a diagnostic point of view) if you want to operate at the right moment on IP abnormal conditions. The proposed approach is based on a prediction multi-factor algorithm which doesn’t need the knowledge of the mathematical working model of the biologic phenomenon, translating the real time series into a fuzzy time series. I