Characterization and analysis of physiological time series through a complex network approach

• Grant number: 15/22293-5
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: January 01, 2016
• End date: December 31, 2017
• Field of knowledge: Engineering - Biomedical Engineering
• Principal Investigator: Andriana Susana Lopes de Oliveira Campanharo
• Grantee: Gustavo Henrique Tomanik
• Host Institution: Instituto de Biociências (IBB). Universidade Estadual Paulista (UNESP). Campus de Botucatu. Botucatu , SP, Brazil
• Associated scholarship(s): 17/09216-7 - Predicting epileptic seizures in EEG recordings with the use of complex networks, BE.EP.IC

Abstract

Nowadays, there are a large number of time series analysis techniques that allow researchers to summarize the characteristics of a time series into compact metrics, which can then be used to understand its dynamics or predict how the system will evolve with time. Recently, Campanharo et al. proposed a time series technique based on the complex network theory. More specifically, it is a map from a time series to a complex network which allows the use of several network metrics to characterize the dynamics of a time series. In this project, we propose an investigation of the map proposed by Campanharo and it will be used to distinguish different dynamic regimes of EEG time series from healthy and unhealthy subjects and to forecast seizures episodes.