Complexity Analysis of Physiological Signals Based on Non-Invasive Techniques

Speaker: Maia Angelova

Affiliation: Northumbria University, Newcastle upon Tyne, UK

Time: Thursday 18/12/2014 from 11:00 to 12:00

Venue: Access Grid UWS. Presented from Parramatta (EB.1.32), accessible from Campbelltown (26.1.50) and Penrith (Y239).

Abstract:

This work focuses on methods for investigation of the dynamics of physiological time series based on complexity analysis. It is part of a wider programme to determine non-invasive markers for healthy ageing. Two case studies will be considered: the case study of sleep and alternations with insomnia, and the case study of effect of ageing on mobility.

For the first time, fractal analysis techniques are implemented to study the correlations present in sleep actigraphy for individuals suffering from acute insomnia with comparisons made against healthy subjects. Analysis was carried out for 21 healthy individuals with no diagnosed sleep disorders and 26 subjects diagnosed with acute insomnia during night-time hours. Detrended fluctuation analysis was applied in order to look for 1=$f$-fluctuations and establish their meaning. The aim was to investigate if complexity analysis can differentiate between people who sleep normally and people who suffer from acute insomnia. The hypothesis was that the complexity will be higher in subjects who suffer from acute insomnia due to increased night time arousals. The complexity results for nearly all of the subjects fell within a 1=$f$-range, indicating the presence of underlying control mechanisms. The subjects with acute insomnia displayed significantly higher levels of complexity, possibly a result of too much activity in the underlying regulatory systems. Moreover, we found a linear relation between complexity and variability, both of which increased with the onset of insomnia. Fractal techniques have been applied to actigraphy of sleep before with the hypothesis of high correlations being a marker of sleep-related health issues. This study showed contributed to the investigations of complexity approach to physiological signals. It is very promising and could prove to be a useful non-invasive identifier for people who suffer from sleep disorders such as insomnia.

Further examples will be demonstrated, showing how complexity analysis is used to investigate healthy ageing, and a number of open problems will be discussed.

Biography:

Professor Angelova joined Northumbria University in 1997 as a Senior Lecturer, being promoted in 2002 to Reader and in 2004 to become Professor of Mathematical Physics and Head of Mathematical Modelling Lab research group.

Maia had worked previously at Oxford University for 7 years as a College Lecturer in Physics at Somerville and Worcester Colleges; Assistant Professor at Sofia University for 2 years; and Research Fellow at the University of Kent for 2 years. She gained a first class degree BSc Physics, followed by MSc in Solid State Physics, and a PhD in Theoretical and Mathematical Physics from Sofia University. Maia had a sabbatical in 2012 at the University of Montreal, University of Yale and the National University of Mexico.

Maia is a Fellow of the Institute of Physics and a Member of the London Mathematical Society and IEEE. She chaired the Organising Committees of the XXVIII International Colloquium on Group-Theoretical Methods in Physics in 2010 (GROUP28) and Mathematics of Human Biology - LMS regional meeting and workshop in 2012.

Maia was the Vice Chair of the Northern Branch of the Institute of Physics from 2003 to 2010. She is a member of the Programme Committees of IEEE Intelligent Systems 2012, Systems Biology and Bioengineering (WCE) and a member of the Editorial Board of Bioinformatics and Biology Insights. Maia is a registered expert and reviewer for the Marie Curie Programmes European Frameworks 5, 6 and 7.