M.Sc. Ilkka Kosunen defends his doctoral thesis Exploring the Dynamics of the Biocybernetic Loop in Physiological Computing on Thursday the 22nd of March 2018 at 12 o'clock noon in the University of Helsinki Exactum Building, Room D122 (Gustaf Hällströmin katu 2b, 1st floor). His opponent is Professor Stephen Fairclough (Liverpool John Moores University, United Kingdom) and custos Professor Giulio Jacucci (University of Helsinki). The defence will be held in English.
Exploring the Dynamics of the Biocybernetic Loop in Physiological Computing
Physiological computing is a highly multidisciplinary emerging field in which the spread of results across several application areas and disciplines creates a challenge of combining the lessons learned from various studies. The thesis comprises diverse publications that together create a privileged position for contributing to a common understanding of the roles and uses of physiological computing systems, generalizability of results across application areas, the theoretical grounding of the field (as with the various ways the psychophysiological states of the user can be modeled), and the emerging data analysis approaches from the domain of machine learning.
The core of physiological computing systems has been built around the concept of biocybernetic loop, aimed at providing real-time adaptation to the cognitions, motivations, and emotions of the user. However, the traditional concept of the biocybernetic loop has been both self-regulatory and immediate; that is, the system adapts to the user immediately. The thesis presents an argument that this is too narrow a view of physiological computing, and it explores scenarios wherein the physiological signals are used not only to adapt to the user but to aid system developers in designing better systems, as well as to aid other users of the system.
The thesis includes eight case studies designed to answer three research questions: 1) what are the various dynamics the biocybernetic loop can display, 2) how do the changes in loop dynamics affect the way the user is represented and modeled, and 3) how do the choices of loop dynamics and user representations affect the selection of machine learning methods and approaches? To answer these questions, an analytical model for physiological computing is presented that divides each of the physiological computing systems into five separate layers.
The thesis presents three main findings corresponding to the three research questions: Firstly, the case studies show that physiological computing extends beyond the simple real-time self-regulatory loop. Secondly, the selected user representations seem to correlate with the type of loop dynamics. Finally, the case studies show that the machine learning approaches are implemented at the level of feature generation and are used when the loop diverges from the traditional real-time and self-regulatory dynamics into systems where the adaptation happens in the future.
Availability of the dissertation
An electronic version of the doctoral dissertation is available on the e-thesis site of the University of Helsinki at http://urn.fi/URN:ISBN:978-951-51-4139-2.
Printed copies will be available on request from Ilkka Kosunen: ilkka.kosunen@gmail.com.