Advances in Physiological Computing

Advances in Physiological Computing, co-edited by Stephen Fairclough and Kiel Gilleade, is a collection of the latest research in Physiological Computing. The book will be published by Springer in Spring 2014.

In the domain of physiological computing, human physiology is directly monitored and used as input to a technological system. Signals from the brain and body can be used to infer a user’s intentions and psychological state which enables a physiological computing system to respond and adapt in an appropriate fashion.  A computer game could modify its level of difficulty according to the player’s motivation or a word processor could disable incoming e-mail notifications when the user is concentrating.

Physiological computing is an exciting area of research which provides a speculative vision of how we may interact with technology in the future. The field is inherently interdisciplinary and encapsulates a significant breadth of knowledge from neuroscience to engineering. Advances in Physiological Computing provides a broad overview across this emerging area of research and emphasizes the common ground between the different disciplines in the field.

Advances in Physiological Computing is available for purchase from Springer.

Book Citation 
Fairclough SH, Gilleade K (eds) Advances in Physiological Computing, Springer-Verlag London (in press) ISBN 978-1-4471-6391-6

 Table of Contents

  • Foreword by Dr Alan Pope (NASA Langley Research Center, Hampton, USA)
  • Introduction to the Edited Collection
  • Chapter 1 – Meaningful Interaction with Physiological Computing
  • Chapter 2 – Engineering Issues in Physiological Computing
  • Chapter 3 – Eye Tracking and Eye-Based Human-Computer Interaction
  • Chapter 4 – Towards BCI-based Implicit Control in Human-Computer Interaction
  • Chapter 5 – Biocybernetic Adaptation as Biofeedback Training Method
  • Chapter 6 – Using fNIRS to Measure Mental Workload in the Real World
  • Chapter 7 – Psychophysiological Feedback for Adaptive Human-Robot Interaction
  • Chapter 8 – The Drive to Explore: Physiological Computing in a Cultural Heritage Context
  • Chapter 9 – The Vitality Bracelet: Bringing Balance to your Life with Psychophysiological Measurements
  • Chapter 10 – Capturing Human Digital Memories for Assisting Memory Recall


Chapter 1 – Meaningful Interaction with Physiological Computing
By Stephen Fairclough and Kiel Gilleade
School of Natural Sciences and Psychology, Liverpool John Moores University, United Kingdom

Physiological data can be used as input to a computerised system. There are many types of interaction that can be facilitated by this form of input ranging from intentional control to implicit software adaptation. This type of interaction directly with the brain and body represent a new paradigm in human-computer interaction and this chapter will discuss how meaning is associated with data interpretation and changes at the interface. The chapter will categorise the different systems physiological input allows and discuss how interaction with the system can be made meaningful for the user.

Chapter 2 – Engineering Issues in Physiological Computing
By Domen Novak
Sensory-Motor Systems Lab, ETH Zurich, Switzerland

Prototypes of physiological computing systems have appeared in countless fields, but few have made the leap from research to widespread use. This is due to several practical problems that can be roughly divided into four major categories: hardware, signal processing, psychophysiological inference, and feedback loop design. This chapter explores these issues from an engineering point of view, discussing major weaknesses and suggesting directions for potential solutions. Specifically, some of the topics covered are: unobtrusiveness and robustness of the hardware, real-time signal processing capability, different approaches to design and validation of a psychophysiological classifier, and the desired complexity of the feedback rules. The chapter also briefly discusses the challenge of finding an appropriate practical application for physiological computing, then ends with a summary of recommendations for future research.

Chapter 3 – Eye Tracking and Eye-Based Human-Computer Interaction
By Päivi Majaranta1 and Andreas Bulling2
University of Tampere, Finland
Max Planck Institute for Informatics, Saarbrücken, Germany

Eye tracking has a long history in medical and psychological research as a tool for recording and studying human visual behavior. Real-time gaze-based text entry can also be a powerful means of communication and control for people with physical disabilities. Following recent technological advances and the advent of affordable eye trackers, there is a growing interest in pervasive attention-aware systems and interfaces that have the potential to revolutionize mainstream human-technology interaction. In this chapter, we provide an introduction to the state-of-the art in eye tracking technology and gaze estimation. We discuss challenges involved in using a perceptual organ, the eye, as an input modality. Examples of real life applications are reviewed, together with design solutions derived from research results. We also discuss how to match the user requirements and key features of different eye tracking systems to find the best system for each task and application.

Chapter 4 – Towards BCI-based Implicit Control in Human-Computer Interaction
By Thorsten O. Zander, Jonas Brönstrup, Romy Lorenz, Laurens R. Krol
Team PhyPA, Berlin Institute of Technology, Germany

In this chapter a specific aspect of Physiological Computing, that of implicit Human-Computer Interaction, is defined and discussed. Implicit Interaction aims at controlling a computer system by behavioural or psychophysiological aspects of user state, independently of any intentionally communicated command. This introduces a new type of Human-Computer Interaction, which in contrast to most forms of interaction implemented nowadays, does not require the user to explicitly communicate with the machine. Users can focus on understanding the current state of the system and developing strategies for optimally reaching the goal of the given interaction. For example, the system can assess the user state by means of passive Brain-Computer Interfaces, which the user needs not even be aware of. Based on this information and the given context the system can adapt automatically to the current strategies of the user. In a first study, a proof of principle is given, by implementing an Implicit Interaction to guide simple cursor movements in a 2D grid to a target. The results of this study clearly indicate the high potential of Implicit Interaction and introduce a new bandwidth of applications for passive Brain-Computer Interfaces.

Chapter 5 – Biocybernetic Adaptation as Biofeedback Training Method
By Alan Pope1, Chad Stephens1, Kiel Gilleade2
1 NASA Langley Research Center, Hampton, United States of America
2 School of Natural Sciences and Psychology, Liverpool John Moores University, United Kingdom

A method developed for adapting an automated flight control system to user state has been applied to the process of biofeedback training. This repurposing enables alternative mechanisms for delivering physiological information feedback to the trainee via a method referred to as physiological modulation. These mechanisms employ reinforcement principles to motivate adherence to the biofeedback training regime, to foster interactions among users and to enhance the experience of immersion in video game entertainment. The approach has implications for a broader dissemination of biofeedback training. This chapter will introduce the traditional biofeedback training method and its clinical applications, followed by a discussion of how biocybernetic adaptation can be applied to the biofeedback training method. This will be followed by a description of different methods of realising this self-regulation technology and where the technology may go in the future.

Chapter 6 – Using fNIRS to Measure Mental Workload in the Real World
By Evan M. Peck, Daniel Afergan, Beste F. Yuksel, Francine Lalooses, Robert J.K.Jacob
Tufts University, United States of America

In the past decade, functional near-infrared spectroscopy (fNIRS) has seen increasing use as a non-invasive brain sensing technology. Using optical signals to approximate blood-oxygenation levels in localized regions of the brain, the appeal of the fNIRS signal is that it is relatively robust to movement artifacts and comparable to fMRI measures. We provide an overview of research that builds towards the use of fNIRS to monitor user workload in real world environments, and eventually to act as input to biocybernetic systems. While there are still challenges for the use of fNIRS in real world environments, its unique characteristics make it an appealing alternative for monitoring the cognitive processes of a user.

Chapter 7 – Psychophysiological Feedback for Adaptive Human-Robot Interaction
By Esubalew Bekele and Nilanjan Sarkar
Vanderbilt University, United States of America

Recent advances in robotics and sensing have given rise to a diverse set of robots and their applications. In recent years robots have increasingly applied in the service industry, search and rescue operations and therapeutic applications. The introduction of robots to interact with humans resulted in a dedicated field called human-robot interaction (HRI). Social HRI is of particular importance as it is the main focus of this chapter. This chapter presents an affect-inspired approach for social HRI. Physiological processing together with machine learning was employed to model affective states for an adaptive social HRI and its application in social interaction in the context of autism therapy was investigated.

Chapter 8 – The Drive to Explore: Physiological Computing in a Cultural Heritage Context
By Alexander J. Karran and Ute Kreplin
School of Nature Science and Psychology, Liverpool John Moores University, United Kingdom

Contemporary heritage institutions model installations and artefacts around a passive receivership where content is consumed but not influenced by visitors. Increasingly, heritage institutions are incorporating ubiquitous technologies to provide visitors with experiences that not only transfer knowledge but also entertain. This poses the challenge of how to incorporate technologies into exhibits to make them more approachable and memorable, whilst preserving cultural salience. We present work towards an adaptive interface which responds to a museum visitor’s level of interest, in order to deliver a personalised experience through adaptive curation within a cultural heritage installation. The interface is realised through the use of psychophysiological measures, physiological computing and a machine learning algorithm. We present studies which serve to illustrate how entertainment, education, aesthetic experience and immersion, identified as four factors of visitor experience, can be operationalised through a psychological construct of “interest”. Two studies are reported which take a subject-dependent experimental approach to record and classify psychophysiological signals using mobile physiological sensors and a machine learning algorithm. The results show that it is possible to reliably infer a state of interest from cultural heritage material, informing future work for the development of a real-time physiological computing system for use within an adaptive cultural heritage experience. We propose a framework for a potential adaptive system for cultural heritage based upon story telling principles and an operationalised model of the “knowledge emotion” interest.

Chapter 9 – The Vitality Bracelet: Bringing Balance to your Life with Psychophysiological Measurements
By Joyce Westerink, William van Beek, Elke Daemen, Joris Janssen, Gert-Jan de Vries, Martin Ouwerkerk
Philips Research Europe, Eindhoven, the Netherlands

We present the concept of the Vitality Bracelet, a wrist-worn device that helps users in bringing more balance in their daily life, especially a balance between stressful and relaxing situations. On the one hand, the Vitality Bracelet comprises the measurement of your skin conductance, reflecting the current level of arousal of your autonomic nervous system. These skin conductance measurements are analyzed in real-time to give an indication of upcoming tension, but they could also be recorded and visualized to present an overview of the daily or weekly tension patterns. On the other hand, the Vitality Bracelet offers paced breathing exercises, supporting instant relaxation as well as general health and vitality on the long run. This chapter describes the design, development and a first evaluation of the Vitality Bracelet concept.

Chapter 10 – Capturing Human Digital Memories for Assisting Memory Recall
By Chelsea Dobbins, Madjid Merabti, Paul Fergus, and David Llewellyn-Jones
School of Computing & Mathematical Sciences, Liverpool John Moores University, UK

As the life expectancy of adults is increasing, so is the occurrence of illness, disability and the demand on hospitals. The probability of becoming cognitively impaired increases with age, with one side effect of increasing life expectancy being the emerging number of dementia patients. In order to enable people to live more independently the use of digital technologies, as an artificial memory aid, is gaining momentum. The area of Human Digital Memories (HDMs) provides such an outlet where users can interact with their data, with the use of visual lifelogs, which can help sufferers relive life experiences. Computing devices are, nowadays, capable of storing a lifetime’s worth of data and capturing our every move, interactions and physiological signals. As a result of living in such a data-rich society, a greater number of data sources are available, which can be incorporated into building more vivid HDMs. This chapter explores the area of human digital memories. More specifically, focusing on wearable systems and physiological devices, the methods that are used to capture human digital memory data are presented. Once it has been established how data can be collected, a more in-depth look at how digital memories are created is also explored. The chapter is then concluded with a summary of the key challenges of the area.