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The role of the tutorials is to provide a platform for a more intensive scientific exchange amongst researchers interested in a particular topic and as a meeting point for the community. Tutorials complement the depth-oriented technical sessions by providing participants with broad overviews of emerging fields. A tutorial can be scheduled for 1.5 or 3 hours.


Adding Physiological Intelligence to Games and Interactive Applications  (BIOSTEC)
Lecturer(s): John Muñoz, Teresa Paulino and Stephen Fairclough

Decision Support Systems in the Era of Evidence-Based and Precision Medicine  (BIOSTEC)
Lecturer(s): Muhammad Afzal

Adding Physiological Intelligence to Games and Interactive Applications


John Muñoz
Universidade da Madeira
Brief Bio
John Muñoz is a PhD student and researcher in the NeuorehabLab of M-iti. His research has been focused on the development of software tools for processing physiological signals related with Electrocardiography (ECG), Electrodermal Activity (EDA) and Electromyography (EMG) in order to provide relevant features of interest about the human physiological, physical and emotional state. Currently, he is an assistant researcher in the AHA project which aims to promote non-sedentary behaviors through the use of novel serious games for health approaches.
Teresa Paulino
Madeira Interactive Technologies Institute
Brief Bio
Teresa Paulino is a technical assistant at Madeira Interactive Technologies Institute under the Augmented Human Assistance project. She has an undergraduate degree in Interactive Media Design from University of Madeira and is currently a Master student in Informatics Engineering. Prior to this project she worked in the Rehabnet project where she developed tools for rehabilitation of stroke patients. Teresa loves team work and she’s always willing to assist her colleagues with their projects whether with programming or with design tasks. She has a particular interest in software and interactive technologies that are able to promote the life quality of their users.
Stephen Fairclough
Liverpool John Moores University
United Kingdom
Brief Bio
Stephen Fairclough is a Professor of Psychophysiology at Liverpool John Moores University. He received his PhD from Loughborough University where he was part of a human factors group working on the development of in-vehicle technology. His work focused on the monitoring of driver impairment due to sleepiness and the development of systems designed to detect impairment. This work involved collaboration with a number of car companies (Ford Europe, Renault) and involved the development of psychophysiological and behavioural markers of driver impairment. Since joining LJMU, he has focused on physiological computing systems where physiological data is used as control input for technological systems. His work has been presented at a range of conferences, from the Annual Meeting of the Society for Psychophysiological Research to IEEE Congress on Evolutionary Computation. He has published research in journals spanning psychology (International Journal of Psychophysiology, Psychophysiology, Journal of Psychosomatic Medicine) and computer science (Interacting with Computers, ACM Transactions on Autonomous and Adaptive Systems, International Journal of Autonomous and Adaptive Communication Systems).

Physiological signals are conventionally used on game user research not only to passively record user’s body responses but also as a way to create real-time adaptations that can enhance the overall game experience. This adaptation strategy uses a biofeedback mechanism called Biocybernetic Loop, which utilizes personal physiological data to infer users’ states (e.g. stress, excitement) and react accordingly. Although this sophisticated technology has shown very promising results in assisting players to either improve the game challenge or avoid frustrations, there are still several limitations regarding the integration of physiological sensors, the signal processing, and psychophysiological inference as well as the communication between the system and the games. To address such issues, the Biocybernetic Loop Engine (BL Engine) proposes an integrated physiological computing architecture that serves as a unifying tool in the collection, analysis, translation pipeline of adding physiological intelligence to games. In this tutorial, we will expose successful use cases of physiologically adaptive games that have been developed and carefully evaluated. We further proposed a hands-on activity in where assistants will be guided through the cumbersome process of adding biocybernetic adaptation to customizable games. The tutorial ends with a provocative discussion about the most promising scenarios in where the use of physiologically augmented games can enhance the quality of gameplay and players’ wellbeing.

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Decision Support Systems in the Era of Evidence-Based and Precision Medicine


Muhammad Afzal
Sejong University
Korea, Republic of
Brief Bio
Muhammad Afzal is now working as Assistant Professor at Sejong University, Seoul, South Korea. He received his PhD from Kyung Hee University, South Korea, in 2017 with Excellent Thesis Award and M.S. degree from the School of Electrical Engineering and Computer Science, National University of Sciences and Technology (NUST), Pakistan in 2009. Being country first HL7 certified specialist, he was nominated for country-level Proctor to HL7 certification training and exams in Pakistan. Additionally, he served as a lead instructor to teach tutorials on health standards in Pakistan and Middle East. Professionally, he has more than 10 years educational, research, and development experience in health informatics application and services. He participated in more than 8 medium-to-large scale academia-industry collaborative projects in a leading role. As a researcher, he contributed to author more than 60 publications in different reputed journals/conferences in addition to 4 local and international patents. He presented his work in different countries including USA, Europe, Japan, South Korea, and Singapore. His current research includes Evidence-adaptive Decision Support Systems, Precision Medicine, Applications of Machine Learning, and Text Mining.

Decision support systems and services have long been utilized to assist clinicians and physicians in making affective decisions while reducing the chance of medical errors and increasing healthcare quality and efficiency. Many different kinds of decision support systems (DSSs) and approaches are in action for their potential to improve the overall healthcare decision process. In the existence of Evidence-based medicine and with the advent of precision medicine, more informed healthcare is envisioned to be practiced. The contemporary DSSs need to be channelized to incorporate the very need of precision medicine components such as genomic and environmental data in addition to patient demographics and clinical data.
In this tutorial session we will elaborate to talk about DSSs, advancements in DSSs, evidence-based medicine, evidence-adaptive DSSs, precision medicine, and role of DSSs in precision medicine. A set of technologies will be discussed while speaking the above-mentioned topics such as; model-driven (e.g. rule-based, case-based), data-driven (e.g. machine learning, deep learning), natural language preprocessing, information retrieval, information extraction, and others.
This tutorial will provide a fair learning opportunity to the audience in terms of understanding the changing role of popular techniques in the domains of health and wellness. They will be able to connect the dots of different co-existed technologies while they are researching, developing, or implementing enterprise level systems and services.

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