Aim and Scope:Nowadays, computational intelligence methods play an importance role in the health technology research, which brings together complementary interdisciplinary research practice, in the development of innovative medical devices and biotechnological processes for health applications. In general, feasible results may be obtained by applying traditional artificial intelligence methods to a health application. However, health technologies demand to be more robust, more precise and more efficient. Applying traditional artificial intelligence methods may not achieve multiple goals for a particular health application. Recent research indicates that the advanced computational intelligence methods can help to achieve a more satisfactory performance for a particular health application. With the rapidly growing complexities of health design problems and more demanding quality of health applications, the development of advanced computational intelligence methods for health technologies is hence a critical issue. This special issue intends to bring together researchers to report the latest results or progress in advanced computational intelligence methods for health technologies.
Topics coveredThe field of interest of this special issue is the application of recent concepts and methods of computational intelligence in health technologies. The topics cover a broad range of health applications, and we are soliciting contributions on (but not limited to) the following aspects:
- Brain-computer interfaces;
- Intelligent powered wheelchair;
- Protein-ligand conformation;
- Analysis of heart rate dynamics, cardiovascular disease, diabetes mellitus, neurological disorders;
- Non-invasive instrumentations;
- Early detection of cancer;
- Biomedical signal and image processing, monitoring, and control;
- Physiological modeling.
- ECG/EEG/EMG classification.
Advanced computational intelligence methods involved the following technologies but not limited to:
- Artificial immune systems;
- Deep learning;
- Ensemble learning;
- Evolutionary algorithms;
- Evolutionary programming;
- Reinforcement Learning;
- Fuzzy systems;
- Neural networks;
- Rough sets and random sets
- Swarm intelligence;
- Support vector machines;
SubmissionPlease follow the IEEE IJCNN2016 instruction for authors and submit your paper via the IEEE IJCNN2016 online submission system. Please specify that your paper is for the Special Session on Advanced Computational Intelligence Methods for Health Technologies and Applications.
Important DatesPaper Submission Deadline: 15 Jan 2016
Notification of Acceptance: 15 Mar 2016
Final Paper Submission Deadline: 15 Apr 2016
Special session organizers1. Name: Dr Steve S. H. Ling (Lead organizer) Email: Steve.Ling@uts.edu.au
Brief biography: S.H. Ling received the Ph.D. degree from the Department of Electronic and Information Engineering in the Hong Kong Polytechnic University in 2006. Currently, he works in University of Technology, Sydney, Australia as Senior Lecturer. His current research interests include evolution computations, fuzzy logics, neural networks, hybrid systems and biomedical applications. He has authored and coauthored over 140 books, book chapters, journal and conference papers on computational intelligence and its industrial applications. Currently, he serves as Editor-in-Chief for Journal of Intelligent Learning Systems and Applications and Associate Editor for Australian Journal of Electrical and Electronics Engineering. In 2012 and 2014, he had been lead guest editor on International Journal of Bioinformatics Research and Applications and Applied Soft Computing. He is a Senior member of IEEE.
He has edited one research books entitled ‘Computational Intelligence and Its Applications (World Scientific, 2012)”. He has chaired a number of special sessions on conferences, such as IEEE WCCI 2012 ‘Computational Intelligence for Industrial Applications’, IEEE WCCI 2010 ‘Computational Intelligence for Bioinformatics-Computational Intelligence in Biomedical Sciences and DNA Forensics. Since 2013, he has been served as seven international conference technical program committee members.
2. Name: Prof. Xin Xu
Brief biography: Xin Xu received the B.S. degree in electrical engineering from the Department of Automatic Control, National University of Defense Technology (NUDT), Changsha, P. R. China, in 1996 and the Ph.D. degree in control science and engineering from the College of Mechatronics and Automation (CMA), NUDT. He has been a visiting scientist for cooperation research in the Hong Kong Polytechnic University, University of Alberta, University of Guelph, and the University of Strathclyde, respectively. Currently, he is a full Professor with the College of Mechatronics and Automation, NUDT.
His main research areas include: reinforcement learning and approximate dynamic programming, learning control, robotics and intelligent vehicles, machine learning and data mining. He has coauthored four books and published more than 110 papers in international journals and conferences. Currently, he is an associate editor of Information Sciences, Acta Automatica Sinica, Intelligent Automation and Soft Computing. He is the founding Editor-in-Chief of Journal of Intelligent Learning Systems and Applications. He has also been a Guest Editor of International Journal of Adaptive Control and Signal Processing.
Prof. Xu is one of the recipients received the 2nd class National Natural Science Award of China in 2012, the 1st class Natural Science Award from Hunan Province, China, in 2009 and the Fork Ying Tong Youth Teacher Fund of China in 2008. He is a Senior Member of IEEE, a Committee Member of the IEEE Technical Committee on Approximate Dynamic Programming and Reinforcement Learning (ADPRL) and the IEEE Technical Committee on Robot Learning. He has served as a PC member or Session Chair in many international conferences.
3. Name Prof. H.K. Lam
Brief biography: H. K. Lam received the B.Eng. (Hons.) and Ph.D. degrees from the Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong, in 1995 and 2000, respectively. During the period of 2000 and 2005, he worked with the Department of Electronic and Information Engineering at The Hong Kong Polytechnic University as Post-Doctoral Fellow and Research Fellow respectively. He joined as a Lecturer at King’s College London in 2005 and currently a Reader.
His current research interests include intelligent control systems and computational intelligence. He has served as a program committee member and international advisory board member for various international conferences and a reviewer for various books, international journals and international conferences. He is an associate editor for IEEE Transactions on Fuzzy Systems, IET Control Theory and Applications, International Journal of Fuzzy Systems and Neorocomputing; and guest editor for a number of international journals. He is in the editorial board of Journal of Intelligent Learning Systems and Applications, Journal of Applied Mathematics, Mathematical Problems in Engineering, Modelling and Simulation in Engineering, Annual Review of Chaos Theory, Bifurcations and Dynamical Systems and The Open Cybernetics and Systemics Journal. He is an IEEE senior member.
He is the coeditor for two edited volumes: Control of Chaotic Nonlinear Circuits (World Scientific, 2009) and Computational Intelligence and Its Applications (World Scientific, 2012), and the coauthor of the monograph: Stability Analysis of Fuzzy-Model-Based Control Systems (Springer, 2011). His co-authored paper (J.S. Dai, H.K. Lam and S.M. Vahed, “Soil Type Identification for Autonomous Excavation Based on Dissipation Energy,” Proceedings of the Institution of Mechanical Engineers, Part I, Journal of Systems and Control Engineering, vol. 225, no. 1, pp. 35-50, 2011) received SAGE Best Paper Award in 2011.
4. Name : Prof. Hung T. Nguyen
Brief biography: Hung Nguyen is Assistant Deputy Vice-Chancellor and Vice President (Innovation), Director of the Centre for Health Technologies, and Professor of Electrical Engineering at the University of Technology, Sydney (UTS). He received a BE with First Class Honours and University Medal in 1976 and a PhD in 1980 from the University of Newcastle, Australia. His research interests are in biomedical engineering, artificial intelligence, and neuroscience. He has developed several medical devices for diabetes, neurological disorders, and cardiovascular disease. Hung has published more than 250 refereed research articles and 9 full patents, received more than $5.8m of external competitive research funding, and has been involved in the generation of $9.5m of commercialisation income. He was Dean of the Faculty of Engineering and Information Technology at UTS from 2010 to 2014, Founding Director and Executive Director of AIMedics Pty Ltd from 2001 to 2006, and Engineering Manager of Power Electronics Pty Ltd from 1988 to 2000. He was appointed a Member of the Order of Australia (AM) in 2002 and was a Finalist for NSW Australian of the Year Award 2012 as a ‘medical inventor’. He is a Fellow of the Institution of Engineers, Australia; the British Computer Society; and the Australian Computer Society.
5. Name: Dr Kit Yan Chan
Brief biography: Kit Yan Chan received his Ph.D. degree in Computing in 2006 from London South Bank University, United Kingdom. From 2004 to 2013, he worked as a postdoctoral fellow/associate in the Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, and the Department of Electrical Computer Engineering, Curtin University, Australia. During the time, he has developed fuzzy and neuromputing systems for new product development, manufacturing process design, traffic flow control. Currently, he is a Senior Lecturer in the Department of Electrical and Computer Engineering, Curtin University, Australia.
He currently serves as the Secretary of the IFIP Working Group TC 12 on Computational Intelligence. He was the guest editor for the IEEE Transactions in Industrial Informatics special issue on ‘Cyber-Physical Systems for Future Industry’, for the Applied Soft Computing journal issues on ‘Hybrid Intelligent Methods for Health Technologies’ and ‘Hybrid Evolutionary Systems for Manufacturing Processes’, for the Neurocomputing journal issue on ‘Computational Intelligence Techniques for New Product Development’, as well as for the Engineering Applications of Artificial Intelligence journal issue on ‘Artificial Intelligence Techniques in Product Engineering’. He is an associate editor for the Neurocomputing journal, International Journal of Fuzzy Systems, journal of Intelligent Learning Systems and Applications, as well as an editorial board member for the Artificial Intelligence Research journal and the Journal of Engineering Design.
He has edited two research books entitled ‘Computational Intelligence Techniques for New Product Development’ and ‘Experimental Design Techniques in Evolutionary Algorithms’. He has chaired a number of special sessions on conferences, such as FUZZ-IEEE 2011 ‘Industrial Applications of Evolving Fuzzy systems’, IEEE WCCI 2012 ‘Computational Intelligence for Industrial Applications’, IEEE CEC 2014 ‘Hybrid evolutionary computational methods for complex optimization problems’ and IEEE SMC 2015 ‘Fuzzy methods for uncertain data mining’. He has also served on the program committee of a number of conferences, such as INTELLI 12/13, IEEE-CIMA12, CaPSICuMS12, ICNSC13, IEEE CEC 2014, IEEE NC 2014, IJCNN 2015, ICSI 2015, IFIP ICAITP 2015. He has published 2 books, 52 journal papers, 41 conference papers and 2 book chapters. His research interests are mainly in applying fuzzy systems and neuro systems for new product development, manufacturing process design, traffic flow control and perceptual signal quality metric. His detailed research contribution can be referred to his homepage - http://ece.curtin.edu.au/people/index.cfm/Kit.Chan
6. Name : Dr. Rifai Chai
Brief biography: Rifai Chai received his PhD in Engineering from the University of Technology, Sydney (UTS) in 2014. Currently, he is an Associate Lecturer in the Centre for Health Technologies, Faculty of Engineering and Information Technology at the UTS. His current research interests on brain-computer interfaces, biomedical instrumentation, biomedical signal processing computational intelligence using neural networks, fuzzy logic, and evolutionary computation and embedded system design. Currently he serves as Associate Editor for Journal of Intelligent Learning Systems and Applications; Chair of the Biomedical track of the 2015 International Conference on Advanced Technologies for Communication (ATC). He is an IEEE member.