Plenary Speaker 

Prof. Dr. Shaikh Fattah, Education Chair, IEEE HAC

Title of Keynote Talk:

Challenges and Opportunities of Bio-signal Based Humanitarian Technologies in Sustainable Development Space

Abstract of Keynote Talk:

Dependence on cellphone applications and fascination for wearable devices have created a large demand for research in automatic disease detection and smart health control systems. Instead of large scale medical instrumentations, this type of low cost handheld bio-signal processing systems are getting popularity because of user’s self operating options and instant service facilities. One greatest advantage of such innovations is their accessibility to under privileged population, irrespective of their location, gender, financial capability, and level of education. Good health and well-being for people is one of the UN sustainable development goals (SDGs), which dictate the success of several other goals. There are lot of opportunities for inventing smart bio-signal processing techniques that can help in achieving good health for a larger community. However, the main challenge here is to offer satisfactory performance with low cost implementation in small sized devices. Some recent examples of such bio-signal based humanitarian applications in sustainable development space will be presented along with initiatives and funding opportunities from IEEE humanitarian activity committee (HAC).

For further details and interactive training on humanitarian project design and funding details of IEEE HAC, IEEE SIGHT and other philanthropic programs, the conference organizer’s arranged a collocated IEEE HAC Education Workshop on 26th July during 9 am- 12 noon at Universiti Malaysia Sarawak. Please feel free to join the interactive training session and learn how to develop a quality humanitarian project. There will be also an IEEE HAC Track inside the conference on 24 th July 2:30 pm – 4:30 pm (Venue: Hilton Kuching (conference venue)).

 Title of Panel (or HAC Track) Talk:

Humanitarian Project Design and Implementation: Key Factors of Humanitarian Technologies and Sustainable Development

Keynote Speaker : Assoc. Prof Dr Andrew Taberner


Andrew Taberner (MSc(Tech), PhD 1999) is a physicist and bioengineer, and Associate Professor with the Auckland Bioengineering Institute at University of Auckland, New Zealand. From 2002-2008 he was a Post-Doctoral Associate, Research Scientist, and co-manager of the Bioinstrumentation Laboratory at Massachusetts Institute of Technology. His teaching is centered on the principles and methods of bioinstrumentation and measurement, and forms part of his University’s BE(Hons) in Biomedical Engineering degree program. The quality of his teaching has been recognized by five “Students’ Choice Top-teacher” awards, and a “Sustained Excellence in Teaching” award. He leads a team of researchers in his Bioinstrumentation Laboratory in novel instrumentation design, construction and development. He has supervised 25 PhD, 15 ME and 50+ honours students.

His research interests include the development of scientific and medical instruments for measuring tissue structure and function, and for needle-free drug delivery. He has developed instruments for studying the mechanical, energetic, optical and geometric properties of living working heart muscle, in health and disease, at whole-heart, single muscle-fibre and muscle-cell levels. Other measurement tools he has developed include programmable multi-axis soft-tissue robots for measuring the mechanical properties of skin, pericardium, and the pelvic floor. Results from his instruments are often integrated and interpreted with the aid of multi-scale computational models. He has also invented and developed a new class of devices for needle-free injection and extraction of fluids through skin and other biological tissues. These devices are being applied to monitoring and managing change and disease in a range of human, animal and agricultural applications.

Professor Taberner is the author of more than 120 refereed scientific articles in journals and published conference proceedings, 75 conference abstracts, and inventor of 20 issued US, European and other patents. He received the “Innovation Excellence in Research” award at the 2014 New Zealand Innovators awards. He is a co-founder of Boston-based medical device company Portal Instruments, which has an exclusive world-wide license to commercialize his jet-injection intellectual property portfolio. He is the secretary and vice-chair of the New Zealand Chapter of the IEEE Instrumentation and Measurement Society, an editor for IEEE Pulse Magazine, and a member of and reviewer for the IEEE Engineering in Medicine and Biology Society.

Abstract Title: Measurement and Instrumentation at the Tissue:Machine interface 

Keynote Speaker : Prof Dr. David Perera

Director, Institute of Health & Community Medicine, Universiti Malaysia Sarawak
Current research project is on enteroviruses, dengue and respiratory tract infection in children.
Areas of interest include molecular diagnostic, viral-host interaction and molecular epidemiology.

Abstract Title: Molecular Epidemiology of Human Enterovirus 71 in Sarawak over the last two decades.

Hand, foot and mouth disease (HFMD) is endemic to Sarawak with outbreaks occurring annually in the state. The disease is primarily caused by Species A enteroviruses which includes enterovirus 71 (EV-A71) and other coxsackievirus A (CVA) serotypes. While the disease is generally presented as a mild childhood disease, it can also be associated with central nervous system involvement particularly when EV-A71 is present. In 1997, Sarawak recorded a large outbreak of HFMD associated with EV-A71 which saw a number of paediatric fatalities. Subsequently, over the next 2 decades, EV-A71-associated HFMD outbreaks have occurred in Sarawak approximately every three years. Major genotype shifts of the EV-A71 strain was recorded in each of the subsequent outbreaks in 2000 and 2003. However from 2003 onwards, a single EV-A71 genotype was recorded in outbreaks in 2006, 2008/9 and 2011/12

Keynote Speaker : Prof Dr Sri Krishnan

  • Associate Dean (Research and External Partnerships) Faculty of Engineering and Architectural Science, Ryerson University, Toronto, Canada
  • Canada Research Chair (2007-2017) in Biomedical Signal Analysis
  • He has published 310 papers in refereed journals and conferences, and six of his papers have won best paper awards.
  • He is a Fellow of the Canadian Academy of Engineering.
  • He is a recipient of many awards including the 2016 Outstanding Canadian Biomedical Engineer Award, 2013 Achievement in Innovation Award from Innovate Calgary, 2011 Sarwan Sahota Distinguished Scholar Award, 2007 Young Engineer Achievement Award from Engineers Canada.
  • Research interests include time-frequency signal analysis, compressive sensing, audio signal processing, and wearables/IoT.

Abstract Title:  Biomedical Signal Feature Extraction – Advances in Methods and Applicatons

With the advancements in sensor technologies, data analytics, and machine learning, the role of meaningful feature extraction is a key area of investigation. Most of the real world signals, and especially the signals from wearable sensors possess long-term, non-stationary and non-linear characteristics. Signal representation, information processing and feature extraction from these signals is a challenging task. This talk will focus on five generations of signal processing algorithms developed for analysis and interpretation of biomedical signals. The talk will touch upon event analysis, spectral analysis, time-frequency domain analysis and multi-modal biomedical signal processing. Recent advances in using sparse signal representation and compressive sensing of long-term signals for Internet of Things (IoT) applications will also be covered. The application of the extraction and classification of features from cardiac signals, bio-acoustical signals, and sleep signals will be discussed in detail.

Md. Atiqur Rahman Ahad, PhD, SMIEEE

Osaka University, Japan; University of Dhaka, Bangladesh


Activity Recognition & Future Challenges


Vision-based human activity recognition and analysis are very important research areas in computer vision and Human Robot/Machine/Computer Interaction. Over a decade, a good number of methodologies have been proposed in the literature to decipher various challenges regarding action and activity. However, due to various complex dimensions, a number of challenges still remain unexplored. In this keynote speech, various important aspects of human activity recognition and analysis will be covered. The talk will emphasis on interesting and challenging research aspects to explore in future.


  1. Atiqur Rahman Ahad, “Motion History Images for Action Recognition and Understanding”, available in Springer, ISBN: 978-1-4471-4730-5, 2012.
  2. Atiqur Rahman Ahad, “Computer Vision and Action Recognition: A Guide for Image Processing and Computer Vision Community for Action Understanding”, available in Springer, ISBN: 978-94-91216-20-6, 2011.

Short Biography: Md. Atiqur Rahman Ahad, Senior Member, IEEE, is a Professor at University of Dhaka (DU), and a Specially Appointed Associate Professor at Osaka University. He works on computer vision, imaging, IoT, etc. He did B.Sc.(honors) [1st class 1st position] & Masters [1st class 2nd position] from the Dept. of Applied Physics & Electronics, DU; Masters from the School of Computer Science & Engineering, University of New South Wales; and PhD from the Faculty of Engineering, Kyushu Institute of Technology [KIT]. He was awarded JSPS Postdoctoral Fellowship and several prestigious awards/scholarships. He was a Visiting Researcher at KIT. He published two books as single author (available in Springer). He has published about 100 journals and conference papers. He has received 10+ international awards in various conference/journal/society. Ahad was invited as keynote/invited speakers about 45 times in different conferences/universities. He has established several international MOU/collaborations (e.g., Clemson University, University of Hyogo, RCCIIT, Fukuoka Women University, Kyushu University, etc.). He has been involved with some academic & editorial activities: e.g., Editorial Board Member, Scientific Reports, Nature; Associate Editor, Frontiers in ICT; Editorial Board Member, Encyclopedia of Computer Graphics and Games, Springer; Assoc. Technical Editor (former), IEEE ComSoc Magazine; Editor-in-Chief: Int. J. of Computer Vision & Signal Processing, Int. J. of Electronics & Informatics, Int. J. of Environment; General Chair, 2018 7th Int. Conf. on Informatics, Electronics & Vision, Japan; Publication Chair, 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC2018); General Chair, 2018 2nd Int. Conf. on Imaging, Vision & Pattern Recognition, Bangladesh; Vice Publication Co-chair and Vice Award Chair, Joint 17th World Congress of International Fuzzy Systems Association (IFSA) and 9th Int. Conf. on Soft Computing and Intelligent Systems; General Chair, 7th Intl. Symposium in Computational Medical and Health Technology; and several other international conferences. He served Guest Editor in Pattern Recognition Letters, Elsevier; Journal of Multimedia User Interface, Springer; Journal of Healthcare Engineering, Hindawi; International Journal of Innovative Computing, Information and Control. Ahad is a Member of OSA, ACM, IEEE Computer Society, IAPR, IEEE RAS, IEEE SMC, etc. He is the founder Secretary of IEEE Computer Society Bangladesh Chapter, and Bangladesh Association of Pattern Recognition. He volunteers some societies in Bangladesh and Japan. More:

Invited Speaker:

Assoc. Prof. Ir. Dr Rubita Sudirman



She received her Bachelor (Hons) and Masters degree from the University of Tulsa and her Ph.D. in Electrical Engineering from Universiti Teknologi Malaysia.

Currently she is an associate professor and certified professional engineer serving at the Faculty of Electrical Engineering, UTM. Her current research interests include Applications of Soft Computing in Biomedical Engineering particularly in Speech Processing, EEG & EOG signal analysis, medical electronics, and rehabilitation engineering.

In addition to teaching and research activities, she acts as an advisor for undergraduate, Masters and PhD research studies, as well as the academic lab coordinator to Electrophysiology Laboratory. She is actively involved in research activities, secured more than 30 grants (14 as Project leader and 17 as co-researcher) with a total value of more than RM2.0 Million. From the research, she has been granted with 4 intellectual property rights, 2 copyright software, wrote more than 20 book chapters, research monographs, and a number of indexed journals and conference proceeding papers. She also published 2 books on electronics, one of them was awarded on its popularity and a chapter in IGI Global Handbook of Solar Radiation which is indexed in Scopus and Thomson Reuters.

Abstract: Profile Indicator for Autistic Children using EEG Biosignal Potential of Sensory Tasks

Electroencephalography (EEG) is a measure of voltages caused due to neural activities within the brain. EEG is a recommended tool for diagnosing neurological problems because it is non-invasive and can be recorded over a longer time-period. The children with Autism Spectrum Disorder (ASD) have difficulty in expressing their emotions due to their inability of proper information processing in brain. Therefore, this research aims to build a sensory profile with the help of EEG biosignal potential. The EEG signals acquired in this research identify different emotional states such as positive-thinking or super-learning and light-relaxation and are within the frequency range of 8 – 12 Hertz. 64 children participated in this research among which 34 were children with ASD and 30 were normal children. The EEG data was recoded while all the children were provided with vestibular, visual, sound, taste and vestibular sensory stimulations. The raw EEG data was filtered with the help of independent component analysis (ICA) using wavelet transform and EEGLAB software. Later, for building the sensory profile, entropy approximation, means and standard deviations were extracted from the filtered EEG signals. Along with that, the filtered EEG data was also fed to a neural networks (NN) algorithm which was implemented in MATLAB. Results from the acquired EEG signals depicted that during the sensory stimulation phase, the responses of all autistic children were in an unstable state. These findings will equip and aid their learning strategy in the future.