NBEC ConferenceNBEC ConferenceAdaptation Towards Green and Emerging Healthcare Technology
Universiti Teknikal Malaysia Melaka
09 : 20 AM
09 : 30 AM – 10 : 30 AM
10 : 30 AM – 11 : 00 AM
11 : 00 AM – 12 : 00 PM
12 : 00 PM
Arrived at UTEM
Tutorial / Workshop Session
1) Introduction to Biosignal Processing and Classification using AI/Deep Learning
Speaker: Dr. Tarmizi Izzuddin & Dr. Norafizah Abas
Venue: Bilik Seminar Staff, Block A, Level 2, FKE UTeM
2) Machine Learning in Healthcare
Speaker: Prof. Dr. Norliza Mohd Noor
Venue: Bilik Seminar Pelajar, Block A, Level 3, FKE UTeM
Morning Break
Laboratory Visit
1) Advance Digital Signal Processing Research Lab, Ground Floor, Block F, FKE
2) Motion Control Research Lab, Level 3, Block E
End of Program
Universiti Teknikal Malaysia Melaka, Melaka
Dr. Tarmizi Izzuddin joined UTeM in 2010 after graduating from Shimane University (Japan) and currently serving as a lecturer in the Faculty of Electrical Engineering (FKE), Mechatronics Department. He recently obtained his Ph.D. from Universiti Teknologi Malaysia (UTM) and also currently has several AI-related professional certificates from industries such as IBM, Skymind and Nvidia. His research interests include artificial neural networks, robotics, and brain-computer interface.
Dr. Norafizah Abas joined the Department of Mechatronics, Universiti Teknikal Malaysia Melaka (UTeM) in 2008 and currently holds the position of senior lecturer. In 2019, she has earned her Ph.D from The University of Sheffield, UK, focusing on Automatic Control and System Engineering. Her current research interests include Control Systems Design (Theory and Applications), System Modelling, (Bio) Signal Processing, Assistive Robotics, and Intelligent Mechatronics Systems. She has received various research funding from national and industrial resources in the field of Robotics and Control, Bio-signal Sensor Fusions, and System Design.
Biosignals are referring to electrical signals generated by various biological processes of human body. The primary goal of biosignal processing and classification is to extract meaningful information from the signals, enabling researchers and healthcare professionals to understand the underlying physiological mechanisms, abnormalities and diagnosis of medical conditions. This tutorial course is intended to introduce participants to the principles of biosignal processing and classification using artificial intelligence (AI) and deep learning. Designed for participants with basic knowledge of signal processing and machine learning, this course is expected to equip participants to employ AI and deep learning for biosignal classification. Moreover, it covers the applications of biosignal classification in healthcare, sports, and other fields.
Detailed Topics:
Director, Advanced Technology Solutions Sdn Bhd.
Norliza Mohd (abbreviated for Mohamed) Noor was a Professor in Razak Faculty of Technology and Informatics, Universiti Teknologi Malaysia (UTM), Kuala Lumpur Campus. Currently, she is one of the directors at Advanced Technology Solution (ATES) Sdn Bhd. She received her B.Sc. in Electrical Engineering from Texas Tech University in Lubbock, Texas, and Master (by research) and PhD both in Electrical Engineering from UTM. Her research areas are in machine learning and image analysis for medical and industrial applications.
Machine learning has made significant advancements in the healthcare industry, revolutionizing various aspects of medical research, diagnostics, treatment, and patient care. Despite these remarkable benefits, the adoption of machine learning in healthcare also raises challenges, such as data privacy concerns, regulatory compliance, and ensuring that models are explainable and transparent to gain trust from medical professionals. Nonetheless, as technology continues to advance, machine learning is expected to play an increasingly crucial role in transforming healthcare and improving patient outcomes. This workshop tutorial will give the audience a brief overview of machine learning contribution in the healthcare industry and some machine learning techniques commonly used currently.