• Bio-science and Bio-engineering

• Health Informatics and Modeling

• Intelligent Medical Imaging

• Neuro-signal Processing

• Pervasive Healthcare

BIO-SCIENCE AND BIO-ENGINEERING

• Biochemicals from Malaysian natural resources.

• Novel drug delivery system to cancer cells.

• Novel materials for Health and Environmental applications.

• Chemical sensor for Health and Environmental applications.

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HEALTH INFORMATICS AND MODELING

• Virtual Reality Stress Therapy

  • Stress is a prevalent and a costly problem in today’s working environment.

  • This project aims to develop an image-based Virtual Reality (VR) stress therapy system to help alleviate stress in a working environment.

  • Our initial work involves developing a low cost image-based VR stress therapy prototype application.






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INTELLIGENT MEDICAL IMAGING

• Diabetic Retinopathy

  • Diabetic Retinopathy (DR) is the  retinal damage due to complications of diabetes that leads to blindness.

  • This project aims to develop a clinical grading system based on foveal avascular zone (FAZ) enlargement measurement in colour fundus images.



 

• Psoriasis Assessment

  • Psoriasis is a non contageous skin disorder which typically consists of red plaques covered by silvery white scales.

  • This project aims to develop a monitoring system that measures all Psoriasis Area and Severity Index (PASI) parameters objectively using 2D/3D imaging.

  • Research started in 2006 in collaboration with Dermatology Department, HKL.

  • To date, the group has successfully developed and proved image algorithms for assessing area, erythema, scaliness and thickness of psoriasis lesions. These algorithms will be used as the basis for the PASI scoring device system.

  • We have also acquired a Technofund grant to develop prototype system and undertake clinical trials.



 

• Ulcer Wound Assessment Device

  • Ulcers are chronic wounds that cause severe pain and discomfort to the patients.

  • This study aims to provide a quantitative assessment of granulation tissue growth and associated volume change by utilizing 2D coloured images and 3D surface scans.

  • This research was started in 2007 in collaboration with the Dermatology Department, Hospital Kuala Lumpur.

  • We have successfully developed and tested ulcer wound volume algorithms which can be used as the basis for the ulcer wound assessment device.



 

• Acne Analysis

  • Acne is a chronic disorder of the  pilosebaceous units with excess sebum production, hyperproliferation, inflammation and P acne activity.

  • This project aims to design a computational system based on image processing for acne grade assessment.



 

• Skin Pigmentation Analysis

  • Pigmentation disorder is a disease due to the abnormality of melanin production.

  • The objective of this project is to develop skin pigmentation model and analysis using digital signal and image analysis of multi-spectral data for classification and quantification of melanin pigment types in clinical settings.



 

• Non-Invasive Ultrasound Imaging for Bone Fracture Detection

  • This project aims to identify and evaluate the use of non-invasive ultrasound imaging for long bone fracture detection.

  • This study explores the possibility of ultrasound imaging for long bone fracture detection in children.

• Early Knee Osteoarthritis Detection

  • Knee osteoarthritis can be characterised by the gradual loss of articular cartilage that leads to permanent disability in elders.

  • This project aims to develop a non-invasive diagnostic tool using quantitative MRI approach to detect early onset osteoarthritis and classify the cases into sub-grades at early stage.



 

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NEURO-SIGNAL PROCESSING

• EEG Analysis for Memory Retention and Recall Process

  • This project aims to design the EEG experiments that can be used to  assess the effect of 3D-based educational tools on learning and memorization processes.

  • Furthermore, the effectiveness of the 3D-based educational tool in comparison to the traditional 2D, on the learning and the memorization process will be investigated.

• Objective Measurement of Visual Fatigue and Visually-induced Motion Sickness Caused by viewing 3D Moving Images

  • Viewers of 3D movies have reported negative side-effects from viewing 3D movies, and these are commonly known as visual fatigue or visually-induced motion sickness (VIMS).

  • This project aims to investigate the correlation between brain activity captured using EEG and the VIMS symptoms experienced by the viewers.

  • Results from this investigation may pave the way to a new objective measurement of VIMS symptoms using EEG data, as well as giving insights on how 3D technology can be further improved.

    

• Visual Evoked Potentials for Optical Pathway Assessment.

• Correlating Visual Evoked Potentials with Brain Abnormalities.

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PERVASIVE HEALTHCARE

• Diabetic Retinopathy

  • After the successful completion of the clinical study of the Diabetic Retinopathy (DR) Grading project, we are now developing the Standalone and Portable DR Monitoring and Grading Syste.

  • This equipment can be used by clinicians in primary care for grading severity and progression of diabetic retinopathy of diabetic patients.

  • It will also enable effective screening and identification of those individuals who may be at risk of developing DR and in assisting ophthalmologists to make accurate diagnosis (identification of DR conditions by means of its pathologies and symptoms) in an efficient manner.

• Energy Efficient Wireless Body Area Network (WBAN)

  • Wireless Body Area Network (WBAN) is a system that consists of wireless sensors for the monitoring of fundamental biomedical & analogue signals such as heart rate, blood pressure, ECG, EMG, temperature and motion.

  • Current work addresses the issues of routing mechanism with the emphasis on reliability and energy efficiency.

• Bio-Inspired Fault Tolerant Network-on-Chip (NoC)

  • Multi core designs of system-on-chip (SoC) requires the use of a network-on-chip (NoC) for a reliable and high bandwidth on-chip communication.

  • However, the future fabrication process of nanoscale VLSI circuits is unreliable and will contain many faulty interconnects.

  • We explore the potential of adapting the highly fault tolerant biological structure of the neural network to develop a fault tolerant on chip interconnect that can overcome this problem.

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