Prof. Madya Ts. Ir. Dr. Nasrul Humaimi Bin Mahmood is a distinguished academic and researcher in Biomedical Engineering whose work integrates Artificial Intelligence, advanced computational modelling, robotics, and intelligent sensing technologies to advance modern healthcare and inclusive engineering systems. With more than two decades of academic and research experience, he has established a strong profile in AI-driven medical imaging, quantitative ultrasound engineering, biomedical signal analytics, intelligent assistive technologies, and human-centered robotic innovation.
His flagship research area is Artificial Intelligence for Medical Imaging and Diagnostics, where he develops advanced deep learning architectures—including Convolutional Neural Networks (CNN), transfer learning frameworks, and intelligent classification models—for automated disease detection and clinical decision-support systems. His contributions include red blood cell abnormality classification, diabetic foot ulcer detection using thermographic imaging, atrial fibrillation recognition using 1D CNN models, white blood cell segmentation, and ultrasound-based thyroid and breast analysis. His work supports the advancement of smart, data-driven healthcare technologies aligned with digital health transformation.
A major technical specialization lies in Quantitative Ultrasound Modelling for Bone Characterization. Through computational simulation and wave propagation modelling, he investigates the interaction between ultrasound reflection parameters, bone thickness, and porosity in cortical and cancellous bone structures, contributing toward non-invasive bone quality assessment and improved orthopedic diagnostic methodologies.
Dr. Nasrul also demonstrates extensive expertise in Biomedical Signal Processing and Physiological Modelling, particularly in EEG, EMG, ECG, and cardiovascular signal analysis. His research includes anxiety state recognition, muscle fatigue assessment, pulse wave transit time modelling, wavelet-based denoising techniques, and advanced time-frequency analysis. These works highlight strong competency in intelligent health monitoring systems and neural network-based biomedical classification frameworks.
In 3D Surface Reconstruction and Prosthetic Engineering, he has developed multiview reconstruction algorithms, Radon transform-based modelling techniques, and sensor-driven 3D imaging systems for orthotic and prosthetic applications, supporting personalized biomedical device innovation and rehabilitation engineering.
Beyond clinical applications, his interdisciplinary research extends into Intelligent Vision Systems, Robotics, IoT, and Assistive Technologies. He has developed abnormal behavior detection systems, deep learning-based vehicle detection models, human motion classification frameworks, smart assistive shoes for visually impaired individuals, sonar-based navigation devices, and augmented-reality sensor platforms.
In addition, he is actively involved in research on Robotic Chess Systems and Inclusive Chess Technologies, focusing on AI-powered robotic chess platforms that integrate computer vision, motion control, and embedded systems for automated gameplay. He also explores adaptive chess technologies designed for persons with disabilities, incorporating sensor-based interfaces and intelligent board recognition systems to promote cognitive engagement, rehabilitation support, and inclusive learning environments. This work reflects his broader commitment to accessible technology and socially responsive engineering innovation.
Key Research Expertise Areas
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Artificial Intelligence for Medical Imaging & Diagnostics
Deep learning, CNN architectures, transfer learning, automated disease detection, thermographic imaging, ultrasound image analysis, clinical decision-support systems. -
Quantitative Ultrasound Modelling & Bone Characterization
Computational simulation of wave propagation, cortical and cancellous bone modelling, ultrasound reflection analysis, non-invasive bone quality assessment. -
Biomedical Signal Processing & Physiological Modelling
EEG, EMG, ECG analytics, anxiety and fatigue detection, cardiovascular modelling, wavelet-based denoising, time-frequency signal analysis, intelligent health monitoring. -
3D Reconstruction & Prosthetic Engineering
Multiview 3D surface reconstruction, Radon transform modelling, sensor-driven imaging systems, personalized orthotic and prosthetic design. -
Intelligent Vision Systems, IoT & Assistive Technologies
Deep learning-based surveillance systems, motion classification, smart assistive devices for visually impaired users, sonar navigation, AI-driven sensor integration.
