Microwave antenna configuration and anatomical head model used for electromagnetic simulation and neurodegenerative disease monitoring.
This research project investigated the development of non-invasive microwave sensing and computational imaging techniques for detecting and monitoring structural brain changes associated with neurodegenerative diseases such as Alzheimer’s disease and Parkinson’s disease.
The work integrates electromagnetic modelling, advanced signal processing, imaging algorithms, and machine learning approaches to enable longitudinal monitoring of disease progression without the need for expensive or invasive clinical imaging modalities such as MRI or CT.
The research explored pathological changes including brain atrophy, ventricular enlargement, and cerebrospinal fluid variations, and analysed how these structural changes affect microwave signal propagation through biological tissues. The resulting framework supports early diagnosis and scalable digital health monitoring solutions.
Experimental phantom and reconstructed microwave imaging results comparing conventional Delay-and-Sum (DAS) with the proposed Delay-Multiply-and-Sum (DMAS) algorithm, illustrating enhanced contrast and localisation accuracy.
Microwave imaging · Computational modelling · Machine learning · Biomedical signal processing · High-performance computing · Electromagnetic simulation
Data-driven microwave imaging and processing techniques for monitoring neurodegenerative diseases
University of Edinburgh, United Kingdom, 2022
Experimental radar data for monitoring brain atrophy progression
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Microwave sensing dataset for non-invasive monitoring of ventricle enlargement due to Alzheimer’s disease
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🌐 University of Edinburgh eWireless Research Page
Published in Neural Networks, 2025
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Recommended citation: Xin Chen, Deze Zeng, Rahmat Ullah, Rab Nawaz, Jiafeng Xu, Tughrul Arslan, others "A deep learning approach for non-invasive Alzheimer’s monitoring using microwave radar data." Neural Networks, 2025.
Published in Biomedical Signal Processing and Control, 2023
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Recommended citation: Rahmat Ullah, Imran Saied, Tughrul Arslan "Multistatic radar-based imaging in layered and dispersive media for biomedical applications." Biomedical Signal Processing and Control, 2023.
Published in IEEE Transactions on Microwave Theory and Techniques, 2023
Recommended citation: Rahmat Ullah, Yinhuan Dong, Tughrul Arslan, Siddharthan Chandran "A machine learning-based classification method for monitoring Alzheimer’s disease using electromagnetic radar data." IEEE Transactions on Microwave Theory and Techniques, 2023.
Published in Biomedical Signal Processing and Control, 2022
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Recommended citation: Rahmat Ullah, Imran Saied, Tughrul Arslan "Measurement of whole-brain atrophy progression using microwave signal analysis." Biomedical Signal Processing and Control, 2022.
Published in Algorithms, 2021
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Recommended citation: Rahmat Ullah, Tughrul Arslan "Parallel delay multiply and sum algorithm for microwave medical imaging using spark big data framework." Algorithms, 2021.