Dr Titus Jayarathna

Position

Postdoctoral Research Fellow in Biomedical Engineering

Position Responsibilities

Dr Titus Jayarathna’s role involves conducting interdisciplinary research in biomedical engineering, with a focus on the development of wearable neurostimulation devices. His responsibilities span embedded system design, electronic hardware development, firmware and app creation, and translating user needs into validated medical technologies. He contributes to the scalability and quality of biomedical systems and actively engages with clinicians, patients, and industry through collaborative initiatives. Dr Jayarathna also supports grant development, publishes in high-impact journals, and mentors Honours, Masters, and PhD students, helping bridge engineering innovation with real-world healthcare applications.

Biography

Dr Titus Nanda Kumara Jayarathna holds a Bachelor's degree in Computer Engineering from the University of Peradeniya, Sri Lanka, where he first developed an interest in biomedical systems and embedded technologies. His academic journey led him to pursue a PhD at Western Sydney University, focusing on the development of wearable, low-power systems for continuous physiological monitoring.

Dr Jayarathna’s research lies at the intersection of biomedical engineering, signal processing, and emerging technologies like edge computing and subsensory neurostimulation. He works to create innovative solutions for real-time health monitoring, contributing to advancements in both clinical and consumer health technologies. His work is aimed at bridging the gap between theoretical research and practical applications in personalized healthcare.

In addition to his doctoral research, Dr Jayarathna has collaborated on numerous interdisciplinary projects, where he has applied his expertise in wearable devices, health data analytics, and low-power algorithms. His contributions to the field are focused on improving patient care through non-invasive monitoring and enhancing our understanding of physiological and cognitive states.

Research Interests

• Wearable health monitoring systems
• Low-power algorithms for real-time data analysis
• Edge computing in biomedical applications
• Subsensory neurostimulation techniques
• Digital health and personalized healthcare
• Sleep science and mental health monitoring
• Physiological signal processing and sensor fusion
• Machine learning applications in health data analytics

Qualifications

• PhD in Biomedical Engineering, Western Sydney University, Australia
• BSc (Hons) Specialised in Computer Engineering, University of Peradeniya, Sri Lanka

Publications

Near real-time data labeling using a depth sensor for EMG-based prosthetic arms. Intelligent Systems and Applications: Proceedings of the 2018 Intelligent Systems Conference (IntelliSys) Volume 2, 310-325, 2019, Springer International Publishing.

Accelerating k-NN classification algorithm using graphics processing units. 2016 IEEE International Conference on Information and Automation for Sustainability (ICIAfS), 1-6, 2016, IEEE.

Generalized and hybrid fast-ICA implementation using GPU. 2016 Sixteenth International Conference on Advances in ICT for Emerging Regions (ICTer), 13-20, 2016, IEEE.

A systematic feature selection process for a Sinhala character recognition system. 2016 IEEE International Conference on Information and Automation for Sustainability (ICIAfS), 1-6, 2016, IEEE.

Continuous vital monitoring during sleep and light activity using carbon-black elastomer sensors. Sensors, 20(6), 1583, 2020, MDPI.

Live Demonstration: Morphic Sensor for Diagnosis of Peripheral Vascular Disease. 2019 IEEE Biomedical Circuits and Systems Conference (BioCAS), 1-1, 2019, IEEE.

Characterization of Coated Piezo-resistive Fabric for Respiration Sensing. 2019 International Conference on Electrical Engineering Research & Practice (ICEERP), 1-6, 2019, IEEE.

Characterisation of Morphic Sensors for Body Volume and Shape Applications. Sensors, 20(1), 90, 2019, MDPI.

Polymer sensor embedded, IOT enabled t-shirt for long-term monitoring of sleep disordered breathing. 2019 IEEE 5th World Forum on Internet of Things (WF-IoT), 139-143, 2019, IEEE.

Live Demonstration: Invisible Vital Monitoring. 2019 IEEE Biomedical Circuits and Systems Conference (BioCAS), 1-1, 2019, IEEE.

Wearable Bluetooth triage healthcare monitoring system. Sensors, 21(22), 7586, 2021, MDPI.

An effective feature set for enhancing printed Tamil character recognition. National Science Foundation of Sri Lanka, 2021.

Electrodeless Heart and Respiratory Rate Estimation during Sleep Using a Single Fabric Band and Event-Based Edge Processing. Sensors, 22(17), 6689, 2022, MDPI.

The Apple Watch for monitoring mental health–related physiological symptoms: Literature review. JMIR Mental Health, 9(9), e37354, 2022, JMIR Publications Inc., Toronto, Canada.

Morphic Sensors for Respiratory Parameters Estimation: Validation against Overnight Polysomnography. Biosensors, 13(7), 703, 2023, MDPI.

The Apple Watch for monitoring mental health–related physiological symptoms: Literature review. JMIR Ment Health, 9(9): e37354, 2022.

A novel ECG compression algorithm using Pulse-Width Modulation integrated quantization for low-power real-time monitoring. Scientific Reports, 14(1), 17162, 2024, Nature Publishing Group, UK.

For a complete list of my publications please see my Google Scholar page.

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