ProfessorWei Chen
Head of School
Faculty of Engineering
Research projects & supervision summary
----------Current Research Projects----------
- Unobtrusive sensor systems for healthcare
- Intelligent multimodal systems for health modulation
- Physiological and behavioural data processing
Project Opportunities
Title: Unobtrusive Sensor Systems for Healthcare
Research Area:
Wearable sensors, unobtrusive sensing, embedded systems, health monitoring.
Opportunity synopsis:
This project aims to create unobtrusive sensor systems to monitor physiological and behavioural data of human body. The signals include EEG, ECG, EOG, EMG, respiration, SpO2, temperature, activities, etc.. The candidate will develop innovative wearable sensing or non-contact sensing techniques with new sensing materials and embedded systems for biomedical data acquisition and processing. Lightweight AI algorithms and software for embedded sensor systems will be proposed for intelligent healthcare systems. The potential applications will be sleep monitoring, neonatal monitoring and smart rehabilitation, etc.
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Project Opportunities
Title: Data Processing for Sleep, Dementia and Mental Health
Research Area:
Signal processing, AI and deep learning, sleep staging and sleep disease analysis, dementia monitoring, mental health.
Opportunity synopsis:
This project focuses on development of signal processing and AI methods and algorithms for sleep staging, sleep disorder analysis, dementia and mental health monitoring. The scope will include proposing dedicated AI and data science methods to explore and analyse relevant biomarkers and features with high sensitivity and specificity from physiological and behavioural signals; building data analytical models to enhance the learning performance, proposing approaches to improve model generalization; investigating explainable AI methods; developing information and computing schemes and algorithms for precise sleep disease detection and prediction.
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Project Opportunities
Title: Investigating optimised stimulation strategies for health modulation
Research Area:
Stimulations, multi-modality, health modulation.
Opportunity synopsis:
Biofeedback based stimulation has emerged as a promising method for regulating health. The approaches include electrical, optical, acoustic, light, magnetic stimulations, etc. For example, by applying controlled electrical currents to specific areas of the brain or body, the technique aims to modulate neural activity and promote restorative brain functions. Understanding the mechanisms and efficacy of stimulations for health enhancement is crucial for developing effective interventions and improving overall health. The project aims to comprehensively understand the role of stimulations and develop optimised stimulation strategies for health modulation to improving wellbeing and health.
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Previous Projects:
• EU H2020-MSCA-ITN-2017, 1.53 million Euro, project title: HEART-HEalth related Activity Recognition system based on IoT, 2017.9-2020.12. In collaboration with Philips, KU Leuven, and University of Macerata, Italy.
• EU Horizon 2020 PHC 26-2014, € 4.7 million, project title – “DO Cardiac Health: Advanced New Generation Ecosystem (DO CHANGE)”, 2015-2018.
• Philips Research project, 150k Euro, project title: Neonatal sleep monitoring, 2019- 2023
• Philips Research project, 130k RMB, project title: Mobile fetal monitoring, 2017- 2018
• EU Erasmus Mundus Joint Doctorate program, € 5 million, project title - “Cognitive and Interactive Environments Doctorate program (ICE)”, 2009-2017.
• IOP IPCR (Netherlands Innovation funding), € 1 million, project title - “Developing Transformative Design Strategies and Tools to build and measure products and services for “Social Wellbeing” (Design for Wellbeing/DfW)”, 2009-2012.
• Point One (SenterNovem), € 1.4 million, project title - “Embedded Neonatal Monitoring (E-NEMO)”, 2010-2013. In collaboration with Philips Research and Maxima Medical Center in the Netherlands.
• STW Autonomous Sensor Systems, € 900k, project title – “Smart Energy Body Area Sensor Networks for Pregnancy Monitoring (SEBAN)”, 2010-2014. In collaboration with Philips Research and Maxima Medical Center in the Netherlands.
• NWO Aspasia 2015, € 200k
• Netherlands VIVIS funding, € 79k, “Bioresponse of physiological signals of blind and mentally disabled patients”, partners: Vrij University Amsterdam, Bartimeus care center, 2015-2016.
RESEARCH PROJECTS & ACTIVITIES
- RESEARCH-BASED DEGREE SUPERVISIONA multimodal brain monitoring platform for cognitive and mental health application
- RESEARCH-BASED DEGREE SUPERVISIONAdaptive and Transferable Deep Learning for Sleep EEG Biomarker Detection
- RESEARCH-BASED DEGREE SUPERVISIONAdaptive and Transferable Deep Learning for Sleep EEG Biomarker Detection
- RESEARCH-BASED DEGREE SUPERVISIONAdvanced Skin Electrode Design for Reliable Biopotential Recording
- RESEARCH-BASED DEGREE SUPERVISIONAutoRSWA: A Configurable Framework for Automated REM Sleep Without Atonia Quantification
- RESEARCH-BASED DEGREE SUPERVISIONCharacterising the Relationship Between Physical Activity and Blood Pressure in Free-Living Adults Using 24-Hour Ambulatory Monitoring
- RESEARCH-BASED DEGREE SUPERVISIONContrastive Self-Supervised Pre-Training with Deep Clustering for EEG-Based Clinical Classification
- RESEARCH-BASED DEGREE SUPERVISIONData processing for sleep monitoring
- RESEARCH-BASED DEGREE SUPERVISIONEfficient Data Processing for Sleep Staging and Sleep Disorder Detection in Portable Monitoring Systems
- RESEARCH-BASED DEGREE SUPERVISIONExplore relationship between activity level and blood pressure in 24 hour ambulatory measurements.
- RESEARCH-BASED DEGREE SUPERVISIONFlexible strain sensors for health monitoring
- RESEARCH-BASED DEGREE SUPERVISIONMultimodal Learning and Interpretability for Sleep Monitoring
- RESEARCH-BASED DEGREE SUPERVISIONPrediction and Diagnosis of Neurodegenerative Disorders Based on Multimodal physiological signal Features Across Sleep Stages
- RESEARCH-BASED DEGREE SUPERVISIONResearch of Human-Computer Interaction Technology Based on Eye Activity
- RESEARCH-BASED DEGREE SUPERVISIONUnobtrusive Sensor Systems for Healthcare