Events

Research Seminar: Internet of Things enabled Health Data Analytics and Utilisation

Dr Po Yang
Dr Po Yang

Date: Thursday 6 October 2022 14:00 - 15:00

Location: Maths. MB-203, QMUL

Register at: teams.microsoft.com/l/meetup-join/19%3ameeting_ZTZiZjQyMz...

This is a module seminar for Statistical Thinking and Applied Machine Learning (EMS702). All students and staff who are interested in the topic are welcome.

The speaker of the seminar is Dr Po Yang, Associate Professor in Large-scale Data Fusion at Sheffield University, UK.

Internet of Things (IoT) enabled Healthcare is defined as a specific research area focusing on the utilization of IoT enabled techniques to offer high quality health services, including faster and safer preventive care, lower overall cost, improved patient-centred practice and enhanced sustainability. Current work on IoT enabled healthcare is highly interdisciplinary involving methodologies from computing, engineering, information science, behaviour science, as well as many different areas in medicine and public health. A promising trend in these studies appears to be developing sophisticated techniques that will enable: 1) Integrating different smart wearable devices into a unified system for intelligently sensing daily human health information; 2) The design and development of IoT enabled healthcare system or applications for efficiently delivering specific health services; 3) Effectively and efficiently managing, analysing and exploring a sheer volume of long-term health data for supporting wise clinical decision-making.

However, addressing this trend is still significantly challenging due to an array of factors that include: shortage of cost-effective and accurate smart medical sensors, unstandardized IoT system architectures, heterogeneity of wearable devices connected, multi-dimensionality and high volume of data generated, and high demand for interoperability. Additionally, successfully empowering the utility of IoT enabled technology in healthcare will need an interoperable IoT environment for care delivery and research, tightly-coupled health data mining applications, adequate data and knowledge standards of self- empowerment and sound clinical decision-making foundation. These challenges and needs require the design and development of a series of innovative and comprehensive informatics methods in IoT enabled healthcare.

This talk would introduce some research work on investigating deep learning based wearable intelligence technologies for providing a cost-effective and non-intrusive human activities recognition in free-living environment. And then it will report that how to use advanced machine learning approaches to effectively match uncertain life-logging data to high level personal life pattern and physical activities. Lastly, it will demonstrate some wearable intelligence techniques using Huawei Smartwatch for self-diagnosis of Parkinson Patient in free-living environments.

Biography

Dr Po Yang is a Senior Lecturer (Associate Professor) in the Department of Computer Science at The University of Sheffield. Dr Yang holds a BSc in Computer Science (with Honours) from Wuhan University (2004) and a MSc in Computer Science (Distinction) from The University of Bristol (2006). Dr Yang has academia and industry combined research experience on pervasive and mobile computing, machine learning and data intelligence, smart healthcare, and precision agriculture. He is/was PI or Co-I of 10+ research projects funded by the Innovate UK, Engineering and Physical Sciences Research Council (EPSRC), Research England and industry. His 2 patents are granted/filed in UK/China. Since 2010, Dr. Yang has published over 130 publications (42 IEEE Trans/Journal papers, 4 ESI hot papers, Google Citations > 3800, h-index 34, RG score=34.56) and 2 Patents. He is internationally known for his work on Pervasive Intelligence in Healthcare. He serves as an Associate Editor in IEEE Journal of Translational Engineering in Health and Medicine and Journal of Biomedical Informatics. He is the co-founder of AntData and Mutus-tech Ltd.

Contact:Yunpeng Zhu
Email:yunpeng.zhu@qmul.ac.uk