PhD Project in AI-enhanced next-generation health sensing using mmWave radar

Location: United Kingdom
Application Deadline: 28 February 2025
Published: 1 week ago

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Overview

Continuous monitoring of vital signs, such as respiration, heartbeat, heart rate variability (HRV), blood pressure (BP), electrocardiogram (ECG), and seismocardiography (SCG), is essential for early detection and prevention of potentially life-threatening conditions.

Continuous monitoring of vital signs, such as respiration, heartbeat, heart rate variability (HRV), blood pressure (BP), electrocardiogram (ECG), and seismocardiography (SCG), is essential for early detection and prevention of potentially life-threatening conditions. However, existing solutions often require users to wear dedicated devices like wrist-worn sensors or chest straps, which can be uncomfortable and may cause skin allergies. With the rapid development of IoT and wireless communication technologies, wireless sensing has emerged as a promising alternative. This approach takes advantage of the ubiquitous presence of wireless devices and the fact that the presence of human body can alter wireless signal propagation, enabling contactless and passive monitoring of human’s vital signs through the analysis of the electromagnetic wave. This innovation offers a more convenient and non-invasive way to monitor health, making it a valuable tool in medical and wellness applications.

As the next generation of wireless communication, millimeter wave (mmWave) radar is becoming increasing available in home routers and vehicles, offering substantial improvements in performance, including larger bandwidth and higher directionality. This enhanced capability makes mmWave radar highly suitable for advanced sensing applications. Meanwhile, artificial intelligence (AI) has made rapid progress in various fields such as computer vision, natural language processing, and autonomous systems. The combination of mmWave radar and AI opens up new possibilities for more accurate, efficient and intelligent systems in areas such as smart homes, smart healthcare, and human-computer interaction. By leveraging AI, mmWave radar can be further optimized for complex tasks, paving the way for more advanced and reliable wireless sensing technologies.

Driven by the growing need for continuous vital sign monitoring, as well as advancements in IoT and AI, this PhD project seeks to develop mmWave radar-based systems for robust and accurate vital sign monitoring by integrating advanced signal processing and AI techniques.

Funding Information

To be eligible for consideration for a Home DfE or EPSRC Studentship (covering tuition fees and maintenance stipend of approx. £19,237 per annum), a candidate must satisfy all the eligibility criteria based on nationality, residency and academic qualifications.

To be classed as a Home student, candidates must meet the following criteria and the associated residency requirements:

• Be a UK National,
or • Have settled status,
or • Have pre-settled status,
or • Have indefinite leave to remain or enter the UK.

Candidates from ROI may also qualify for Home student funding.

Previous PhD study MAY make you ineligible to be considered for funding.

Please note that other terms and conditions also apply.

Please note that any available PhD studentships will be allocated on a competitive basis across a number of projects currently being advertised by the School.

A small number of international awards will be available for allocation across the School. An international award is not guaranteed to be available for this project, and competition across the School for these awards will be highly competitive.

Academic Requirements:

The minimum academic requirement for admission is normally an Upper Second Class Honours degree from a UK or ROI Higher Education provider in a relevant discipline, or an equivalent qualification acceptable to the University.

Entrance requirements

Graduate
The minimum academic requirement for admission to a research degree programme is normally an Upper Second Class Honours degree from a UK or ROI HE provider, or an equivalent qualification acceptable to the University. Further information can be obtained by contacting the School.

International Students

For information on international qualification equivalents, please check the specific information for your country.

English Language Requirements

Evidence of an IELTS* score of 6.0, with not less than 5.5 in any component, or equivalent qualification acceptable to the University is required (*taken within the last 2 years).

International students wishing to apply to Queen’s University Belfast (and for whom English is not their first language), must be able to demonstrate their proficiency in English in order to benefit fully from their course of study or research. Non-EEA nationals must also satisfy UK Visas and Immigration (UKVI) immigration requirements for English language for visa purposes.

For more information on English Language requirements for EEA and non-EEA nationals see: www.qub.ac.uk/EnglishLanguageReqs.

If you need to improve your English language skills before you enter this degree programme, INTO Queen’s University Belfast offers a range of English language courses. These intensive and flexible courses are designed to improve your English ability for admission to this degree.

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