Artificial Intelligence enabled investigation of biometric data using radar systems for advancements in assistive technologies

In this project, we aim to develop an artificial intelligence enabled ultra-wideband (UWB) radar system, the purpose of which would be for the non-invasive measurement and prediction of human biometric data. The primary application for this type of project is for uses in elderly people's homes for the detection of severe and sudden health issues. This research also investigates into novel methods of detecting multiple people within closed environments. The data measured and predicted by such a system can undoubtedly be used for a multitude of applications; in industrial settings for example, automated awareness on the presence of people within specific areas is a matter of great security and safety. Within commercial environments, where visual camera data is a source of great data security concern, understanding the presence and behaviour of multiple people can, for example, be used to make the surroundings more energy efficient. The main and primary use of the system is to measure and recognise the human heart rate of an individual or individuals within a room using radar technology. Using this information, and machine learning algorithms, the system should then be able to recognise abnormalities or any other major issues, such as a heart attacks or the sudden stopping of the heart completely. This is to be used as a preventative alarm system for individuals particularly prone to sudden medical conditions, mainly speaking elderly people or infants.
This PhD project is specifically looking into embedded systems utilising artificial intelligence capabilities to analyse inherently weak and noisy radar signals. This project hopes to answer questions related to using machine learning for the purpose of signal processing; mainly being, are there any effective methods of analysing weak radar signals for the biometric data measurements? And can a radar system be refined to possibly detect brain waves?
To attempt to solve this problem, we must take a holistic view of the questions at hand and understand that this project combines areas of computer science, electrical engineering and the medical sciences. We will begin by developing the radar system, which is integral to the acquisition of the specified data and then refining the hardware to the point where measurements can be made. Using this acquired information, it is important to understand the data from a medical perspective and build this understanding into any computational algorithms that may be developed for analysis. Finally, thorough testing must be done on the system in order to maximise its efficiency in recognising patterns within the biometric data.
To successfully carry out this project, we must develop novel signal processing algorithms and apply machine learning to them. We must also identify optimized techniques for identifying and processing biometric data from weak and noisy radar signals. Finally, we should investigate into the possibility of this stationary radar system being capable of ultimately detecting brain waves. These are some of the major technical challenges to be addressed by this PhD project.