AI Characterisation of millimetre-Wave Signals from Human-centric Mechanical Actions applicable to Paediatric Neurological Diagnosis

The use of several high frequency bands of radar for the extraction of some medical information (such as cardiorespiratory features) has in recent years been of huge interest to researchers. Millimetre-wave radar is non-invasive, non-contact and non-ionising, therefore very suitable for applications in paediatric medicine. Very small vibrations of the heart and lung including movements of other body parts can be detected, monitored and classified with greater reliability using the millimetre-band radar signals. The primary focus of this research is the deployment of deep learning algorithms to characterising radar signal outputs of these two vital human organs together with certain body gestures which are critical to the study and recognition of infantile neurological development. Through a combination of medical AI and radar technology, the project will also examine the prospect of identifying one or two neurological conditions as revealed by human-induced actions: following successful characterisation of attendant radar signals.