Advanced biosignal analysis from multiparameter physiological dataset
The recent advancements in physiological sensors (optical and electrical) have enabled the acquisition of physiological data non-invasively which was not possible in the past. With the help of such a multiparameter dataset it might be possible, utilising advance linear and non-linear signal processing techniques such as Time-Frequency Distribution (TFD), Empirical Mode Decomposition (EMD) etc., to extract features that will provide useful physiological information related to the haemodynamic and cardiovascular state of a person. The combined information obtained from different non-invasive modalities such as Electrocardiograph (ECG), Respiration, Photoplethysmograph (PPG), Blood pressure (BP) and Near-infrared Spectroscopy (NIRS) can be beneficial and has a significant impact in various fields such as anaesthesia management, paediatric care and sports medicine. This work is in collaboration with national and international partners including St Bartholomew’s Hospital, The Royal London Hospital, Great Ormond street hospital for Children and Yale School of medicine.