Imaging Photoplethysmography (iPPG) is an emerging optical imaging technology to non-invasively detect changes of microvascular blood volume in tissues with selective region of interest (RoI). Loughborough University iPPG is one of the pioneering outcomes derived from fundamental research of opto-physiological interaction (NASA/TM-2011-216145) employing a Lambert-Beer law and motion artefact photoplethysmography (PPG). The LU physiological monitoring work was recognised as being at the forefront of worldwide PPG-based pulse oximetry research by Drexel University in 2008 (www.pages.drexel.edu/~kmg462/currentresearch.html).
However, the present state of introduction of iPPG into imaging monitoring and diagnosis systems is still far away from meeting criteria of clinical setups for routine monitoring and assessment, and individual health monitoring due to uncontrollable motion artefacts (MAs). We believe that the widespread acceptance of iPPG can accelerate dramatically the promotion of this healthcare model once the MAs are overcome with a suitable engineering approach. The goal of the PhD project is to explore an auto-correlation model of 3D moving objective(s) to establish a calibration-free iPPG (LU-iPPG) for real-time vital-sign monitoring and blood perfusion mapping.
Excellence in Science and Technology
The LU-iPPG will be one of the outcomes resulting from the fundamental research of opto-physiological interaction (http://dx.doi.org/10.1260/2040-22188.8.131.525
). Opto-physiological modelling associated with a microvascular circulation mechanism will be primarily pursued to understand principles of opto-illumination to assess blood-flow microcirculation of moving objective. Together with a deep-learning (DL) procedure (DoI: 10.1109/MIE.2018.2824843), essential engineering modelling of 3D measurements will be undertaken to provide optimal solutions toward viable innovative LU-iPPG products. The LU-iPPG will be integrated into smart electronics and manufacturing processes explored in a user-centred design context.
The LU-iPPG will have miniaturised, system integrated and self-learning features with a reliable and better performance to deliver one-stop solutions in imaging monitoring of critical signs. The developed LU-iPPG prototype will be examined using standardised physiological testing procedures to demonstrate its reliability and resistance to motion artefacts. The LU-iPPG prototype will offer both clinicians and scientists the ability to gain more in-depth knowledge of physiological processes within the body as its design makes it easy to collect data continuously over long periods of thanks to its light weight, comfortable, unobtrusive design that does not impede or restrict movement.
The project will integrate dynamic opto-physiological modelling into an enabling optoelectronic multi-image sensing architecture design of a user prototype leading to a motion-free imaging technology. The novelties of the project are related to unique characteristics of the forthcoming LU-iPPG as follows:
1) Optimal opto-illumination of moving objective(s) with a well understanding of mechanical principles of blood-flow microcirculation.
2) A mathematical model to interpret a coordination of multiple cameras to auto-tract moving objective(s).
3) A DL architecture to enable image processing with a higher self-calibration and for accurate measurement.
4) A diverse and coherent engineering solution to provide motion resistance and real-time functionalities of LU-iPPG with a better performance of physiological measurements.
5) Physiological testing to be undertaken not only to validate a 3D auto-track model for iPPG applications but also to gain a further real-time insight into physiological variations.
This multidisciplinary research across applied mathematics, photonics engineering, mechanical microfluidics, DL and healthcare applications will lead to a new research paradigm of imaging technology for physiologic monitoring and event assessment in real-time.
Applicants should have, or expect to achieve, at least a 2:1 Honours degree (or equivalent) in Physical sciences (Applied Physics) or Engineering (Electronic Engineering, Computer Programming).
A relevant Master's degree and / or experience in one or more of the following will be an advantage: Embedded Software, Electronics, Signal processing, opto-physiological monitoring.