Signal Processing for Ultrasound Diagnosis of Cardiac Output

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EPSRC Portfolio: EPSRC Theme: Healthcare Technologies, Challenge: Optimising Treatment/ Optimising care through effective diagnosis, patient-specific prediction and evidence-based intervention, Research areas: Digital signal processing (grow)Cardiac output is important for diagnosing shock and monitoring the patients' response to therapy at Emergency Departments, and could be measured using advanced non-invasive, stand-alone devices using Continuous Wave Doppler technology. However, despite the growing evidence that measuring cardiovascular haemodynamic parameters is directly linked to the prospects of the patients, monitoring is rarely administered as the procedure requires the involvement of highly-skilled medical professionals. The procedure involves placing a small device in the suprasternal notch aiming directly down the longitudinal axis at the ascending aorta and across the aortic root. The device transmits continuous wave Doppler ultrasound signal, which is used to calculate the ejection velocity of the blood as it exits the aortic valve. Heart beat is also monitored. This approach, however, is often difficult in all but young and fit individuals, because of restricted and sometimes painful access to the suprasternal notch. For this reason, cardiac output via the pulmonary valve can generally be more conveniently monitored at the left parasternal edge if the device is placed directly anterior to the heart. This is a challenging procedure as it requires (i) accurate transducer and patient positioning, (ii) accurate transducer manipulation, hand movement and pressure control, (iii) abilities to recognise the appearance of the Doppler profile and optimise its characteristics, (iv) an understanding that each patient may need slight variation to the standard approach, and (v) an understanding that suboptimal appearances may occur with low flow states.The proposed PhD project will contribute to developing a novel, low-cost, non-invasive robotic solution for fine positioning and adjustments of the ultrasound device that will enable the procedure to be administered by individuals with minimal training. This will enable timely and accurate diagnosis and repeated monitoring, therefore improving the choice and reducing the cost of any subsequent intervention, and increasing the likelihood of successful health outcomes.The project will involve an investigation of how the method is administered in different clinical situations and variable body physique in order to gather experience and to collect required data for the robotic device. Advanced new signal processing algorithms will be developed for recognising the Doppler profile and providing feedback for automatic positioning of the ultrasound device in order to optimise its characteristics. The positioning of the ultrasound device will be investigated in order to assess the blood flow through the pulmonary valve, and new advanced signal processing algorithms will be developed for recognising the Doppler profile and providing feedback for automatic positioning of the ultrasound device in order to optimise its characteristics. The PhD student will receive training in cross-disciplinary areas including signal processing, ultrasound and cardiac assessment and monitoring.