Demographic changes induce an ever-higher burden on the healthcare system. Early detection of complications and diseases and the determination of effective personalized treatments are essential to lower this burden, to prevent comorbidities, and to lower healthcare costs while simultaneously improving patient outcome and quality of life. The PISANO project seeks to leverage technological advances in pathophysiological modeling, unobtrusive sensing, monitoring and artificial intelligence (AI) towards this end. As part of the PISANO project, this PhD position addresses the need for improved hemodynamic measurements in critical care. The main hypothesis is that the standard hemodynamic monitoring technology might not be used up to its full potential. This project explores how to adapt existing critical care technology for the purpose to improve existing measurement quality, or developing new measurement strategies, aiming at extracting new parameters and obtain early and comprehensive information on the hemodynamic status of patients at risk of deterioration.
A major thrust is on radical innovations towards widespread use of ultrasound (US) technology. Cuff with integrated US might enable continuous peri-operative monitoring to detect hemodynamic instabilities earlier and with higher accuracy. More in general, using such new non-invasive smart measurement technique aims to replace current invasive methods to monitor functional hemodynamic parameters, which reveal useful for early detection of patient deterioration and for guiding critical care treatments.
The position is available within the Biomedical Diagnostics (BM/d) research lab, part of the Signal Processing Systems (SPS) group (Electrical Engineering department, TU/e), and it involves tight collaborations with the Catharina Hospital Eindhoven and Philips, as part of the Eindhoven MedTech Innovation Center (e/MTIC).
The BM/d lab at TU/e is devoted to model-based quantitative analysis of medical images and bio-signals, with the goal of improving patient care and management. In the context of perioperative care, we focus on modeling and analysis of bio-signals, taking into account the full measurement chain, with the goal of improving diagnosis and prognosis, and enabling long-term monitoring.
The Catharina Hospital Eindhoven is a large clinical and teaching medical center hospital in the Eindhoven area specialized in cardiovascular disease, obesity and oncology and serves as tertiary referral center in several areas. The departments of Anesthesiology, Cardiology, Intensive care, (cardiothoracic) surgery and laboratory service participate in many international trials and actively contribute to the development of diagnostic devices and clinical decision support systems.
Royal Philips is a leading health technology company with the purpose to improve people’s health and well-being through meaningful innovation. Aim is to deliver superior, long-term value
to customers and shareholders, while acting responsibly towards our planet and society, in partnership with the stakeholders.
We are seeking a highly motivated master graduate with a strong background and interest in the analysis and interpretation of biomedical signals.
We are looking for candidates that meet the following requirements:
Do you recognize yourself in this profile and would you like to know more?
For more information about this position contact dr. ing. Simona Turco, e-mail: s.turco[at]tue.nl.
For information about terms of employment, click here or contact contact HRServices.flux[at]tue.nl.
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The selection process will start in November 2021 and will continue until the position gets filled. The position is fully funded and immediately available. The successful candidate is expected to start ASAP.
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