Patient monitoring consists of the repeated or continuous measurement of important physiological parameters that can inform clinicians on the patient’s health status. Monitoring of parameters such as heart rate and rhythm, respiratory rate, blood pressure, blood-oxygen saturation, and many others has become a crucial tool for the care of critically ill patients, but also for (home) monitoring of patients at risk.
Despite improvements in anesthesia and post-operative care, up to 17% of patients undergoing surgery suffer from serious post-operative complications. In case of respiratory failure, patients need to be connected to a mechanical ventilator until they can breathe on their own. Patient-ventilator asynchrony can occur during mechanical ventilation, possibly causing damage to the lungs and increasing the risk of mortality in the intensive care unit. Timely identification of patients at risk is crucial.
Clinical decision support systems can provide clinicians with assistance during the decision-making process by combining patient data acquired at all stages of patient care to generate a case specific advice. The BM/d lab is devoted to development of statistical models for timely prediction of patient deterioration and for detection and classification of patient-ventilator asynchronies, combining model-driven and data-driven approaches. In tight collaboration with clinical partners, we focus on interpretable methods that allow including domain knowledge, and at the same time can provide the clinicians with novel insights. In parallel, we seek do develop novel non-invasive, non-obtrusive solutions to enable long-term monitoring and more accurate characterization of patient’s vascular status, with special attention to technologies that can also be translated to home monitoring settings. This involves continuous hemodynamic monitoring by Doppler ultrasound, complemented by assessment of vascular stiffness and by modelling the (patho)physiological transfer function between peripheral and central circulation. Assessment of respiratory efforts by electromyography is also investigated to contribute to optimal assisted ventilation, while analysis of sweat metabolites by advanced sensing technology is employed to infer their blood concentrations.
Patient monitoring research is carried out in tight collaboration with the Catharina Hospital Eindhoven (the Netherlands) and Philips.