Sub Projects
Thorax-study
Clinical validation of a novel ultrasound probe (RescueDoppler) during physiological perturbations and initiation of- and weaning from cardiopulmonary bypass in adult, cardiac surgery patients.
In the current project we use RescueDoppler and measure blood flow to the brain in subjects aged 18-80 years, male and female, accepted for cardiac surgery in the Department of Cardiothoracic surgery in St.Olavs hospital in Trondheim, Norway. We intend to include 42 patients and have until now (June 2024) included 21 patients.
Primary objective is to evaluate if the RescueDoppler device is noninferior to conventional Doppler ultrasound, a standard method to measure blood flow curves and -velocities, by comparing the flow patterns and velocities recorded with the two methods.
Secondary objectives are to compare the blood flow velocity trends between both technologies, to synchronize the timing of measurements with hemodynamic physiologic values (ECG, blood pressure) and to evaluate the accuracy and functionality of the RescueDoppler fastening device
REACT
RescueDoppler Assessment for Cardiac arresT
The REACT project is located within Nord University's PhD program in the Science of Professions. It consists of three individual research projects, each aiming to foster knowledge of how the RescueDoppler system can affect cardiac arrest management in the ambulance service.
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The first project aims to explore existing barriers and enablers towards using chest compression feedback devices in the ambulance service. The results of this study will be used to develop the RescueDoppler system further.
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The second project will assess the RescueDoppler’s capability to detect variations in chest compressions by measuring the blood flow in the carotid artery using the RescueDoppler system.
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The third study assesses the RescueDoppler’s ability to detect and differentiate between true and false pulseless electrical activity (PEA).
RAID
RescueDoppler AI Assessment
- an AI assistant for improved outcome after Cardiac arrest
This project aims to further develop RescueDoppler - a new and proprietary solution for improved outcome after sudden cardiac arrest that measures blood flow continuously and non-invasively in the carotid artery. The main goal of this work is to extend the RescueDoppler technology with AI based tools that can give real-time assistance regarding the quality of the chest compressions in the case of a sudden cardiac arrest as well as detect automatically successful restoration of blood flow.
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The initial AI model will be developed annotating cardiac arrest events from the experimental study including 15 pigs. The second part will use data from the clinical study.