作者
Eleni Kaldoudi,Vaidotas Marozas,Jurkonis Rytis,Nicolas Pousset,Mathieu Legros,Marco Kircher,D. Novikov,Andrius Sakalauskas,Pavlos Moustakidis,Babajide O. Ayinde,Lara Alessia Moltani,Susann Balling,Antti Vehkaoja,Niku Oksala,Andrius Macas,Neringa Balčiūnienė,Maria Bigaki,Michael Potoupnis,Sousana Κ. Papadopoulou,Elvira Grandone,Maxime Gautier,Sabrina Bouda,Cord Schloetelburg,Thorsten Prinz,Pietro Dionisio,S.-P. Anagnostopoulos,Ioanna Drougka,Frans Folkvord,George Drosatos,Stylianos Didaskalou
摘要
Deep vein thrombosis (DVT) is the formation of a blood clot within the deep veins, most commonly those of the lower limbs, causing obstruction of blood flow. In 50% of people with DVT, the clot eventually breaks off and travels to the lung to cause pulmonary embolism. Clinical assessment of DVT is notoriously unreliable because up to 2/3 of DVT episodes are clinically silent and patients are symptom free even when pulmonary embolism has developed. Early diagnosis of DVT is crucial, and despite the progress made in ultrasound imaging and plethysmography techniques, there is a need for new methods to enable continuous monitoring of DVT at the point of care. This paper presents the conceptual design and methodology towards a novel wearable diagnostic device for point-of-care, operator-free, continuous monitoring in patients with high DVT risk. The device will combine novel wearable hardware for ultrasound imaging and impedance plethysmography with autonomous, AI driven DVT detection, to allow continuous monitoring for blood clot formation in the lower limb. Activity and other physiological measurements will be used to provide a continuous assessment of DVT risk and guide the automated scanning via an intelligent decision support unit that will provide accurate monitoring and alerts. The work is supported by the Horizon project ThrombUS+ co-funded by the European Union. (Grant Agreement No. 101137227).