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 notori-ously unreliable because up to 2/3 of DVT episodes are clinically silent and pa-tients 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 con-tinuous monitoring of DVT at the point of care. This paper presents the concep-tual 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 as-sessment of DVT risk and guide the automated scanning via an intelligent deci-sion 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).

This is the presentation of the accepted paper (citation bellow) as presented in the EMBEC 2024, Portorož , Slovenia.  The Version of Record of this contribution is published in Jarm, T., Šmerc, R., Mahnič-Kalamiza, S. (eds) 9th European Medical and Bio-logical Engineering Conference. EMBEC 2024. IFMBE Proceedings, vol 113. Springer, Cham, and is available online at https://doi.org/10.1007/978-3-031-61628-0_36