Development of a digital and noninvasive diagnostic tool to measure capillary refill time on patient with severe circulatory failure (DiCART)
Total budget: €196k
Total Funding: €196k
DicarTech is developing an innovative non-invasive diagnostic medical device for intensive care, pediatry, emergency physicians. DiCART measures the tissue perfusion for patients in severe circulatory failure. Critical situation which, without treatment, can lead to multi-organ failure, lethal situation. DiCART enables reliable, accurate rapid diagnosis to objectively appreciate the efficiency of the therapies involved. Replaces manual and visual assessments, imprecise. Patented, Europe and USA. DiCART is used with a disposable protector, allowing repeated sales and a cost to the user proportional to the use of the device. The time to market is estimated 18-24 months. A very positive independent market study has been done. The market adressed by Dicartech is estimated 200 millions € in Europe
DICARTECH SAS, France
Dicartech has been created by 2 expert biomedical and intensivist to design, develop, and industrialize medical device for automatic diagnosis of tissue perfusion. The device is dedicated to emergency department to replace manual analogic evaluation. The start-up is organized (fabless) to achieve developpment, certification and marketing of the product.
Emka-medical GmbH, Germany
emka MEDICAL is a living quality management organisation. A spin-off of former MHM Michael Harzbecher Medizintechnik GmbH, the key staff of this young company (founded 2012) has together more than 80 years experience in the medical device sector, especially in the following areas:
sensors for physiological parameters
injection molded plastics
emka MEDICAL (under its former name CGS Sensors GmbH) got recognition
Laboratoire Mathématique Image Application University La Rochelle, France
Mia Lab in La Rochelle Université has developed a strong expertise in mathematical image processing and analysis, mainly with multidimensional and/or multimodal acquisition for extracting the relevant medical information. Breakthrough approaches are dedicated to the design of new specific tools for color information treatment as well as for the extraction of relevant information in multidimensional signals. The statistical descriptors are exploited for constructing new deep learning algorithms. Beside the production of efficient algorithms of segmentation, classification, restauration, etc, theoretical works are devoted to the mathematical aspects of harmonic theory for higher dimensional signals. The team is composed of pure and applied mathematicians together with researchers in signal processing and computer science. MIA skills and know-how were for instance labeled by the ITEA board in 2015, by the PIA board in 2016 for collaborative projects with industrial partners, based on medical imaging.