Projektbeschreibung
Robotik zur Neudefinition von Effizienz von Kolonoskopien
Die Wirksamkeit der Kolonoskopie bei der Erkennung von Krebs hängt von den Fähigkeiten der behandelnden Person ab, was angesichts der steigenden Nachfrage nach Vorsorgeuntersuchungen, insbesondere in europäischen Ländern mit nationalen Programmen, eine Herausforderung darstellt. Vor diesem Hintergrund zielt das EU-finanzierte Projekt IRE darauf ab, die herkömmliche Endoskoptechnologie zu verändern. Konkret sollen Daten der bedienenden Person, innovative biomechanische Modelle, sensorisches Feedback und Soft-Robotik-Phantomtraining zusammengeführt werden. Das Projektteam nutzt einen umfangreichen Datensatz von über 2 000 realen Kolonoskopien und kombiniert reale Erfahrungen mit simuliertem Training an biomechanischen Modellen. Das Ergebnis werden intelligente Roboter sein, die in der Lage sind, autonom durch die Feinheiten der menschlichen Anatomie zu steuern und den Standard für die Krebsfrüherkennung zu erhöhen.
Ziel
In Intelligent Robotic Endoscopes (IRE) for Improved Healthcare Services we envision creating intelligent robotics solutions, extending current endoscope technology with robotics control that is based on learning from currently collected human operator data, coupled with novel bio-mechanical modeling techniques, and sensory feedback as well as soft robotics phantom for training.
The challenge with colonoscopy is that the success rate of detecting cancer depends on the skills of the clinician that operates the endoscope. From a health and societal perspective, the number of colonoscopies is bound to increase as they are the only way to screen patients for early cancer detection. Many European countries have national screening programs. This is a very big market in need of improved technology.
IRE enables a new generation of intelligent robots that through data, simulation and learning can interact with the interior of a living human while communicating with a human operator. The huge variation of human anatomy and the dynamic effect of human physiology make it a complicated navigational task to use endoscopes. Entanglement, haemorrhage, and perforation risks create a critical and difficult environment to navigate autonomously in where even trained human operators meet challenges. We exploit one of the largest datasets on real-life colonoscopies with more than 2,000 operations to learn safe navigation, combined with simulated training on a population of biomechanical models of the abdominal region.
IRE boosts the design and configuration of the robotic endoscope using digital twins and simulation, and careful inclusion of clinicians will speed up the process of integration. IRE will raise the level of autonomy by building upon simulation, imaging, and learning to yield an increased interpretation and understanding of the complex real- world environments, capable of anticipating the effect of human motions, adapting and replanning to avoid entanglement.
Wissenschaftliches Gebiet
- medical and health sciencesbasic medicineanatomy and morphology
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringroboticssoft robotics
- medical and health sciencesclinical medicineoncology
- medical and health sciencesbasic medicinephysiology
- medical and health scienceshealth scienceshealth care services
Schlüsselbegriffe
Programm/Programme
Aufforderung zur Vorschlagseinreichung
HORIZON-CL4-2023-DIGITAL-EMERGING-01
Andere Projekte für diesen Aufruf anzeigenFinanzierungsplan
HORIZON-RIA - HORIZON Research and Innovation ActionsKoordinator
1165 Kobenhavn
Dänemark