Descrizione del progetto
La robotica ridefinirà l’efficienza della colonscopia
L’efficacia della colonscopia nel rilevare il cancro dipende dall’abilità dell’operatore, il che rappresenta una sfida dato la crescente domanda di screening, soprattutto nei Paesi europei con programmi nazionali in merito. Partendo da questo presupposto, il progetto IRE, finanziato dall’UE, si propone di trasformare la tecnologia tradizionale degli endoscopi. In particolare, unirà i dati dell’operatore umano, un’innovativa modellazione bio-meccanica, il feedback sensoriale e l’addestramento di fantocci robotici morbidi. Il progetto sfrutta un vasto set di dati relativo a oltre 2 000 effettive colonscopie, combinando l’esperienza reale con la formazione simulata su modelli biomeccanici. Il progetto produrrà robot intelligenti in grado di orientarsi autonomamente tra le complessità dell’anatomia umana, elevando gli standard per la diagnosi precoce del cancro.
Obiettivo
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.
Campo scientifico
- 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
Parole chiave
Programma(i)
Invito a presentare proposte
HORIZON-CL4-2023-DIGITAL-EMERGING-01
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HORIZON-RIA - HORIZON Research and Innovation ActionsCoordinatore
1165 Kobenhavn
Danimarca