DESIGN AND VALIDATION OF AN IN VIVO LONG-TERM ATTACHMENT CAPSULE ROBOT

The invention of capsule endoscopy (CE) made the non-invasive monitoring of the entire small bowel possible and became the primary means for diagnosing small bowel pathology. In the last decade, capsule robots have been transformed from diagnostic devices into a widely studied biomedical platform with the potential for active locomotion, drug delivery and therapeutic capabilities. To perform accurate on-site drug release and therapy, it is necessary for a capsule robot to be able to attach to the intestinal tissue and maintain its position long-term. Design challenges derive from the task of long-term mucosal adhesion which requires firm, quick-response attachment without causing unacceptable trauma or complications. In this work, we initiate a study to address the challenges associated with long-term attachment and explore possible solutions. First, a method to quantify the attachment behavior of parasites was developed. This method could be applied to studies of parasite biomechanics and the results may help medical device researchers better mimic the unique functional morphology of intestinal parasites. Second, a tissue attachment mechanism inspired by the parasite attachment approach was designed, optimized and tested for safety and adhesive capabilities on animal models in vitro and in vivo. Next, a long-term, non-invasive, non-restrictive implantation capsule robot for delivering and implanting a biosensor within the tissue attachment mechanism in the intestine was developed. Testing on a live porcine model provided evidence that this is a promising approach for implanting a biosensor within the small intestine. Finally, a finite element method for simulating the attachment interaction between the intestine and capsule was applied with the goal of providing a detailed guide to further system optimization. The prototype of this study offers more than 40 hours in vivo attachment without causing serious damage and has the potential to be translated into clinical usage. Advisor: Benjamin S. Terr