Wireless capsule endoscopy: from diagnostic devices to multipurpose robotic systems View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2007-04

AUTHORS

Andrea Moglia, Arianna Menciassi, Marc Oliver Schurr, Paolo Dario

ABSTRACT

In the recent past, the introduction of miniaturised image sensors with low power consumption, based on complementary metal oxide semiconductor (CMOS) technology, has allowed the realisation of an ingestible wireless capsule for the visualisation of the small intestine mucosa. The device has received approval from Food and Drug Administration and has gained momentum since it has been more successful than traditional techniques in the diagnosis of small intestine disorders. In 2004 an esophagus specific capsule was launched, while a solution for colon is still under development. However, present solutions suffer from several limitations: they move passively by exploiting peristalsis, are not able to stop intentionally for a prolonged diagnosis, they receive power from an internal battery with short length, and their usage is restricted to one organ, either small bowel or esophagus. However the steady progresses in many branches of engineering, including microelectromechanical systems (MEMS), are envisaged to affect the performances of capsular endoscopy. The near future foreshadows capsules able to pass actively through the whole gastrointestinal tract, to retrieve views from all organs and to perform drug delivery and tissue sampling. In the long term, the advent of robotics could lead to autonomous medical platforms, equipped with the most advanced solutions in terms of MEMS for therapy and diagnosis of the digestive tract. In this review, we discuss the state of the art of wireless capsule endoscopy (WCE): after a description on the current status, we present the most promising solutions. More... »

PAGES

235-243

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10544-006-9025-3

DOI

http://dx.doi.org/10.1007/s10544-006-9025-3

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1018486350

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/17160703


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