Maneuverable Capsule Endoscope Based on Gimbaled Ducted-Fan System: Concept and Simulation Results
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Wireless capsule endoscopes are a growing research area because they can be easily swallowed by patients to capture images of the digestive system without pain. However, a drawback of current capsule endoscopes is that most use passive motion. To overcome this drawback, a maneuverable capsule endoscope (MCE) based on a gimbaled ducted-fan (GDF) system is proposed in this study. The system design, prototype development of the GDF system, and associated modeling and simulation are presented. The concept of the GDF is adopted from the thrust-vector control algorithm of a space shuttle. To prevent organ damage, the ducted fan, which generates and controls the thrust required for achieving maneuverability, is mounted on a gimbal structure. A scaled-up prototype of the GDF system was manufactured. The overall conceptual design of the MCE based on the GDF system is presented. A flow simulation and a three-dimensional path-following simulation are performed to evaluate the proposed MCE’s applicability. The mean terminal velocity of the 6:1 scaled-up MCE prototype was calculated from flow simulation to be 0.6047, 0.5941, and 0.9204 m/s for the three postures of the GDF system, respectively, which represented the three translational degrees of freedom. For the 1:1 scale prototype, the mean terminal velocity was calculated to be 0.1147, 0.1127, and 0.1746 m/s for the above three postures, respectively. The proposed MCE dynamic model follows the desired path profile when the Lyapunov stability-based path-following algorithm was applied to it. In summary, the terminal velocity achieved in this research is sufficient for maneuvering inside the stomach organ. The results show that the MCE concept could be used for detecting and diagnosing abnormalities in the digestive system.
KeywordsManeuverable capsule endoscope (MCE) Wireless capsule endoscope (WCE) Gimbaled ducted-fan (GDF) system Flow simulation Three-dimensional (3D) path-following algorithm
This research was supported by Grant 0320140030 from the SNUH Research Fund and Global Ph. D. Fellowship Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (Grant 2014H1A2A1020384).
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