There is significant interest in exploring the human body’s internal activities and measuring important parameters to understand, treat and diagnose the digestive system environment and related diseases. Wireless capsule endoscopy (WCE) is widely used for gastrointestinal (GI) tract exploration due to its effectiveness as it provides no pain and is totally tolerated by the patient. Current ingestible sensing technology provides a valuable diagnostic tool to establish a platform for monitoring the physiological and biological activities inside the human body. It is also used for visualizing the GI tract to observe abnormalities by recording the internal cavity while moving. However, the capsule endoscopy is still passive, and there is no successful locomotion method to control its mobility through the whole GI tract. Drug delivery, localization of abnormalities, cost reduction and time consumption are improvements that can be gained from having active ingestible WCEs. In this article, the current technological developments of ingestible devices including sensing, locomotion and navigation are discussed and compared. The main features required to implement next-generation active WCEs are explored. The methods are evaluated in terms of the most important features such as safety, velocity, complexity of design, control, and power consumption.
Conventional radiological and endoscopic techniques utilizing long tubes were ineffective in visualizing the small bowel mucosa until the development of wireless capsule endoscopy (WCE). WCE is a revolutionary endoscopic technology that can diagnose the complete gastrointestinal tract. However, the existing capsule technologies are passive, and thus they cannot be navigated to or held in a specific location. The design of an active capsule will present the opportunity to move and stop a device at any targeted locations leading to numerous medical applications such as drug delivery or collecting tissue samples for examinations in the laboratory. This paper implements a new locomotion methodology for WCE systems using an electromagnetic platform. The platform produces a dynamic electromagnetic field to control the motion of the capsule. The strength and the direction of the electromagnetic field that is generated by the platform are continuously adjusted in order to maintain the equilibrium state during the capsule movement. We present the detailed design of the proposed platform with an experimental setup with polyvinyl chloride tubes and ex vivo to demonstrate the performance of the capsule motion.
This work investigates the efficacy of high-pressure torsion (HPT), as a severe plastic deformation mechanism for processing plain and silicon-carbide-reinforced AA6061, with the broader objective of using the technique for improving the properties of lightweight materials for a range of objectives. The interactions between input variables, such as the pressure and equivalent strain (εeq) applied during HPT processing, and the presence of SiCp and response variables, like the relative density, grain refinement, homogeneity of the structure, and the mechanical properties of the AA6061 aluminum matrix, were investigated. Hot compaction (HC) of the mixed powders followed by HPT were employed to produce AA6061 discs with and without 15% SiCp. The experimental findings were then analyzed statistically using the response surface methodology (RSM) and a machine learning (ML) approach to predict the output variables and to optimize the input parameters. The optimum combination of HPT process parameters was confirmed by the genetic algorithm (GA) and ML approaches. Furthermore, the constructed ML and RSM models were validated experimentally by HPT processing the same material under new conditions not fed into the models and comparing the experimental results to those predicted by the model. From the ML and RSM models, it was found that processing the AA6061/SiCp composite HPT via four revolutions at 3 GPa produced the highest mechanical properties coupled with significant grain refinement compared to the HC condition. ML analysis revealed that the equivalent strain induced by the number of revolutions was the most effective parameter for grain refinement, whereas the presence of SiCp played the highest role in improving both the hardness values and the compressive strength of the AA6061 matrices.
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