Video Capsule Endoscopy Designs for AI-assisted Medical Imaging of the Human Gastrointestinal Tract

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Nurul Huda binti Abdullah
Mohd Rahman bin Abdullah

Abstract

Monitoring the gastrointestinal tract in real-time, in a both safe and comfortable manner, is informative for diagnosing and treating various diseases of the gastrointestinal tract. The intricacy of the Gastrointestinal (GI) tract in humans and other animals, along with the potential complications that may arise, necessitates a comprehensive understanding and interaction with its different parts and other systems. By gaining imaging access to the GI tract, we can not only detect physiological and pathophysiological signals from the human body but also utilize ingestible electronics in medical diagnostics and therapy. This allows for direct interaction with the digestive system, enabling a more extensive collection of data and the administration of treatment. In this review, we discuss the gastrointestinal tract and the guidelines set by the Food and Drug Administration (FDA) for wireless telemetric medical devices that can be ingested. We discuss capsule systems that are in medical use and under research development, while mentioning the individual components that are utilized for gastrointestinal health monitoring. We also discuss the ongoing research on biocompatible materials and batteries, edible electronics, and alternative energy sources for powering the ingestible capsule systems. To assess the safety and effectiveness of ingestible capsule procedures, we examine the results from clinical studies and analyze key performance indicators. Finally, we discuss the current challenges and future trends to address the concerns related to health risks, the clinical testing and approval process, and the user acceptance of the technology by both patients and clinicians.

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How to Cite
Abdullah, N. H. binti, & Abdullah, M. R. bin. (2022). Video Capsule Endoscopy Designs for AI-assisted Medical Imaging of the Human Gastrointestinal Tract . AI, IoT and the Fourth Industrial Revolution Review, 12(11), 11–22. Retrieved from https://scicadence.com/index.php/AI-IoT-REVIEW/article/view/35
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Articles
Author Biographies

Nurul Huda binti Abdullah, Department of Agricultural Engineering at College of Agriculture Malaya.

1. Nurul Huda binti Abdullah, Department of Agricultural Engineering at College of Agriculture Malaya.

Mohd Rahman bin Abdullah, Department of Computer Engineering, Universiti Malaysia Perlis, Arau, Perlis, Malaysia

2. Mohd Rahman bin Abdullah, Department of Computer Engineering, Universiti Malaysia Perlis, Arau, Perlis, Malaysia