Research Article Monitoring and Analysis Solid Formulation Dissolution Phenomenon with Image Recognition Technologies Haoyu Wang, 1 Chiew Foong Kwong , 1,2 Qianyu Liu, 3 Junyao Liu, 4 Zhixin Liu, 5 Boon Giin Lee, 6 and Liang Huang 1 1 Department of Electrical and Electronic Engineering, University of Nottingham Ningbo China, Ningbo, China 2 Next Generation Internet of Everything (NGIoE) Laboratory, University of Nottingham Ningbo China, Ningbo, China 3 School of Information Science and Engineering, NingboTech University, Ningbo, China 4 Central Research Institute, Shanghai Pharmaceutical Holding Co., Ltd., Shanghai, China 5 Department of Outpatient, Liaoning Blood Embolus Medical Centre, Shenyang, China 6 Department of Computer Science, University of Nottingham Ningbo China, Ningbo, China Correspondence should be addressed to Chiew Foong Kwong; sgxhw1@nottingham.edu.cn Received 5 July 2022; Revised 12 August 2022; Accepted 22 August 2022; Published 14 September 2022 Academic Editor: Tao Zhou Copyright © 2022 Haoyu Wang et al. is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. e dissolution test has become the most important quality index in the research and development of solid formulation, especially the evaluation of drug bioequivalence. However, it had low operability, was tedious, and was always overlooked. e previously related studies required a fixed tablet and analysed the recorded video by disso GUARO PRO and Microsoft Paint ™ . erefore, we have developed a novel image recognition system to automatically track the moving tablet and analyse the volume change at the same time. Image recognition technology is often used to monitor the dissolution process. e camera system with visible light and infrared camera functions was placed on the dissolution tester. e system collects the plate image for binary processing and then records and calculates its pixel area, which can automatically record the volume change of the tablet in the dissolution test, no matter disintegration or corrosion. 1. Introduction Image recognition technology is an important tool to monitor different experimental phenomena in the absence of experimental personnel. Recording and analysis of dis- solution test videos are for studying tablet behavior during the dissolution test. In Felicijan’s study [1], an iron wire was used to fix the tablet at the bottom of the dissolution cup. en, a 10-second video of the dissolution process was recorded at each sampling point. After that, the video is fed into software named disso GUARO PRO to reduce the noise of particles in the dissolution liquid before Microsoft Paint ™ calculates the relative volume of the tablet. A red-light source was used to record photo instability tablets. e fixed tablet can provide a stable image to capture but may influence the dissolution result. Besides, real-time monitoring cannot be realized by recording the video and then entering it into other software, which also makes monitoring more com- plicated. e red-light source can basically solve the re- cording of photo instability tablet behavior, but infrared ray with lower light particle energy is a better choice. Li et al. [2] also use a camera to record the dissolution test. Morita et al. [3] chose three tablets to calculate the trim size of tablets, which were fixed at the bottom of the dissolution cup by an iron wire. A camera on the top of the dissolution cup recorded the changes on the surface of these three tablets, and the space between these three tablets was used to cal- culate the area changes on the tablet surface. Nevertheless, based on the guidance of drug administration in all coun- tries, both tablet fixing and multitablet dissolution tests were limited. Chinese patents 201721009959 [4] were focused on carrying out the overall design of the monitoring dissolution equipment. However, its function is relatively simple, only with real-time monitoring and video recording functions. In Hindawi Computational Intelligence and Neuroscience Volume 2022, Article ID 3997870, 16 pages https://doi.org/10.1155/2022/3997870