{"title":"利用接收信号强度和质心算法对人体内超宽带无线内窥镜胶囊进行定位","authors":"Memduh Suveren, Rustu Akay, M. Kanaan","doi":"10.11121/ijocta.2022.1146","DOIUrl":null,"url":null,"abstract":"Wireless capsule endoscopy (WCE) is used for imaging and diagnosing diseases in the gastrointestinal (GI) system. The location of the disease detected by WCE is still an important problem. Location information is very important for the surgical or drug treatment of the detected disease. In this study, RSS-based centroid algorithm has been used in order to accurately predict the capsule position on a sample data set. The effect of different parameters such as number of sensors used on the proposed mathematical model, location of sensors on positioning is analyzed in detail. The results show that a precise position detection is possible with fewer sensors positioned correctly. As a result, the positioning error with the correctly selected sensors is reduced by approximately 55%. In addition, the performance of the proposed method was compared with the classical centroid algorithm and more than 50% improvement was achieved.","PeriodicalId":37369,"journal":{"name":"International Journal of Optimization and Control: Theories and Applications","volume":"1965 1","pages":""},"PeriodicalIF":2.2000,"publicationDate":"2022-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Localization of an ultra wide band wireless endoscopy capsule inside the human body using received signal strength and centroid algorithm\",\"authors\":\"Memduh Suveren, Rustu Akay, M. Kanaan\",\"doi\":\"10.11121/ijocta.2022.1146\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Wireless capsule endoscopy (WCE) is used for imaging and diagnosing diseases in the gastrointestinal (GI) system. The location of the disease detected by WCE is still an important problem. Location information is very important for the surgical or drug treatment of the detected disease. In this study, RSS-based centroid algorithm has been used in order to accurately predict the capsule position on a sample data set. The effect of different parameters such as number of sensors used on the proposed mathematical model, location of sensors on positioning is analyzed in detail. The results show that a precise position detection is possible with fewer sensors positioned correctly. As a result, the positioning error with the correctly selected sensors is reduced by approximately 55%. In addition, the performance of the proposed method was compared with the classical centroid algorithm and more than 50% improvement was achieved.\",\"PeriodicalId\":37369,\"journal\":{\"name\":\"International Journal of Optimization and Control: Theories and Applications\",\"volume\":\"1965 1\",\"pages\":\"\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2022-07-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Optimization and Control: Theories and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.11121/ijocta.2022.1146\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MATHEMATICS, APPLIED\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Optimization and Control: Theories and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.11121/ijocta.2022.1146","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
Localization of an ultra wide band wireless endoscopy capsule inside the human body using received signal strength and centroid algorithm
Wireless capsule endoscopy (WCE) is used for imaging and diagnosing diseases in the gastrointestinal (GI) system. The location of the disease detected by WCE is still an important problem. Location information is very important for the surgical or drug treatment of the detected disease. In this study, RSS-based centroid algorithm has been used in order to accurately predict the capsule position on a sample data set. The effect of different parameters such as number of sensors used on the proposed mathematical model, location of sensors on positioning is analyzed in detail. The results show that a precise position detection is possible with fewer sensors positioned correctly. As a result, the positioning error with the correctly selected sensors is reduced by approximately 55%. In addition, the performance of the proposed method was compared with the classical centroid algorithm and more than 50% improvement was achieved.