{"title":"偏最小二乘法与神经网络在无创血糖监测系统中的比较分析","authors":"Chuah Zheng Ming, P. Raveendran, Poh Sin Chew","doi":"10.1109/ICBPE.2009.5384079","DOIUrl":null,"url":null,"abstract":"A non-invasive blood glucose monitoring system with six laser diodes is used to obtain a total of 290 NIR spectra from the Oral Glucose Tolerance Test (OGTT) experiment with the participation of a healthy volunteer over 4 days. Each laser diode operates at the discrete wavelengths between 1500nm and 1800nm with the power of 6mW each. A comparative analysis using the Partial Least Squares (PLS) model and the Neural Network (NN) model is studied. The study shows that the NN model performs better than the PLS model due to the presence of nonlinearity in the collected data. The presence of the nonlinearity is tested by using the Durbin-Watson test.","PeriodicalId":384086,"journal":{"name":"2009 International Conference on Biomedical and Pharmaceutical Engineering","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"A comparison analysis between partial least squares and Neural Network in non-invasive blood glucose concentration monitoring system\",\"authors\":\"Chuah Zheng Ming, P. Raveendran, Poh Sin Chew\",\"doi\":\"10.1109/ICBPE.2009.5384079\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A non-invasive blood glucose monitoring system with six laser diodes is used to obtain a total of 290 NIR spectra from the Oral Glucose Tolerance Test (OGTT) experiment with the participation of a healthy volunteer over 4 days. Each laser diode operates at the discrete wavelengths between 1500nm and 1800nm with the power of 6mW each. A comparative analysis using the Partial Least Squares (PLS) model and the Neural Network (NN) model is studied. The study shows that the NN model performs better than the PLS model due to the presence of nonlinearity in the collected data. The presence of the nonlinearity is tested by using the Durbin-Watson test.\",\"PeriodicalId\":384086,\"journal\":{\"name\":\"2009 International Conference on Biomedical and Pharmaceutical Engineering\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Conference on Biomedical and Pharmaceutical Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICBPE.2009.5384079\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Conference on Biomedical and Pharmaceutical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICBPE.2009.5384079","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A comparison analysis between partial least squares and Neural Network in non-invasive blood glucose concentration monitoring system
A non-invasive blood glucose monitoring system with six laser diodes is used to obtain a total of 290 NIR spectra from the Oral Glucose Tolerance Test (OGTT) experiment with the participation of a healthy volunteer over 4 days. Each laser diode operates at the discrete wavelengths between 1500nm and 1800nm with the power of 6mW each. A comparative analysis using the Partial Least Squares (PLS) model and the Neural Network (NN) model is studied. The study shows that the NN model performs better than the PLS model due to the presence of nonlinearity in the collected data. The presence of the nonlinearity is tested by using the Durbin-Watson test.
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