M. Noshiro, H. Shindou, Y. Fukuoka, M. Ishikawa, H. Minanitani, K. Sakamoto, A. Tanakadate, S. Nebuya
{"title":"NARMAX model of the pCO/sub 2/ control system in man estimated by neural computation","authors":"M. Noshiro, H. Shindou, Y. Fukuoka, M. Ishikawa, H. Minanitani, K. Sakamoto, A. Tanakadate, S. Nebuya","doi":"10.1109/IEMBS.1996.647616","DOIUrl":null,"url":null,"abstract":"Subjects voluntarily inspire a gas mixture in which the CO/sub 2/ concentration is changed stepwise or randomly. The respiratory flow rate and pCO/sub 2/ in the inspired and expired gases are measured to yield the end-tidal pCO/sub 2/ and minute ventilation, which are the input and output of the pCO/sub 2/ control system, respectively. A NARMAX (Nonlinear Auto-Regressive Moving Average with eXogeneous inputs) model of the system is estimated using a three-layered feedforward neural network. The estimated model contains terms, y(t-1), x(t-1), x(t-2), X/sup 2/(t-2) and y(t-1)x(t-2). A measure of nonlinearity calculated from the data used for estimation shows the pCO/sub 2/ control system in most subjects has a nonlinearity which cannot be neglected.","PeriodicalId":20427,"journal":{"name":"Proceedings of 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society","volume":"64 1","pages":"1693-1694 vol.4"},"PeriodicalIF":0.0000,"publicationDate":"1996-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEMBS.1996.647616","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Subjects voluntarily inspire a gas mixture in which the CO/sub 2/ concentration is changed stepwise or randomly. The respiratory flow rate and pCO/sub 2/ in the inspired and expired gases are measured to yield the end-tidal pCO/sub 2/ and minute ventilation, which are the input and output of the pCO/sub 2/ control system, respectively. A NARMAX (Nonlinear Auto-Regressive Moving Average with eXogeneous inputs) model of the system is estimated using a three-layered feedforward neural network. The estimated model contains terms, y(t-1), x(t-1), x(t-2), X/sup 2/(t-2) and y(t-1)x(t-2). A measure of nonlinearity calculated from the data used for estimation shows the pCO/sub 2/ control system in most subjects has a nonlinearity which cannot be neglected.
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