@inproceedings{ba5e5ee2541c4c85bab64cb8d74853ac,
title = "Recognizing aspiration presence using model parameter classification from microwave doppler signals",
abstract = "A study on the healthcare application is very important for the solitary death in aging society. Many previous works had been proposed a detection method of aspiration using the non-contact radar. But the works are only in subjects with sitting in a chair. We consider that user falls down in the state when he happen abnormal situation as daily life. In this study, we focus on the detection of {"}aspiration{"} or {"}apnea{"} for the lying position, because the final decision of the life or death is aspiration. As initial stage of the system, we propose the recognition method for the presence of aspiration with lying position under the low-disturbance environment from microwave Doppler signals by using support vector machine (SVM).",
author = "Shuhei Inui and Kosuke Okusa and Kurato Maeno and Toshinari Kanakura",
note = "Publisher Copyright: {\textcopyright} 2012 Newswood Limited. All rights reserved.; 2012 World Congress on Engineering and Computer Science, WCECS 2012 ; Conference date: 24-10-2012 Through 26-10-2012",
year = "2012",
language = "English",
isbn = "9789881925114",
series = "Lecture Notes in Engineering and Computer Science",
publisher = "Newswood Limited",
pages = "509--512",
editor = "Jon Burgstone and Ao, {S. I.} and Craig Douglas and Grundfest, {W. S.}",
booktitle = "International MultiConference of Engineers and Computer Scientists, IMECS 2012",
}