Automatic Sleep Stage Classification and Sleep Efficiency Estimation Using Reduced Features of ECG and Activity Signals

碩士 === 國立成功大學 === 電機工程學系碩博士班 === 100

Bibliographic Details
Main Authors:	Guan-RongShih, 施冠榮
Other Authors:	Jeen-Shing Wang
Format:	Others
Language:	en_US
Published:	2012
Online Access:	http://ndltd.ncl.edu.tw/handle/24994359255992006737

id	ndltd-TW-100NCKU5442026
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spelling	ndltd-TW-100NCKU54420262015-10-13T20:51:36Z http://ndltd.ncl.edu.tw/handle/24994359255992006737 Automatic Sleep Stage Classification and Sleep Efficiency Estimation Using Reduced Features of ECG and Activity Signals 利用心電及活動訊號之特徵選取於自動睡眠階層判讀及睡眠效率估測之開發 Guan-RongShih 施冠榮碩士國立成功大學電機工程學系碩博士班 100 Jeen-Shing Wang 王振興 2012 學位論文 ; thesis 87 en_US
collection	NDLTD
language	en_US
format	Others
sources	NDLTD
description	碩士 === 國立成功大學 === 電機工程學系碩博士班 === 100
author2	Jeen-Shing Wang
author_facet	Jeen-Shing Wang Guan-RongShih 施冠榮
author	Guan-RongShih 施冠榮
spellingShingle	Guan-RongShih 施冠榮 Automatic Sleep Stage Classification and Sleep Efficiency Estimation Using Reduced Features of ECG and Activity Signals
author_sort	Guan-RongShih
title	Automatic Sleep Stage Classification and Sleep Efficiency Estimation Using Reduced Features of ECG and Activity Signals
title_short	Automatic Sleep Stage Classification and Sleep Efficiency Estimation Using Reduced Features of ECG and Activity Signals
title_full	Automatic Sleep Stage Classification and Sleep Efficiency Estimation Using Reduced Features of ECG and Activity Signals
title_fullStr	Automatic Sleep Stage Classification and Sleep Efficiency Estimation Using Reduced Features of ECG and Activity Signals
title_full_unstemmed	Automatic Sleep Stage Classification and Sleep Efficiency Estimation Using Reduced Features of ECG and Activity Signals
title_sort	automatic sleep stage classification and sleep efficiency estimation using reduced features of ecg and activity signals
publishDate	2012
url	http://ndltd.ncl.edu.tw/handle/24994359255992006737
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Automatic Sleep Stage Classification and Sleep Efficiency Estimation Using Reduced Features of ECG and Activity Signals

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