کتاب های Hernández-Tamames, Juan Antonio; Mato Abad, Virginia; García-Álvarez, Roberto; González-Zabaleta, Javier; Pereira-Loureiro, Javier; Álvarez-Linera, Juan

download pdf Effect of water T2 shortening in the quantification of in-vitro proton MR spectroscopy, دانلود Effect of water T2 shortening in the quantification of in-vitro proton MR spectroscopy,Hernández-Tamames, Juan Antonio; Mato Abad, Virginia; García-Álvarez, Roberto; González-Zabaleta, Javier; Pereira-Loureiro, Javier; Álvarez-Linera, Juan, کتاب های Hernández-Tamames, Juan Antonio; Mato Abad, Virginia; García-Álvarez, Roberto; González-Zabaleta, Javier; Pereira-Loureiro, Javier; Álvarez-Linera, Juan,Wiley 2015-05-21, لیست کتاب های Wiley 2015-05-21,WorldCat, کتاب های WorldCat

گت بلاگز Internet Automatic detection of EEG arousals / دانلود فایل

مشخصات کلی Automatic detection of EEG arousals

نویسنده کتاب (Author):

Fernández Varela, Isaac; Hernández Pereira, Elena; Álvarez Estévez, Diego; Moret Bonillo, Vicente

انتشارات (Publisher):

ESANN 2016-04-27

ویرایش و نوع فایل (Edition/Format):

 Downloadable article : English

منبع (Database):

WorldCat

عنوان ژورنال (Publication):

isaac-fernandez-elena-hernandez-diego-alvarez-vicente-moret-bonillo-automatic-detection-of-eeg-arousals-in-proceedings-esann-2016-european-symposium-on-artificial-neural-networks-c

موضوع (Subject):

Fragmented sleep       Electroencephalographic signals       Signal processing       View all subjects      

توضیحات خلاصه (Summary):

[Abstract] Fragmented sleep is commonly caused by arousals that can be detected with the observation of electroencephalographic (EEG) signals. As this is a time consuming task, automatization processes are required. A method using signal processing and machine learning models, for arousal detection, is presented. Relevant events are identified in the EEG signals and in the electromyography, during the signal processing phase. After discarding those events that do not meet the required characteristics, the resulting set is used to extract multiple parameters. Several machine learning models — Fisher’s Linear Discriminant, Artificial Neural Networks and Support Vector Machines — are fed with these parameters. The final proposed model, a combination of the different individual models, was used to conduct experiments on 26 patients, reporting a sensitivity of 0.72 and a specificity of 0.89, while achieving an error of 0.13, in the arousal events detection.  Read more…

ژانر / فرم:info:eu-repo/semantics/conferenceObject

موضوع:Internet resource

نوع منبع:Internet Resource, Article

تمام نویسندگان / همکاران: Fernández Varela, Isaac; Hernández Pereira, Elena; Álvarez Estévez, Diego; Moret Bonillo, Vicente

شناسه OCLC:979265244

Language Note:English

فهرست محتوا:978-287587027-8. http://hdl.handle.net/2183/18134

نویسنده : getblogs