Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Hadi Ratham Al Ghayab"'
Autor:
Wessam Al-Salman, Yan Li, Peng Wen, Firas Sabar Miften, Atheer Y. Oudah, Hadi Ratham Al Ghayab
Publikováno v:
Brain Research. 1779:147777
The detection of epileptic seizures from electroencephalogram (EEG) signals is traditionally performed by clinical experts through visual inspection. It is a long process, is error prone, and requires a highly trained expert. In this research, a new
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8da1302dacbeb8a45d5d5e68c174b6d2
https://doi.org/10.1016/j.brainres.2022.147777
https://doi.org/10.1016/j.brainres.2022.147777
Publikováno v:
Soft Computing. 23:227-239
This paper proposes a new algorithm which combines the information in frequency domain with the Information Gain (InfoGain) technique for the detection of epileptic seizures from electroencephalogram (EEG) data. The proposed method consists of four m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3db36e4f105280c6c1cf2a6f2880c400
https://doi.org/10.1007/s00500-018-3487-0
https://doi.org/10.1007/s00500-018-3487-0
Epileptic EEG signal classification using optimum allocation based power spectral density estimation
Publikováno v:
IET Signal Processing. 12:738-747
This study proposes a novel approach blending optimum allocation (OA) technique and spectral density estimation to analyse and classify epileptic electroencephalogram (EEG) signals. This study employs the OA to determine representative sample points
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b5e4ddb8fd0e45e028cbf8a869e7228f
https://doi.org/10.1049/iet-spr.2017.0140
https://doi.org/10.1049/iet-spr.2017.0140
Publikováno v:
Brain Informatics
Electroencephalogram (EEG) signals are used broadly in the medical fields. The main applications of EEG signals are the diagnosis and treatment of diseases such as epilepsy, Alzheimer, sleep problems and so on. This paper presents a new method which
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::34b77ed70d4ef4e200432bda06fcd4c7
http://europepmc.org/articles/PMC4883170
http://europepmc.org/articles/PMC4883170
Developing a Tunable Q-Factor Wavelet Transform Based Algorithm for Epileptic EEG Feature Extraction
Publikováno v:
Health Information Science ISBN: 9783319691817
HIS
HIS
Brain signals refer to electroencephalogram (EEG) data that contain the most important information in the human brain, which are non-stationary and nonlinear in nature. EEG signals are a mixture of sustained oscillation and non-oscillatory transients
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7a52380d122e834b232a89f234da0fcd
https://doi.org/10.1007/978-3-319-69182-4_6
https://doi.org/10.1007/978-3-319-69182-4_6
