Matches in SemOpenAlex for { <https://semopenalex.org/work/W2805295511> ?p ?o ?g. }
Showing items 1 to 97 of
97
with 100 items per page.
- W2805295511 abstract "The regular excessive consumption of alcohol may leads to alcohol use disorder (AUD). AUD is considered a serious health issue which may hamper physical health and social life of a patient if not detected and treated timely. The screening of AUD patients using physiological characteristics is very difficult task for the doctors. Therefore, brain electroencephalograms (EEGs) signal analysis is popularly used to accurately detect the AUD disorder (or the person is alcoholic or normal). Manual analyses of EEG signals are complicated and time-consuming as it is recorded in microvolt (μv). Therefore, computer-aided diagnosis (CAD) is used by a neurologist to analyze the EEG signals from their frequency sub-bands. The EEG signals recording obtained from the subject are nonlinear and unstable with respect to time. In this paper, support vector machine techniques are used with nonlinear parametric signals in time-frequency domain on features extracted from EEG signals. The features are extracted with the help of continuous wavelet transform, Tuned Q wavelet transform (TQWT) is used for decomposition of the signals. The decomposed subband, Centered Correntropy (CC) features are extracted and used to find out the minute changes in the nonlinear signal with lag time delay, which is very similar to the autocorrelation of the signal. Then these features are reduced by applying principal component analysis (PCA), which is then passed to least squares support vector machine (LS-SVM) for classification between alcoholic and normal EEG signals. Training of the data is done with ten-fold cross-validation to increase the accuracy. Our proposed work is with three different types of kernel functions like linear, RBF and Polynomial kernel. Comparing the result, we found that the RBF kernel gives the highest performance having accuracy is 97.06%, sensitivity is 97.45%, specificity is 97.666%, and Matthews's correlation coefficient is 0.94 by varying the Q parameter of wavelet transform from 3 to 8." @default.
- W2805295511 created "2018-06-13" @default.
- W2805295511 creator A5011070228 @default.
- W2805295511 creator A5013636671 @default.
- W2805295511 date "2017-11-01" @default.
- W2805295511 modified "2023-09-27" @default.
- W2805295511 title "Alcoholism detection using support vector machines and centered correntropy features of brain EEG signals" @default.
- W2805295511 cites W1998302204 @default.
- W2805295511 cites W1999771120 @default.
- W2805295511 cites W2005791255 @default.
- W2805295511 cites W2026699230 @default.
- W2805295511 cites W2044305003 @default.
- W2805295511 cites W2049270581 @default.
- W2805295511 cites W2087189978 @default.
- W2805295511 cites W2097002922 @default.
- W2805295511 cites W2135160607 @default.
- W2805295511 cites W2491407016 @default.
- W2805295511 cites W2556777653 @default.
- W2805295511 cites W4301501800 @default.
- W2805295511 doi "https://doi.org/10.1109/icici.2017.8365294" @default.
- W2805295511 hasPublicationYear "2017" @default.
- W2805295511 type Work @default.
- W2805295511 sameAs 2805295511 @default.
- W2805295511 citedByCount "8" @default.
- W2805295511 countsByYear W28052955112020 @default.
- W2805295511 countsByYear W28052955112021 @default.
- W2805295511 countsByYear W28052955112023 @default.
- W2805295511 crossrefType "proceedings-article" @default.
- W2805295511 hasAuthorship W2805295511A5011070228 @default.
- W2805295511 hasAuthorship W2805295511A5013636671 @default.
- W2805295511 hasConcept C104267543 @default.
- W2805295511 hasConcept C105795698 @default.
- W2805295511 hasConcept C118552586 @default.
- W2805295511 hasConcept C12267149 @default.
- W2805295511 hasConcept C153180895 @default.
- W2805295511 hasConcept C154945302 @default.
- W2805295511 hasConcept C15744967 @default.
- W2805295511 hasConcept C185592680 @default.
- W2805295511 hasConcept C19118579 @default.
- W2805295511 hasConcept C199360897 @default.
- W2805295511 hasConcept C27438332 @default.
- W2805295511 hasConcept C2779442783 @default.
- W2805295511 hasConcept C2779843651 @default.
- W2805295511 hasConcept C2781066024 @default.
- W2805295511 hasConcept C28490314 @default.
- W2805295511 hasConcept C31972630 @default.
- W2805295511 hasConcept C33923547 @default.
- W2805295511 hasConcept C41008148 @default.
- W2805295511 hasConcept C47432892 @default.
- W2805295511 hasConcept C522805319 @default.
- W2805295511 hasConcept C52622490 @default.
- W2805295511 hasConcept C5297727 @default.
- W2805295511 hasConcept C55493867 @default.
- W2805295511 hasConcept C84462506 @default.
- W2805295511 hasConcept C9390403 @default.
- W2805295511 hasConceptScore W2805295511C104267543 @default.
- W2805295511 hasConceptScore W2805295511C105795698 @default.
- W2805295511 hasConceptScore W2805295511C118552586 @default.
- W2805295511 hasConceptScore W2805295511C12267149 @default.
- W2805295511 hasConceptScore W2805295511C153180895 @default.
- W2805295511 hasConceptScore W2805295511C154945302 @default.
- W2805295511 hasConceptScore W2805295511C15744967 @default.
- W2805295511 hasConceptScore W2805295511C185592680 @default.
- W2805295511 hasConceptScore W2805295511C19118579 @default.
- W2805295511 hasConceptScore W2805295511C199360897 @default.
- W2805295511 hasConceptScore W2805295511C27438332 @default.
- W2805295511 hasConceptScore W2805295511C2779442783 @default.
- W2805295511 hasConceptScore W2805295511C2779843651 @default.
- W2805295511 hasConceptScore W2805295511C2781066024 @default.
- W2805295511 hasConceptScore W2805295511C28490314 @default.
- W2805295511 hasConceptScore W2805295511C31972630 @default.
- W2805295511 hasConceptScore W2805295511C33923547 @default.
- W2805295511 hasConceptScore W2805295511C41008148 @default.
- W2805295511 hasConceptScore W2805295511C47432892 @default.
- W2805295511 hasConceptScore W2805295511C522805319 @default.
- W2805295511 hasConceptScore W2805295511C52622490 @default.
- W2805295511 hasConceptScore W2805295511C5297727 @default.
- W2805295511 hasConceptScore W2805295511C55493867 @default.
- W2805295511 hasConceptScore W2805295511C84462506 @default.
- W2805295511 hasConceptScore W2805295511C9390403 @default.
- W2805295511 hasLocation W28052955111 @default.
- W2805295511 hasOpenAccess W2805295511 @default.
- W2805295511 hasPrimaryLocation W28052955111 @default.
- W2805295511 hasRelatedWork W2126100045 @default.
- W2805295511 hasRelatedWork W2132729794 @default.
- W2805295511 hasRelatedWork W2147478239 @default.
- W2805295511 hasRelatedWork W2150085486 @default.
- W2805295511 hasRelatedWork W2336974148 @default.
- W2805295511 hasRelatedWork W2907827771 @default.
- W2805295511 hasRelatedWork W3004377704 @default.
- W2805295511 hasRelatedWork W4225691219 @default.
- W2805295511 hasRelatedWork W2187500075 @default.
- W2805295511 hasRelatedWork W2345184372 @default.
- W2805295511 isParatext "false" @default.
- W2805295511 isRetracted "false" @default.
- W2805295511 magId "2805295511" @default.
- W2805295511 workType "article" @default.