Matches in SemOpenAlex for { <https://semopenalex.org/work/W3203398259> ?p ?o ?g. }
Showing items 1 to 89 of
89
with 100 items per page.
- W3203398259 endingPage "11141" @default.
- W3203398259 startingPage "11135" @default.
- W3203398259 abstract "In March 2020, a cohort of 26 is treated critically ill hospitalized SARS-CoV-2 infected patients who received EEGs to assess unexplained altered mental status, loss of consciousness, or poor arousal and responsiveness. The objective of the present work is to develop a method that is able to automatically determine mental status of vigilance, i.e., a person's state of alertness. Such a task is relevant to diverse domains, where a person is expected or required to be in a particular state of mind. Aiming at the EEG feature selection and classification model in the identification of fatigue driving, the discretization algorithm using rough set theory is proposed to select the channel and EEG signal feature quantities. The support vector machine (SVM) is selected as the fatigue driving recognition model, and the risk of fatigue misjudgment is taken as SVM model parameters for model optimization. The experimental results of subjects show that compared with the principal component method, the rough set discretization algorithm selects fewer features, and the compatibility threshold 0.8. The number of features selected among the candidate features is 208. The features selected by different subjects are different and have an impact on the establishment of the support vector machine recognition model. Fatigue misjudgment risk control parameters can adjust the support vector machine recognition model error judgment risk. Even if the present approach is costly in computation time, it allows constructing a decision rule that provides an accurate and fast prediction of the alertness state of an unseen individual." @default.
- W3203398259 created "2021-10-11" @default.
- W3203398259 creator A5022524104 @default.
- W3203398259 creator A5040950160 @default.
- W3203398259 creator A5073078116 @default.
- W3203398259 date "2021-10-05" @default.
- W3203398259 modified "2023-10-06" @default.
- W3203398259 title "EEG Signal Feature Selection Algorithm and Support Vector Machine Model in Patient's Fatigue Recognition" @default.
- W3203398259 cites W1487399206 @default.
- W3203398259 cites W1563644780 @default.
- W3203398259 cites W1991919071 @default.
- W3203398259 cites W1993369399 @default.
- W3203398259 cites W2030737932 @default.
- W3203398259 cites W2046004769 @default.
- W3203398259 cites W2092728879 @default.
- W3203398259 cites W2093067793 @default.
- W3203398259 cites W2119656429 @default.
- W3203398259 cites W2146976664 @default.
- W3203398259 cites W2147413692 @default.
- W3203398259 cites W2164846889 @default.
- W3203398259 cites W2174958781 @default.
- W3203398259 cites W2292553612 @default.
- W3203398259 doi "https://doi.org/10.1007/s13369-021-06206-1" @default.
- W3203398259 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/8490845" @default.
- W3203398259 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/34631359" @default.
- W3203398259 hasPublicationYear "2021" @default.
- W3203398259 type Work @default.
- W3203398259 sameAs 3203398259 @default.
- W3203398259 citedByCount "1" @default.
- W3203398259 countsByYear W32033982592022 @default.
- W3203398259 crossrefType "journal-article" @default.
- W3203398259 hasAuthorship W3203398259A5022524104 @default.
- W3203398259 hasAuthorship W3203398259A5040950160 @default.
- W3203398259 hasAuthorship W3203398259A5073078116 @default.
- W3203398259 hasBestOaLocation W32033982591 @default.
- W3203398259 hasConcept C118552586 @default.
- W3203398259 hasConcept C119857082 @default.
- W3203398259 hasConcept C12267149 @default.
- W3203398259 hasConcept C134306372 @default.
- W3203398259 hasConcept C138885662 @default.
- W3203398259 hasConcept C148483581 @default.
- W3203398259 hasConcept C153180895 @default.
- W3203398259 hasConcept C154945302 @default.
- W3203398259 hasConcept C15744967 @default.
- W3203398259 hasConcept C200678441 @default.
- W3203398259 hasConcept C2776401178 @default.
- W3203398259 hasConcept C33923547 @default.
- W3203398259 hasConcept C41008148 @default.
- W3203398259 hasConcept C41895202 @default.
- W3203398259 hasConcept C522805319 @default.
- W3203398259 hasConcept C73000952 @default.
- W3203398259 hasConceptScore W3203398259C118552586 @default.
- W3203398259 hasConceptScore W3203398259C119857082 @default.
- W3203398259 hasConceptScore W3203398259C12267149 @default.
- W3203398259 hasConceptScore W3203398259C134306372 @default.
- W3203398259 hasConceptScore W3203398259C138885662 @default.
- W3203398259 hasConceptScore W3203398259C148483581 @default.
- W3203398259 hasConceptScore W3203398259C153180895 @default.
- W3203398259 hasConceptScore W3203398259C154945302 @default.
- W3203398259 hasConceptScore W3203398259C15744967 @default.
- W3203398259 hasConceptScore W3203398259C200678441 @default.
- W3203398259 hasConceptScore W3203398259C2776401178 @default.
- W3203398259 hasConceptScore W3203398259C33923547 @default.
- W3203398259 hasConceptScore W3203398259C41008148 @default.
- W3203398259 hasConceptScore W3203398259C41895202 @default.
- W3203398259 hasConceptScore W3203398259C522805319 @default.
- W3203398259 hasConceptScore W3203398259C73000952 @default.
- W3203398259 hasIssue "8" @default.
- W3203398259 hasLocation W32033982591 @default.
- W3203398259 hasLocation W32033982592 @default.
- W3203398259 hasOpenAccess W3203398259 @default.
- W3203398259 hasPrimaryLocation W32033982591 @default.
- W3203398259 hasRelatedWork W2041399278 @default.
- W3203398259 hasRelatedWork W2077563416 @default.
- W3203398259 hasRelatedWork W2136184105 @default.
- W3203398259 hasRelatedWork W2160451891 @default.
- W3203398259 hasRelatedWork W2320736787 @default.
- W3203398259 hasRelatedWork W2336974148 @default.
- W3203398259 hasRelatedWork W2399116914 @default.
- W3203398259 hasRelatedWork W2937631562 @default.
- W3203398259 hasRelatedWork W2187500075 @default.
- W3203398259 hasRelatedWork W2345184372 @default.
- W3203398259 hasVolume "48" @default.
- W3203398259 isParatext "false" @default.
- W3203398259 isRetracted "false" @default.
- W3203398259 magId "3203398259" @default.
- W3203398259 workType "article" @default.