Matches in SemOpenAlex for { <https://semopenalex.org/work/W3136107281> ?p ?o ?g. }
- W3136107281 endingPage "104338" @default.
- W3136107281 startingPage "104338" @default.
- W3136107281 abstract "Epileptic seizure detection is of great significance in the diagnosis of epilepsy and relieving the heavy workload of visual inspection of electroencephalogram (EEG) recordings. This paper presents a novel method for seizure detection using the Stein kernel-based sparse representation (SR) for EEG recordings. Different from the traditional SR scheme that works with vector data in Euclidean space, the Stein kernel-based SR framework is constructed for seizure detection in the space of the symmetric positive definite (SPD) matrices, which form a Riemannian manifold. Due to the non-Euclidean geometry of the Riemannian manifold, the Stein kernel on the manifold permits the embedding of the manifold in a high-dimensional reproducing kernel Hilbert space (RKHS) to perform SR. In the Stein kernel-based SR framework, EEG samples are described by SPD matrices in the form of covariance descriptors (CovDs). Then, a test EEG sample is sparsely represented on the training set, and the test sample is classified as a member of the class, which leads to the minimum reconstructed residual. Finally, by using three widely used EEG datasets to evaluate the detection performance of the proposed method, the experimental results demonstrate that it achieves good classification accuracy on each dataset. Furthermore, the fast computational speed of the Stein kernel-based SR also meets the basic requirements for real-time seizure detection." @default.
- W3136107281 created "2021-03-29" @default.
- W3136107281 creator A5020526465 @default.
- W3136107281 creator A5034377373 @default.
- W3136107281 creator A5038696152 @default.
- W3136107281 creator A5048403532 @default.
- W3136107281 creator A5060713958 @default.
- W3136107281 creator A5063906574 @default.
- W3136107281 creator A5068163224 @default.
- W3136107281 date "2021-05-01" @default.
- W3136107281 modified "2023-10-06" @default.
- W3136107281 title "Automatic epileptic seizure detection via Stein kernel-based sparse representation" @default.
- W3136107281 cites W1964321627 @default.
- W3136107281 cites W1964749215 @default.
- W3136107281 cites W1965166602 @default.
- W3136107281 cites W1971891445 @default.
- W3136107281 cites W1981211771 @default.
- W3136107281 cites W1983496390 @default.
- W3136107281 cites W1998711164 @default.
- W3136107281 cites W1999977403 @default.
- W3136107281 cites W2023335485 @default.
- W3136107281 cites W2032236594 @default.
- W3136107281 cites W2048192550 @default.
- W3136107281 cites W2053744708 @default.
- W3136107281 cites W2081895431 @default.
- W3136107281 cites W2113957296 @default.
- W3136107281 cites W2125003829 @default.
- W3136107281 cites W2125447566 @default.
- W3136107281 cites W2125513893 @default.
- W3136107281 cites W2129812935 @default.
- W3136107281 cites W2142848040 @default.
- W3136107281 cites W2160829192 @default.
- W3136107281 cites W2162800060 @default.
- W3136107281 cites W2277425195 @default.
- W3136107281 cites W2290580792 @default.
- W3136107281 cites W2516904419 @default.
- W3136107281 cites W2559256361 @default.
- W3136107281 cites W2568407436 @default.
- W3136107281 cites W2621374544 @default.
- W3136107281 cites W2759483166 @default.
- W3136107281 cites W2790950056 @default.
- W3136107281 cites W2794422422 @default.
- W3136107281 cites W2796229782 @default.
- W3136107281 cites W2810229480 @default.
- W3136107281 cites W2866637366 @default.
- W3136107281 cites W2899459625 @default.
- W3136107281 cites W2907368743 @default.
- W3136107281 cites W2963532276 @default.
- W3136107281 cites W2964267916 @default.
- W3136107281 cites W2965048225 @default.
- W3136107281 cites W2973010960 @default.
- W3136107281 cites W2973096226 @default.
- W3136107281 cites W2990238942 @default.
- W3136107281 cites W2991800222 @default.
- W3136107281 cites W2992736482 @default.
- W3136107281 cites W2996420055 @default.
- W3136107281 cites W3001901462 @default.
- W3136107281 cites W3002879843 @default.
- W3136107281 cites W3006560451 @default.
- W3136107281 cites W3010838287 @default.
- W3136107281 cites W3015929423 @default.
- W3136107281 cites W3048786211 @default.
- W3136107281 cites W3105392613 @default.
- W3136107281 doi "https://doi.org/10.1016/j.compbiomed.2021.104338" @default.
- W3136107281 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/33780870" @default.
- W3136107281 hasPublicationYear "2021" @default.
- W3136107281 type Work @default.
- W3136107281 sameAs 3136107281 @default.
- W3136107281 citedByCount "32" @default.
- W3136107281 countsByYear W31361072812021 @default.
- W3136107281 countsByYear W31361072812022 @default.
- W3136107281 countsByYear W31361072812023 @default.
- W3136107281 crossrefType "journal-article" @default.
- W3136107281 hasAuthorship W3136107281A5020526465 @default.
- W3136107281 hasAuthorship W3136107281A5034377373 @default.
- W3136107281 hasAuthorship W3136107281A5038696152 @default.
- W3136107281 hasAuthorship W3136107281A5048403532 @default.
- W3136107281 hasAuthorship W3136107281A5060713958 @default.
- W3136107281 hasAuthorship W3136107281A5063906574 @default.
- W3136107281 hasAuthorship W3136107281A5068163224 @default.
- W3136107281 hasConcept C118552586 @default.
- W3136107281 hasConcept C122280245 @default.
- W3136107281 hasConcept C12267149 @default.
- W3136107281 hasConcept C127413603 @default.
- W3136107281 hasConcept C153180895 @default.
- W3136107281 hasConcept C154945302 @default.
- W3136107281 hasConcept C182335926 @default.
- W3136107281 hasConcept C186450821 @default.
- W3136107281 hasConcept C202444582 @default.
- W3136107281 hasConcept C2779334592 @default.
- W3136107281 hasConcept C2779593128 @default.
- W3136107281 hasConcept C33923547 @default.
- W3136107281 hasConcept C41008148 @default.
- W3136107281 hasConcept C41608201 @default.
- W3136107281 hasConcept C522805319 @default.
- W3136107281 hasConcept C529865628 @default.
- W3136107281 hasConcept C62799726 @default.
- W3136107281 hasConcept C71924100 @default.