Name
Title | ||
|---|---|---|
Performance evaluation of empirical mode decomposition, discrete wavelet transform, and wavelet packed decomposition for automated epileptic seizure detection and prediction. |
Abstract | ||
|---|---|---|
•EEG databases used to find a model for better detection and prediction of seizure onsets.•MSPCA is used to remove artefact-contaminated parts from EEG measurements.•EMD, DWT and WPD used to decompose EEG signals into different sub-bands.•Different statistical values are used to extract relevant features.•ANN, k-NN, SVM and random forest machine learning algorithms used for classification. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.bspc.2017.07.022 | Biomedical Signal Processing and Control |
Keywords | Field | DocType |
Electroencephalography (EEG),Epilepsy,Seizure detection and prediction,Multiscale PCA (MSPCA),Discrete wavelet transform (DWT),Empirical mode decomposition (EMD),Wavelet packet decomposition (WPD) | Pattern recognition,Computer science,Speech recognition,Epileptic seizure,Discrete wavelet transform,Artificial intelligence,Wavelet packet decomposition,Electroencephalography,Principal component analysis,Ictal,Wavelet,Hilbert–Huang transform | Journal |
Volume | ISSN | Citations |
39 | 1746-8094 | 17 |
PageRank | References | Authors |
0.72 | 19 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| emina alickovic | 1 | 89 | 4.30 |
| Jasmin Kevric | 2 | 162 | 7.27 |
| Abdulhamit Subasi | 3 | 1349 | 81.18 |