Name
Title | ||
|---|---|---|
Automatic focal and non-focal EEG detection using entropy-based features from flexible analytic wavelet transform |
Abstract | ||
|---|---|---|
•We explore the ability of FAWT without reconstruction analysis in the feature extraction of epilepsy signals.•Fuzzy distribution entropy is firstly introduced to discriminate the focal and non-focal EEG signals, and a satisfied classification performance is achieved using the combination of log energy entropy and fuzzy distribution entropy.•In order to obtain more reliable results, different classifiers have been considered in this work.•The entire Bern Barcelona database is used to verify the proposed method which makes the results more statistically significant. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.bspc.2019.101761 | Biomedical Signal Processing and Control |
Keywords | Field | DocType |
Electroencephalogram (EEG),Focal (F) and non-focal (NF),Flexible analytic wavelet transform (FAWT),Entropy,Classifier | General regression neural network,Pattern recognition,Least squares support vector machine,Fuzzy logic,Support vector machine,Artificial intelligence,Clinical diagnosis,Classifier (linguistics),Electroencephalography,Mathematics,Wavelet transform | Journal |
Volume | ISSN | Citations |
57 | 1746-8094 | 1 |
PageRank | References | Authors |
0.36 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yang You | 1 | 4 | 2.08 |
| Wanzhong Chen | 2 | 1 | 0.36 |
| Mingyang Li | 3 | 3 | 0.71 |
| Tao Zhang | 4 | 220 | 69.03 |
| Yun Jiang | 5 | 4 | 2.76 |
| Xiao Zheng | 6 | 3 | 1.04 |