A Multivariate Approach for Patient-Specific EEG Seizure Detection Using Empirical Wavelet Transform
By Abhijit Bhattacharyya, Ram Bilas Pachori. IEEE Transactions on Biomedical Engineering, 2017
365 citations recorded by the source corpus.
Subfields: Cardiology and Cardiovascular Medicine, Cognitive Neuroscience, Psychiatry and Mental health
View Paper: https://www.semanticscholar.org/paper/a4ca3c99b4e259150c28f3aa2050ba36593bdd07
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Cardiology and Cardiovascular Medicine
In Cognitive Neuroscience
- Xiaorong Gao
- Qingqing Zheng
- Bingchuan Liu
- Yonghao Song
- Shangkai Gao
- Tzyy-Ping Jung
- Xiaogang Chen
- Masaki Nakanishi
In Psychiatry and Mental health
Citations in the corpus
- EEG Conformer: Convolutional Transformer for EEG Decoding and Visualization (2022, methodology): “Empirical wavelet transform (EWT) is applied to obtain improved time-frequency features from EEG with good performance for seizure detection [11], [12].”