Comparison of Wavelet Transform and FFT Methods in the Analysis of EEG Signals

By Mehmet Akin. Journal of medical systems, 2002

297 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering

View Paper: https://www.semanticscholar.org/paper/c6131070de6ee810719dd3e4aa288095501aca95

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Civil and Structural Engineering

1. Khansa Rasheed
2. Junaid Qadir
3. Adeel Razi
4. Patrick Kwan
5. T. O'Brien
6. Levin Kuhlmann
7. Shobi Sivathamboo
8. Adnan Qayyum

Citations in the corpus

• Machine Learning for Predicting Epileptic Seizures Using EEG Signals: A Review (2020, methodology): “frequency based analysis technique, is widely used to obtain multi-resolution decomposed sub-band signals by passing the EEG signal through filter banks [29].”
• Feature Extraction and Selection for Emotion Recognition from EEG (2014, background): “For details, the reader is referred to [38], for example.”
• EEG-Based Emotion Recognition Using Regularized Graph Neural Networks (2019, background): “majority of existing features is single-channel features such as statistical features [23], Hjorth features [24], fractal dimension (FD) [25], PSD, differential entropy (DE) [8], and wavelet features [26]. A more detailed comparison of EEG features is discussed in [27]. A few features are computed o”