# Detection of Epileptic Seizures Using Wavelet Transform, Peak Extraction and PSR from EEG Signals

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^{2}

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## Abstract

**:**

## 1. Introduction

## 2. Overview of Epileptic-Seizure Detection

#### 2.1. Experimental Data

#### 2.2. Wavelet Transforms

#### 2.3. Peak Extraction

#### 2.4. Phase Space Reconstruction

#### 2.5. Feature Extraction Using Euclidean Distances and Statistical Techniques

#### 2.6. Neural Networks with Weighted Fuzzy Membership (NEWFM)

_{h}= {A

_{h}= (a

_{1}, a

_{2}, a

_{3}, a

_{4}, …, a

_{n}), class}, where class is the class node and A

_{h}is n features. A total of 16 features were used as the inputs, as represented in Figure 5.

_{l}) operation adjusts the weights and the center of the membership in Figure 6. W

_{1}, W

_{2}and W

_{3}are moved up or down, v

_{1}and v

_{2}are moved up to a

_{i}and v

_{3}stays in the same position. After finishing the Adjust(B

_{l}) operation, each fuzzy set in the hyperbox node B

_{l}in Figure 5 contains three weighted fuzzy memberships (WFMs). The WFM implies gray memberships, as depicted in Figure 7. The bounded sum of WFMs (BSWFM) in the ith fuzzy set, ${B}_{l}^{i}(x)$ denoted as, ${\mu}_{b}^{i}(x)$ is defined as follows:

## 3. Experimental Results

## 4. Conclusions

## Author Contributions

## Funding

## Acknowledgments

## Conflicts of Interest

## References

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Class | Training Set | Test Set | Total Set |
---|---|---|---|

Epileptic seizure | 500 | 300 | 800 |

Normal | 500 | 300 | 800 |

Total | 1000 | 600 | 1600 |

No | Description of the Features |
---|---|

1 | Mean of the Euclidean distances of the peaks in D1, D2, A1 and A2 |

2 | Median of the Euclidean distances of the peaks in D1, D2, A1 and A2 |

3 | Average power of the Euclidean distances of the peaks in D1, D2, A1 and A2 |

4 | Standard deviation of the Euclidean distances of the peaks in D1, D2, A1 and A2 |

Class | Results | |
---|---|---|

Epileptic seizure (300) | TP | FN |

285 | 15 | |

Normal (300) | FP | TN |

0 | 300 |

Accuracy | Sensitivity | Specificity | |
---|---|---|---|

Subasi [15] | 94.5% | 95% | 94% |

NEWFM | 97.5% | 95% | 100% |

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**MDPI and ACS Style**

Jang, S.-W.; Lee, S.-H.
Detection of Epileptic Seizures Using Wavelet Transform, Peak Extraction and PSR from EEG Signals. *Symmetry* **2020**, *12*, 1239.
https://doi.org/10.3390/sym12081239

**AMA Style**

Jang S-W, Lee S-H.
Detection of Epileptic Seizures Using Wavelet Transform, Peak Extraction and PSR from EEG Signals. *Symmetry*. 2020; 12(8):1239.
https://doi.org/10.3390/sym12081239

**Chicago/Turabian Style**

Jang, Seok-Woo, and Sang-Hong Lee.
2020. "Detection of Epileptic Seizures Using Wavelet Transform, Peak Extraction and PSR from EEG Signals" *Symmetry* 12, no. 8: 1239.
https://doi.org/10.3390/sym12081239