Epileptic seizure detection using EEG
Seizures occur at unpredictable times and is usually without warnings. Seizures can be dangerous and potentially life-threatening if left without assistance and treatments. This poses a challenge for medical personnel as immediate assistance is required should a patient suffers from a seizure. Th...
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| Format: | Final Year Project |
| Language: | English |
| Published: |
2017
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| Online Access: | http://hdl.handle.net/10356/70408 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | Seizures occur at unpredictable times and is usually without warnings. Seizures can be dangerous and potentially life-threatening if left without assistance and treatments. This poses a challenge for medical personnel as immediate assistance is required should a patient suffers from a seizure.
This project aims to develop an algorithm to allow detection of epileptic seizures of a patient through the use of electroencephalogram (EEG) signal. This algorithm will determine if the input EEG data is epileptic or not. This algorithm consists of two processes: feature extraction and classification. For this purpose, power spectral density is used to extract features of the EEG signals. Classification is done by using a Support Vector Machine (SVM).
With a working algorithm in detection of seizure, future implementation of such detection methods could be used in real-life situations where an alarm could be triggered to notify the medical personnel of a seizure of patient so that immediate response could be activated. |
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