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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| Other Authors: | |
| Format: | Final Year Project (FYP) |
| Language: | English |
| Published: |
2017
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| Online Access: | http://hdl.handle.net/10356/70408 |
| _version_ | 1826114595785277440 |
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| author | Ye, Ruofan |
| author2 | Rajapakse Jagath Chandana |
| author_facet | Rajapakse Jagath Chandana Ye, Ruofan |
| author_sort | Ye, Ruofan |
| collection | NTU |
| description | 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. |
| first_indexed | 2024-10-01T03:41:43Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/70408 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T03:41:43Z |
| publishDate | 2017 |
| record_format | dspace |
| spelling | ntu-10356/704082023-03-03T20:28:07Z Epileptic seizure detection using EEG Ye, Ruofan Rajapakse Jagath Chandana School of Computer Science and Engineering DRNTU::Engineering::Computer science and engineering 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. Bachelor of Engineering (Computer Engineering) 2017-04-24T02:28:24Z 2017-04-24T02:28:24Z 2017 Final Year Project (FYP) http://hdl.handle.net/10356/70408 en Nanyang Technological University 40 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Computer science and engineering Ye, Ruofan Epileptic seizure detection using EEG |
| title | Epileptic seizure detection using EEG |
| title_full | Epileptic seizure detection using EEG |
| title_fullStr | Epileptic seizure detection using EEG |
| title_full_unstemmed | Epileptic seizure detection using EEG |
| title_short | Epileptic seizure detection using EEG |
| title_sort | epileptic seizure detection using eeg |
| topic | DRNTU::Engineering::Computer science and engineering |
| url | http://hdl.handle.net/10356/70408 |
| work_keys_str_mv | AT yeruofan epilepticseizuredetectionusingeeg |