Minimizing the Number of Electrodes for Epileptic Seizures Prediction
Epilepsy is a neurological disorder affecting 1-2 % of the population in the world. People diagnosed with epilepsy are put at high risk of getting injured due to the unpredictable seizures caused by the disorder. Electroencephalography (EEG) in combination with machine learning can be used for predi...
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KTH, Skolan för teknik och hälsa (STH)
2017
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ndltd-UPSALLA1-oai-DiVA.org-kth-2130012017-09-20T05:24:49ZMinimizing the Number of Electrodes for Epileptic Seizures PredictionengEmilsson, LinneaTarasov, YevgenKTH, Skolan för teknik och hälsa (STH)KTH, Skolan för teknik och hälsa (STH)2017EEGEpileptic SeizureMedical EngineeringMedicinteknikEpilepsy is a neurological disorder affecting 1-2 % of the population in the world. People diagnosed with epilepsy are put at high risk of getting injured due to the unpredictable seizures caused by the disorder. Electroencephalography (EEG) in combination with machine learning can be used for prediction of an epileptic seizure. Therefore, a portable prediction device is of great interest with high emphasis for it to be user-friendly. One way to achieve this is by minimizing the number of electrodes placed on the scalp. This study examines the number of electrodes that provide sufficient information for prediction of a seizure. The highest prediction accuracy of 91 %, 97 % sensitivity and 85 % specificity was achieved with as few as 16 electrodes. Due to the limitation of the intracranial EEG recordings further testing must be performed on scalp EEG recordings to provide valid results. Student thesisinfo:eu-repo/semantics/bachelorThesistexthttp://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-213001TRITA-STH ; 59application/pdfinfo:eu-repo/semantics/openAccess |
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NDLTD |
language |
English |
format |
Others
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EEG Epileptic Seizure Medical Engineering Medicinteknik |
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EEG Epileptic Seizure Medical Engineering Medicinteknik Emilsson, Linnea Tarasov, Yevgen Minimizing the Number of Electrodes for Epileptic Seizures Prediction |
description |
Epilepsy is a neurological disorder affecting 1-2 % of the population in the world. People diagnosed with epilepsy are put at high risk of getting injured due to the unpredictable seizures caused by the disorder. Electroencephalography (EEG) in combination with machine learning can be used for prediction of an epileptic seizure. Therefore, a portable prediction device is of great interest with high emphasis for it to be user-friendly. One way to achieve this is by minimizing the number of electrodes placed on the scalp. This study examines the number of electrodes that provide sufficient information for prediction of a seizure. The highest prediction accuracy of 91 %, 97 % sensitivity and 85 % specificity was achieved with as few as 16 electrodes. Due to the limitation of the intracranial EEG recordings further testing must be performed on scalp EEG recordings to provide valid results. |
author |
Emilsson, Linnea Tarasov, Yevgen |
author_facet |
Emilsson, Linnea Tarasov, Yevgen |
author_sort |
Emilsson, Linnea |
title |
Minimizing the Number of Electrodes for Epileptic Seizures Prediction |
title_short |
Minimizing the Number of Electrodes for Epileptic Seizures Prediction |
title_full |
Minimizing the Number of Electrodes for Epileptic Seizures Prediction |
title_fullStr |
Minimizing the Number of Electrodes for Epileptic Seizures Prediction |
title_full_unstemmed |
Minimizing the Number of Electrodes for Epileptic Seizures Prediction |
title_sort |
minimizing the number of electrodes for epileptic seizures prediction |
publisher |
KTH, Skolan för teknik och hälsa (STH) |
publishDate |
2017 |
url |
http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-213001 |
work_keys_str_mv |
AT emilssonlinnea minimizingthenumberofelectrodesforepilepticseizuresprediction AT tarasovyevgen minimizingthenumberofelectrodesforepilepticseizuresprediction |
_version_ |
1718539689391030272 |