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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Bibliographic Details
Main Authors: Emilsson, Linnea, Tarasov, Yevgen
Format: Others
Language:English
Published: KTH, Skolan för teknik och hälsa (STH) 2017
Subjects:
EEG
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-213001
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spelling 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
collection NDLTD
language English
format Others
sources NDLTD
topic EEG
Epileptic Seizure
Medical Engineering
Medicinteknik
spellingShingle 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
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