EEG signal analysis in frequency domains for healthy and epileptic patients
One of the most common abnormal electrical activities of the brain is epileptic seizures, which reflect the abnormal behavior of brain signals, which may occur in patients of all ages. in medical management system the Electroencephalograph (EEG) signals are essential way to monitor this abnormal beh...
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description | One of the most common abnormal electrical activities of the brain is epileptic seizures, which reflect the abnormal behavior of brain signals, which may occur in patients of all ages. in medical management system the Electroencephalograph (EEG) signals are essential way to monitor this abnormal behavior to detect the epileptic seizures in aim of acting proper reaction. Analysis EEG signal in accurate way is an important step for brain diseases detection that help in extract relevant features used to classify and detect these diseases. This research produced analysis study for EEG signal in both time and frequency domain where the frequency domain contains the most relevant discriminate features. Filtering technique is used to isolates four bands (beta, theta, alpha, and delta) from EEG channel. Database of healthy and epileptic patients has been processed in time and frequency domain. Then power spectrum density (PSD) is calculated as feature to distinguish between healthy and epileptic patients. The results show that PSD for the EEG of epileptic patients is higher than PSD of EEG of healthy person. |
doi_str_mv | 10.1063/5.0181895 |
format | Conference Proceeding |
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Analysis EEG signal in accurate way is an important step for brain diseases detection that help in extract relevant features used to classify and detect these diseases. This research produced analysis study for EEG signal in both time and frequency domain where the frequency domain contains the most relevant discriminate features. Filtering technique is used to isolates four bands (beta, theta, alpha, and delta) from EEG channel. Database of healthy and epileptic patients has been processed in time and frequency domain. Then power spectrum density (PSD) is calculated as feature to distinguish between healthy and epileptic patients. The results show that PSD for the EEG of epileptic patients is higher than PSD of EEG of healthy person.</description><identifier>ISSN: 0094-243X</identifier><identifier>EISSN: 1551-7616</identifier><identifier>DOI: 10.1063/5.0181895</identifier><identifier>CODEN: APCPCS</identifier><language>eng</language><publisher>Melville: American Institute of Physics</publisher><subject>Brain ; Convulsions & seizures ; Data base management systems ; Electroencephalography ; Epilepsy ; Frequency domain analysis ; Seizures ; Signal analysis</subject><ispartof>AIP Conference Proceedings, 2023, Vol.2977 (1)</ispartof><rights>Author(s)</rights><rights>2023 Author(s). Published by AIP Publishing.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://pubs.aip.org/acp/article-lookup/doi/10.1063/5.0181895$$EHTML$$P50$$Gscitation$$H</linktohtml><link.rule.ids>309,310,314,780,784,789,790,794,4512,23930,23931,25140,27924,27925,76384</link.rule.ids></links><search><contributor>Aldahan, N.</contributor><contributor>Ramadhan, Ali J.</contributor><creatorcontrib>Alwan, Ali H.</creatorcontrib><creatorcontrib>Oleiwi, Zahraa Ch</creatorcontrib><creatorcontrib>Abed, Sudad Najim</creatorcontrib><title>EEG signal analysis in frequency domains for healthy and epileptic patients</title><title>AIP Conference Proceedings</title><description>One of the most common abnormal electrical activities of the brain is epileptic seizures, which reflect the abnormal behavior of brain signals, which may occur in patients of all ages. in medical management system the Electroencephalograph (EEG) signals are essential way to monitor this abnormal behavior to detect the epileptic seizures in aim of acting proper reaction. Analysis EEG signal in accurate way is an important step for brain diseases detection that help in extract relevant features used to classify and detect these diseases. This research produced analysis study for EEG signal in both time and frequency domain where the frequency domain contains the most relevant discriminate features. Filtering technique is used to isolates four bands (beta, theta, alpha, and delta) from EEG channel. Database of healthy and epileptic patients has been processed in time and frequency domain. Then power spectrum density (PSD) is calculated as feature to distinguish between healthy and epileptic patients. The results show that PSD for the EEG of epileptic patients is higher than PSD of EEG of healthy person.</description><subject>Brain</subject><subject>Convulsions & seizures</subject><subject>Data base management systems</subject><subject>Electroencephalography</subject><subject>Epilepsy</subject><subject>Frequency domain analysis</subject><subject>Seizures</subject><subject>Signal analysis</subject><issn>0094-243X</issn><issn>1551-7616</issn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2023</creationdate><recordtype>conference_proceeding</recordtype><recordid>eNotkE9LwzAchoMoOKcHv0HAm9CZ_2mOMuoUB14UvIVf09RldG1NskO_vZXt8r6Xh5eHF6F7SlaUKP4kV4SWtDTyAi2olLTQiqpLtCDEiIIJ_n2NblLaE8KM1uUCvVfVBqfw00OHYY4phYRDj9vof4--dxNuhgOEPuF2iHjnocu7aSYb7MfQ-TEHh0fIwfc53aKrFrrk7869RF8v1ef6tdh-bN7Wz9tipJznQjnGmBBEawlEgSiBGcUBoGHSNNx5VQvZcq-dc4yysvSC1iCE9EQxqWu-RA-n3TEOs2TKdj8c4yyfLDNEaK6pYTP1eKKSC3k2HHo7xnCAOFlK7P9ZVtrzWfwP8B9a7w</recordid><startdate>20231222</startdate><enddate>20231222</enddate><creator>Alwan, Ali H.</creator><creator>Oleiwi, Zahraa Ch</creator><creator>Abed, Sudad Najim</creator><general>American Institute of Physics</general><scope>8FD</scope><scope>H8D</scope><scope>L7M</scope></search><sort><creationdate>20231222</creationdate><title>EEG signal analysis in frequency domains for healthy and epileptic patients</title><author>Alwan, Ali H. ; Oleiwi, Zahraa Ch ; Abed, Sudad Najim</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p133t-6c222440775a06a48a2963aaad259d3ce6b45f3e7ccc21288e41ba445e06257b3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Brain</topic><topic>Convulsions & seizures</topic><topic>Data base management systems</topic><topic>Electroencephalography</topic><topic>Epilepsy</topic><topic>Frequency domain analysis</topic><topic>Seizures</topic><topic>Signal analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Alwan, Ali H.</creatorcontrib><creatorcontrib>Oleiwi, Zahraa Ch</creatorcontrib><creatorcontrib>Abed, Sudad Najim</creatorcontrib><collection>Technology Research Database</collection><collection>Aerospace Database</collection><collection>Advanced Technologies Database with Aerospace</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Alwan, Ali H.</au><au>Oleiwi, Zahraa Ch</au><au>Abed, Sudad Najim</au><au>Aldahan, N.</au><au>Ramadhan, Ali J.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>EEG signal analysis in frequency domains for healthy and epileptic patients</atitle><btitle>AIP Conference Proceedings</btitle><date>2023-12-22</date><risdate>2023</risdate><volume>2977</volume><issue>1</issue><issn>0094-243X</issn><eissn>1551-7616</eissn><coden>APCPCS</coden><abstract>One of the most common abnormal electrical activities of the brain is epileptic seizures, which reflect the abnormal behavior of brain signals, which may occur in patients of all ages. in medical management system the Electroencephalograph (EEG) signals are essential way to monitor this abnormal behavior to detect the epileptic seizures in aim of acting proper reaction. Analysis EEG signal in accurate way is an important step for brain diseases detection that help in extract relevant features used to classify and detect these diseases. This research produced analysis study for EEG signal in both time and frequency domain where the frequency domain contains the most relevant discriminate features. Filtering technique is used to isolates four bands (beta, theta, alpha, and delta) from EEG channel. Database of healthy and epileptic patients has been processed in time and frequency domain. Then power spectrum density (PSD) is calculated as feature to distinguish between healthy and epileptic patients. The results show that PSD for the EEG of epileptic patients is higher than PSD of EEG of healthy person.</abstract><cop>Melville</cop><pub>American Institute of Physics</pub><doi>10.1063/5.0181895</doi><tpages>11</tpages></addata></record> |
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subjects | Brain Convulsions & seizures Data base management systems Electroencephalography Epilepsy Frequency domain analysis Seizures Signal analysis |
title | EEG signal analysis in frequency domains for healthy and epileptic patients |
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