Selection probe of EEG using dynamic graph of autocatalytic set (ACS)
Electroencephalography (EEG) machine is a medical equipment which is used to diagnose seizure. EEG signal records data in the form of graph which consist of abnormal patterns such as spikes, sharp waves and also spikes and wave complexes. This pattern also come in multiple line series which then giv...
| Published in: | Communications in Computer and Information Science |
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| Format: | Conference paper |
| Language: | English |
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Springer Verlag
2016
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| Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84989336818&doi=10.1007%2f978-981-10-2777-2_3&partnerID=40&md5=8362f5d16d2608cad894a1e3a9ffdea8 |
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2-s2.0-84989336818 Ashaari A.; Ahmad T.; Zenian S.; Shukor N.A. Selection probe of EEG using dynamic graph of autocatalytic set (ACS) 2016 Communications in Computer and Information Science 652 10.1007/978-981-10-2777-2_3 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84989336818&doi=10.1007%2f978-981-10-2777-2_3&partnerID=40&md5=8362f5d16d2608cad894a1e3a9ffdea8 Electroencephalography (EEG) machine is a medical equipment which is used to diagnose seizure. EEG signal records data in the form of graph which consist of abnormal patterns such as spikes, sharp waves and also spikes and wave complexes. This pattern also come in multiple line series which then give some difficulties to analyze. This paper introduce the implementation of dynamic graph of Autocatalytic Set (ACS) for EEG signal during seizure. The result is then compared with other publish method namely Principal Component Analysis (PCA) of same EEG data. © Springer Nature Singapore Pte Ltd. 2016. Springer Verlag 18650929 English Conference paper |
| author |
Ashaari A.; Ahmad T.; Zenian S.; Shukor N.A. |
| spellingShingle |
Ashaari A.; Ahmad T.; Zenian S.; Shukor N.A. Selection probe of EEG using dynamic graph of autocatalytic set (ACS) |
| author_facet |
Ashaari A.; Ahmad T.; Zenian S.; Shukor N.A. |
| author_sort |
Ashaari A.; Ahmad T.; Zenian S.; Shukor N.A. |
| title |
Selection probe of EEG using dynamic graph of autocatalytic set (ACS) |
| title_short |
Selection probe of EEG using dynamic graph of autocatalytic set (ACS) |
| title_full |
Selection probe of EEG using dynamic graph of autocatalytic set (ACS) |
| title_fullStr |
Selection probe of EEG using dynamic graph of autocatalytic set (ACS) |
| title_full_unstemmed |
Selection probe of EEG using dynamic graph of autocatalytic set (ACS) |
| title_sort |
Selection probe of EEG using dynamic graph of autocatalytic set (ACS) |
| publishDate |
2016 |
| container_title |
Communications in Computer and Information Science |
| container_volume |
652 |
| container_issue |
|
| doi_str_mv |
10.1007/978-981-10-2777-2_3 |
| url |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84989336818&doi=10.1007%2f978-981-10-2777-2_3&partnerID=40&md5=8362f5d16d2608cad894a1e3a9ffdea8 |
| description |
Electroencephalography (EEG) machine is a medical equipment which is used to diagnose seizure. EEG signal records data in the form of graph which consist of abnormal patterns such as spikes, sharp waves and also spikes and wave complexes. This pattern also come in multiple line series which then give some difficulties to analyze. This paper introduce the implementation of dynamic graph of Autocatalytic Set (ACS) for EEG signal during seizure. The result is then compared with other publish method namely Principal Component Analysis (PCA) of same EEG data. © Springer Nature Singapore Pte Ltd. 2016. |
| publisher |
Springer Verlag |
| issn |
18650929 |
| language |
English |
| format |
Conference paper |
| accesstype |
|
| record_format |
scopus |
| collection |
Scopus |
| _version_ |
1809677910012854272 |