Rule-base wearable embedded platform for seizure detection from real EEG data in ambulatory state
This paper describes a classification method is presented using an empirical Rule-base System to detect the occurrences of Partial Seizures from Epilepsy data, which can be implemented in any embedded system as a wearable detection system. The system distinguishes between 'Normal' and ...
| Main Authors: | Shakir, M., Malik, A.S., Kamel, N., Qidwai, U. |
|---|---|
| Format: | Conference or Workshop Item |
| Institution: | Universiti Teknologi Petronas |
| Record Id / ISBN-0: | utp-eprints.31248 / |
| Published: |
Institute of Electrical and Electronics Engineers Inc.
2014
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| Online Access: |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84911982080&doi=10.1109%2ftenconspring.2014.6862995&partnerID=40&md5=ab1e87baa3b7618c758bf268781e340d http://eprints.utp.edu.my/31248/ |
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