Epileptic seizure detection on patients with mental retardation based on EEG features : a pilot study
| Autor: | Johan Arends, Pierre J. M. Cluitmans, Andrei Sazonov, Lei Wang, Yan Wu |
|---|---|
| Přispěvatelé: | Signal Processing Systems, Video Coding & Architectures |
| Jazyk: | angličtina |
| Rok vydání: | 2015 |
| Předmět: |
medicine.medical_specialty
Epilepsy medicine.diagnostic_test business.industry Pattern recognition Electroencephalography Pilot Projects Audiology medicine.disease Seizure detection Feature (computer vision) Seizures Intellectual Disability Intellectual disability medicine Epileptic eeg Humans Epileptic seizure Selection method Artificial intelligence medicine.symptom business Algorithms |
| Zdroj: | 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2015, 26-29 August 2015, Milan, Italy, 578-581 STARTPAGE=578;ENDPAGE=581;TITLE=37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2015, 26-29 August 2015, Milan, Italy EMBC |
| Popis: | Mental retardation (MR) is one of the most common secondary disabilities in people with Epilepsy. However, to our knowledge there are no reliable seizure detection methods specified for MR-patients. In this paper we performed a pilot study on a group of six patients with mental retardation to assess what EEG features potentially work well on this group. A group of EEG features on the time, frequency and spatio-temporal domain were extracted, the modified wrapper approach was then employed as an improved feature subset selection method. Results show high variance on obtained features subset across this group, meanwhile there exist some common features which characterize the high-frequency components of epileptic EEG signals. |
| Databáze: | OpenAIRE |
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