Fuzzy information graph of epileptic seizures
| Autor: | Vinod Ramachandran, Tahir Ahmad |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
medicine.diagnostic_test
Degree (graph theory) business.industry General Mathematics General Physics and Astronomy Information flow Pattern recognition General Chemistry Electroencephalography Machine learning computer.software_genre medicine.disease Fuzzy logic General Biochemistry Genetics and Molecular Biology Epilepsy medicine Fuzzy graph Graph (abstract data type) Epileptic seizure Artificial intelligence medicine.symptom General Agricultural and Biological Sciences business computer Mathematics |
| Zdroj: | Malaysian Journal of Fundamental and Applied Sciences. 10 |
| ISSN: | 2289-599X 2289-5981 |
| DOI: | 10.11113/mjfas.v10n1.69 |
| Popis: | The mathematical modelling of EEG signals provides valuable data to neurologists, and is heavily utilized in the diagnosis and treatment of epilepsy. The erratic nature of these signals, coupled with their lack of a consistent visible trend results in a high degree of difficulty in forming a statistical model to describe seizures. Working with Delia-normalized signals, the authors compute the associated Shannon entropies for three sets of data, and show via construction that the information flow during an epileptic seizure can be viewed as a type-2 fuzzy graph. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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