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Introduction: Migraine is one of the widespread discases in the word, being 15-20 percent prevalent in women, and 6 percent in men. The attacks resulting from the migraine usually range from minor to major, and even may make the patient unable to work. Its dangerous and permanenet effects may also led to paralysis of different parts of the body. Therefore, it is necessary to do more investigations concerning diagnosis and drug treatments which can prevent the migraine attacks better.
Materials and Methods: The study was a randomized controlled trial which lasted for six months. The patients have been studied through different ways including case history, checkup. electroencephalogram (EEG), computed tomography scanning, blood sampling, kidney and liver function and starting time of the treatment. Successful treatment responses to control migrainc attacks using the prophylactic drugs. Valproate Sodium and Propranolol with tricyclic antidepression drugs, i.e., Amitriptyline and/or Nortriptyline were studied.
Results: Of 126 patients studied (31.8% were men and 68.2% women), 65.1% had normal EEG and 34.9% had abnormal EEG. The patients using Valproate Sodium with normal and abnormal EEG had successful treatment responses equal to 35% and 95.6%, respectively. Additionally, other patients using Propranolol with tricyclic antidepressant Amitriptyline and/or Nortriptyline with normal and abnormal EEGs had successful treatment responses equal to 61.9% and 28.6%, respectively. Statistically, the results were significantly different. However, there were not significant differences between interactive effects of the drugs in sexes, and sexes in EEG types. The most prevalent side effects due to Valproate Sodium and Propranolol with tricyclic antidepressant drugs, i.e., Amitriptyline and/or Nortiptyline were vertigo and exhaustation, respectively.
Conclusion: This study revealed that the best treatment to prevent migraine attacks was using Valproate Sodium tablets in patients with abnormal EEGs, and using Propranolol tablets along with Amitriptyline and/or Nortriptyline for those who had normal EEG.

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Background: Epileptic seizures are manifestation of epilepsy. Understanding of the mechanisms causing epileptic disorder needs careful analyses of the electroencephalograph (EEG) records. The detection of epileptic form discharges (spike wave) in the EEG is an important component in the diagnosis of epilepsy. Approximately one in every 100 persons will experience a seizure at some time in their life. Already intelligence spike detection method discucsed but purpose of this research is diagnosis of different kind of epilepsy (grandmal and Petitmal) by design of an intelligence diagnosis processing. Methods and Materials: In this descriptive study, 100 EEG signals of brain hemispheres from different person in healthy, interictal and ictal conditions were used. Fifty Hz noise and artifact signals were removed by soft ware procedure then signals separated by expert neurologist to three categories, healthy (frequency band 8-12 Hz), petitmal seizures (typical 3 Hz), grandmal seizures (clonic stage with 4 Hz frequency) and divided each of them to 6 seconds segments. Information of this signals (background alpha, spike and slow, poly spike and poly sharp) were extracted by wavelet transform and classified by soft ware procedure neural network to there groups healthy, ptitmal and grandmal epilepsy. Results: In designed software accuracy of diagnosis ptitmal and grandmal epilepsies was obtained about 80% Conclusion: This method introduced intelligent diagnosis of epilepsy (ptitmal and gradmal) and automatically detected healthy person from epileptic patients. One of the other advantages is help to neurologist for detection of sickness clearly and expendable different kinds of other epilepsy