# Comparing EEG-Based Epilepsy Diagnosis Using Neural Networks and Wavelet Transform
The World Health Organization reports that 20% of patients have primary epilepsy, while the remaining 80% experience focal epilepsy [2]. Factors affecting seizures and epilepsy include stroke diseases related to blood vessels, as well as the use of certain drugs that affect brain function. These diseases lead to brain damage, and in most cases, they cause tension. These brain diseases, especially infection, can lead to problems in the brain, and as a result, this is one of the effective factors in epilepsy. Factors affecting seizures in epilepsy include lack of sleep, alcohol, pressure, sinus infection, and even influenza. Epilepsy, characterized by brain seizures, can be categorized as either focal or non-focal. Focal seizures originate from abnormal brain cells, whereas non-focal seizures arise from normal brain cells. To detect epilepsy accurately, specialized signal processing techniques have been developed to differentiate between focal and non-focal seizures. Additionally, careful analysis of focal signals is crucial, particularly for patients being considered for surgery. This ensures comprehensive evaluation and informed decision-making regarding surgical intervention. The severity of epilepsy can be classified as \"early\" or \"progressive\", with patients in the latter category requiring surgery. Decomposing the electroencephalogram (EEG) signal can help clinicians and neurophysiologists to identify focal signals by extracting characteristics from each sub-band layer [3]. Automatic identification and detection of epilepsy or brain-related disorders is a major concern for neurologists and researchers. Neurologists and brain surgeons often rely on the interpretation of EEG signals to diagnose epilepsy. Therefore, it is essential to develop a reliable and automated technique for detecting epilepsy attacks. There are various neuroimaging techniques for measuring brain activity, such as electroencephalography (EEG), magnetoencephalography (MEG), functional magnetic resonance imaging (fMRI), and functional near-infrared spectroscopy (fNIRS). EEG and FMRI are two completely non-invasive methods and are used to investigate the function and neural mechanisms of the brain. In the diagnosis of epilepsy, EEG and FMRI techniques can be introduced as complementary to each other. EEG signal can display the function of the brain in different frequency bands, and fMRI shows the neural activity of the brain. By using these two techniques, a complete mapping of the brain can be obtained, which plays an important role in the investigation of epilepsy. One of the main abnormalities in patients with epilepsy is interictal epileptic discharges, which are easily identified using these two techniques. EEG is commonly used to capture brain activity through sensors called electrodes, as neurons communicate through electrical signals that reach the surface of the brain [4; 5]. Researchers from various interdisciplinary fields, including engineering, neurology, microelectronics, bioengineering, and neurophysiology, are using EEG-based signal processing technology for a variety of applications, such as controlling external devices, communication, and medical diagnosis. This technology is particularly useful for diagnosing and monitoring neurological brain disorders because it allows for the non-invasive detection of electrical activity in the brain. One common application of EEG is in the diagnosis of epilepsy [6]. Epilepsy is defined as a condition characterized by recurrent seizures that are sometimes caused by external stimuli. According to research, about 4% of people worldwide will experience epilepsy seizure at some point in their lives, with 1% developing the condition. Epilepsy is a neurological disorder characterized by abnormal brain activity in the central nervous system (CNS) that can occur in one part or throughout the entire brain [7]. The result of this irregular activity is seizures, loss of consciousness, exaggerated emotions, and abnormal behavior. Epilepsy can affect anyone regardless of gender, age, or ethnicity.