| Autor: |
Bharathipriya, C., Manigandan, M. D., Sudha, G., Velvizhi, V. A., Prakash, Jeya, Kadambarajan, Sasikala, V. |
| Předmět: |
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| Zdroj: |
AIP Conference Proceedings; 9/28/2022, Vol. 2518 Issue 1, p1-15, 15p |
| Abstrakt: |
Epilepsy, one of the most common neurological conditions characterized by epileptic seizures, is the second most common neurological disorder behind stroke, according to the World Health Organization (WHO). Epilepsy is a neurological disorder that affects approximately fifty million people according to the World Health Organization. Patients with epilepsy suffer from sudden and unforeseen seizures, during which they are unable to protect themselves and are vulnerable to suffocation, death, or injury due to fainting and traffic accidents. Electroencephalography (EEG) plays an important role in detecting epilepsy, as it measures differences in voltage changes between electrodes along the subject's scalp by sense ionic currents flowing within brain neurons and provides temporal and spatial information about the brain. Electroencephalography (EEG) is an effective and non-invasive technique for directly recording the brain electrical activity and diagnosing clinical brain diseases. Detection with EEG requires a direct examination by a physician as well as a substantial amount of time and effort. The development of an automated, computer-aided method for the diagnosis of epilepsy is urgently needed. Electroencephalography (EEG) signals play important roles in monitoring the brain activity of patients with epilepsy and diagnosing epilepsy, analyzing all EEG recordings to detect epileptic activity is quintessential. [ABSTRACT FROM AUTHOR] |
| Databáze: |
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