Abstract
It is a commonly known fact that one out of 26 people worldwide suffers from epilepsy or will develop epilepsy at some point in their life. Epilepsy is a common condition that affects the brain and causes frequent seizures. Seizures are bursts of electrical activity in the brain that temporarily affect how it works. Most of the people that suffer from epilepsy cannot predict when the seizure is going to occur. If seizure occurs for example, when someone is driving, or when the patient is climbing the stairs, outcome could be fatal for the patient. Also, patients do not always know that they experienced a seizure, due to memory loss during the seizure itself. Commonly used method for detecting seizures is video electroencephalography. This method is utilized with clinical monitoring, but seizures can be detected only while patients are admitted and while testing occurs. Since clinical monitoring is not an everyday activity, a great number of seizures goes unnoticed. Advancements in biosensors and machine learning principles allow us the opportunity to design an affordable mobile device, which would be used daily to monitor and register epileptic seizures.
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Notes
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Arends, JBAM. Movement-based seizure detection. Epilepsia. 2018; 59( S1): 30– 35.
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Smajić, H., Duspara, T. (2023). Hardware Design of a Smart Wristband Used for Epileptic Seizure Detection. In: Auer, M.E., El-Seoud, S.A., Karam, O.H. (eds) Artificial Intelligence and Online Engineering. REV 2022. Lecture Notes in Networks and Systems, vol 524. Springer, Cham. https://doi.org/10.1007/978-3-031-17091-1_65
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DOI: https://doi.org/10.1007/978-3-031-17091-1_65
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