A Framework for Epileptic Seizure Monitoring Based on IoT and Machine Learning Technologies

Alhasan Alharbi,Mukta Dhopeshwarkar,Zeyad A.T. Ahmed, Ezzaldeen Mahyoub, Mohammed Tawfik, Ali Manour Almadani

2024 3rd International Conference for Innovation in Technology (INOCON)(2024)

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摘要
Epilepsy is a neurological disorder characterized by recurrent, unprovoked seizures that affects millions of people globally. The unpredictable nature of seizures in epilepsy necessitates vigilant monitoring of these patients to mitigate the risk of adverse events, including physical injury, that may occur during convulsive seizures. It is essential in handling cases of epilepsy that episodes be detected and patient data be stored for later examination. The Internet of Things (IoT) is a potentially revolutionary development in the medical industry since it makes it possible to collect data from individuals using biosensors. This information is then sent to a remote server or cloud storage where it can be analyzed by machine learning software. This article reviews epilepsy patient monitoring IoT platforms and systems that use machine learning and deep learning. It also discusses new research that has greatly used these technologies in monitoring and seizure detection. The most effective sensor devices for detecting and monitoring seizures are also highlighted, and information on the most prevalent kinds of epilepsy types is provided.
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关键词
Epilepsy,IoT,Healthcare,Cloud Computing,Classification,H-IoT,Remote Monitoring
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