Why the study?
New generation communication technologies and deep learning present an opportunity to develop fast, accurate, and seamless distributed systems for pathology detection in healthcare.
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A proposed deep learning-based framework for EEG pathology detection using edge and cloud computing demonstrated appropriateness on a public database.
New generation communication technologies and advanced deep learning models present a tremendous opportunity to develop fast, accurate, and seamless distributed systems in different sectors including the healthcare sector. in this article, we suggest a smart healthcare framework consisting of a pathology detection system, which is developed using deep learning. The pathology can be detected from electroencephalogram signals of a subject. in the framework, a smart EEG headset captures EEG signals and sends them to a mobile edge computing server. The server preprocesses the signals and transmits them to a cloud server. The cloud server does the main processing using deep learning and decides on whether the subject has pathology or not. Clients and stakeholders of the framework are connected via an authentication manager located in the cloud server. Experiment results on a publicly available database confirm the appropriateness of the proposed framework.
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Hossain et al. (2020) studied this question.
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