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Computing and Processing on the Edge: Smart Pathology Detection for Connected Healthcare

Muhammad, Ghulam ; Alhamid, Mohammed F. ; Long, Xiaomi

IEEE network, 2019-11, Vol.33 (6), p.44-49 [Periódico revisado por pares]

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Título:
Computing and Processing on the Edge: Smart Pathology Detection for Connected Healthcare
Autor: Muhammad, Ghulam ; Alhamid, Mohammed F. ; Long, Xiaomi
Assuntos: Brain modeling ; Cloud computing ; Computational modeling ; Electroencephalography ; Intelligent sensors ; Medical services ; Pathology
É parte de: IEEE network, 2019-11, Vol.33 (6), p.44-49
Descrição: With the progress of new generation wireless communication technology and machine learning algorithms to deal with big data, a variety of smart systems are realized to bring comfort to human life. Smart healthcare systems are one of the important developments recently. Such systems will become a necessary ingredient in our connected living. In this article, we propose a new smart pathology detection system using deep learning, edge computing, and cloud computing. Sensors will capture electroencephalogram (EEG) signals of a person and send the signals to a nearby edge computing server. The server will distribute a preprocessing step to available edge devices. The preprocessed signal will then be sent to a cloud computing server. In the cloud server, a proposed tree-based deep model will extract deep features from the EEG signal. The classified decision of whether the signal belongs to a normal person or a pathological person will be distributed to the stakeholders.
Editor: IEEE
Idioma: Inglês

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