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A Handbook of Internet of Things in Biomedical and Cyber Physical SystemA Deep Learning Framework for Heart Disease Classification in an IoTs-Based System

A Handbook of Internet of Things in Biomedical and Cyber Physical System: A Deep Learning... [Accurate classification of heart diseases plays an important role and IoTs applied in a medical system will increase the effectiveness of diagnosis. In this chapter, we propose an IoTs-based diagnostic system for heart diseases classification. This system is designed to transmit classified data to server for storage and diagnosis. In particular, ECG devices are connected to internet systems through wifi or 3G/4G technologies for transmitting ECG data to a cloud-based processing system for storing patient’s profiles. Therefore, datasets are pre-processed for extracting features using a WPD algorithm. In addition, a wkPCA method and a deep learning framework are employed for classifying heart diseases. Experimental results and the IoTs-based system description are shown to illustrate the effectiveness of the proposed method. ] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

A Handbook of Internet of Things in Biomedical and Cyber Physical SystemA Deep Learning Framework for Heart Disease Classification in an IoTs-Based System

Part of the Intelligent Systems Reference Library Book Series (volume 165)
Editors: Balas, Valentina E.; Solanki, Vijender Kumar; Kumar, Raghvendra; Ahad, Md. Atiqur Rahman
Nguyen, Thanh-Hai; Nguyen, Thanh-Nghia; Nguyen, Thanh-Tam
A Handbook of Internet of Things in Biomedical and Cyber Physical System — Jul 17, 2019
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Publisher
Springer International Publishing
Copyright
© Springer Nature Switzerland AG 2020
ISBN
978-3-030-23982-4
Pages
217 –244
DOI
10.1007/978-3-030-23983-1_9
Publisher site
See Chapter on Publisher Site

Abstract

[Accurate classification of heart diseases plays an important role and IoTs applied in a medical system will increase the effectiveness of diagnosis. In this chapter, we propose an IoTs-based diagnostic system for heart diseases classification. This system is designed to transmit classified data to server for storage and diagnosis. In particular, ECG devices are connected to internet systems through wifi or 3G/4G technologies for transmitting ECG data to a cloud-based processing system for storing patient’s profiles. Therefore, datasets are pre-processed for extracting features using a WPD algorithm. In addition, a wkPCA method and a deep learning framework are employed for classifying heart diseases. Experimental results and the IoTs-based system description are shown to illustrate the effectiveness of the proposed method. ]

Published: Jul 17, 2019

Keywords: IoTs-based system; WPD algorithm; wkPCA method; Deep learning framework; ECG data; Wifi or 3G/4G technologies; A cloud-based processing

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