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IoT Platform for Real-Time Multichannel ECG Monitoring and Classification with Neural Networks

  • Jose GranadosEmail author
  • Tomi WesterlundEmail author
  • Lirong ZhengEmail author
  • Zhuo ZouEmail author
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 310)

Abstract

Internet of Things (IoT) platforms applied to health promise to offer solutions to the challenges in healthcare systems by providing tools for lowering costs while increasing efficiency in diagnostics and treatment. Many of the works on this topic focus on explaining the concepts and interfaces between different parts of an IoT platform, including the generation of knowledge based on smart sensors gathering bio-signals from the human body which are processed by data mining and more recently, deep neural networks hosted on cloud computing infrastructure. These techniques are designed to serve as useful intelligent companions to healthcare professionals in their practice. In this work we present details about the implementation of an IoT Platform for real-time analysis and management of a network of bio-sensors and gateways, as well as the use of a cloud deep neural network architecture for the classification of ECG data into multiple cardiovascular conditions.

Keywords

IoT ECG Healthcare AI Neural networks 

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Copyright information

© IFIP International Federation for Information Processing 2018

Authors and Affiliations

  1. 1.School of Information Science and TechnologyFudan UniversityShanghaiChina
  2. 2.Department of Information TechnologyUniversity of TurkuTurkuFinland

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