Real-Time Cardiac Arrhythmia Classification Using Memristor Neuromorphic Computing System.

Conference Paper

Cardiac arrhythmia is known to be one of the most common causes of death worldwide. Therefore, development of efficient arrhythmia detection techniques is essential to save patients' lives. In this paper, we introduce a new real-time cardiac arrhythmia classification using memristor neuromorphic computing system for classification of 5 different beat types. Neuromorphic computing systems utilize new emerging devices, such as memristors, as a basic building block. Hence, these systems provide excellent trade-off between real-time processing, power consumption, and overall accuracy. Experimental results showed that the proposed system outperforms most of the methods in comparison in terms of accuracy and testing time, since it achieved 96.17% average accuracy and 34 ms average testing time per beat.

Full Text

Duke Authors

Cited Authors

  • Hassan, AM; Khalaf, AF; Sayed, KS; Li, HH; Chen, Y

Published Date

  • July 2018

Published In

  • Annual International Conference of the Ieee Engineering in Medicine and Biology Society. Ieee Engineering in Medicine and Biology Society. Annual International Conference

Volume / Issue

  • 2018 /

Start / End Page

  • 2567 - 2570

PubMed ID

  • 30440932

Electronic International Standard Serial Number (EISSN)

  • 2694-0604

International Standard Serial Number (ISSN)

  • 2375-7477

Digital Object Identifier (DOI)

  • 10.1109/embc.2018.8512868