Noise-Removal from Spectrally-Similar Signals Using Reservoir Computing for MCG Monitoring

Sadman Sakib, Mostafa M.M.A.E Fouda, Muftah Al-Mahdawi, Attayeb Mohsen, Mikihiko Oogane, Yasuo Ando, Zubair Md Fadlullah

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Continuous low-rate monitoring is an important IoT application, which requires high-fidelity in observing signals with low frequency. However, most sensors exhibit noise that is inversely-proportional to spectral frequency (1/f noise). Because both the relevant signal and noise share the same spectral properties, standard linear filtering techniques cannot be used. We are looking into a special application for remote healthcare of the magnetic field sensing of cardiac activity, magnetocardiography (MCG). For such an application, we need to develop a noise separation method, that is also resource-efficient. Previously, we demonstrated AI-based removal of 1/f noise in MCG by a convolutional neural network coupled with gated recurrent units. However, it needs a large amount of data for training, requiring significant training time and computational power. In this work, we employ reservoir computing (RC) for noise-removal, while being conservative in computing resources.

Original languageEnglish
Title of host publicationICC 2021 - IEEE International Conference on Communications, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728171227
DOIs
Publication statusPublished - 2021 Jun
Event2021 IEEE International Conference on Communications, ICC 2021 - Virtual, Online, Canada
Duration: 2021 Jun 142021 Jun 23

Publication series

NameIEEE International Conference on Communications
ISSN (Print)1550-3607

Conference

Conference2021 IEEE International Conference on Communications, ICC 2021
Country/TerritoryCanada
CityVirtual, Online
Period21/6/1421/6/23

Keywords

  • Internet of Things (IoT)
  • medical analytics
  • noise
  • reservoir computing
  • Smart health
  • spintronic sensor

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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