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Event-triggered sensing for high-quality and low-power cardiovascular monitoring systems

Surrel, Gregoire ; Teijeiro, Tomas ; Aminifar, Amir LU orcid ; Atienza, David and Chevrier, Matthieu (2020) In IEEE Design and Test 37(5). p.85-93
Abstract

Editor's notes: Non-Nyquist sampling-based event-triggered systems can enable adaptive sampling of IoT nodes resulting in large energy savings. This article reviews introductory concepts and building blocks of non-Nyquist sampling for cardiovascular monitoring systems. It further analyzes the performance of a knowledge-based adaptive sampling strategy applied to biophysiological signals such as electrocardiogram resulting in the order of magnitude reduction in sampling rates. - Subhanshu Gupta, Washington State University.

Please use this url to cite or link to this publication:
author
; ; ; and
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Electrocardiogram (ECG), Event-triggered systems, Medical systems, Non-Nyquist sampling, Online computation, Personalized healthcare, Polygonal approximation, Time to Digital Converter (TDC), Wearable systems
in
IEEE Design and Test
volume
37
issue
5
article number
8890734
pages
9 pages
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
external identifiers
  • scopus:85074603392
ISSN
2168-2356
DOI
10.1109/MDAT.2019.2951126
language
English
LU publication?
no
additional info
Publisher Copyright: © 2013 IEEE.
id
4c07335d-6ade-4041-910f-a4821a122d19
date added to LUP
2022-02-05 01:14:58
date last changed
2022-04-14 22:08:23
@article{4c07335d-6ade-4041-910f-a4821a122d19,
  abstract     = {{<p>Editor's notes: Non-Nyquist sampling-based event-triggered systems can enable adaptive sampling of IoT nodes resulting in large energy savings. This article reviews introductory concepts and building blocks of non-Nyquist sampling for cardiovascular monitoring systems. It further analyzes the performance of a knowledge-based adaptive sampling strategy applied to biophysiological signals such as electrocardiogram resulting in the order of magnitude reduction in sampling rates. - Subhanshu Gupta, Washington State University.</p>}},
  author       = {{Surrel, Gregoire and Teijeiro, Tomas and Aminifar, Amir and Atienza, David and Chevrier, Matthieu}},
  issn         = {{2168-2356}},
  keywords     = {{Electrocardiogram (ECG); Event-triggered systems; Medical systems; Non-Nyquist sampling; Online computation; Personalized healthcare; Polygonal approximation; Time to Digital Converter (TDC); Wearable systems}},
  language     = {{eng}},
  number       = {{5}},
  pages        = {{85--93}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  series       = {{IEEE Design and Test}},
  title        = {{Event-triggered sensing for high-quality and low-power cardiovascular monitoring systems}},
  url          = {{http://dx.doi.org/10.1109/MDAT.2019.2951126}},
  doi          = {{10.1109/MDAT.2019.2951126}},
  volume       = {{37}},
  year         = {{2020}},
}