Event-triggered sensing for high-quality and low-power cardiovascular monitoring systems
(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:
https://lup.lub.lu.se/record/4c07335d-6ade-4041-910f-a4821a122d19
- author
- Surrel, Gregoire
; Teijeiro, Tomas
; Aminifar, Amir
LU
; Atienza, David and Chevrier, Matthieu
- publishing date
- 2020-10
- 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}}, }