The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
Comparative Evaluation of Susceptibility to Motion Artifact in Different Wearable Systems for Monitoring Respiratory Rate
Open accessAbstract
The purpose of this study is to comparatively evaluate the performance of different wearable systems based on indirect breathing monitoring in terms of susceptibility to motion artifacts. These performances are compared with direct respiratory measurements using a spirometer, which is accurate, reliable, and less sensitive to movement artifacts, but cannot be integrated into truly wearable form. Experiments were carried out on four indirect methods implemented into wearable systems, inductive plethysmography, impedance plethysmography, piezoresistive pneumography, and piezoelectric pneumography, to ascertain the performance of each of them in terms of noise due to movement artifacts, as well as to study the effects of different movements or gestures during each test. A group of volunteers was asked to wear all of the breath monitoring systems simultaneously along with the face mask of the spirometer while carrying out four physical exercises in a gym under controlled conditions. Data are analyzed in the time and frequency domain to estimate the frequency respiration from each wearable system and compare it with those of the spirometer. Results confirmed that all the wearable systems are somehow affected by movement artifacts, but statistical investigation showed that for most of the physical exercises, three out of four, piezoelectric pneumography provided best performance in terms of robustness and reduced susceptibility to movement artifacts.
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“The analysis showed that piezoelectric pneumography performs better than spirometry.”
From A review of wearable sensors and systems with application in rehabilitation (2012) · cites this paper as [29]
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“A comparative analysis of different wearable systems for monitoring respiratory function was presented by Lanata et al. [29].”
From A review of wearable sensors and systems with application in rehabilitation (2012) · cites this paper as [29]
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Zito, D., & Pepe, D. (2015) · Cambridge University Press eBooks · doi:10.1017/cbo9781139629539.014
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Non-contact Vital Signs Monitoring through Visible Light SensingPreprint
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Development of a Stand-alone Portable Respiratory Rate Monitor Using a Doppler Radar
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Development of a Novel Ventilation Estimation Model Based on Convolutional Neural Network (CNN)
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Metadata
- Authors
- Lanatà, A., Scilingo, E. P., Nardini, E., Loriga, G., Paradiso, R., & De-Rossi, D.
- Affiliations
- University of Pisa (IT)
- Smartex (Italy) (IT)
- Venue
- IEEE Transactions on Information Technology in Biomedicine
- Published
- 2010-03
- Volume
- 14
- Issue
- 2
- Pages
- 378-386
- ISSN
- 1089-7771 (ISSN-L)
- 1558-0032
- OpenAlex
- W2123350533
- Cited by
- 111
- References
- 24
- Citations by year
- 2026: 1 · 2025: 4 · 2024: 3 · 2023: 7 · 2022: 5 · 2021: 9 · 2020: 6 · 2019: 10 · 2018: 8 · 2017: 4 · 2016: 4 · 2015: 9 · 2014: 14 · 2013: 11 · 2012: 8
- FWCI
- 3.20
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Locations
- IEEE Transactions on Information Technology in Biomedicine (publishedVersion)
- PubMed (publishedVersion)
- Florence Research (University of Florence) (submittedVersion, other-oa)
- CINECA IRIS Institutial research information system (University of Pisa) (submittedVersion)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Physical Sciences › Engineering › Biomedical Engineering › Wireless Body Area Networks
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Heart Rate Variability and Autonomic Control
- Keywords
- respiratory rate estimation, wearable sensors, motion artifacts, respiratory inductance plethysmography, impedance plethysmography, spirometer, physical activity, artifact robustness, frequency domain analysis
- MeSH terms
- Adult, Clothing, Female, Humans, Male, Motor Activity, Plethysmography, Signal Processing, Computer-Assisted, Spirometry, Artifacts, Monitoring, Ambulatory, Statistics, Nonparametric, Respiratory Rate
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