The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Monitoring Respiration and Cardiac Activity Using Fiber Bragg Grating-Based Sensor
Abstract
This paper shows the design of a fiber-based sensor for living activities in human body and the results of a laboratory evaluation carried out on it. The authors have developed a device that allows for monitoring the vibrations of human body evoked by living activities--breathing and cardiac rhythm. The device consists of a Bragg grating inscribed into a single mode optical fiber and operating on a wavelength of around 1550 nm. The fiber Bragg grating (FBG) is mounted inside a pneumatic cushion to be placed between the backrest of the seat and the back of the monitored person. Deformations of the cushion, involving deformations of the FBG, are proportional to the vibrations of the body leaning on the cushion. Laboratory studies have shown that the sensor allows for obtaining dynamic strains on the sensing FBG in the range of 50-124 μ strain caused by breathing and approximately 8.3 μstrain induced by heartbeat, which are fully measurable by today's FBG interrogation systems. The maximum relative measurement error of the presented sensor is 12%. The sensor's simple design enables it to be easily implemented in pilot's and driver's seats for monitoring the physiological condition of pilots and drivers.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Measuring agreement in method comparison studies
Bland, J. M., & Altman, D. G. (1999) · Statistical Methods in Medical Research · doi:10.1177/096228029900800204 · Cited by 9,619
Measuring agreement in method comparison studies
Bland, J. M., & Altman, D. G. (1999) · Statistical Methods in Medical Research · doi:10.1191/096228099673819272 · Cited by 9,619
Cited by
Ballistocardiography and Seismocardiography: A Review of Recent Advances
Inan, O. T., Migeotte, P.-F., Park, K.-S., Etemadi, M., Tavakolian, K., Casanella, R., Zanetti, J., Tank, J., Funtova, I., Prisk, G. K., et al. (2015) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2014.2361732 · Cited by 775
Unobtrusive Sensing and Wearable Devices for Health Informatics
Zheng, Y.-L., Ding, X.-R., Poon, C. C. Y., Lo, B. P. L., Zhang, H., Zhou, X.-L., Yang, G.-Z., Zhao, N., & Zhang, Y.-T. (2014) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2014.2309951 · Cited by 722
Contact-Based Methods for Measuring Respiratory Rate
Massaroni, C., Nicolò, A., Lo Presti, D., Sacchetti, M., Silvestri, S., & Schena, E. (2019) · Sensors · doi:10.3390/s19040908 · Cited by 426
Review and Analysis of Peak Tracking Techniques for Fiber Bragg Grating Sensors
Tosi, D. (2017) · Sensors · doi:10.3390/s17102368 · Cited by 266
Wearable System Based on Flexible FBG for Respiratory and Cardiac Monitoring
Lo Presti, D., Massaroni, C., D'Abbraccio, J., Massari, L., Caponero, M., Longo, U. G., Formica, D., Oddo, C. M., & Schena, E. (2019) · IEEE Sensors Journal · doi:10.1109/jsen.2019.2916320 · Cited by 219
Metadata
- Authors
- Dziuda, L., Skibniewski, F. W., Krej, M., & Lewandowski, J.
- Venue
- IEEE Transactions on Biomedical Engineering
- Published
- 2012-07
- Volume
- 59
- Issue
- 7
- Pages
- 1934-1942
- ISSN
- 0018-9294 (ISSN-L)
- 1558-2531
- OpenAlex
- W2031509625
- Cited by
- 186
- References
- 2
- FWCI
- 6.51
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
