The DOI matches its Crossref record; 35 of the 37 references it cites were found in a registry or an index.
Medical Devices for Measuring Respiratory Rate in Children: a Review
Abstract
Respiratory rate is an important vital sign used for diagnosing illnesses in children as well as prioritising patient care. All children presenting acutely to hospital should have a respiratory rate measured as part of their initial and ongoing assessment. However measuring the respiratory rate remains a subjective assessment and in children can be liable to measurement error especially if the child is uncooperative. Devices to measure respiratory rate exist but many provide only an estimate of respiratory rate due to the associated methodological complexities. Some devices are used within the intensive care, post-operative or more specialised investigatory settings none however have made their way into the everyday clinical setting. A non-contact device may be better tolerated in children and not cause undue stress distorting the measurement. Further validation and adaption to the acute clinical setting is needed before such devices can supersede current methods.
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“This platform is effective in detecting rapid temporal changes in frequency, most commonly due to motion artifact, as a simple but effective means to reduce motion artifact effects22,23”
From Skin-interfaced biosensors for advanced wireless physiological monitoring in neonatal and pediatric intensive-care units (2020) · cites this paper as [23]
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Cites
Clinical Practice Guideline: Diagnosis and Management of Childhood Obstructive Sleep Apnea Syndrome
Pulmonology, S. O. P. (2002) · PEDIATRICS · doi:10.1542/peds.109.4.704 · Cited by 930
Respiration rate monitoring methods: A review
Al-Khalidi, F. Q., Saatchi, R., Burke, D. P., Elphick, H., & Tan, S. (2011) · Pediatric Pulmonology · doi:10.1002/ppul.21416 · Cited by 538
Subbe, C. P., Davies, R. G., Williams, E., Rutherford, P., & Gemmell, L. (2003) · Anaesthesia · doi:10.1046/j.1365-2044.2003.03258.x · Cited by 444
Lovett, P. B., Buchwald, J. M., Stürmann, K., & Bijur, P. E. (2004) · Annals of Emergency Medicine · doi:10.1016/j.annemergmed.2004.06.016 · Cited by 243
Aarts, L. A. M., Jeanne, V., Cleary, J. P., Lieber, C. A., Nelson, J. S., Oetomo, S. B., & Verkruysse, W. (2013) · Early Human Development · doi:10.1016/j.earlhumdev.2013.09.016 · Cited by 241
Neonatal non-contact respiratory monitoring based on real-time infrared thermography
Abbas, A. K., Heimann, K., Jergus, K., Orlikowsky, T. W., & Leonhardt, S. K. (2011) · BioMedical Engineering OnLine · doi:10.1186/1475-925x-10-93 · Cited by 227
Respiratory Rate and Flow Waveform Estimation from Tri-axial Accelerometer Data
Bates, A., Ling, M. J., Mann, J., & Arvind, D. K. (2010) · Wearable and Implantable Body Sensor Networks · doi:10.1109/bsn.2010.50 · Cited by 168
Radar sensing of heartbeat and respiration at a distance with applications of the technology
Greneker, E. F. (1997) · doi:10.1049/cp:19971650 · Cited by 149
Non-contact respiratory rate measurement validation for hospitalized patients
Droitcour, A. D., Seto, T. B., Park, B.-K., Yamada, S., Vergara, A., Hourani, C. E., Shing, T., Yuen, A., Lubecke, V. M., & Boric-Lubecke, O. (2009) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/iembs.2009.5332635 · Cited by 135
Wireless patch sensor for remote monitoring of heart rate, respiration, activity, and falls
Chan, A. M., Selvaraj, N., Ferdosi, N., & Narasimhan, R. (2013) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2013.6610948 · Cited by 107
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Chen, L., Hu, M., Liu, N., Zhai, G., & Yang, S. X. (2020) · Infrared Physics & Technology · doi:10.1016/j.infrared.2020.103504 · Cited by 21
Respiratory rate on exercise measured by nanoparticle-based humidity sensor
Kano, S., Yamamoto, A., Ishikawa, A., & Fujii, M. (2019) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2019.8856875 · Cited by 19
Hu, M., Zhai, G., Li, D., Li, H., Liu, M., Tang, W., & Chen, Y. (2018) · Infrared Physics & Technology · doi:10.1016/j.infrared.2018.05.026 · Cited by 14
Daw, W., Kingshott, R. N., & Elphick, H. (2017) · BMJ Paediatrics Open · doi:10.1136/bmjpo-2017-000173 · Cited by 17
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Khan, A. M., Ahmed, S., Chowdhury, N. H., Islam, M. S., McCollum, E. D., King, C., Shi, T., Nahar, K., Simpson, R., Ahmed, A., et al. (2022) · BMJ Open · doi:10.1136/bmjopen-2022-067389 · Cited by 9
Respiration Measurement in a Simulated Setting Incorporating the Internet of Things
Abdulqader, T., Saatchi, R., & Elphick, H. (2021) · Technologies · doi:10.3390/technologies9020030 · Cited by 8
Rethink Respiratory Rate for Diagnosing Childhood Pneumonia
Amirav, I., & Lavie, M. (2019) · EClinicalMedicine · doi:10.1016/j.eclinm.2019.06.013 · Cited by 7
Detection of Abnormal Respiration from Multiple-Input Respiratory Signals
Kim, J. O., & Lee, D. (2020) · Sensors · doi:10.3390/s20102977 · Cited by 6
Novel Non-contact Respiration Rate Detector for Analysis of Emotions
Prince, P. G. K., Rajkumar, I., & Premalatha, J. S. (2019) · Learning and analytics in intelligent systems · doi:10.1007/978-3-030-35139-7_8 · Cited by 6
The Use of Thermal Imaging Techniques as a Method of Monitoring the New Born
Luca, C. M., Corciovă, C., Andriţoi, D., & Ciorap, R. (2019) · World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany · doi:10.1007/978-981-13-6207-1_6 · Cited by 3
Gibson, K., Al‐Naji, A., Fleet, J., Steen, M., Chahl, J., Huynh, J. Y., & Morris, S. A. (2019) · JMIR Research Protocols · doi:10.2196/13400 · Cited by 3
Kong, L., Li, G., Wang, Y., & Lin, L. (2023) · Measurement · doi:10.1016/j.measurement.2023.113444 · Cited by 2
Saatchi, R., Holloway, A., Travis, J. R., Elphick, H., Daw, W., Daw, W., Hughes, B., Burke, D. P., Jones, A. H., & Evans, R. L. (2025) · Technologies · doi:10.3390/technologies13060237 · Cited by 2
Self-citationNoninvasive Measurement of Infant Respiration During Sleep: A Validation Study
Horger, M. N., Lucchini, M., Thakur, S., Spencer, R. M. C., & Barnett, N. (2026) · Italian National Conference on Sensors · doi:10.3390/s26072275 · Cited by 1
Noncontact Respiration Rate Monitoring: An Evaluation of Four Methods
Stratton, H. H., Saatchi, R., Evans, R. E. C., & Elphick, H. (2021) · SHURA (Sheffield Hallam University Research Archive) (Sheffield Hallam University) · Cited by 1
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Bakshi, S., Feng, T., Chen, D., & Li, W. (2019) · Journal of Engineering and Science in Medical Diagnostics and Therapy · doi:10.1115/1.4045147
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Manullang, M. C. T., Siswanto, Y. T., & Resfita, N. (2023) · AIP conference proceedings · doi:10.1063/5.0129743
Khan, A. M., Islam, M. S., Chowdhury, N. H., Ahmed, S., Shi, T., Baqui, A. H., Cunningham, S., McCollum, E. D., & Campbell, H. (2025) · BMJ Open Respiratory Research · doi:10.1136/bmjresp-2025-003591
Khan, A. M., Islam, M. S., Chowdhury, N. H., Ahmed, S., Tabassum, R., Haque, K. S., Afrin, S., Amin, Z. F., Rumi, A. Y., Rahman, J., et al. (2026) · Discover Public Health · doi:10.1186/s12982-026-01513-0
Metadata
- Authors
- Daw, W.
- Affiliations
- Sheffield Children's Hospital (GB)
- Corresponding author
- Daw, William
- Venue
- Journal of Advances in Biomedical Engineering and Technology
- Publisher
- Cosmos Scholars Publishing House
- Published
- 2016-05-31
- Volume
- 3
- Issue
- 1
- ISSN
- 2409-3394 (ISSN-L)
- OpenAlex
- W2802457949
- Cited by
- 35
- References
- 37
- Citations by year
- 2026: 2 · 2025: 2 · 2023: 2 · 2022: 3 · 2021: 6 · 2020: 4 · 2019: 12 · 2018: 2 · 2017: 1 · 2016: 1
- FWCI
- 2.57
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Advances in Biomedical Engineering and Technology (publishedVersion)
- SHURA (Sheffield Hallam University Research Archive) (Sheffield Hallam University) (acceptedVersion)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Health Sciences › Medicine › Surgery › Hemodynamic Monitoring and Therapy
- Health Sciences › Medicine › Surgery › Healthcare Technology and Patient Monitoring
- Keywords
- respiratory rate measurement, medical devices, children, vital signs, non-contact monitoring, measurement error, clinical evaluation, device validation, paediatric care
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