Age and gender do not influence the ability to detect respiration by photoplethysmography
Abstract
Objective The non-invasive technique photoplethysmography (PPG) can detect changes in blood volume and perfusion in a tissue. Respiration causes variations in the peripheral circulation, making it possible to monitor breaths using an optical sensor attached to the skin. The respiratory-synchronous part of the PPG signal (PPGr) has been used to monitor respiration during anaesthesia, and in postoperative and neonatal care. Studies addressing possible differences in PPGr signal characteristics depending on gender or age are lacking.Methods We studied three groups of 16 healthy subjects each during normal breathing; young males, old males and young females, and calculated the concordance between PPGr, derived from a reflection mode PPG sensor on the forearm, and a reference CO(2 )signal. The concordance was quantified by using a squared coherence analysis. Time delay between the two signals was calculated. In this process, we compared three different methods for calculating time delay.Results Coherence values >or=0.92 were seen for all three groups without any significant differences depending on age or gender (p = 0.67). Comparison between the three different methods for calculating time delay showed a correlation r = 0.93.Conclusions These results demonstrate clinically important information implying the possibility to register qualitative PPGr signals for respiration monitoring, regardless of age and gender.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
For respiratory measurements, respiratory synchronous variation in the PPG signal is irrespective of gender, and thus no action is required.
“For respiratory measurements, Nilsson et al. have reported that respiratory synchronous variation in the PPG signal is irrespective of gender, and thus no action is required [111].”
From Sources of inaccuracy in photoplethysmography for continuous cardiovascular monitoring (2021) · cites this paper as [111]
Cites
Tremper, K. K., & Barker, S. J. (1989) · Anesthesiology · doi:10.1097/00000542-198901000-00019 · Cited by 438 · see citing works
Critical review of non-invasive respiratory monitoring in medical care
Folke, M., Cernerud, L., Ekström, M., & Hök, B. (2003) · Medical & Biological Engineering & Computing · doi:10.1007/bf02348078 · Cited by 430 · see citing works
Compliance and diameter in the human abdominal aorta—The influence of age and sex
Sonesson, B., Hansen, F., Stale, H., & Länne, T. (1993) · European Journal of Vascular Surgery · doi:10.1016/s0950-821x(05)80718-2 · Cited by 252 · see citing works
Monitoring of respiratory rate in postoperative care using a new photoplethysmographic technique
Nilsson, L. M., Johansson, A., & Kálmán, S. (2000) · Journal of Clinical Monitoring and Computing · doi:10.1023/a:1011424732717 · Cited by 157 · see citing works
Autonomic Control of Skin Microvessels: Assessment by Power Spectrum of Photoplethysmographic Waves
Bernardi, L., Radaelli, A., Soldà, P. L., Coats, A. J. S., REEDER, M. K., Calciati, A., Garrard, C. S., & Sleight, P. (1996) · Clinical Science · doi:10.1042/cs0900345 · Cited by 146 · see citing works
Non invasive physiological measurements
(1985) · General Pharmacology The Vascular System · doi:10.1016/0306-3623(85)90184-3 · Cited by 119 · see citing works
Johansson, A., Öberg, P. Å., & Sedin, G. (1999) · Journal of Clinical Monitoring and Computing · doi:10.1023/a:1009912831366 · Cited by 91 · see citing works
Sandberg, M., Zhang, Q., STYF, J. R., Gerdle, B. U. C., & Lindberg, L. (2005) · Acta Physiologica Scandinavica · doi:10.1111/j.1365-201x.2005.01412.x · Cited by 91 · see citing works
Nilsson, L. M., Johansson, A., & Kálmán, S. (2005) · Acta Anaesthesiologica Scandinavica · doi:10.1111/j.1399-6576.2005.00721.x · Cited by 78 · see citing works
Sensors in Medicine and Health Care
(2004) · Wiley eBooks · doi:10.1002/3527601414 · Cited by 67 · see citing works
Nilsson, L. M., Johansson, A., & Kálmán, S. (2003) · Medical & Biological Engineering & Computing · doi:10.1007/bf02348428 · Cited by 56 · see citing works
Nilsson, L., Johansson, A., & Kalman, S. (2003) · Physiological Measurement · doi:10.1088/0967-3334/24/4/009 · Cited by 55 · see citing works
Continuous Noninvasive Monitoring of Respiratory Rate in Critically III Patients
Krieger, B. P., Feinerman, D., Zaron, A., & Bizousky, F. (1986) · CHEST Journal · doi:10.1378/chest.90.5.632 · Cited by 54 · see citing works
Experimental evaluation of two new sensors for respiratory rate monitoring
Vegfors, M., Ugnell, H., Hök, B., Öberg, P. Å., & Lennmarken, C. (1993) · Physiological Measurement · doi:10.1088/0967-3334/14/2/008 · Cited by 34 · see citing works
Photoplethysmography for simultaneous recording of heart and respiratory rates in newborn infants
Olsson, E., Ugnell, H., Öberg, P. Å., & Sedin, G. (2000) · Acta Paediatrica · doi:10.1080/080352500750043774 · Cited by 31 · see citing works
A New Probe for Ankle Systolic Pressure Measurement Using Photoplethysmography (PPG)
J�nsson, B., Laurent, C. M., Skau, T., & Lindberg, L. (2005) · Annals of Biomedical Engineering · doi:10.1007/s10439-005-8982-7 · Cited by 31 · see citing works
Bjarnegård, N., Ahlgren, Å. R., Sandgren, T., Sonesson, B., & Länne, T. (2003) · Ultrasound in Medicine & Biology · doi:10.1016/s0301-5629(03)00052-8 · Cited by 20 · see citing works
Non-invasive physiological measurement
(1985) · Comparative Biochemistry and Physiology Part A Physiology · doi:10.1016/0300-9629(85)90527-4 · Cited by 20 · see citing works
Development of a Compact Home Health Monitor for Telemedicine
Yoon, G., Lee, J. Y., Jeon, K. J., Park, K. K., & Kim, H. S. (2005) · Telemedicine Journal and e-Health · doi:10.1089/tmj.2005.11.660 · Cited by 15 · see citing works
Johansson, A. F., & Strömberg, T. (2000) · Journal of Clinical Monitoring and Computing · doi:10.1023/a:1012260415191 · Cited by 11 · see citing works
[Hypertension as a function of age].
Gensini, G. F., & Corradi, F. (2000) · PubMed · Cited by 9 · see citing works
Principles & guidelines for respiratory monitoring on the general cake floor
Chiu, L., Eichhorn, J. H., HESS, D. R., Hoffman, L. A., Miaskowski, C. A., Trosty, R. S., Youngberg, B. J., & Robins, D. S. (1996) · The Journal of Clinical Monitoring · doi:10.1007/bf02077640 · Cited by 9 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Photoplethysmography and its application in clinical physiological measurement
Allen, J. (2007) · Physiological Measurement · doi:10.1088/0967-3334/28/3/r01 · Cited by 3,967 · see citing works
Sources of inaccuracy in photoplethysmography for continuous cardiovascular monitoring
Fine, J., Branan, K. L., Rodriguez, A. J., Boonya-ananta, T., Ajmal, Ramella-Roman, J. C., McShane, M. J., & Coté, G. L. (2021) · Biosensors · doi:10.3390/bios11040126 · Cited by 348 · see citing works
Respiration Signals from Photoplethysmography
Nilsson, L. M. (2013) · Anesthesia & Analgesia · doi:10.1213/ane.0b013e31828098b2 · Cited by 129 · see citing works
Tarassenko, S. G. F. L. (2007) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.1080903 · Cited by 100 · see citing works
Nilsson, L., Goscinski, T., Kalman, S., Lindberg, L. ‐., & Johansson, A. (2007) · Acta Anaesthesiologica Scandinavica · doi:10.1111/j.1399-6576.2007.01375.x · Cited by 88 · see citing works
Huang, Y., Zhao, Y., Wang, Y., Guo, X., Zhang, Y., Liu, P., Liu, C., & Zhang, Y. (2018) · Smart Materials and Structures · doi:10.1088/1361-665x/aaaba0 · Cited by 61 · see citing works
Probabilistic Estimation of Respiratory Rate from Wearable Sensors
Pimentel, M. A. F., Charlton, P. H., & Clifton, D. A. (2015) · Smart sensors, measurement and instrumentation · doi:10.1007/978-3-319-18191-2_10 · Cited by 61 · see citing works
Wearable low power dry surface wireless sensor node for healthcare monitoring application
Magno, M., Luca Benini, C., Spagnol, C., & Popovici, E. M. (2013) · IEEE International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob) · doi:10.1109/wimob.2013.6673360 · Cited by 59 · see citing works
Fahoum, A. S. A., Al-Haija, A. O. A., & Alshraideh, H. A. (2023) · Bioengineering · doi:10.3390/bioengineering10020249 · Cited by 59 · see citing works
Wearable Graphene-based smart face mask for Real-Time human respiration monitoring
Bidsorkhi, H. C., Faramarzi, N., Ali, B., Ballam, L. R., D’Aloia, A. G., Tamburrano, A., & Sarto, M. S. (2023) · Materials & Design · doi:10.1016/j.matdes.2023.111970 · Cited by 56 · see citing works
Wearable In-Ear PPG: Detailed Respiratory Variations Enable Classification of COPD
Davies, H. J., Bächtiger, P., Williams, I., Molyneaux, P. L., Peters, N. S., & Mandic, D. P. (2022) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2022.3145688 · Cited by 51 · see citing works
Liu, H., Chen, F., Hartmann, V., Khalid, S. G., Hughes, S., & Zheng, D. (2020) · Physiological Measurement · doi:10.1088/1361-6579/abaaf0 · Cited by 49 · see citing works
Monitoring heart and respiratory rates at radial artery based on PPG
Wang, C., Li, Z., & Wei, X. (2013) · Optik · doi:10.1016/j.ijleo.2012.11.044 · Cited by 44 · see citing works
Choi, S. J., AHN, H. J., Yang, M., Kim, C. S., Sim, W.-S., Kim, J. A., Kang, J. G., KIM, J. K., & Kang, J. (2009) · Acta Anaesthesiologica Scandinavica · doi:10.1111/j.1399-6576.2009.02101.x · Cited by 41 · see citing works
Wearable Vital Signs Monitoring for Patients With Asthma: A Review
Taylor, L., Ding, X., Clifton, D. A., & Lu, H. Y. (2022) · IEEE Sensors Journal · doi:10.1109/jsen.2022.3224411 · Cited by 39 · see citing works
A low power wireless node for contact and contactless heart monitoring
Magno, M., Spagnol, C., Luca Benini, C., & Popovici, E. M. (2014) · Microelectronics Journal · doi:10.1016/j.mejo.2014.07.002 · Cited by 38 · see citing works
Knitted piezoresistive smart chest band and its application for respiration patterns assessment
Raji, R. K., Miao, X., Wan, A., Niu, L., Li, Y., & Boakye, A. (2019) · Journal of Engineered Fibers and Fabrics · doi:10.1177/1558925019868474 · Cited by 27 · see citing works
Zheng, X., Dwyer, V. M., Barrett, L. A., Derakhshani, M., & Hu, S. (2023) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2023.3268240 · Cited by 16 · see citing works
Nilsson, L. M., Goscinski, T., Lindenberger, M., Länne, T., & Johansson, A. (2010) · Physiological Measurement · doi:10.1088/0967-3334/31/7/006 · Cited by 12 · see citing works
Cernat, R. A., Ciorecan, S. I., Ungureanu, C., Arends, J. B. A. M., Strungaru, R., & Ungureanu, G. M. (2015) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2015.7319753 · Cited by 10 · see citing works
Romero, E., Andújar, C. S. D. B., & López-Ongil, C. (2023) · Sensors · doi:10.3390/s23125483 · Cited by 9 · see citing works
Respiration rate calculation using low power DSP processor and SpO2 sensor
Canu, A., Canu, M., Marinkovic, S., Faul, S., & Popovici, E. M. (2011) · IEEE International Symposium on Medical Measurements and Applications (MeMeA) · doi:10.1109/memea.2011.5966757 · Cited by 8 · see citing works
Soubelet, A., Pathinarupothi, R. K., Rangan, E. S., Kripesh, Durga, P., & Menon, K. A. U. (2019) · EAI/Springer Innovations in Communication and Computing · doi:10.1007/978-3-030-30335-8_8 · Cited by 6 · see citing works
Efficacy of dynamic indices in predicting fluid responsiveness in patients with obstructive jaundice
Pei, S., Yuan, W., Mai, H., Wang, M., Hao, C., Mi, W., & Fu, Q. (2014) · Physiological Measurement · doi:10.1088/0967-3334/35/3/369 · Cited by 4 · see citing works
Mahri, N., Gan, K. B., & Ali, M. A. M. (2014) · IEEE-EMBS Conference on Biomedical Engineering and Sciences · doi:10.1109/iecbes.2014.7047544 · Cited by 4 · see citing works
Nilsson, L. M. (2006) · Acta Anaesthesiologica Scandinavica · doi:10.1111/j.1399-6576.2006.01198.x · Cited by 1 · see citing works
- Authors
- Nilsson, L., Goscinski, T., Johansson, A., Lindberg, L.-G., & Kalman, S.
- Affiliations
- Linköping University Hospital (SE)
- Linköping University (SE)
- Corresponding author
- Nilsson, Lena
- Venue
- Journal of Clinical Monitoring and Computing
- Published
- 2006-10-11
- Volume
- 20
- Issue
- 6
- Pages
- 431-436
- ISSN
- 1387-1307 (ISSN-L)
- 1573-2614
- OpenAlex
- W1975186956
- Cited by
- 26
- References
- 22
- Citations by year
- 2023: 4 · 2022: 2 · 2021: 1 · 2020: 1 · 2019: 2 · 2018: 1 · 2015: 2 · 2014: 3 · 2013: 3
- FWCI
- 1.28
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Journal of Clinical Monitoring and Computing (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Health Sciences › Medicine › Surgery › Hemodynamic Monitoring and Therapy
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Heart Rate Variability and Autonomic Control
- Keywords
- photoplethysmography, respiratory monitoring, breathing detection, age differences, gender differences, coherence analysis, time delay estimation, peripheral circulation, anesthesia monitoring
- MeSH terms
- Adult, Age Factors, Aged, Female, Humans, Male, Middle Aged, Monitoring, Physiologic, Respiratory Function Tests, Respiratory Physiological Phenomena, Sex Characteristics, Signal Processing, Computer-Assisted, Photoplethysmography
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
