Digital Photoplethysmography for Assessment of Arterial Stiffness: Repeatability and Comparison with Applanation Tonometry
Open accessAbstract
INTRODUCTION: Arterial stiffness is an independent risk factor for cardiovascular morbidity and can be assessed by applanation tonometry by measuring pulse wave velocity (PWV) and augmentation index (AIX) by pressure pulse wave analysis (PWA). As an inexpensive and operator independent alternative, photoelectric plethysmography (PPG) has been introduced with analysis of the digital volume pulse wave (DPA) and its second derivatives of wave reflections. OBJECTIVE: The objective was to investigate the repeatability of arterial stiffness parameters measured by digital pulse wave analysis (DPA) and the associations to applanation tonometry parameters. METHODS AND RESULTS: 112 pregnant and non-pregnant individuals of different ages and genders were examined with SphygmoCor arterial wall tonometry and Meridian DPA finger photoplethysmography. Coefficients of repeatability, Bland-Altman plots, intraclass correlation coefficients and correlations to heart rate (HR) and body height were calculated for DPA variables, and the DPA variables were compared to tonometry variables left ventricular ejection time (LVET), PWV and AIX. No DPA variable showed any systematic measurement error or excellent repeatability, but dicrotic index (DI), dicrotic dilatation index (DDI), cardiac ejection elasticity index (EEI), aging index (AI) and second derivatives of the crude pulse wave curve, b/a and e/a, showed good repeatability. Overall, the correlations to AIX were better than to PWV, with correlations coefficients >0.70 for EEI, AI and b/a. Considering the level of repeatability and the correlations to tonometry, the overall best DPA parameters were EEI, AI and b/a. The two pansystolic time parameters, ejection time compensated (ETc) by DPA and LVET by tonometry, showed a significant but weak correlation. CONCLUSION: For estimation of the LV function, ETc, EEI and b/a are suitable, for large artery stiffness EEI, and for small arteries DI and DDI. The only global parameter, AI, showed a high repeatability and the overall best correlations with AIX and PWV.
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
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.
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?
Over 30 features have been proposed for assessing the stiffness of both large and small arteries from a single PPG.
“Over 30 features have been proposed for assessing the stiffness of both the large and small arteries from a single PPG”
From Wearable Photoplethysmography for Cardiovascular Monitoring (2022) · cites this paper as [172]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
STATISTICAL METHODS FOR ASSESSING AGREEMENT BETWEEN TWO METHODS OF CLINICAL MEASUREMENT
Martin Bland, J., & Altman, D. (1986) · The Lancet · doi:10.1016/s0140-6736(86)90837-8 · Cited by 47,965 · see citing works
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 · cited 1× · see citing works
“We described agreement between the two DPA measurements with Bland-Altman plots [36,37].”
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 · see citing works
Expert consensus document on arterial stiffness: methodological issues and clinical applications
Laurent, S., Cockcroft, J., Van Bortel, L., Boutouyrie, P., Giannattasio, C., Hayoz, D., Pannier, B., Vlachopoulos, C., Wilkinson, I., Struijker-Boudier, H., et al. (2006) · European Heart Journal · doi:10.1093/eurheartj/ehl254 · Cited by 6,077 · see citing works
McDonald's blood flow in arteries; theoretical, experimental and clinical principles
(1992) · General Pharmacology The Vascular System · doi:10.1016/0306-3623(92)90079-y · Cited by 2,394 · see citing works
Aortic Stiffness Is an Independent Predictor of Primary Coronary Events in Hypertensive Patients
Boutouyrie, P., Tropeano, A., Asmar, R. G., Gautier, I., Bénétos, A., Lacolley, P. J., & Laurent, S. (2002) · Hypertension · doi:10.1161/hy0102.099031 · Cited by 1,745 · cited 2× · see citing works
“Although pressure PW analysis shows benefits in predicting cardiovascular morbidity [1,10], the impact in clinical practice is small because the tonometry method is cumbersome with a need for highly specialized operators.”
McDonald's Blood Flow in Arteries: Theoretical, Experimental and Clinical Principles
Vlachopoulos, C., O'Rourke, M., & Nichols, W. W. (2011) · doi:10.1201/b13568 · Cited by 1,613 · see citing works
Aortic pulse wave velocity as a marker of cardiovascular risk in hypertensive patients
Blacher, J., Asmar, R., Djane, S., London, G. M., & Safar, M. E. (1999) · Hypertension · doi:10.1161/01.hyp.33.5.1111 · Cited by 1,493 · cited 1× · see citing works
“The PWV is correlated to age, blood pressure (BP) and arteriosclerosis and has a better predictive value for cardiovascular disease than traditional risk markers [3,4].”
On the Analysis of Fingertip Photoplethysmogram Signals
Elgendi, M. (2012) · Current Cardiology Reviews · doi:10.2174/157340312801215782 · Cited by 1,206 · cited 3× · see citing works
“The e wave represents the dictrotic notch and corresponds to the aortic valve closure [11].”
InfluentialClinical measurement of arterial stiffness obtained from noninvasive pressure waveforms
NICHOLS, W. (2005) · American Journal of Hypertension · doi:10.1016/j.amjhyper.2004.10.009 · Cited by 1,002 · cited 1× · see citing works
“AIX is influenced by both large artery stiffness and properties in the PW-reflecting peripheral arterial tree [5 – 7] and is associated with cardiovascular risk, although it is less established than the PWV as a risk factor for cardiovascular morbidity [8 – 10].”
Foundations of Clinical Research
Portney, L. G., & Watkins, M. P. (1993) · Cited by 981 · see citing works
Bartlett, J. W., & Frost, C. D. (2008) · Ultrasound in Obstetrics and Gynecology · doi:10.1002/uog.5256 · Cited by 943 · cited 9× · see citing works
“Agreement quantifies how close measurements made on the same subject are under identical conditions over a short period of time [34].”
InfluentialKawaguchi, M., Hay, I., Fetics, B. J., & Kass, D. A. (2003) · Circulation · doi:10.1161/01.cir.0000048123.22359.a0 · Cited by 929 · cited 1× · see citing works
“An inverse relation exists between myocardial contractility and arterial compliance [47] and both the b/a ratio and the AIX reflect these entities.”
A critical review of the systolic time intervals.
Lewis, R. P., Rittogers, S. E., Froester, W. F., & Boudoulas, H. (1977) · Circulation · doi:10.1161/01.cir.56.2.146 · Cited by 624 · see citing works
Determination of age-related increases in large artery stiffness by digital pulse contour analysis
Millasseau, S., Kelly, R. P., Ritter, J., & Chowienczyk, P. (2002) · Clinical Science · doi:10.1042/cs1030371 · Cited by 624 · see citing works
Takazawa, K., Tanaka, N., Fujita, M., Matsuoka, O., Saiki, T., Aikawa, M., Tamura, S., & Ibukiyama, C. (1998) · Hypertension · doi:10.1161/01.hyp.32.2.365 · Cited by 589 · see citing works
The Case for Using the Repeatability Coefficient When Calculating Test–Retest Reliability
Vaz, S. M. A., Falkmer, T., Passmore, A. E., Parsons, R. W., & Andreou, P. (2013) · PLoS ONE · doi:10.1371/journal.pone.0073990 · Cited by 476 · cited 2× · see citing works
“The ICC takes dimensionless values between zero and one [34,35], where the value of (1 –ICC) relates to the errors in the measurement process.”
Augmentation index is associated with cardiovascular risk
Nürnberger, J., Keflioglu-Scheiber, A., Saez, A. M. O., Wenzel, R. R., Philipp, T., & Schäfers, R. F. (2002) · Journal of Hypertension · doi:10.1097/00004872-200212000-00020 · Cited by 441 · cited 1× · see citing works
“AIX is influenced by both large artery stiffness and properties in the PW-reflecting peripheral arterial tree [5 – 7] and is associated with cardiovascular risk, although it is less established than the PWV as a risk factor for cardiovascular morbidity [8 – 10].”
Weissler, A. M., Peeler, R. G., & Roehll, W. H. (1961) · American Heart Journal · doi:10.1016/0002-8703(61)90403-3 · Cited by 440 · cited 1× · see citing works
“The ET varies inversely with the HR and directly with stroke volume [31] and ETc is therefore adjusted to a HR of 60 bpm (beats/second = bpm/60) in the Meridian DPA, reading the calculation equation as ETc = (S-C time)/ p (HR/60); this is a non-linear HR correction equation, originally presented by Bazett in 1920 [32].”
Kelly, R. P., Millasseau, S., Ritter, J. M., & Chowienczyk, P. (2001) · Hypertension · doi:10.1161/01.hyp.37.6.1429 · Cited by 390 · see citing works
Heart rate dependency of pulse pressure amplification and arterial stiffness
Wilkinson, I. B., Mohammad, N. H., Tyrrell, S., Hall, I. R., Webb, D. J., Paul, V. E., Levy, T., & Cockcroft, J. (2002) · American Journal of Hypertension · doi:10.1016/s0895-7061(01)02252-x · Cited by 357 · cited 1× · see citing works
“from the heart and the amplification is positively correlated to the HR [21], but due to an alteration in the relative timing of the reflected pressure PW, the AIX is inversely related to HR [23].”
Contour analysis of the photoplethysmographic pulse measured at the finger
Millasseau, S., Ritter, J. M., Takazawa, K., & Chowienczyk, P. (2006) · Journal of Hypertension · doi:10.1097/01.hjh.0000239277.05068.87 · Cited by 351 · cited 1× · see citing works
“Millasseau and colleagues [25] have described the physiological background to the contour analysis of the PPG PW measured in a finger.”
Pulse wave analysis and pulse wave velocity
Davies, J. I., & Struthers, A. D. (2003) · Journal of Hypertension · doi:10.1097/00004872-200303000-00004 · Cited by 292 · cited 3× · see citing works
“Davies & Struther [20] have described the applanation tonometry method with assessment of the pressure PW.”
InfluentialNoninvasive Assessment of the Digital Volume Pulse
Millasseau, S., Guigui, F. G., Kelly, R. P., Prasad, K., Cockcroft, J., Ritter, J. M., & Chowienczyk, P. (2000) · Hypertension · doi:10.1161/01.hyp.36.6.952 · Cited by 292 · cited 2× · see citing works
“[12] have in parallel recordings showed that there are close correlations between the contours and characteristics of the peripheral arterial pressure PW and the digital volume PW.”
Bortolotto, L. A., Blacher, J., Kondo, T., Takazawa, K., & Safar, M. E. (2000) · American Journal of Hypertension · doi:10.1016/s0895-7061(99)00192-2 · Cited by 272 · cited 2× · see citing works
“the more negative, the better; AI increases with age and arteriosclerosis [4,14,16].”
Yasmin, Y. (1999) · QJM · doi:10.1093/qjmed/92.10.595 · Cited by 242 · cited 1× · see citing works
“AIX is influenced by both large artery stiffness and properties in the PW-reflecting peripheral arterial tree [5 – 7] and is associated with cardiovascular risk, although it is less established than the PWV as a risk factor for cardiovascular morbidity [8 – 10].”
The peripheral pulse wave: Information overlooked
Murray, W. B., & Foster, P. A. (1996) · The Journal of Clinical Monitoring · doi:10.1007/bf02077634 · Cited by 231 · cited 2× · see citing works
“A correct identification of the dicrotic notch is therefore essential to determine the systolic time [27], but due to variations in HR, cardiac output and vascular tone, with drifting in time positioning of the dicrotic notch with distance from the aortic valve, and to interference with the reflected wave, its applica…”
BackgroundPHOTO-ELECTRIC PLETHYSMOGRAPHY AS A MONITORING DEVICE IN ANAESTHESIA
Dorlas, J. C., & Nijboer, J. A. (1985) · British Journal of Anaesthesia · doi:10.1093/bja/57.5.524 · Cited by 160 · see citing works
Assessing Reproducibility by the Within-Subject Coefficient of Variation with Random Effects Models
Quan, H., & Shih, W.-C. (1996) · Biometrics · doi:10.2307/2532835 · Cited by 152 · see citing works
Hashimoto, J., Chonan, K., Aoki, Y., Nishimura, T., Ohkubo, T., Hozawa, A., Suzuki, M., Matsubara, M., Michimata, M., Araki, T., et al. (2002) · Journal of Hypertension · doi:10.1097/00004872-200212000-00021 · Cited by 122 · cited 5× · see citing works
“Hashimoto and coworkers [16] write that the weak correlations with PWV are not due to poor reproducibility of the PWV and DPA parameters, but occur because the parameters reflect different physiological properties at central and peripheral sites in the arterial vascular system.”
InfluentialImanaga, I., Hara, H., KOYANAGI, S., & TANAKA, K. (1998) · Japanese Heart Journal · doi:10.1536/ihj.39.775 · Cited by 118 · cited 1× · see citing works
“Studies have demonstrated that the APG parameters are closely associated with aging and risk factors for arteriosclerotic vascular disease [13 – 15], but it is still unclear which one is clinically most informative [11].”
Photoplethysmography and nociception
Korhonen, I., & Yli‐Hankala, A. (2009) · Acta Anaesthesiologica Scandinavica · doi:10.1111/j.1399-6576.2009.02026.x · Cited by 105 · cited 2× · see citing works
“A correct identification of the dicrotic notch is therefore essential to determine the systolic time [27], but due to variations in HR, cardiac output and vascular tone, with drifting in time positioning of the dicrotic notch with distance from the aortic valve, and to interference with the reflected wave, its applica…”
Salvi, V., Karnad, D. R., Panicker, G. K., & Kothari, S. (2009) · British Journal of Pharmacology · doi:10.1111/j.1476-5381.2009.00427.x · Cited by 103 · cited 2× · see citing works
“The Bazett equation has been criticized for over-correcting at high HRs and under-correcting at low HRs [51].”
Otsuka, T., Kawada, T., Katsumata, M., & Ibuki, C. (2006) · Circulation Journal · doi:10.1253/circj.70.304 · Cited by 103 · cited 5× · see citing works
“The d / a ratio correlates negatively to the Framingham score [17].”
InfluentialDetection of a and b waves in the acceleration photoplethysmogram
Elgendi, M., Norton, I., Brearley, M. B., Abbott, D., & Schuurmans, D. (2014) · BioMedical Engineering OnLine · doi:10.1186/1475-925x-13-139 · Cited by 100 · see citing works
Patvardhan, E. A., Heffernan, K. S., Ruan, J., Hession, M. J., Warner, P. J., Karas, R. H., & Kuvin, J. T. (2011) · Cardiology Research and Practice · doi:10.4061/2011/253758 · Cited by 80 · cited 1× · see citing works
“AIX is influenced by both large artery stiffness and properties in the PW-reflecting peripheral arterial tree [5–7] and is associated with cardiovascular risk, although it is less established than the PWV as a risk factor for cardiovascular morbidity [8–10].”
Detection of c, d, and e waves in the acceleration photoplethysmogram
Elgendi, M. (2014) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2014.08.001 · Cited by 73 · see citing works
Second Derivative of Photoplethysmography for Estimating Vascular Aging
Baek, H. J., Kim, J. S., Kim, Y. S., Lee, H. B., & Park, K. S. (2007) · IEEE International Conference on Information Technology and Applications in Biomedicine · doi:10.1109/itab.2007.4407346 · Cited by 69 · see citing works
Janner, J. H., Godtfredsen, N. S., Ladelund, S., Vestbo, J., & Prescott, E. (2011) · Journal of Human Hypertension · doi:10.1038/jhh.2011.59 · Cited by 62 · cited 1× · see citing works
“Although pressure PW analysis shows benefits in predicting cardiovascular morbidity [1,10], the impact in clinical practice is small because the tonometry method is cumbersome with a need for highly specialized operators.”
Takada, H., Washino, K., Harrell, J. S., & Iwata, H. (1996) · PubMed · Cited by 56 · see citing works
The finger volume pulse and assessment of arterial properties
Avolio, A. P. (2002) · Journal of Hypertension · doi:10.1097/00004872-200212000-00007 · Cited by 45 · see citing works
Standard Terminologies for Photoplethysmogram Signals
Elgendi, M. (2012) · Current Cardiology Reviews · doi:10.2174/157340312803217184 · Cited by 43 · see citing works
Trends in Citations to Books on Epidemiological and Statistical Methods in the Biomedical Literature
Porta, M. S., Vandenbroucke, J. P., Ioannidis, J. P. A., Sanz, S., Fernández, E., Bhopal, R. S., Morabia, A., Victora, C. G., & López‐Jiménez, T. (2013) · PLoS ONE · doi:10.1371/journal.pone.0061837 · Cited by 38 · see citing works
Measurement of the left ventricular ejection time by digital plethysmography
Chirife, R., Pigott, V. M., & Spodick, D. H. (1971) · American Heart Journal · doi:10.1016/0002-8703(71)90269-9 · Cited by 26 · cited 1× · see citing works
“[49] Digital Photoplethysmography for Assessment of Arterial Stiffness”
Jang, D.-G., Park, S.-H., & Hahn, M. (2014) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2014.2306679 · Cited by 23 · cited 1× · see citing works
“On the other hand, differences in age and gender have impacts on the accuracy of the pulse contour analyses [40], indicating that in a heterogeneous population like ours the repeatability of measurements differs from a homogenous population [34,41].”
BackgroundApplication and Interpretation
Stuart D. Summerhayes BSc, M. (2008) · doi:10.1002/9781444302554.ch2 · Cited by 20 · see citing works
Dicrotic notch detection using wavelet transform analysis
Antonelli, L. T., Ohley, W. J., & Khamlach, R. (2002) · Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society · doi:10.1109/iembs.1994.415400 · Cited by 20 · see citing works
A morphological approach to calculation of the second derivative of photoplethysmography
Jang, D.-G., Park, J.-H., Park, S.-H., & Hahn, M. (2010) · International Conference on Signal Processing · doi:10.1109/icosp.2010.5656472 · Cited by 8 · cited 1× · see citing works
“[44].”
Ishikawa, H., Honjo, A., Kagoshima, T., Doi, M., Nonaka, H., & Saishin, M. (1975) · Japanese Circulation Journal-english Edition · doi:10.1253/jcj.39.133 · Cited by 4 · cited 1× · see citing works
“[50] found, in contrast to Jang et al.”
ResultFeature Extraction from Finger Pulse Profile for High Pitta Detection
Sharma, T., & Singh, M. (2012) · Cited by 2 · see citing works
A comparison of correction algorithms to pulse parameters for estimation of arterial stiffness
Jang, D.-G., Park, S.-H., & Hahn, M. (2010) · International Conference on Signal Processing · doi:10.1109/icosp.2010.5656481 · Cited by 1 · cited 1× · see citing works
“[39], linear regression equations can be used for adjustments of timerelated PPG parameters.”
Method
Flagged first, then by citations
2 of the 53 references couldn’t be matched to a known paper.
Research works printed but not linked: 3
- [19]Gonzales R, Manzo A, Delgado J, Padilla JM, Trenor B, Saiz J. A computer base photoplethysmographic vascular analyser through derivatives. Comp Cardiol 2008; 35: 177– 80
- [26]Ozawa T. Pattern of second derivative of volume pulse wave, the relation between non-invasive index of ventricular function and peak acceleration and effect of preloading to peak velocity. Myakuha (Pulse Wave) 1978; 8: 22– 31 (In Japanese).
- [32]Bazett HC. An analysis of the time-relations of electrocardiograms. Heart 1920; 7: 35– 70.
Cited by
Sorted by citations
Self‐Powered Pulse Sensor for Antidiastole of Cardiovascular Disease
Ouyang, H., Tian, J., Sun, G., Zou, Y., Liu, Z., Li, H., Zhao, L., Shi, B., Fan, Y., Fan, Y., et al. (2017) · Advanced Materials · doi:10.1002/adma.201703456 · Cited by 468 · see citing works
Photoplethysmogram Analysis and Applications: An Integrative Review
Park, J., Seok, H. S., Kim, S.-S., & Shin, H. (2022) · Frontiers in Physiology · doi:10.3389/fphys.2021.808451 · Cited by 450 · 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
Wearable Photoplethysmography for Cardiovascular Monitoring
Charlton, P. H., Kyriacou, P. A., Mant, J., Marozas, V., Chowienczyk, P., & Alastruey, J. (2022) · Proceedings of the IEEE · doi:10.1109/jproc.2022.3149785 · Cited by 250 · see citing works
An optimal filter for short photoplethysmogram signals
Liang, Y., Elgendi, M., Chen, Z., & Ward, R. (2018) · Scientific Data · doi:10.1038/sdata.2018.76 · Cited by 242 · see citing works
A new, short-recorded photoplethysmogram dataset for blood pressure monitoring in China
Liang, Y., Chen, Z., Liu, G., & Elgendi, M. (2018) · Scientific Data · doi:10.1038/sdata.2018.20 · Cited by 215 · see citing works
Diagnostic Features and Potential Applications of PPG Signal in Healthcare: A Systematic Review
Almarshad, M. A., Islam, M. S., Al-Ahmadi, S. A., & BaHammam, A. S. (2022) · Healthcare · doi:10.3390/healthcare10030547 · Cited by 200 · see citing works
Charlton, P. H., Paliakaitė, B., Pilt, K., Bachler, M., Zanelli, S., Kulin, D., Allen, J., Hallab, M., Bianchini, E., Mayer, C. C., et al. (2021) · American Journal of Physiology-Heart and Circulatory Physiology · doi:10.1152/ajpheart.00392.2021 · Cited by 152 · see citing works
“For instance, coef fi cients with absolute values from 0.64 to 0.72 have been found between reference PWVs and PPG-derived parameters ( fi nger-toe PWV and pulse wave parameters) (73, 86, 94, 127, 139).”
InfluentialPhotoplethysmography signal processing and synthesis
Mejía-Mejía, E., Allen, J., Budidha, K., El-Hajj, C., Kyriacou, P. A., & Charlton, P. H. (2022) · Photoplethysmography · doi:10.1016/b978-0-12-823374-0.00015-3 · Cited by 138 · see citing works
“Studies have found limits of agreement for between PPG-derived and reference LVETs of -24 to 17 ms [263], -41 to 13 ms [259], and (HR corrected LVET) -70 to 67 ms [262].”
BackgroundMethodWearable Photoplethysmography for Cardiovascular Monitoring.
Charlton, P. H., Kyriacou, P. A., Mant, J., Marozas, V., Chowienczyk, P., & Alastruey, J. (2022) · KTUePubl (Repository of Kaunas University of Technology) · doi:10.17863/cam.81148 · Cited by 113 · see citing works
Toward Generating More Diagnostic Features from Photoplethysmogram Waveforms
Elgendi, M., Liang, Y., & Ward, R. K. (2018) · Diseases · doi:10.3390/diseases6010020 · Cited by 107 · see citing works
Song, Z., Li, W., Bao, Y., Wang, W., Liu, Z., Han, F., Han, D., & Niu, L. (2018) · Advanced Electronic Materials · doi:10.1002/aelm.201800252 · Cited by 90 · see citing works
Barvik, D., Černý, M., Penhaker, M., & Noury, N. (2021) · IEEE Reviews in Biomedical Engineering · doi:10.1109/rbme.2021.3109643 · Cited by 85 · see citing works
Finnegan, E., Davidson, S. M., Harford, M., Watkinson, P., Tarassenko, L., & Villarroel, M. (2023) · Scientific Reports · doi:10.1038/s41598-022-27170-2 · Cited by 83 · see citing works
Arterial pulse wave modeling and analysis for vascular-age studies: a review from VascAgeNet
Alastruey, J., Charlton, P. H., Bikia, V., Paliakaitė, B., Hametner, B., Bruno, R. M., Mulder, M. P., Vennin, S., Pişkin, Ş., Khir, A. W., et al. (2023) · American Journal of Physiology-Heart and Circulatory Physiology · doi:10.1152/ajpheart.00705.2022 · Cited by 75 · see citing works
XGBoost Regression of the Most Significant Photoplethysmogram Features for Assessing Vascular Aging
Shin, H. (2022) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2022.3151091 · Cited by 78 · see citing works
Djeldjli, D., Bousefsaf, F., Maaoui, C., Bereksi-Reguig, F., & Pruski, A. (2020) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2020.102242 · Cited by 74 · see citing works
A water-resistant, ultrathin, conformable organic photodetector for vital sign monitoring
Du, B., Xiong, S., Sun, L., Tagawa, Y., Inoue, D., Hashizume, D., Wang, W., Guo, R., Yokota, T., Wang, S., et al. (2024) · Science Advances · doi:10.1126/sciadv.adp2679 · Cited by 74 · see citing works
Mazumder, O., Roy, D., Bhattacharya, S., Sinha, A., & Pal, A. (2019) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2019.8856691 · Cited by 66 · see citing works
Photoplethysmography for the Assessment of Arterial Stiffness
Karimpour, P., May, J. M., & Kyriacou, P. A. (2023) · Sensors · doi:10.3390/s23249882 · Cited by 52 · see citing works
“Wowern et al. [55] conducted an in vivo trial on people of various ages and genders, including pregnant women, using the SphygmoCor-Px System and Meridian digital pulse wave analysis (DPA) (Salcor AB, Uppsala, Sweden).”
MethodpyPPG: a Python toolbox for comprehensive photoplethysmography signal analysis
Goda, M. Á., Charlton, P. H., & Behar, J. A. (2024) · Physiological Measurement · doi:10.1088/1361-6579/ad33a2 · Cited by 52 · see citing works
“The u-point has been used to assess arterial stiffness [78].”
MethodPeltokangas, M., Telembeci, A. A., Verho, J., Mattila, V. M., Romsi, P., Vehkaoja, A., Lekkala, J., & Oksala, N. (2018) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2017.2679904 · Cited by 32 · see citing works
“84 reported in [27].”
Estimation of phase distortions of the photoplethysmographic signal in digital IIR filtering
Lapitan, D. G., Рогаткин, Д. А., Molchanova, E. A., & Tarasov, A. P. (2024) · Scientific Reports · doi:10.1038/s41598-024-57297-3 · Cited by 34 · see citing works
“However, morphological analysis of the pulse waveform extracted from the AC component of a PPG signal provides other important information about the state of blood vessels, for example, their stiffness, tone, compliance, etc. 8,9 .”
Wang, H., Wang, L., Sun, N., Yao, Y., Hao, L., Xu, L., & Greenwald, S. E. (2020) · Frontiers in Physiology · doi:10.3389/fphys.2019.01563 · Cited by 36 · see citing works
“The optical sensor contains an infrared-emitting diode and a phototransistor to detect the light and acts as a photoplethysmograph (Jingfan Technology, Tianjin, China) (von Wowern et al., 2015).”
MethodReddy, G. N. K., Manikandan, M. S., & Murty, N. V. L. N. (2022) · IEEE Access · doi:10.1109/access.2022.3148256 · Cited by 34 · see citing works
Rabow, S., Hjorth, U., Schönbeck, S., & Olofsson, P. (2018) · BMC Pregnancy and Childbirth · doi:10.1186/s12884-018-2029-1 · Cited by 29 · see citing works
“Lewis et al. pointed out already in 1977 that LV muscle failure and diminished preload is associated with a shortened LVET, and that a marked increase in SV would lengthen the LVET [19].”
InfluentialSelf-citationBousefsaf, F., Djeldjli, D., Ouzar, Y., Maaoui, C., & Pruski, A. (2021) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2021.104860 · Cited by 26 · see citing works
Bousefsaf, F., Desquins, T., Djeldjli, D., Ouzar, Y., Maaoui, C., & Pruski, A. (2022) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2022.103895 · Cited by 27 · see citing works
Inverse Relationship between Sleep Duration and Cardio-Ankle Vascular Index in Children
Morita, N., Kambayashi, I., Okuda, T., Oda, S., Takada, S., Nakajima, T., Shide, N., Shinkaiya, H., & Okita, K. (2016) · Journal of Atherosclerosis and Thrombosis · doi:10.5551/jat.36517 · Cited by 20 · see citing works
Mahri, N., Gan, K. B., Meswari, R., Jaáfar, M. H., & Ali, M. A. M. (2017) · Journal of Medical Engineering & Technology · doi:10.1080/03091902.2017.1299229 · Cited by 20 · see citing works
““d” waves correspond to the late systolic phase [25].”
BackgroundSharkey, E., Maria, C. D., Klinge, A., Murray, A., Zheng, D., O’Sullivan, J. J., & Allen, J. (2018) · Physiological Measurement · doi:10.1088/1361-6579/aac76a · Cited by 20 · see citing works
Hellqvist, H., Karlsson, M. K., Hoffman, J., Kahan, T., & Spaak, J. (2024) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2024.1350726 · Cited by 19 · see citing works
“…r = − 0.75, respectively), which are stronger than what has been reported before; for the “ spring constant ” with cfPWV ( r = − 0.72) (44), the ageing index “ (b − c − d − e)/a ” with cfPWV ( r = 0.65) (31), and for the stiffness index with central PWV ( r = 0.65, r = 0.58 and r = 0.66) (45 – 47).”
MethodInfluentialSondej, T., Jannasz, I., Sieczkowski, K., Dobrowolski, A. P., Obiała, K., Targowski, T., & Olszewski, R. (2021) · Journal of Applied Biomedicine · doi:10.1016/j.bbe.2021.11.001 · Cited by 19 · see citing works
Weismann, C. G., Maretic, A., Grell, B. S., Åkesson, A., Hlebowicz, J., & Liuba, P. (2020) · International Journal of Cardiology · doi:10.1016/j.ijcard.2020.08.095 · Cited by 17 · see citing works
Zhang, T. H., Tang, X. C., Xu, L., Yan, W., Hu, Y. G., Cui, H. R., Tang, Y. Y., Chen, T., Li, C. B., Zhou, L., et al. (2021) · Schizophrenia Bulletin · doi:10.1093/schbul/sbab080 · Cited by 16 · see citing works
Wearable Blood Pressure Monitoring Devices: Understanding Heterogeneity in Design and Evaluation
Cheung, M. Y., Sabharwal, A., Coté, G. L., & Veeraraghavan, A. (2024) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2024.3434344 · Cited by 16 · see citing works
“Somefeaturesare morerepeatable(multiplemeasurementsinidenticalconditions forthesamesubject),reproducible(multiplemeasurementsin different conditions for the same subject), and reliable (multiple measurements in different conditions for different subjects) [115], [137].”
Kaewboonchoo, O., Sembajwe, G. N., & Li, J. (2018) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph15040659 · Cited by 15 · see citing works
“Therefore, a new method of digital finger photoplethysmography has been developed in recent years to measure pulse-wave velocity [76,77] and the aging index derived from this new method has been verified to have a high repeatability and best correlations with other standard measures of pulse-wave velocity in clinical…”
MethodRabow, S., & Olofsson, P. (2016) · The Journal of Maternal-Fetal & Neonatal Medicine · doi:10.1080/14767058.2016.1186162 · Cited by 15 · see citing works
“The DPA has been validated against invasive aortic measurement and correlates well with radial pulse applanation tonometry [10,11].”
BackgroundMethodInfluentialSelf-citationA comparative study of photoplethysmogram and piezoelectric plethysmogram signals
Qananwah, Q. M., Dagamseh, A., Alquran, H., Ibrahim, K. S., Alodat, M. T., & Hayden, O. (2020) · Physical and Engineering Sciences in Medicine · doi:10.1007/s13246-020-00923-x · Cited by 14 · see citing works
Nowak, J. K., Wykrętowicz, A., Mądry, E., Krauze, T., Drzymała-Czyż, S., Krzyżanowska-Jankowska, P., Sobkowiak, P., Schneider, A., Goździk-Spychalska, J., Kurek, S., et al. (2021) · Journal of Cystic Fibrosis · doi:10.1016/j.jcf.2021.06.010 · Cited by 14 · see citing works
Cunningham, J. W., Achille, P. D., Morrill, V. N., Weng, L.-C. C., Choi, S. H., Khurshid, S. S., Nauffal, V. D., Pirruccello, J. P., Solomon, S. D., Batra, P., et al. (2022) · Circulation Genomic and Precision Medicine · doi:10.1161/circgen.121.003676 · Cited by 13 · see citing works
Rabow, S., Jonsson, H., Bro, E., & Olofsson, P. (2023) · The Journal of Maternal-Fetal & Neonatal Medicine · doi:10.1080/14767058.2023.2208252 · Cited by 14 · see citing works
Self-citationPulse Wave Variation during the Menstrual Cycle in Women with Menstrual Pain
Jeon, S. H., Kim, K. K., Lee, I. S., Lee, Y. T., Kim, G. C., Chi, G. Y., Cho, H. S., Kang, H. J., & Kim, J. W. (2016) · BioMed Research International · doi:10.1155/2016/1083208 · Cited by 13 · see citing works
Bays, H. E., Khera, A., Blaha, M. J., Budoff, M. J., & Toth, P. P. (2021) · American Journal of Preventive Cardiology · doi:10.1016/j.ajpc.2021.100176 · Cited by 13 · see citing works
von Wowern, E., Källén, K., & Olofsson, P. (2018) · Pregnancy Hypertension · doi:10.1016/j.preghy.2018.11.002 · Cited by 13 · see citing works
Self-citationAn, D., Muhammad, I. F., Li, M., Borné, Y., Sheng, C., Persson, M., Cai, R., Guo, Q., Wang, J., Engström, G., et al. (2021) · Hypertension · doi:10.1161/hypertensionaha.121.17891 · Cited by 13 · see citing works
Self-citationKulin, D., Antali, F., Kulin, S., Wafa, D., Lucz, K. I., Veres, D. S., & Miklós, Z. (2020) · Applied Sciences · doi:10.3390/app10227977 · Cited by 11 · see citing works
Alian, A. A., & Shelley, K. H. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-823374-0.00006-2 · Cited by 12 · see citing works
Lee, J. J., Heo, J. H., Han, J. H., Kim, B. R., Gwon, H. Y., & Yoon, Y. R. (2020) · Journal of Medical and Biological Engineering · doi:10.1007/s40846-020-00507-w · Cited by 11 · see citing works
Lapitan, D. G., Tarasov, A. P., & Рогаткин, Д. А. (2022) · Journal of Biomedical Photonics & Engineering · doi:10.18287/jbpe22.08.030306 · Cited by 11 · see citing works
Cardiovascular variations in patients with major depressive disorder versus bipolar disorder
Xie, F., Zhou, L., Hu, Q., Zeng, L., Wei, Y., Tang, X., Gao, Y., Hu, Y., Xu, L., Chen, T., et al. (2023) · Journal of Affective Disorders · doi:10.1016/j.jad.2023.08.128 · Cited by 11 · see citing works
Chen, Y., Yang, X., Song, R., Liu, X., & Zhang, J. (2024) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2024.3383234 · Cited by 11 · see citing works
“(cid:2) AGI: The aging index, which is defined as: AGI = ( Hb − Hc − Hd − He ) / Ha , (10) revealed a better correlation of PWV and a high reproducibility [35].”
BackgroundAminuddin, A. (2016) · Medicine & health · doi:10.17576/mh.2016.1102.11 · Cited by 9 · see citing works
“A study by von Wowern et al. (2015) found that b/a ratio was correlated significantly with PWV (r=0.56).”
BackgroundInfluentialWeismann, C. G., Ljungberg, S., Åkesson, A., & Hlebowicz, J. (2021) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2021.643900 · Cited by 10 · see citing works
“decelerations of the blood flow (Acceleration Plethysmography) (13).”
BackgroundMethodInfluentialWearable photoplethysmography devices
Charlton, P. H., & Marozas, V. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-823374-0.00011-6 · Cited by 10 · see citing works
“Several pulse wave features have been identified as potentially indicative of arterial stiffness [102], [130], based on similar physiological mechanisms to those exploited when assessing BP from a single pulse wave.”
BackgroundNoninvasive hemodynamic indices of vascular aging: an in silico assessment
Hong, J., Nandi, M., Charlton, P. H., & Alastruey, J. (2023) · American Journal of Physiology-Heart and Circulatory Physiology · doi:10.1152/ajpheart.00454.2023 · Cited by 10 · see citing works
Bae, J.-H., Ku, B. U., Jeon, Y. J., Kim, H., Kim, J., Lee, H., Kim, J. U., & Kim, J. U. (2017) · Chinese Journal of Integrative Medicine · doi:10.1007/s11655-017-2972-0 · Cited by 10 · see citing works
“variables for investigating the characteristics of the pulse in TEAM practice.((34)) The AIr was calculated to estimate the changes in the left ventricular load and the peripheral resistance.”
MethodPhotoplethysmography signal analysis to assess obesity, age group and hypertension
Ferdinando, H., Huotari, M., & Myllyla, T. (2019) · 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2019.8857570 · Cited by 9 · see citing works
“Several attempts have been made to use PPG signals to estimate blood pressure using the PPG signals [1]–[5] and arterial stiffness [6]–[8].”
Casacanditella, L., Cosoli, G., Casaccia, S., Tomasini, E. P., & Scalise, L. (2016) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2016.7591499 · Cited by 9 · see citing works
“Recent studies have demonstrated a strong relationship between photoplethysmographic signal (PPG) and arterial tonometry measured at radial level [10].”
Backgroundvon Wowern, E., Saldeen, P., & Olofsson, P. (2018) · Hypertension in Pregnancy · doi:10.1080/10641955.2018.1516225 · Cited by 8 · see citing works
Self-citationPhotoplethysmography Detection of Overreaching
Bourdillon, N., Nilchian, M., & Millet, G. P. (2018) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0000000000001836 · Cited by 9 · see citing works
A novel method for vascular age estimation via pressure pulse wave of radial artery
Tang, Q., Tao, C., Pan, Z., Wang, G., Liu, K., Pan, Z., Liu, G., Su, B., & Liu, N. (2022) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2022.103904 · Cited by 7 · see citing works
Non-Invasive Diagnostic Approach for Diabetes Using Pulse Wave Analysis and Deep Learning
Gunathilaka, H., Rajapaksha, R., Kumarika, T., Perera, D. P., Herath, U., Jayathilaka, K. M. D. C., Liyanage, J. A., & Kalingamudali, S. R. D. (2024) · Informatics · doi:10.3390/informatics11030051 · Cited by 9 · see citing works
Pernice, R., Parisi, A., Guarino, S., Fallica, G., Vinciguerra, V., Ferla, G., Faes, L., & Busacca, A. (2020) · IEEE Mediterranean Electrotechnical Conference (MELECON) · doi:10.1109/melecon48756.2020.9140716 · Cited by 7 · see citing works
“In particular, in [6] we showed the capability of extracting heart and breath rate, pulse arrival time, pulse transit time and pulse wave velocity (we refer to [24], [27] for further details) and also of estimating blood pressure, while in [25] we described a more advanced version of the combo system supporting a high…”
BackgroundTAMURA, T., & Maeda, Y. (2017) · Springer eBooks · doi:10.1007/978-3-319-69362-0_6 · Cited by 7 · see citing works
Analysis of myocardial infarction signals using optical technique
Mahri, N., Gan, K. B., Ali, M. A. M., Jaáfar, M. H., & Meswari, R. (2016) · Journal of Medical Engineering & Technology · doi:10.3109/03091902.2016.1153740 · Cited by 7 · see citing works
“[12] stated that the ‘‘d’’ wave mainly reflects the intensity of the reflected pulse wave from small peripheral arteries and the time for the reflected tidal wave to travel is proportional to the height of the individual and a prolonged a–d time might indicate vasodilation or low vascular tone.[12] Zahedi et al.”
BackgroundJanjua, G. M. W., Finlay, D., Guldenring, D., Haq, A. U., & McLaughlin, J. A. (2019) · IEEE Access · doi:10.1109/access.2019.2944212 · Cited by 6 · see citing works
Analysis of Cardiovascular Changes Caused by Epileptic Seizures in Human Photoplethysmogram SignalPreprint
Safavi, S. M., Valisharifabad, N., Sabino, R. C., Chen, H., HeydariGorji, A., Tran, D., Lin, J. J., Lopour, B. A., & Chou, P. H. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1912.05083 · Cited by 6 · see citing works
von Wowern, E., Andersson, J., Skarping, I. D., Howie, M. T., & Olofsson, P. (2016) · The Journal of Maternal-Fetal & Neonatal Medicine · doi:10.1080/14767058.2016.1247264 · Cited by 5 · see citing works
“For further description of the DPA parameters, see [20] and Table 1.”
BackgroundMethodInfluentialSelf-citationAreas under peripheral pulse waves: a potential marker of atherosclerotic changes
Peltokangas, M., Verho, J. A., Mattila, V. M., Romsi, P., Vehkaoja, A. T., Lekkala, J. O., & Oksala, N. (2017) · Physiological Measurement · doi:10.1088/1361-6579/aaa46b · Cited by 5 · see citing works
“These include aging index (AGI) based on the second derivative of the index finger photoplethysmographic (PPG) blood volume PW (Bortolotto et al 2000), index finger PPG-derived reflection index as a ratio of diastolic and systolic peak amplitudes (Millasseau et al 2002), stiffness index inversely proportional to the t…”
MethodInfluentialPhotoplethysmographic assessment of arterial stiffness and endothelial function
Zheng, D., Yao, Y., Morrison, I., & Greenwald, S. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-823374-0.00007-4 · Cited by 6 · see citing works
Kock, K. D. S., da Silva, J. B. F., & Marques, J. L. B. (2019) · Jornal Vascular Brasileiro · doi:10.1590/1677-5449.180084 · Cited by 7 · see citing works
Shin, H. (2024) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2024.108952 · Cited by 4 · see citing works
Pilt, K., & Reiu, A. (2023) · Medical & Biological Engineering & Computing · doi:10.1007/s11517-023-02992-y · Cited by 4 · see citing works
“6, it can be debated that the transmural pressure might affect as well the other waveform parameters used for the estimation of the arterial stiffness [33] or blood pressure [11].”
Parameter Estimation of Hemodynamic Cardiovascular Model for Synthesis of Photoplethysmogram Signal
Roy, D., Mazumder, O., Chakravarty, K., Sinha, A., Ghose, A., & Pal, A. (2020) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc44109.2020.9175352 · Cited by 4 · see citing works
“There have been few prototypes which are deriving PPG signals from the estimation of PPG features [8], [11] to study the impact of the Atrial Fibrillation using a hemodynamic model.”
BackgroundMethodInfluentialMuhajir, M., Aminuddin, A., Ugusman, A., Salamt, N., Asmawi, Z., Zulkefli, A. F., Azmi, M. F., Chellappan, K., & Nordin, N. A. M. M. (2018) · Sains Malaysiana · doi:10.17576/jsm-2018-4710-25 · Cited by 4 · see citing works
The Effect of Short-Term Breath Holding on Pulse Wave Velocity and Vascular Stiffness
Sobol, K. V., Бурдыгин, А. И., & Нестеров, В. П. (2019) · BIOPHYSICS · doi:10.1134/s0006350919060204 · Cited by 3 · see citing works
Zhang, M., Zhang, T., & Cheng, Y. (2021) · International Conference on Applied Machine Learning (ICAML) · doi:10.1109/icaml54311.2021.00094 · Cited by 3 · see citing works
Using Smart Wearables to Monitor Cardiac Ejection
Mathieu, A. J. W., Charlton, P. H., & Alastruey, J. (2018) · International Electronic Conference on Sensors and Applications (ECSA) · doi:10.3390/ecsa-5-05744 · Cited by 3 · see citing works
“Techniques have been previously proposed for estimating LVET from BP [6-8] and PPG [9-11] PWs.”
MethodAcute Cardiovascular Effects of Hydrotreated Vegetable Oil Exhaust
Marc-Derrien, Y., Gren, L., Dierschke, K., Albin, M. C., Gudmundsson, A., Wierzbicka, A., & Sandberg, F. (2022) · Frontiers in Physiology · doi:10.3389/fphys.2022.828311 · Cited by 2 · see citing works
Diabetes‐Associated Changes in the Toe Photoplethysmogram During Local Heating Test
Lapitan, D. G., Xing, X., Glazkov, A. A., Krasulina, K. A., Kovaleva, Y. A., Glazkova, P. A., Альбертович, Б. Т., Загаров, С. С., Николаевич, Л. Р., & Рогаткин, Д. А. (2025) · Journal of Biophotonics · doi:10.1002/jbio.202500190 · Cited by 2 · see citing works
Wang, L., Wang, L., LI, Q., Zhang, W., & Wang, Y. (2019) · Journal of Mechanics in Medicine and Biology · doi:10.1142/s0219519419400578 · Cited by 2 · see citing works
von Wowern, E., & Olofsson, P. (2017) · The Journal of Maternal-Fetal & Neonatal Medicine · doi:10.1080/14767058.2017.1341483 · Cited by 2 · see citing works
“described the physiologic background of photoplethysmographic pulse wave contour analysis and we have described and validated the different indexes [41].”
MethodSelf-citationReal-Time Pulse Waveform Profiling Algorithm for Wearable Applications
Liu, H., Fujita, D., Zhang, L., & Suzuki, A. (2018) · IEEE Access · doi:10.1109/access.2018.2875548 · Cited by 2 · see citing works
“However, because these parameters are not straightforward compared to the original PPG signal, the physiological characteristics behind these derived parameters are not clearly understood, and some parameters do not have acceptable repeatability [32], [33].”
BackgroundReal-time classification of blood pressure changes using photoplethysmography and deep learning
Hong, J., Jin, W., Nandi, M., & Alastruey, J. (2025) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2025.108380 · Cited by 1 · see citing works
Contactless Hemodynamic Monitoring Based on Multi-Scale Gaussian Filtering via Imaging PPG
Tong, Y., Huang, Z., Qiu, F., Wu, C., Tao, X., Huang, W. F., & Qin, F. (2025) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2025.3605591 · Cited by 1 · see citing works
“The relative amplitude ratios of these points have been shown to correlate with vascular aging and arterial stiffness [34].”
Zhao, A., Chong, Y., Zhong, H., Ma, J., Zhang, H., Luo, Z., Li, G., & Luo, X. (2017) · IEEE International Conference on Bioinformatics and Bioengineering (BIBE) · doi:10.1109/bibe.2017.00008 · Cited by 1 · see citing works
“Although carotid-femoral PWV (cfPWV) obtained through applanation tonometry is considered as the gold standard measure of arterial stiffness, brachial-ankle PWV (baPWV) is performed more easily than cfPWV , and has been used as an effective tool for screening vascular damage and cardiovascular risk in various populati…”
MethodWang, J.-J., Liu, S.-H., Tseng, W., & Chen, W. (2020) · Sensors · doi:10.3390/s20226463 · Cited by 1 · see citing works
“Photoplethysmography can continuously detect change in blood volume because red blood cells have a similar light absorption coefficient [19].”
BackgroundSystem of Comfortable Live Level Improvement
Zheliazkov, Y., Globa, L. S., & Yamnenko, I. (2023) · International Conference on Information and Digital Technologies (IDT) · doi:10.1109/idt59031.2023.10194427 · Cited by 1 · see citing works
Sobol, C. V., Korotkov, S. M., & Нестеров, В. П. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-819265-8.00108-x · Cited by 1 · see citing works
Manoj, R., Kiran, V. R., Nabeel, P. M., Sivaprakasam, M., & Joseph, J. (2022) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc48229.2022.9871405 · Cited by 1 · see citing works
“Most of the conventions in defining these markers are referred to elsewhere [5].”
BackgroundSleep Arousal and Cardiovascular Dynamics
Shahrbabaki, S. S. (2020) · Adelaide Research & Scholarship (AR&S) (University of Adelaide) · Cited by 1 · see citing works
Short-term stability of combined finger and toe photoplethysmogram analysis
Peltokangas, M., Huotari, M. J., Verho, J. A., Mattila, V. M., Röning, J., Romsi, P., Lekkala, J. O., Vehkaoja, A. T., & Oksala, N. (2017) · World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany · doi:10.1007/978-981-10-5122-7_86
Screening Test on Metabolic Syndrome Using Electro Interstitial Scan Instrument
Norchai, P., Tharavanij, T., Suwannahitatorn, P., & Charernboon, T. (2020) · Medical Devices Evidence and Research · doi:10.2147/mder.s268948
A PPG-ECG Combo System for the Monitoring of the Aging State of Arteries
Andò, B., Baglio, S., Fallica, P. G., Marletta, V., Ambra, E., Pace, M., Garozzo, F. S., & Vinciguerra, V. (2020) · IEEE Sensors Applications Symposium (SAS) · doi:10.1109/sas48726.2020.9220015
“From the amplitude of the five peaks, it is possible to evaluate the following ratios b/a, c/a, d/a and e/a, that has been demonstrated to be correlated with aging and arterial stiffness [20].”
BackgroundPliego‐Carrillo, A. C., Vega, R., García, D. E. F., Ramírez, C. I. L., & Soto, E. (2022) · doi:10.22533/at.ed.4142221048
SISTEMA SUPERVISÓRIO E CONTROLE MIMO ATRAVÉS DE LÓGICA
Mendonça, M., Trancolin, G. M. S., dos Santos, M. R. P., Paschoalino, C. A., Finocchio, M. A. F., Scannavino, F. D. A., Fabri, J. A., Koroishi, E. H., Shiguemoto, A. L., Corrêa, C. A., et al. (2022) · doi:10.22533/at.ed.4142221044
de Oliveira, E. E. C., Júnior, P. C. D. A., de Queiroz, V. N., & Rodrigues, M. L. (2022) · doi:10.22533/at.ed.4142221041
- Authors
- von Wowern, E., Östling, G., Nilsson, P. M., & Olofsson, P.
- Affiliations
- Lund University (SE)
- Venue
- PLOS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2015-08-20
- Volume
- 10
- Issue
- 8
- Pages
- e0135659
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC4546304
- OpenAlex
- W1784071036
- Cited by
- 134
- References
- 53
- Citations by year
- 2026: 3 · 2025: 8 · 2024: 9 · 2023: 8 · 2022: 39 · 2021: 19 · 2020: 12 · 2019: 7 · 2018: 13 · 2017: 9 · 2016: 7
- FWCI
- 7.03
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- PLoS ONE (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Lund University Publications (Lund University) (submittedVersion, other-oa)
- Funders
- Lunds Universitet
- Region Skåne
- Topics
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiovascular Health and Disease Prevention
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Heart Rate Variability and Autonomic Control
- Keywords
- arterial stiffness, digital photoplethysmography, applanation tonometry, pulse wave analysis, pulse wave velocity, augmentation index, repeatability, aging index, left ventricular ejection time, pregnancy, cardiovascular risk
- MeSH terms
- Adult, Aged, Aged, 80 and over, Aorta, Arteries, Blood Pressure, Elasticity, Female, Heart Rate, Humans, Male, Manometry, Middle Aged, Pregnancy, Pulse, Risk Factors, Photoplethysmography, Young Adult, Vascular Stiffness, Pulse Wave Analysis
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
