Application of biomechanical modeling and simulation in the development of non-invasive technologies and devices for cardiovascular testing_Journal of Biomedical Engineering

Authors：

ZHANG Xujie , GOU Zhonglin , WANG Tianqi ,  LIANG Fuyou

School of Naval Architecture, Ocean & Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, P.R.China;

Corresponding author：

Keywords：

biomechanical modeling and simulation; non-invasive cardiovascular testing; blood pressure; arterial stiffness

DOI：

10.7507/1001-5515.202008076

Video：

Export PDF Favorites Scan Get Citation

Abstract Full text Figures/Tables Video References Cited by

The prevalence of cardiovascular disease in our country is increasing, and it has been a big problem affecting the social and economic development. It has been demonstrated that early intervention of cardiovascular risk factors can effectively reduce cardiovascular disease-caused mortality. Therefore, extensive implementation of cardiovascular testing and risk factor screening in the general population is the key to the prevention and treatment of cardiovascular disease. However, the categories of devices available for quick cardiovascular testing are limited, and in particular, many existing devices suffer from various technical problems, such as complex operation, unclear working principle, or large inter-individual variability in measurement accuracy, which lead to an overall low popularity and reliability of cardiovascular testing. In this study, we introduce the non-invasive measurement mechanisms and relevant technical progresses for several typical cardiovascular indices (e.g., peripheral/central arterial blood pressure, and arterial stiffness), with emphasis on describing the applications of biomechanical modeling and simulation in mechanism verification, analysis of influential factors, and technical improvement/innovation.

Citation： ZHANG Xujie, GOU Zhonglin, WANG Tianqi, LIANG Fuyou. Application of biomechanical modeling and simulation in the development of non-invasive technologies and devices for cardiovascular testing. Journal of Biomedical Engineering, 2020, 37(6): 990-999. doi: 10.7507/1001-5515.202008076 Copy

1.	胡盛寿, 高润霖, 刘力生, 等. 《中国心血管病报告2018》概要. 中国循环杂志, 2019, 34(3): 209-220.
2.	Arnett D K, Blumenthal R S, Albert M A, et al. 2019 ACC/AHA guideline on the primary prevention of cardiovascular disease: a report of the American college of cardiology/American heart association task force on clinical practice guidelines. J Am Coll Cardiol, 2019, 74(10): e177-e232.
3.	Xia S, Du X, Guo L, et al. Sex differences in primary and secondary prevention of cardiovascular disease in China. Circulation, 2020, 141(7): 530-539.
4.	Burnier M, Egan B M. Adherence in hypertension:a review of prevalence, risk factors, impact, and management. Circ Res, 2019, 124(7): 1124-1140.
5.	Alpert B S, Quinn D, Gallick D. Oscillometric blood pressure: a review for clinicians. J Am Soc Hypertens, 2014, 8(12): 930-938.
6.	Skirton H, Chamberlain W, Lawson C, et al. A systematic review of variability and reliability of manual and automated blood pressure readings. J Clin Nurs, 2011, 20(5/6): 602-614.
7.	Liang F Y, Liu H, Takagi S. The effects of brachial arterial stiffening on the accuracy of oscillometric blood pressure measurement: a computational model study. Journal of Biomechanical Science and Engineering, 2012, 7(1): 15-30.
8.	Deng Zhipeng, Liang Fuyou. Numerical analysis of stress distribution in the upper arm tissues under an inflatable cuff: Implications for noninvasive blood pressure measurement. Acta Mechanica Sinica, 2016, 32(5): 959-969.
9.	Ursino M, Cristalli C. A mathematical study of some biomechanical factors affecting the oscillometric blood pressure measurement. IEEE Trans Biomed Eng, 1996, 43(8): 761-778.
10.	Forster F K, Turney D. Oscillometric determination of diastolic, mean and systolic blood pressure--a numerical model. J Biomech Eng, 1986, 108(4): 359-364.
11.	Liu J, Cheng H M, Chen C H, et al. Patient-Specific oscillometric blood pressure measurement: validation for accuracy and repeatability. IEEE J Transl Eng Health Med, 2017, 5: 1900110.
12.	Babbs C F. Oscillometric measurement of systolic and diastolic blood pressures validated in a physiologic mathematical model. Biomed Eng Online, 2012, 11(1): 56.
13.	Liu J, Sodini C G, Ou Y, et al. Feasibility of fingertip oscillometric blood pressure measurement: model-based analysis and experimental validation. IEEE J Biomed Health Inform, 2020, 24(2): 533-542.
14.	泽野井幸哉, 佐野佳彦, 久保大, 等. 血压测定用袖带及血压计. CN109195513A, 2019-01-11.
15.	Kuwabara M, Harada K, Hishiki Y, et al. Validation of two watch-type wearable blood pressure monitors according to the ANSI/AAMI/ISO81060-2:2013 guidelines: Omron HEM-6410T-ZM and HEM-6410T-ZL. J Clin Hypertens (Greenwich), 2019, 21(6): 853-858.
16.	Kario K, Shimbo D, Tomitani N, et al. The first study comparing a wearable watch-type blood pressure monitor with a conventional ambulatory blood pressure monitor on in-office and out-of-office settings. J Clin Hypertens (Greenwich), 2020, 22(2): 135-141.
17.	Kollias A, Lagou S, Zeniodi M E, et al. Association of central versus brachial blood pressure with target-organ damage: systematic review and meta-analysis. Hypertension, 2016, 67(1): 183-190.
18.	Sun P, Yang Y, Cheng G, et al. Noninvasive central systolic blood pressure, not peripheral systolic blood pressure, independently predicts the progression of carotid intima-media thickness in a Chinese community-based population. Hypertens Res, 2019, 42(3): 392-399.
19.	Liang F Y, Takagi S, Himeno R, et al. Biomechanical characterization of ventricular-arterial coupling during aging: a multi-scale model study. J Biomech, 2009, 42(6): 692-704.
20.	McEniery C M, Mcdonnell B, Munnery M A, et al. Central pressure: variability and impact of cardiovascular risk factors-the Anglo-Cardiff collaborative trial Ⅱ. Hypertension, 2008, 51(6): 1476-1482.
21.	Liang F Y, Guan D B, Alastruey J. Determinant factors for arterial hemodynamics in hypertension: theoretical insights from a computational model-based study. J Biomech Eng, 2018, 140(3): 031006.
22.	Thomas F, Burke J P, Parker J, et al. The risk of infection related to radial vs femoral sites for arterial catheterization. Crit Care Med, 1983, 11(10): 807-812.
23.	Sharman J E, Avolio A P, Baulmann J, et al. Validation of non-invasive central blood pressure devices: ARTERY society task force consensus statement on protocol standardization. Eur Heart J, 2017, 38(37): 2805-2812.
24.	Weber T, Wassertheurer S, Rammer M, et al. Validation of a brachial cuff-based method for estimating central systolic blood pressure. Hypertension, 2011, 58(5): 825-832.
25.	Hope S A, Meredith I T, Tay D, et al. 'Generalizability' of a radial-aortic transfer function for the derivation of central aortic waveform parameters. J Hypertens, 2007, 25(9): 1812-1820.
26.	Schultz M G, Picone D S, Armstrong M K, et al. Validation study to determine the accuracy of central blood pressure measurement using the sphygmocor Xcel cuff device. Hypertension, 2020, 76(1): 244-250.
27.	Shih Y T, Cheng H M, Sung S H, et al. Application of the n-point moving average method for brachial pressure waveform-derived estimation of central aortic systolic pressure. Hypertension, 2014, 63(4): 865-870.
28.	Williams B, Lacy P S, Yan P, et al. Development and validation of a novel method to derive central aortic systolic pressure from the radial pressure waveform using an n-point moving average method. J Am Coll Cardiol, 2011, 57(8): 951-961.
29.	Xiao H, Butlin M, Qasem A, et al. N-Point moving average: a special generalized transfer function method for estimation of central aortic blood pressure. IEEE Trans Biomed Eng, 2018, 65(6): 1226-1234.
30.	Yao Y, Xu L, Sun Y, et al. Validation of an adaptive transfer function method to estimate the aortic pressure waveform. IEEE J Biomed Health Inform, 2017, 21(6): 1599-1606.
31.	Millasseau S C, Patel S J, Redwood S R, et al. Pressure wave reflection assessed from the peripheral pulse: is a transfer function necessary?. Hypertension, 2003, 41(5): 1016-1020.
32.	Hickson S S, Butlin M, Mir F A, et al. The accuracy of central SBP determined from the second systolic peak of the peripheral pressure waveform. J Hypertens, 2009, 27(9): 1784-1788.
33.	Yao Y, Wang L, Hao L, et al. The noninvasive measurement of central aortic blood pressure waveform. Blood pressure-from bench to bed. Intech Open, 2018.
34.	Papaioannou T G, Karageorgopoulou T D, Sergentanis T N, et al. Accuracy of commercial devices and methods for noninvasive estimation of aortic systolic blood pressure a systematic review and meta-analysis of invasive validation studies. J Hypertens, 2016, 34(7): 1237-1248.
35.	Guala A, Tosello F, Leone D, et al. Multiscale mathematical modeling vs. the generalized transfer function approach for aortic pressure estimation: a comparison with invasive data. Hypertens Res, 2019, 42(5): 690-698.
36.	Ghasemi Z, Lee J C, Kim C S, et al. Estimation of cardiovascular risk predictors from non-invasively measured diametric pulse volume waveforms via multiple measurement information fusion. Sci Rep, 2018, 8(1): 10433.
37.	梁夫友, 李逸, 李力军. 基于振荡式血压计信号的中心动脉压检测系统及方法. CN103479343A, 2014-01-01.
38.	Liang F. Numerical validation of a suprasystolic brachial cuff-based method for estimating aortic pressure. Biomed Mater Eng, 2014, 24(1): 1053-1062.
39.	Liang F, Yin Z, Fan Y, et al. In vivo validation of an oscillometric method for estimating central aortic pressure. Int J Cardiol, 2015, 199: 439-441.
40.	张絮洁, 章亚平, 殷兆芳, 等. 基于上臂袖带振荡波估测动脉僵硬度的理论方法及临床实验. 中国医疗设备, 2018, 33(4): 22-28.
41.	Mozos I, Malainer C, Horbańczuk J, et al. Inflammatory markers for arterial stiffness in cardiovascular diseases. Front Immunol, 2017, 8: 1058.
42.	Zanoli L, Lentini P, Briet M, et al. Arterial stiffness in the heart disease of CKD. J Am Soc Nephrol, 2019, 30(6): 918-928.
43.	Tomiyama H, Shiina K, Matsumoto-Nakano C, et al. The contribution of inflammation to the development of hypertension mediated by increased arterial stiffness. J Am Heart Assoc, 2017, 6(7): e005729.
44.	Laurent S, Cockcroft J, Van Bortel L, et al. Expert consensus document on arterial stiffness: methodological issues and clinical applications. Eur Heart J, 2006, 27(21): 2588-2605.
45.	Tang C J, Lee P Y, Chuang Y H, et al. Measurement of local pulse wave velocity for carotid artery by using an ultrasound-based method. Ultrasonics, 2020, 102: 106064.
46.	Liang F, Takagi S, Liu H. The influences of cardiovascular properties on suprasystolic brachial cuff wave studied by a simple arterial-tree model. J Mech Med Biol, 2012, 12(03): 1250040.
47.	Safar M E. Arterial stiffness as a risk factor for clinical hypertension. Nat Rev Cardiol, 2018, 15(2): 97-105.
48.	Milan A, Zocaro G, Leone D, et al. Current assessment of pulse wave velocity: comprehensive review of validation studies. J Hypertens, 2019, 37(8): 1547-1557.
49.	Vardoulis O, Papaioannou T G, Stergiopulos N. Validation of a novel and existing algorithms for the estimation of pulse Transit time: advancing the accuracy in pulse wave velocity measurement. Am J Physiol Heart Circ Physiol, 2013, 304(11): H1558-H1567.
50.	Huttunen J M J, Kärkkäinen L, Lindholm H. Pulse transit time estimation of aortic pulse wave velocity and blood pressure using machine learning and simulated training data. PLoS computational biology, 2019, 15(8): e1007259.
51.	Obeid H, Soulat G, Mousseaux E, et al. Numerical assessment and comparison of pulse wave velocity methods aiming at measuring aortic stiffness. Physiol Meas, 2017, 38(11): 1953-1967.
52.	Ma Y, Choi J, Hourlier-Fargette A, et al. Relation between blood pressure and pulse wave velocity for human arteries. Proc Natl Acad Sci U S A, 2018, 115(44): 11144-11149.
53.	Liberson A S, Lillie J S, Day S W, et al. A physics based approach to the pulse wave velocity prediction in compliant arterial segments. J Biomech, 2016, 49(14): 3460-3466.
54.	Zhang Y, Yin P, Xu Z, et al. Non-Invasive assessment of early atherosclerosis based on new arterial stiffness indices measured with an upper-arm oscillometric device. Tohoku J Exp Med, 2017, 241(4): 263-270.
55.	Tazawa Yasushi, Mori N, Ogawa Y, et al. Arterial stiffness measured with the cuff oscillometric method is predictive of exercise capacity in patients with cardiac diseases. Tohoku J Exp Med, 2016, 239(2): 127-134.
56.	Komine H, Asai Y, Yokoi T, et al. Non-invasive assessment of arterial stiffness using oscillometric blood pressure measurement. Biomed Eng Online, 2012, 11(1): 6.
57.	Hitsumoto T. Arterial velocity pulse index as a novel marker of atherosclerosis using pulse wave analysis on high sensitivity troponin T in hypertensive patients. Cardiol Res, 2017, 8(2): 36-43.
58.	Sasaki-Nakashima R, Kino T, Chen L, et al. Successful prediction of cardiovascular risk by new non-invasive vascular indexes using suprasystolic cuff oscillometric waveform analysis. J Cardiol, 2017, 69(1): 30-37.
59.	Wan J, Liu S, Yang Y, et al. Roles of arterial pressure volume index and arterial velocity pulse index trajectories in risk prediction in hypertensive patients with heart failure with preserved ejection fraction. Clin Exp Hypertens, 2020, 42(5): 469-478.
60.	Kobayashi R, Iwanuma S, Ohashi N, et al. New indices of arterial stiffness measured with an upper-arm oscillometric device in active versus inactive women. Physiol Rep, 2018, 6(5): e13574.
61.	Liang Fuyou, Takagi S, Himeno R, et al. A computational model of the cardiovascular system coupled with an upper-arm oscillometric cuff and its application to studying the suprasystolic cuff oscillation wave, concerning its value in assessing arterial stiffness. Comput Methods Biomech Biomed Engin, 2013, 16(2): 141-157.
62.	Komine H, Asai Y, Yokoi T, et al. Arterial-wall stiffness evaluation system: U.S. Patent 9, 730, 594. 2017-8-15.

1. 胡盛寿, 高润霖, 刘力生, 等. 《中国心血管病报告2018》概要. 中国循环杂志, 2019, 34(3): 209-220.
2. Arnett D K, Blumenthal R S, Albert M A, et al. 2019 ACC/AHA guideline on the primary prevention of cardiovascular disease: a report of the American college of cardiology/American heart association task force on clinical practice guidelines. J Am Coll Cardiol, 2019, 74(10): e177-e232.
3. Xia S, Du X, Guo L, et al. Sex differences in primary and secondary prevention of cardiovascular disease in China. Circulation, 2020, 141(7): 530-539.
4. Burnier M, Egan B M. Adherence in hypertension:a review of prevalence, risk factors, impact, and management. Circ Res, 2019, 124(7): 1124-1140.
5. Alpert B S, Quinn D, Gallick D. Oscillometric blood pressure: a review for clinicians. J Am Soc Hypertens, 2014, 8(12): 930-938.
6. Skirton H, Chamberlain W, Lawson C, et al. A systematic review of variability and reliability of manual and automated blood pressure readings. J Clin Nurs, 2011, 20(5/6): 602-614.
7. Liang F Y, Liu H, Takagi S. The effects of brachial arterial stiffening on the accuracy of oscillometric blood pressure measurement: a computational model study. Journal of Biomechanical Science and Engineering, 2012, 7(1): 15-30.
8. Deng Zhipeng, Liang Fuyou. Numerical analysis of stress distribution in the upper arm tissues under an inflatable cuff: Implications for noninvasive blood pressure measurement. Acta Mechanica Sinica, 2016, 32(5): 959-969.
9. Ursino M, Cristalli C. A mathematical study of some biomechanical factors affecting the oscillometric blood pressure measurement. IEEE Trans Biomed Eng, 1996, 43(8): 761-778.
10. Forster F K, Turney D. Oscillometric determination of diastolic, mean and systolic blood pressure--a numerical model. J Biomech Eng, 1986, 108(4): 359-364.
11. Liu J, Cheng H M, Chen C H, et al. Patient-Specific oscillometric blood pressure measurement: validation for accuracy and repeatability. IEEE J Transl Eng Health Med, 2017, 5: 1900110.
12. Babbs C F. Oscillometric measurement of systolic and diastolic blood pressures validated in a physiologic mathematical model. Biomed Eng Online, 2012, 11(1): 56.
13. Liu J, Sodini C G, Ou Y, et al. Feasibility of fingertip oscillometric blood pressure measurement: model-based analysis and experimental validation. IEEE J Biomed Health Inform, 2020, 24(2): 533-542.
14. 泽野井幸哉, 佐野佳彦, 久保大, 等. 血压测定用袖带及血压计. CN109195513A, 2019-01-11.
15. Kuwabara M, Harada K, Hishiki Y, et al. Validation of two watch-type wearable blood pressure monitors according to the ANSI/AAMI/ISO81060-2:2013 guidelines: Omron HEM-6410T-ZM and HEM-6410T-ZL. J Clin Hypertens (Greenwich), 2019, 21(6): 853-858.
16. Kario K, Shimbo D, Tomitani N, et al. The first study comparing a wearable watch-type blood pressure monitor with a conventional ambulatory blood pressure monitor on in-office and out-of-office settings. J Clin Hypertens (Greenwich), 2020, 22(2): 135-141.
17. Kollias A, Lagou S, Zeniodi M E, et al. Association of central versus brachial blood pressure with target-organ damage: systematic review and meta-analysis. Hypertension, 2016, 67(1): 183-190.
18. Sun P, Yang Y, Cheng G, et al. Noninvasive central systolic blood pressure, not peripheral systolic blood pressure, independently predicts the progression of carotid intima-media thickness in a Chinese community-based population. Hypertens Res, 2019, 42(3): 392-399.
19. Liang F Y, Takagi S, Himeno R, et al. Biomechanical characterization of ventricular-arterial coupling during aging: a multi-scale model study. J Biomech, 2009, 42(6): 692-704.
20. McEniery C M, Mcdonnell B, Munnery M A, et al. Central pressure: variability and impact of cardiovascular risk factors-the Anglo-Cardiff collaborative trial Ⅱ. Hypertension, 2008, 51(6): 1476-1482.
21. Liang F Y, Guan D B, Alastruey J. Determinant factors for arterial hemodynamics in hypertension: theoretical insights from a computational model-based study. J Biomech Eng, 2018, 140(3): 031006.
22. Thomas F, Burke J P, Parker J, et al. The risk of infection related to radial vs femoral sites for arterial catheterization. Crit Care Med, 1983, 11(10): 807-812.
23. Sharman J E, Avolio A P, Baulmann J, et al. Validation of non-invasive central blood pressure devices: ARTERY society task force consensus statement on protocol standardization. Eur Heart J, 2017, 38(37): 2805-2812.
24. Weber T, Wassertheurer S, Rammer M, et al. Validation of a brachial cuff-based method for estimating central systolic blood pressure. Hypertension, 2011, 58(5): 825-832.
25. Hope S A, Meredith I T, Tay D, et al. 'Generalizability' of a radial-aortic transfer function for the derivation of central aortic waveform parameters. J Hypertens, 2007, 25(9): 1812-1820.
26. Schultz M G, Picone D S, Armstrong M K, et al. Validation study to determine the accuracy of central blood pressure measurement using the sphygmocor Xcel cuff device. Hypertension, 2020, 76(1): 244-250.
27. Shih Y T, Cheng H M, Sung S H, et al. Application of the n-point moving average method for brachial pressure waveform-derived estimation of central aortic systolic pressure. Hypertension, 2014, 63(4): 865-870.
28. Williams B, Lacy P S, Yan P, et al. Development and validation of a novel method to derive central aortic systolic pressure from the radial pressure waveform using an n-point moving average method. J Am Coll Cardiol, 2011, 57(8): 951-961.
29. Xiao H, Butlin M, Qasem A, et al. N-Point moving average: a special generalized transfer function method for estimation of central aortic blood pressure. IEEE Trans Biomed Eng, 2018, 65(6): 1226-1234.
30. Yao Y, Xu L, Sun Y, et al. Validation of an adaptive transfer function method to estimate the aortic pressure waveform. IEEE J Biomed Health Inform, 2017, 21(6): 1599-1606.
31. Millasseau S C, Patel S J, Redwood S R, et al. Pressure wave reflection assessed from the peripheral pulse: is a transfer function necessary?. Hypertension, 2003, 41(5): 1016-1020.
32. Hickson S S, Butlin M, Mir F A, et al. The accuracy of central SBP determined from the second systolic peak of the peripheral pressure waveform. J Hypertens, 2009, 27(9): 1784-1788.
33. Yao Y, Wang L, Hao L, et al. The noninvasive measurement of central aortic blood pressure waveform. Blood pressure-from bench to bed. Intech Open, 2018.
34. Papaioannou T G, Karageorgopoulou T D, Sergentanis T N, et al. Accuracy of commercial devices and methods for noninvasive estimation of aortic systolic blood pressure a systematic review and meta-analysis of invasive validation studies. J Hypertens, 2016, 34(7): 1237-1248.
35. Guala A, Tosello F, Leone D, et al. Multiscale mathematical modeling vs. the generalized transfer function approach for aortic pressure estimation: a comparison with invasive data. Hypertens Res, 2019, 42(5): 690-698.
36. Ghasemi Z, Lee J C, Kim C S, et al. Estimation of cardiovascular risk predictors from non-invasively measured diametric pulse volume waveforms via multiple measurement information fusion. Sci Rep, 2018, 8(1): 10433.
37. 梁夫友, 李逸, 李力军. 基于振荡式血压计信号的中心动脉压检测系统及方法. CN103479343A, 2014-01-01.
38. Liang F. Numerical validation of a suprasystolic brachial cuff-based method for estimating aortic pressure. Biomed Mater Eng, 2014, 24(1): 1053-1062.
39. Liang F, Yin Z, Fan Y, et al. In vivo validation of an oscillometric method for estimating central aortic pressure. Int J Cardiol, 2015, 199: 439-441.
40. 张絮洁, 章亚平, 殷兆芳, 等. 基于上臂袖带振荡波估测动脉僵硬度的理论方法及临床实验. 中国医疗设备, 2018, 33(4): 22-28.
41. Mozos I, Malainer C, Horbańczuk J, et al. Inflammatory markers for arterial stiffness in cardiovascular diseases. Front Immunol, 2017, 8: 1058.
42. Zanoli L, Lentini P, Briet M, et al. Arterial stiffness in the heart disease of CKD. J Am Soc Nephrol, 2019, 30(6): 918-928.
43. Tomiyama H, Shiina K, Matsumoto-Nakano C, et al. The contribution of inflammation to the development of hypertension mediated by increased arterial stiffness. J Am Heart Assoc, 2017, 6(7): e005729.
44. Laurent S, Cockcroft J, Van Bortel L, et al. Expert consensus document on arterial stiffness: methodological issues and clinical applications. Eur Heart J, 2006, 27(21): 2588-2605.
45. Tang C J, Lee P Y, Chuang Y H, et al. Measurement of local pulse wave velocity for carotid artery by using an ultrasound-based method. Ultrasonics, 2020, 102: 106064.
46. Liang F, Takagi S, Liu H. The influences of cardiovascular properties on suprasystolic brachial cuff wave studied by a simple arterial-tree model. J Mech Med Biol, 2012, 12(03): 1250040.
47. Safar M E. Arterial stiffness as a risk factor for clinical hypertension. Nat Rev Cardiol, 2018, 15(2): 97-105.
48. Milan A, Zocaro G, Leone D, et al. Current assessment of pulse wave velocity: comprehensive review of validation studies. J Hypertens, 2019, 37(8): 1547-1557.
49. Vardoulis O, Papaioannou T G, Stergiopulos N. Validation of a novel and existing algorithms for the estimation of pulse Transit time: advancing the accuracy in pulse wave velocity measurement. Am J Physiol Heart Circ Physiol, 2013, 304(11): H1558-H1567.
50. Huttunen J M J, Kärkkäinen L, Lindholm H. Pulse transit time estimation of aortic pulse wave velocity and blood pressure using machine learning and simulated training data. PLoS computational biology, 2019, 15(8): e1007259.
51. Obeid H, Soulat G, Mousseaux E, et al. Numerical assessment and comparison of pulse wave velocity methods aiming at measuring aortic stiffness. Physiol Meas, 2017, 38(11): 1953-1967.
52. Ma Y, Choi J, Hourlier-Fargette A, et al. Relation between blood pressure and pulse wave velocity for human arteries. Proc Natl Acad Sci U S A, 2018, 115(44): 11144-11149.
53. Liberson A S, Lillie J S, Day S W, et al. A physics based approach to the pulse wave velocity prediction in compliant arterial segments. J Biomech, 2016, 49(14): 3460-3466.
54. Zhang Y, Yin P, Xu Z, et al. Non-Invasive assessment of early atherosclerosis based on new arterial stiffness indices measured with an upper-arm oscillometric device. Tohoku J Exp Med, 2017, 241(4): 263-270.
55. Tazawa Yasushi, Mori N, Ogawa Y, et al. Arterial stiffness measured with the cuff oscillometric method is predictive of exercise capacity in patients with cardiac diseases. Tohoku J Exp Med, 2016, 239(2): 127-134.
56. Komine H, Asai Y, Yokoi T, et al. Non-invasive assessment of arterial stiffness using oscillometric blood pressure measurement. Biomed Eng Online, 2012, 11(1): 6.
57. Hitsumoto T. Arterial velocity pulse index as a novel marker of atherosclerosis using pulse wave analysis on high sensitivity troponin T in hypertensive patients. Cardiol Res, 2017, 8(2): 36-43.
58. Sasaki-Nakashima R, Kino T, Chen L, et al. Successful prediction of cardiovascular risk by new non-invasive vascular indexes using suprasystolic cuff oscillometric waveform analysis. J Cardiol, 2017, 69(1): 30-37.
59. Wan J, Liu S, Yang Y, et al. Roles of arterial pressure volume index and arterial velocity pulse index trajectories in risk prediction in hypertensive patients with heart failure with preserved ejection fraction. Clin Exp Hypertens, 2020, 42(5): 469-478.
60. Kobayashi R, Iwanuma S, Ohashi N, et al. New indices of arterial stiffness measured with an upper-arm oscillometric device in active versus inactive women. Physiol Rep, 2018, 6(5): e13574.
61. Liang Fuyou, Takagi S, Himeno R, et al. A computational model of the cardiovascular system coupled with an upper-arm oscillometric cuff and its application to studying the suprasystolic cuff oscillation wave, concerning its value in assessing arterial stiffness. Comput Methods Biomech Biomed Engin, 2013, 16(2): 141-157.
62. Komine H, Asai Y, Yokoi T, et al. Arterial-wall stiffness evaluation system: U.S. Patent 9, 730, 594. 2017-8-15.

Previous Article
Numerical study on the mechanical coupling of external vascular stent and vein graft in coronary artery bypass surgery

Journal of Biomedical Engineering

Application of biomechanical modeling and simulation in the development of non-invasive technologies and devices for cardiovascular testing

Abstract Full text Figures/Tables Video References Cited by

Previous Article

Format

Content