[103] Mukkamala R, Shroff SG, Landry C, Kyriakoulis KG, Avolio AP, Stergiou GS. The Microsoft research aurora project: important findings on cuffless blood pressure measurement. Hypertension, 2022.

[102] Yavarimanesh M, Cheng HM, Chen CH, Sung SH, Mahajan A, Chaer RA, Shroff SG, Hahn JO, Mukkamala R. Abdominal aortic aneurysm monitoring via arterial waveform analysis: towards a convenient point-of-care device. NPJ Digital Medicine, 5(1):168, 2022.

[101] Dhamotharan V, Chandrasekher A, Cheng HM, Chen CH, Sung SH, Landry C, Hahn JO, Mahajan A, Shroff SG, Mukkamala R. Mathematical modeling of oscillometric blood pressure measurement: a complete, reduced oscillogram model. IEEE Transactions on Biomedical Engineering, 1-8, 2022.

[100] Stergiou GS, Mukkamala R, Avolio A, Kyriakoulis KG, Mieke S, Murray A, Parati G, Schutte AE, Sharman JE, Asmar R, McManus RJ, Asayama K, De La Sierra A, Head G, Kario K, Kollias A, Myers M, Niiranen T, Ohkubo T, Wang J, Wuerzner G, O'Brien E, Kreutz R, Palatini P. Cuffless blood pressure measuring devices: review and statement by the european society of hypertension working group on blood pressure monitoring and cardiovascular variability. Hypertension, 40(8):1449-1460, 2022.

[99] Kawada T, Miyamoto T, Mukkamala R, Saku K. Linear and nonlinear identification of the carotid sinus baroreflex in the very low-frequency range. Physiological Reports, 10(14): 15392, 2022

[98] Mukkamala R, Stergiou GS, Avolio AP. Cuffless blood pressure measurement. Annual Review of Biomedical Engineering, 24:203-230, 2022.

[97] Yavarimanesh M, Block RC, Natarajan K, Mestha LK, Inan OT, Hahn JO, Mukkamala R. Assessment of calibration models for cuff-less blood pressure measurement after one year of aging.  IEEE Transactions on Biomedical Engineering, 69(6):2087-2093, 2022.

[96] Lisheng Xu, Shuran Z, Wang L, Yang Y, Hao L, Qi L, Yudong Y, Han H, Mukkamala R, Greenwald SE. Improving the accuracy and robustness of carotid-femoral pulse wave velocity measurement using a simplified tube-load model. Scientific Reports, 12(1):5147, 2022.

[95] Du S, Yao Y, Sun G, Mukkamala R, Xu L.  Simultaneous adaption of the gain and phase of a generalized transfer function for aortic pressure waveform estimation.  Comput Biol Med, 141:105187, 2022.

[94] Shin S, Mousavi A, Lyle S, Jang E, Yousefian P, Mukkamala R, Jang DG, Kwon UK, Kim Y, Hahn JO. Posture-dependent variability in wrist ballistocardiogram-photoplethysmogram pulse transit time: implication to cuff-less blood pressure tracking. IEEE Trans Biomed Eng, 69(1):347-355, 2022.

[93] Natarajan K, Block RC, Yavarimanesh M, Chandrasekhar A, Mestha LK, Inan O, Hahn JO, Mukkamala R. Photoplethysmography fast upstroke time intervals can be useful features for cuff-less measurement of blood pressure changes in humans. IEEE Trans Biomed Eng, 69(1):53-62, 2022.

[92] Mukkamala R, Hahn JO, Chandrasekhar.  Photoplethysmography in non-invasive blood pressure monitoring.  Photoplethysmography.  Eds. Kyriacou P, Allen J.  London: Academic Press, pp. 359-400, 2022.

[91] Natarajan K, Yavarimanesh M, Weng W, Mukkamala R.  Camera-based blood pressure monitoring.  Contactless Vital Signs Monitoring.  Eds. Wang W, Wang X.  London: Academic Press, 117-148, 2022.

[90] Mukkamala R, Yavarimanesh M, Natarajan K, Hahn JO, Kyriakoulis KG, Avolio AP, Stergiou GS. Evaluation of the accuracy of cuffless blood pressure measurement devices: challenges and proposals. Hypertension. 78(5):1161-1167, 2021.

[89] Mukkamala R, Kohl BA, Mahajan A. Comparison of accuracy of two uncalibrated pulse contour cardiac output monitors in off-pump coronary artery bypass surgery patients using pulmonary artery catheter-thermodilution as a reference. BMC Anesthesiol, 21(1):189, 2021.

[88] Di Rienzo M, Mukkamala R. Wearable and nearable biosensors and systems for healthcare. Sensors, 21(4):1291, 2021.

[87] Shin S, Yousefian P, Mousavi AS, Kim CS, Mukkamala R, Jang DG, Ko BH, Lee J, Kwon UK, Kim YH, Hahn JO. A unified approach to wearable ballistocardiogram gating and wave localization. IEEE Trans Biomed Eng, 68(4):1115-1122, 2021.

[86] Block RC*, Yavarimanesh M*, Natarajan K, Carek A, Mousavi A, Chandrasekhar A, Kim CS, Zhu J, Schifitto G, Mestha LK, Inan OI, Hahn JO, Mukkamala R. Conventional pulse transit times as markers of blood pressure in humans. Scientific Reports, 10(1):16373, 2020.

[85] Chandrasekhar A, Yavarimanesh M, Natarajan K, Hahn JO, Mukkamala R. PPG sensor contact pressure should be taken into account for cuff-less blood pressure measurement. IEEE Transactions on Biomedical Engineering, 67(11):3124-3140, 2020.

[84] Yao Y, Ghasemi Z, Ashouri H, Shandhi MH, Xu L, Mukkamala R, Inan OT, Hahn JO. Mitigation of instrument-dependent variability in ballistocardiogram morphology: case study on force plate versus weighing scale. IEEE Journal of Biomedical and Health Informatics, 24(1):69-78, 2020.

[83] Chandrasekhar A, Yavarimanesh M, Hahn JO, Mukkamala R. Formulas for explaining popular oscillometric blood pressure estimation algorithms. Frontiers in Physiology, 10:1415, 2019.

[82] Yavarimanesh M, Chandrasekhar A, Hahn JO, Mukkamala R. Commentary: relation between blood pressure and pulse wave velocity for human arteries. Frontiers in Physiology, 10:1179, 2019.

[81] Mousavi A, Tivay A, Finegan B, McMurtry SM, Mukkamala R, Hahn JO. Tapered versus uniform tube-load modeling of blood pressure wave propagation in human aorta. Frontiers in Physiology, 10:974, 2019.

[80] Mukkamala R. Blood pressure with a click of a camera? Circulation: Cardiovascular Imaging, 12(8):e009531, 2019.

[79] Mukkamala R, Hahn JO. Calibration of pulse transit time-based blood pressure monitors. The handbook of cuffless blood pressure monitoring. Eds. Sola J, Delgado-Gonzalo R. New York: Springer, 163-190, 2019.

[78] Yousefian P, Shin S, Mousavi A, Kim CS, Mukkamala R, Jang DG, Ko BH, Lee J, Kwon UK, Kim YH, Hahn JO. The potential of wearable limb ballistocardiogram in blood pressure monitoring via pulse transit time. Scientific Reports, 9(1):5146, 2019.

[77] Yao Y, Shin S, Mousavi A, Kim CS, Xu L, Mukkamala R, Hahn JO. Unobtrusive estimation of cardiovascular parameters with limb ballistocardiography. Sensors, 19(13):E2922, 2019.

[76] Kawada T, Mukkamala R, Sugimachi M. Linear and Nonlinear Analysis of the Carotid Sinus Baroreflex Dynamic Characteristics. Advanced Biomedical Engineering, 8:110-123, 2019.

[75] Yousefian P, Shin S, Mousavi AS, Kim CS, Finegan B, McMurtry MS, Mukkamala R, Jang DG, Kwon U, Kim YH, Hahn JO. Physiological association between limb ballistocardiogram and arterial blood pressure waveforms: a mathematical model-based analysis. Scientific Reports, 9(1):5146, 2019.

[74] Kim CS, Carek AM, Ashouri H, Inan OT, Mukkamala R, Hahn JO. Ballistocardiogram-based approach to cuff-less blood pressure monitoring: proof-of-concept and potential challenges. IEEE Transactions on Biomedical Engineering, 65(11):2384-2391, 2018.

[73] Chandrasekhar A*, Natarajan K*, Yavarimanesh M*, Mukkamala R. An iPhone application for blood pressure monitoring via the oscillometric finger pressing method. Scientific Reports, 8(1):13136, 2018.

[72] Yousefian P, Shin S, Mousavi A, Kim CS, Mukkamala R, Jang DG, Ko BH, Lee J, Kwon UK, Kim YH, Hahn JO. Data mining investigation of the association between a limb ballistocardiogram and blood pressure. Physiological Measurement, 39(7):075009, 2018.

[71] Ghasemi Z, Lee A, Kim CS, Cheng HM, Sung SH, Chen CH, Mukkamala R, Hahn JO. Estimation of cardiovascular risk parameters from non-invasively measured diametric pulse volume waveforms via multiple measurement information fusion. Scientific Reports, 8(1):10433, 2018.

[70] Mukkamala R, Hahn JO. Toward ubiquitous blood pressure monitoring via pulse transit time: predictions on maximum calibration period and acceptable error limits. IEEE Transactions on Biomedical Engineering, 65(6):1410-1420, 2018.

[69] Chandrasekhar A, Kim CS, Naji M, Natarajan K, Hahn JO, Mukkamala R. Smartphone-based blood pressure monitoring via the oscillometric finger pressing method. Science Translational Medicine, 10(431):eaap8674, 2018.

[68] Lee JC, Ghasemi Z, Kim CS, Cheng HM, Chen CH, Sung SH Mukkamala R, Hahn JO. Investigation of viscoelasticity in the relationship between carotid artery blood pressure and distal pulse volume waveforms. IEEE Journal of Biomedical and Health Informatics, 22(2):460-470, 2018.

[67] Natarajan K*, Cheng HM*, Liu J, Gao M, Sung SH, Chen CH, Hahn JO, Mukkamala R. Central blood pressure monitoring via a standard automatic arm cuff. Scientific Reports, 7(1):14441, 2017.

[66] Liu J, Cheng HM, Chen CH, Sung SH, Hahn JO, Mukkamala R. Patient-specific oscillometric blood pressure measurement: validation for accuracy and repeatability. IEEE Journal of Translational Engineering in Health and Medicine, 5:1900110, eCollection 2017.

[65] Gao M, Cheng HM, Sung SH, Chen CH, Olivier NB, Mukkamala R. Estimation of pulse transit time as a function of blood pressure using a nonlinear arterial tube-load model. IEEE Transactions on Biomedical Engineering, 64(7):1524-1534, 2017.

[64] Martin SL, Carek AM, Kim CS, Ashouri H, Inan OT, Hahn JO, Mukkamala R. Weighing scale-based pulse transit time is a superior marker of blood pressure than conventional pulse arrival time. Scientific Reports, 6:39273, 2016. (Author correction: 8(1):15838, 2018.)

[63] Moslehpour M*, Kawada T*, Sunagawa K, Sugimachi M, Mukkamala R. Nonlinear identification of the total baroreflex arc: higher-order nonlinearity. American Journal of Physiology, 311(6):R994-R1003, 2016.

[62] Gao M, Rose WC, Fetics B, Kass DA, Chen CH, Mukkamala R. A simple adaptive transfer function for deriving the central blood pressure waveform from a radial blood pressure waveform. Scientific Reports, 6:33230, 2016.

[61] Kim CS, Ober SL, McMurtry MS, Finegan BA, Inan OT, Mukkamala R*, Hahn JO*. Ballistocardiogram: mechanism and potential for unobtrusive cardiovascular health monitoring. Scientific Reports, 6:31297, 2016.

[60] Liu J, Cheng HM, Chen CH, Sung SH, Moslehpour M, Hahn JO, Mukkamala R. Patient-specific oscillometric blood pressure measurement. IEEE Transactions on Biomedical Engineering, 63(6):1220-1228, 2016.

[59] Gao M, Oliver NB, Mukkamala R. Comparison of non-invasive pulse transit time estimates as markers of blood pressure using invasive pulse transit time measurements as a reference. Physiological Reports, 4(10):e12768, 2016.

[58] Moslehpour M, Kawada T, Sunagawa K, Sugimachi M, Mukkamala R. Nonlinear identification of the total baroreflex arc: chronic hypertension model. American Journal of Physiology, 310(9):R819-R827, 2016.

[57] Moslehpour M, Kawada T, Sunagawa K, Sugimachi M, Mukkamala R. Nonlinear identification of the total baroreflex arc. American Journal of Physiology, 309(12):R1479-R1489, 2015.

[56] Kim CS, Carek AM, Mukkamala R, Inan OT, Hahn JO. Ballistocardiogram as proximal timing reference for pulse transit time measurement: potential for cuffless blood pressure monitoring. IEEE Transactions on Biomedical Engineering, 62(11):2657-2664, 2015.

[55] Mukkamala R, Gao M. A comparative analysis of reduced arterial models for hemodynamic monitoring. Proceedings of the 35th Annual Conference of the IEEE Engineering in Medicine and Biology Society, 1:225-228, 2015.

[54] Mukkamala R, Hahn JO, Inan OT, Mestha LK, Kim CS, Toreyin H, Kyal S. Toward ubiquitous blood pressure monitoring via pulse transit time: theory and practice. IEEE Transactions on Biomedical Engineering, 62(8):1879-1901, 2015.

[53] Sala-Mercado JA*, Moslehpour M*, Hammond RL, Ichinose M, Chen X, Evan S, O’Leary DS, Mukkamala R. Stimulation of the cardiopulmonary baroreflex enhances ventricular contractility in awake dogs: a mathematical analysis study. American Journal of Physiology, 307(4):R455-R464, 2014.

[52] Gao M, Moslehpour M, Olivier NB, Mukkamala R. Emax monitoring by aortic pressure waveform analysis. Proceedings of the 36th Annual Conference of the IEEE Engineering in Medicine and Biology Society, 1:6762-6765, 2014.

[51] Gao M, Zhang G, Olivier NB, Mukkamala R. Improved pulse wave velocity estimation using an arterial tube-load model. IEEE Transactions on Biomedical Engineering, 61(3):848-858, 2014.

[50] Aletti F, Hammond RL, Sala-Mercado JA, Chen X, O’Leary DS, Baselli G, Mukkamala R. Cardiac output is not a significant source of low frequency arterial blood pressure variability. Physiological Measurement, 34(9):1207-1216, 2013.

[49] Liu J, Hahn JO, Mukkamala R. An initial step towards improving the accuracy of the oscillometric blood pressure measurement. Proceedings of the 35th Annual Conference of the IEEE Engineering in Medicine and Biology Society, 1:4082-4085, 2013.

[48] Liu J, Hahn JO, Mukkamala R. Error mechanisms of the oscillometric fixed-ratio blood pressure measurement method. Annals of Biomedical Engineering, 41(3):587-597, 2013.

[47] Zhang G, Mukkamala R. Continuous and minimally invasive cardiac output monitoring by long time interval analysis of a radial arterial blood pressure waveform: assessment using a large, public intensive care unit patient database. British Journal of Anaesthesia, 109(3):339-344, 2012.

[46] Moshlehpour M, Zhang G, Mukkamala R. Cardiac output monitoring by long time interval analysis of a radial arterial blood pressure waveform with correction for arterial compliance changes using pulse transit time. Proceedings of the 33rd Annual Conference of the IEEE Engineering in Medicine and Biology Society, 1:5496-5498, 2011.

[45] Zhang G, Gao M, Xu D, Olivier NB, Mukkamala R. Pulse arrival time is not an adequate surrogate for pulse transit time as a marker of blood pressure. Journal of Applied Physiology. 111(6):1681-1686, 2011.

[44] Zhang G, Hahn JO, Mukkamala R. Tube-load model parameter estimation for monitoring arterial hemodynamics. Frontiers in Physiology, 2(72):1-18, 2011.

[43] Xu D, Ryan KL, Rickards CA, Zhang G, Convertino VA, Mukkamala R. Improved pulse transit time estimation by system identification analysis of proximal and distal arterial waveforms. American Journal of Physiology, 301(4):H1389,H1395, 2011.

[42] Reisner AT, Xu D, Ryan KL, Convertino VA, Rickards CA, Mukkamala R. Monitoring non-invasive cardiac output and stroke volume during experimental human hypovolemia and resuscitation. British Journal of Anaesthesia, 106(1):23-30, 2011.

[41] Heldt T, Mukkamala R, Moody GB, Mark RG. CVSim: An open-source cardiovascular simulator for teaching and research. The Open Pacing, Electrophysiology & Therapy Journal, 3:45-54, 2010.

[40] Swamy G, Olivier NB, Mukkamala R. Calculation of forward and backward arterial waves by analysis of two pressure waveforms. IEEE Transactions on Biomedical Engineering, 57(12):2833-2839, 2010.

[39] Mukkamala R, Xu D. Continuous and less invasive monitoring of central hemodynamics by blood pressure waveform analysis. American Journal of Physiology, 299(3):H584-H599, 2010.

[38] Chen X, Sala-Mercado JA, Hammond RL, Ichinose M, Soltani S, Mukkamala R, O’Leary DS. Dynamic control of maximal ventricular elastance via the baroreflex and force-frequency relation in awake dogs before and after pacing induced heart failure. American Journal of Physiology, 299(1):H62-H69, 2010.

[37] Batzel J, Baselli G, Mukkamala R, Chon KH. Modelling and disentangling physiological mechanisms: linear and nonlinear identification techniques for analysis of cardiovascular regulation. Philosophical Transactions of the Royal Society A, 367:1377-1391, 2009.

[36] Chen X, Xu D, Zhang G, Mukkamala R. Forecasting acute hypotensive episodes in intensive care patients based on a peripheral arterial blood pressure waveform. Computers in Cardiology, 36:545-548, 2009.

[35] Swamy G, Kuiper J, Gudur MSR, Olivier NB, Mukkamala R. Continuous left ventricular ejection fraction monitoring by aortic pressure waveform analysis. Annals of Biomedical Engineering, 37(6):1055-1068, 2009.

[34] Swamy G, Xu D, Mukkamala R. Estimation of the aortic pressure waveform from a radial artery pressure waveform via an adaptive transfer function: feasibility demonstration in swine. Proceedings of the 31th Annual Conference of the IEEE Engineering in Medicine and Biology Society, 1:2362-2364, 2009.

[33] Swamy G, Xu D, Olivier NB, Mukkamala R. Adaptive transfer function for deriving the aortic pressure waveform from a peripheral artery pressure waveform. American Journal of Physiology, 297(5):H1956-H1963, 2009.

[32] Xu D, Olivier NB, Mukkamala R. Cardiac output and left atrial pressure monitoring by right ventricular pressure waveform analysis for potential implantable device application. IEEE Transactions on Biomedical Engineering, 56(9):2335-2339, 2009.

[31] Xu D, Olivier NB, Mukkamala R. Continuous cardiac output and left atrial pressure monitoring by long time interval analysis of the pulmonary artery pressure waveform: proof of concept in dogs. Journal of Applied Physiology, 106(2):651-661, 2009.

[30] Chen X, Mukkamala R. Selective quantification of the cardiac sympathetic and parasympathetic nervous systems by multisignal analysis of cardiorespiratory variability. American Journal of Physiology, 294(1):H362-H371, 2008.

[29] Chen X, Kim JK, Sala-Mercado JA, Hammond RL, Elahi RI, Scislo TJ, Swamy G, O’Leary DS, Mukkamala R. Estimation of the total peripheral resistance baroreflex impulse response from spontaneous hemodynamic variability. American Journal of Physiology, 294(1):H293-H301, 2008.

[28] Swamy G, Mukkamala R. Estimation of the aortic pressure waveform and beat-to-beat cardiac output from multiple peripheral artery pressure waveforms. IEEE Transactions on Biomedical Engineering, 55(5):1521-1529, 2008.

[27] Mukkamala R, Reisner AT. Reply to Van Lieshout and Jansen. Journal of Applied Physiology, 102(2):827, 2007.

[26] Swamy G, Ling Q, Li T, Mukkamala R. Blind identification of the aortic pressure waveform from multiple peripheral artery pressure waveforms. American Journal of Physiology, 292(5):H2257-H2264, 2007.

[25] Lu Z, Mukkamala R. Continuous cardiac output monitoring in humans by invasive and non-invasive peripheral blood pressure waveform analysis. Journal of Applied Physiology, 101(2):598-608, 2006.

[24] Mukkamala R, Kim J, Li Y, Sala-Mercado J, Hammond RL, Scislo T, O'Leary DS. Estimation of arterial and cardiopulmonary total peripheral resistance baroreflex gain values: validation by chronic arterial baroreceptor denervation. American Journal of Physiology, 290(5):H1830-H1836, 2006.

[23] Mukkamala R, Kuiper J, Sala-Mercado JA, Hammond RL, Kim J, Stephenson LW, O'Leary DS. Continuous left ventricular ejection fraction monitoring by central aortic pressure waveform analysis. Proceedings of the 28th Annual Conference of the IEEE Engineering in Medicine and Biology Society, 1:620-623, 2006.

[22] Mukkamala R, Reisner AT, Hojman HM, Mark RG, Cohen RJ. Continuous cardiac output monitoring by peripheral blood pressure waveform analysis. IEEE Transactions on Biomedical Engineering, 53(3):459-467, 2006.

[21] Xiao X, Mukkamala R, Cohen RJ. A weighted-principal component regression method for the identification of physiologic systems. IEEE Transactions on Biomedical Engineering, 53(8):1521-1530, 2006.

[20] Lu Z, Mukkamala R. Non-invasive monitoring of left ventricular contractility and ventilatory mechanics. Proceedings of the 27th Annual Conference of the IEEE Engineering in Medicine and Biology Society, 7:7636-7639, 2005.

[19] Xiao X, Li Y, Mukkamala R. A model order selection criterion with applications to cardio-respiratory-renal systems. IEEE Transactions on Biomedical Engineering, 52(3):445-453, 2005.

[18] Xiao X, Mullen TJ, Mukkamala R. System identification: a multi-signal approach for probing neural cardiovascular regulation. Physiological Measurement, 26:R41-R71, 2005.

[17] Lu Z, Mukkamala R. Monitoring left ventricular contractility from respiratory-induced blood pressure variability. Computers in Cardiology, 31:705-708, 2004.

[16] Xiao X, Mukkamala R, Sheynberg N, Grenon SM, Ehrman MD, Mullen TJ, Ramsdell CD, Williams GH, Cohen RJ. Effects of simulated microgravity on closed-loop cardiovascular regulation and orthostatic intolerance: analysis by means of system identification. Journal of Applied Physiology, 96(2):489-497, 2004.

[15] Armoundas AA, Feldman AB, Mukkamala R, He B, Mullen TJ, Belk PA, Lee YZ, Cohen RJ. Statistical accuracy of a moving equivalent dipole method to identify sites of origin of cardiac electrical activation. IEEE Transactions on Biomedical Engineering, 50(12):1360-1370, 2003.

[14] Armoundas AA, Feldman AB, Mukkamala R, Cohen RJ. A single equivalent moving dipole model: an efficient approach for localizing sites of origin of ventricular electrical activation. Annals of Biomedical Engineering, 31(5):564-576, 2003.

[13] Mukkamala R, Toska K, Cohen RJ. Noninvasive identification of the total peripheral resistance baroreflex. American Journal of Physiology, 284(3):H947-H959, 2003.

[12] Mukkamala R, Cohen RJ, Mark RG. A computational model-based validation of guyton's analysis of cardiac output and venous return curves. Computers in Cardiology, 29:561-564, 2002.

[11] Murphy S, Coolahan J, Lutz R, Saunders R, Feldman A, Mukkamala R. Integrating cardiac and cardiovascular simulations using the hla. Spring Simulation Interoperability Workshop, 02S-SIW-012:1-16, 2002.

[10] Choi HG, Mukkamala R, Moody GB, Mark RG. Do nonlinearities play a significant role in short-term, beat-to-beat variability? Computers in Cardiology, 28:53-56, 2001.

[9] Mukkamala R, Cohen RJ. A forward model-based validation of cardiovascular system identification. American Journal of Physiology, 281(6):H2714-H2730, 2001.

[8] Mukkamala R, Mark RG, Cohen RJ. A noninvasive method for characterizing ventricular diastolic filling dynamics. Proceedings of the 23th Annual Conference of the IEEE Engineering in Medicine and Biology Society, 1:147-150, 2001.

[7] Mukkamala R, Moody GB, Mark RG. Introduction of computational models to physionet. Computers in Cardiology, 28:77-80, 2001.

[6] Ramsdell CD, Mullen TJ, Sundby GH, Rostoft S, Sheynberg N, Aljuri N, Maa M, Mukkamala R, Sherman D, Toska K, Yelle J, Bloomfield D, Williams GH, Cohen RJ. Midodrine prevents orthostatic intolerance associated with simulated spaceflight. Journal of Applied Physiology, 90(6):2245-2248, 2001.

[5] Zong W, Mukkamala R, Mark RG. A methodology for predicting paroxysmal atrial fibrillation based on ECG arrhythmia feature analysis. Computers in Cardiology, 28:125-128, 2001.

[4] Mullen TJ, Mukkamala R, Cohen RJ. Cardiovascular system identification. Advances in noninvasive electrocardiographic monitoring techniques. Developments in cardiovascular medicine. Eds. Osterhues HH, Hombach V, Moss AJ. Dordrecht:Springer, 229, 453-461, 2000.

[3] Mukkamala R, Mathias JM, Mullen TJ, Cohen RJ, Freeman R. System identification of closed-loop cardiovascular control mechanisms: diabetic autonomic neuropathy. American Journal of Physiology, 276(45):R905-R912, 1999.

[2] Chon KH, Mukkamala R, Toska K, Mullen TJ, Armoundas AA, Cohen RJ. Linear and nonlinear system identification of autonomic heart-rate modulation. IEEE Engineering in Medicine and Biology Magazine, 16(5):96-105, 1997.

[1] Mullen TJ, Appel ML, Mukkamala R, Mathias TJ, Cohen RJ. System identification of closed-loop cardiovascular control mechanisms: effects of posture and autonomic blockade. American Journal of Physiology, 272(41):H448-H461, 1997.

Patents