Independent, peer‑reviewed research supported by Tele‑stethoscope technology.
Our approach has been developed over 6 years of continuous study. Currently published papers, listed below, reflect the evolution of our approach from its most rudimentary beginnings. As we currently have access to the world’s most robust mHealth database we can, and do, resimulate all of our studies every 6 months to ensure that we are developing one platform approach across all disease states.
It should be noted that, in all of our studies, no completed patient recording has ever been discarded in our analytical work because we want our solutions to be as durable as possible under real world conditions. It should also be noted that all of our papers utilize rigorous mathematical and physics throughout. Our ability to extract powerful physics-based features obsoletes the need for neural networks entirely which has been viewed favorably by the FDA.
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2026 | 2025 | 2024 | Conference abstracts & invited presentations || Turbulence – Background reading
Peer‑reviewed publications
2026
Close, R., et al. (2026). Feasibility of detecting aortic stenosis with mobile phone auscultation data: A pilot study. Frontiers in Cardiovascular Medicine. To be published.
Otte, E., & Huecker, M. (2026). Mobile phone auscultation to detect carotid stenosis and cerebral ischemia. American Journal of Emergency Medicine. https://doi.org/10.1016/j.ajem.2026.02.004
Huecker M, Close R, Mattingly J, et al. Mobile phone auscultation to delineate pneumonia from other respiratory conditions and controls: a prospective cohort study. BMC Pulmonary Medicine. 2026. https://doi.org/10.1186/s12890-026-04135-z
2025
Kowalski, K., Judson, G., Martinez, D., Zhang, J., Diaz, M., & Close, R. (2025). Mobile phone auscultation using non-linear dynamics analysis to detect aortic stenosis. Circulation. https://doi.org/10.1161/circ.152.suppl_3.4357265
Huecker, M., et al. (2025). Mobile phone auscultation to determine VO2Max: Implications for emergency medicine and telehealth. Annals of Emergency Medicine, 86(3), S158–S159. https://doi.org/10.1016/j.annemergmed.2025.06.383
Gosser, C., Daniel, L., Huecker, M., et al. (2025). Mobile phone auscultation accurately diagnoses chronic obstructive pulmonary disease using nonlinear respiratory biofluid dynamics. Diagnostics, 15(12), 1550. https://doi.org/10.3390/diagnostics15121550
2024 and earlier
Huecker, M., et al. (2024). Accurate modeling of ejection fraction and stroke volume with mobile phone auscultation: A prospective case-control study. JMIR Cardio, 8, e57111. https://doi.org/10.2196/57111
Heironimus, K., et al. (2022). Detecting COVID-19 respiratory markers with ordinary mobile phones. International Journal of Digital Healthcare, 2, 109. https://doi.org/10.15344/ijdh/2022/109
Conference abstracts & invited presentations
Close, R. M. (2025). Mobile phone auscultation for the detection of structural heart disease: A step toward addressing urban–rural disparities in cardiovascular disease. Invited speaker, Emerging Areas of Science IDeA Symposium, Brown University, Providence, RI; June 2025.
Parson, A., & Huecker, M. (2024). Obstetrics and gynecology auscultatory mapping and chaotic reconstruction of fluid dynamics. Research Louisville, Louisville, KY; September 2024.
Daniel, L., Huecker, M., et al. (2024). Mobile phone auscultation to diagnose chronic obstructive pulmonary disease using pulmonary fluid dynamics. American College of Emergency Physicians Scientific Assembly, Las Vegas, NV; September 2024.
Dickens, J., Huecker, M., et al. (2021). Auscultatory mapping and chaotic reconstruction of cardiovascular fluid dynamics using unmodified cell phone recordings. American College of Emergency Physicians Scientific Assembly, Boston, MA; 2021. Winner of Student Section.
Turbulence – Background reading
We offer the following external references to connect our technology with research on biofluid turbulence. Since the TSI device is based on hemodynamic and pneumodynamic turbulence, the work below represents foundational information.
Saqr KM, Tupin S, Rashad S, Endo T, Niizuma K, Tominaga T, Ohta M. Physiologic blood flow is turbulent. Sci Rep. 2020 Sep 23;10(1):15492. doi: 10.1038/s41598-020-72309-8. PMID: 32968087; PMCID: PMC7512016.
Keunen RW, Pijlman HC, Visée HF, Vliegen JH, Tavy DL, Stam KJ. Dynamical chaos determines the variability of transcranial Doppler signals. Neurol Res. 1994 Oct;16(5):353-8. doi: 10.1080/01616412.1994.11740253. PMID: 7870274.
Ozturk A, Arslan A. Classification of transcranial Doppler signals using their chaotic invariant measures. Comput Methods Programs Biomed. 2007 May;86(2):171-80. doi: 10.1016/j.cmpb.2007.02.004. Epub 2007 Mar 26. PMID: 17386958.
Orel V, Kozarenko T, Galachin K, Romanov A, Morozoff A. Nonlinear analysis of digital images and Doppler measurements for trophoblastic tumor. Nonlinear Dynamics Psychol Life Sci. 2007 Jul;11(3):309-31. PMID: 17572987.
Elif Derya Übeylı, İnan Güler, Determining variability of ophthalmic arterial Doppler signals using Lyapunov exponents, Computers in Biology and Medicine, Volume 35, Issue 5, 2005, Pages 405-420, ISSN 0010-4825,
https://doi.org/10.1016/j.compbiomed.2004.03.004.
Liu, M., Song, D., Hong, S., Dong, Y., Gao, W., Du, Y., … & Dong, F. (2024). Characteristics and correlations of wall shear stress and flow turbulence in the carotid bifurcation evaluated using an ultrasound vector flow imaging. Journal of Vascular Research, 61(1), 38-49.
Saqr, K. M., Kano, K., Rashad, S., Niizuma, K., Kaku, Y., Iwama, T., & Tominaga, T. (2022). Non-Kolmogorov turbulence in carotid artery stenosis and the impact of carotid stenting on near-wall turbulence. AIP Advances, 12(1).
Wang, Y. (2025). Hydrodynamic Behavior of Blood Components in Elastic Vessels. Science and Technology of Engineering, Chemistry and Environmental Protection, 1(1).
Saqr, K. M., Tupin, S., Rashad, S., Endo, T., Niizuma, K., Tominaga, T., & Ohta, M. (2020). Origins of Chaos and Turbulence in Blood Flow: Revisiting the Principles of Hemodynamics. arXiv preprint arXiv:2002.03857.
May, P., Arrouvel, C., Revol, M., Servant, J. M., & Vicaut, E. (2002). Detection of hemodynamic turbulence in experimental stenosis: an in vivo study in the rat carotid artery. Journal of vascular research, 39(1), 21-29.
Wagner, C. D., & Persson, P. B. (1995). Nonlinear chaotic dynamics of arterial blood pressure and renal blood flow. American Journal of Physiology-Heart and Circulatory Physiology, 268(2), H621-H627.
Ahlstrom, C., Johansson, A., Hult, P., & Ask, P. (2006). Chaotic dynamics of respiratory sounds. Chaos, Solitons & Fractals, 29(5), 1054-1062.
Raj, V., Renjini, A., Swapna, M. S., Sreejyothi, S., & Sankararaman, S. (2020). Nonlinear time series and principal component analyses: Potential diagnostic tools for COVID-19 auscultation. Chaos, Solitons & Fractals, 140, 110246.
Last updated: February 2026