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Magnetohydrodynamic Voltage Recorder for Comparing Peripheral Blood Flow

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Abstract

Blood flow is a clinical metric for monitoring of cardiovascular diseases but current measurements methods are costly or uncomfortable for patients. It was shown that the interaction of the magnetic field (B 0) during MRI and blood flow in the body, through the magnetohydrodynamic (MHD) effect, produce voltages (V MHD) observable through intra-MRI electrocardiography (ECG), which are correlated with regional blood flow. This study shows the reproducibility of V MHD outside the MRI and its application in a portable flow monitoring device. To recreate this interaction outside the MRI, a static neodymium magnet (0.4T) was placed in between two electrodes to induce the V MHD in a single lead ECG measurement. V MHD was extracted, and integrated over to obtain a stroke volume metric. A smartphone-enabled device utilizing this interaction was developed in order to create a more accessible method of obtaining blood flow measurements. The portable device displayed a <6% error compared to a commercial recorder, and was able to successfully record V MHD using the 0.4T magnet. Exercise stress testing showed a V MHD increase of 23% in healthy subjects, with an 81% increase in the athlete. The study demonstrates a new device utilizing MHD interactions with body circulation to obtain blood flow metrics.

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References

  1. Abi-Abdallah, D., V. Robin, A. Drochon, and O. Fokapu. Alterations in human ECG due to the MagnetoHydroDynamic effect: a method for accurate R peak detection in the presence of high MHD artifacts. In: Conf Proc IEEE Eng Med Biol Soc, 2007, pp. 1842–1845.

  2. Agu, E., P. Pedersen, D. Strong, B. Tulu, Q. He, L. Wang, and Y. Li. The smartphone as a medical device: assessing enablers, benefits and challenges. In: Internet-of-Things Networking and Control (IoT-NC), IEEE International Workshop of 2013, 2013, pp. 48–52.

  3. Albert, D., B. R. Satchwell, and K. N. Barnett. Wireless, ultrasonic personal health monitoring system. Google Patents, 2012.

  4. Aldaoud, A., C. Laurenson, F. Rivet, M. R. Yuce, and J. M. Redout. Design of a miniaturized wireless blood pressure sensing interface using capacitive coupling. IEEE/ASME Trans. Mechatron. 20:487–491, 2015.

    Article  Google Scholar 

  5. Association, A. H. Heart and stroke facts. The Association, 1993.

  6. Berson, A. S., and H. V. Pipberger. Electrocardiographic distortions caused by inadequate high-frequency response of direct-writing electrocardiographs. Am. Heart J. 74:208–218, 1967.

    Article  CAS  PubMed  Google Scholar 

  7. Bessette, F., and L. Nguyen. Automated electrocardiogram analysis: the state of the art. Inform. Health Soc. Care 14:43–51, 1989.

    CAS  Google Scholar 

  8. Birkholz, T., M. Schmid, C. Nimsky, J. Schuttler, and B. Schmitz. ECG artifacts during intraoperative high-field MRI scanning. J. Neurosurg. Anesthesiol. 16:271–276, 2004.

    Article  PubMed  Google Scholar 

  9. Chung, E. H., and K. D. Guise. QTC intervals can be assessed with the AliveCor heart monitor in patients on dofetilide for atrial fibrillation. J. Electrocardiol. 48:8–9, 2015.

    Article  PubMed  Google Scholar 

  10. Di Carli, M., J. Czernin, C. K. Hoh, V. H. Gerbaudo, R. C. Brunken, S.-C. Huang, M. E. Phelps, and H. R. Schelbert. Relation among stenosis severity, myocardial blood flow, and flow reserve in patients with coronary artery disease. Circulation 91:1944–1951, 1995.

    Article  PubMed  Google Scholar 

  11. Dolan, B. AliveCor launches smartphone-enabled heart monitor, analysis services direct-to-consumer. MobiHealth-News, 2014.

  12. Fensli, R., E. Gunnarson, and O. Hejlesen. A wireless ECG system for continuous event recording and communication to a clinical alarm station. In: Engineering in Medicine and Biology Society, 2004. IEMBS’04. 26th Annual International Conference of the IEEE, IEEE, 2004, pp. 2208–2211.

  13. Fischer, S. E., S. A. Wickline, and C. H. Lorenz. Novel real-time R-wave detection algorithm based on the vectorcardiogram for accurate gated magnetic resonance acquisitions. Magn. Reson. Med. 42:361–370, 1999.

    Article  CAS  PubMed  Google Scholar 

  14. Gregory, T., E. Schmidt, S. Zhang, and Z. Tse. 3DQRS: a method to obtain reliable QRS complex detection within high field MRIs using 12-lead ECG traces. Magn. Reson. Med. 71:1374–1380, 2014.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Gregory, T. S., J. Oshinski, E. J. Schmidt, R. Y. Kwong, W. G. Stevenson, and Z. T. H. Tse. Continuous rapid quantification of stroke volume using magnetohydrodynamic voltages in 3T magnetic resonance imaging. Circ. Cardiovasc. Imaging 8:e003282, 2015.

    PubMed  Google Scholar 

  16. Gregory, T. S., E. J. Schmidt, S. H. Zhang, R. Y. Kwong, W. G. Stevenson, J. Oshinski, and Z. T. H. Tse. Rapid quantification of stroke volume using magnetohydrodynamic voltages in 3T MRI: a feasibility study. J. Cardiovasc. Magn. Reson. 17:P32, 2015.

    Article  PubMed Central  Google Scholar 

  17. Gupta, A., A. R. Weeks, and S. M. Richie. Simulation of elevated T-waves of an ECG inside a static magnetic field (MRI). IEEE Trans. Biomed. Eng. 55:1890–1896, 2008.

    Article  PubMed  Google Scholar 

  18. Hazas, M., and A. Hopper. Broadband ultrasonic location systems for improved indoor positioning. Mob. Comput. IEEE Trans. 5:536–547, 2006.

    Article  Google Scholar 

  19. Health, N. I. O. How is peripheral artery disease diagnosed? 2016.

  20. Heitzer, T., T. Schlinzig, K. Krohn, T. Meinertz, and T. Münzel. Endothelial dysfunction, oxidative stress, and risk of cardiovascular events in patients with coronary artery disease. Circulation 104:2673–2678, 2001.

    Article  CAS  PubMed  Google Scholar 

  21. Hickey, K. T., J. Dizon, and A. Frulla. Detection of recurrent atrial fibrillation utilizing novel technology. J. Atr. Fibrillation 6, 2013.

  22. Jalaleddine, S., C. G. Hutchens, R. D. Strattan, and W. Coberly. ECG data compression techniques-a unified approach. Biomed. Eng. IEEE Trans. 37:329–343, 1990.

    Article  CAS  Google Scholar 

  23. Katoh, K., and H. Toh. Recent developments in the MAFFT multiple sequence alignment program. Brief. Bioinform. 9:286–298, 2008.

    Article  CAS  PubMed  Google Scholar 

  24. Kim, S. H., C. H. Yu, and K. Ishiyama. Rotary-type electromagnetic power generator using a cardiovascular system as a power source for medical implants. IEEE/ASME Trans. Mechatron. 21:122–129, 2016.

    Google Scholar 

  25. Kligfield, P., and P. M. Okin. Prevalence and clinical implications of improper filter settings in routine electrocardiography. Am. J. Cardiol. 99:711–713, 2007.

    Article  PubMed  Google Scholar 

  26. Kligfield, P., L. S. Gettes, J. J. Bailey, R. Childers, B. J. Deal, E. W. Hancock, G. van Herpen, J. A. Kors, P. Macfarlane, and D. M. Mirvis. Recommendations for the standardization and interpretation of the electrocardiogram: part I: the electrocardiogram and its technology a scientific statement from the American Heart Association Electrocardiography and Arrhythmias Committee, Council on Clinical Cardiology; the American College of Cardiology Foundation; and the Heart Rhythm Society endorsed by the International Society for Computerized Electrocardiology. J. Am. Coll. Cardiol. 49:1109–1127, 2007.

    Article  PubMed  Google Scholar 

  27. Ku, D. N. Blood flow in arteries. Ann. Rev. Fluid Mech. 29:399–434, 1997.

    Article  Google Scholar 

  28. Kyriakou, A., E. Neufeld, D. Szczerba, W. Kainz, R. Luechinger, S. Kozerke, R. McGregor, and N. Kuster. Patient-specific simulations and measurements of the magneto-hemodynamic effect in human primary vessels. Physiol. Meas. 33:117–130, 2012.

    Article  PubMed  Google Scholar 

  29. Martin, V., A. Drochon, O. Fokapu, and J.-F. Gerbeau. MagnetoHemoDynamics in the aorta and electrocardiograms. Phys. Med. Biol. 57:3177–3195, 2012.

    Article  PubMed  Google Scholar 

  30. Mercer, K., L. Giangregorio, E. Schneider, P. Chilana, M. Li, and K. Grindrod. Acceptance of commercially available wearable activity trackers among adults aged over 50 and with chronic illness: a mixed-methods evaluation. JMIR mHealth uHealth 4:e7, 2016.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Mozaffarian, D., E. J. Benjamin, A. S. Go, D. K. Arnett, M. J. Blaha, M. Cushman, S. R. Das, S. de Ferranti, J.-P. Després, H. J. Fullerton, V. J. Howard, M. D. Huffman, C. R. Isasi, M. C. Jiménez, S. E. Judd, B. M. Kissela, J. H. Lichtman, L. D. Lisabeth, S. Liu, R. H. Mackey, D. J. Magid, D. K. McGuire, E. R. Mohler, C. S. Moy, P. Muntner, M. E. Mussolino, K. Nasir, R. W. Neumar, G. Nichol, L. Palaniappan, D. K. Pandey, M. J. Reeves, C. J. Rodriguez, W. Rosamond, P. D. Sorlie, J. Stein, A. Towfighi, T. N. Turan, S. S. Virani, D. Woo, R. W. Yeh, and M. B. Turner. Heart disease and stroke statistics—2016 update. A report from the American Heart Association. Circulation 133:e38–e360, 2016.

    Article  PubMed  Google Scholar 

  32. Nijm, G., S. Swiryn, A. Larson, and A. Sahakian. Extraction of the magnetohydrodynamic blood flow potential from the surface electrocardiogram in magnetic resonance imaging. Med. Biol. Eng. Comput. 46:729–733, 2008.

    Article  PubMed  Google Scholar 

  33. Oster, J., R. Llinares, S. Payne, Z. T. H. Tse, E. J. Schmidt, and G. D. Clifford. Comparison of three artificial models of the magnetohydrodynamic effect on the electrocardiogram. Comput. Methods Biomech. Biomed. Eng. 1–18, 2014.

  34. Panescu, D. Emerging technologies [wireless communication systems for implantable medical devices]. IEEE Eng. Med. Biol. Mag. 27:96–101, 2008.

    Article  PubMed  Google Scholar 

  35. Rendell, M. S., B. K. Milliken, M. F. Finnegan, D. A. Finney, and J. C. Healy. The skin blood flow response in wound healing. Microvasc. Res. 53:222–234, 1997.

    Article  CAS  PubMed  Google Scholar 

  36. Righter, W. H., A. J. Nicoll, and H. L. Kennedy. Portable, multi-channel ECG data monitor/recorder. Google Patents, 1994.

  37. Righter, W. H. Portable ECG monitor/recorder. Google Patents, 1993.

  38. Segura-Juárez, J. J., D. Cuesta-Frau, L. Samblas-Pena, and M. Aboy. A microcontroller-based portable electrocardiograph recorder. IEEE Trans. Biomed. Eng. 51:1686–1690, 2004.

    Article  PubMed  Google Scholar 

  39. Shojaei-Baghini, M., R. K. Lai, and D. K. Sharma. A low-power and compact analog CMOS processing chip for portable ECG recorders. In: Asian Solid-State Circuits Conference, 2005, IEEE, 2005, pp. 473–476.

  40. Sowers, J. R., M. Epstein, and E. D. Frohlich. Diabetes, hypertension, and cardiovascular disease an update. Hypertension 37:1053–1059, 2001.

    Article  CAS  PubMed  Google Scholar 

  41. Taheri, B. A., R. T. Knight, and R. L. Smith. A dry electrode for EEG recording. Electroencephalogr. Clin. Neurophysiol. 90:376–383, 1994.

    Article  CAS  PubMed  Google Scholar 

  42. Togawa, T., O. Okai, and M. Oshima. Observation of blood flow EMF in externally applied strong magnetic field by surface electrodes. Med. Biol. Eng. Comput. 5:169–170, 1967.

    Article  CAS  Google Scholar 

  43. Tse, Z., C. L. Dumoulin, G. D. Clifford, J. Schweitzer, L. Qin, J. Oster, M. Jerosch-Herold, R. Y. Kwong, G. Michaud, W. G. Stevenson, and E. J. Schmidt. A 1.5T MRI-conditional 12-lead electrocardiogram for MRI and intra-MR intervention. Magn. Reson. Med. 71:1336–1347, 2013.

    Article  Google Scholar 

  44. Weissler, A. M., R. G. Peeler, and W. H. Roehll, Jr. Relationships between left ventricular ejection time, stroke volume, and heart rate in normal individuals and patients with cardiovascular disease. Am. Heart J. 62:367–378, 1961.

    Article  CAS  PubMed  Google Scholar 

  45. West, D. M., and E. A. Miller. Digital medicine: health care in the Internet era. Washington, DC: Brookings Institution Press, 2009.

    Google Scholar 

  46. Wu, K. J., T. S. Gregory, C. Reader, B. Leitmann, A. Huffines, S. Donovan, L. Mosteller, J. R. Murrow, and Z. T. H. Tse. Smartphone-enabled flow-monitoring device for peripheral artery disease. J. Med. Dev. 10:020958, 2016.

    Article  Google Scholar 

  47. Yazdandoost, K. Y., and R. Kohno. Wireless communications for body implanted medical device. In: Microwave Conference, 2007. APMC 2007. Asia-Pacific, 2007, pp. 1–4.

  48. Zywietz, C., G. Wagner, and B. Scherlag. Sampling rate of ECGs in relation to measurement accuracy. In: Computerized Interpretation of the Electrocardiogram. New York: Engineering Foundation, 1986, pp. 122–125.

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Acknowledgments

The initial design for the proposed system was developed by senior design team members Kevin Wu, Sheila Donovan, Augustus Huffines, Bobby Leitmann, Luke Mosteller, and Charles Reeder. This research was supported by a NSF I-Corps Grant (#1617340) and a UGA Clinical and Translational Research Unit Grant.

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Correspondence to Zion Tsz Ho Tse.

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Associate Editor Agata A. Exner oversaw the review of this article.

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Wu, K.J., Gregory, T.S., Lastinger, M.C. et al. Magnetohydrodynamic Voltage Recorder for Comparing Peripheral Blood Flow. Ann Biomed Eng 45, 2298–2308 (2017). https://doi.org/10.1007/s10439-017-1878-5

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  • DOI: https://doi.org/10.1007/s10439-017-1878-5

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