Non-Intrusive Device for Real-Time Circulatory System Assessment with Advanced Signal Processing Capabilities
By: E. Pinheiro, O. Postolache and P. Girão
Open Access
|Dec 2010References
- Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. (1996). Heart rate variability - standards of measurement, physiological interpretation, and clinical use., 93 (5), 1043-1065.
- Parati, G., Saul, J. P., Rienzo, M. D., Mancia, G. (1995). Spectral analysis of blood pressure and heart rate variability in evaluating cardiovascular regulation: a critical appraisal., 25, 1267-1286.
- Berntson, G., Cacciopo, J., Quigley, K., Fabro, V. (1994). Autonomic space and psychophysiological response., 31 (1), 44-61.
- Dawson, S. L., Manktelow, B. N., Robinson, T. G., Panerai, R. B., Potter, J. F. (2000). Which parameters of beat-to-beat blood pressure and variability best predict early outcome after acute ischemic stroke?, 31, 463-468.
- American College of Cardiology Cardiovascular Technology Assessment Committee. (1993). Heart rate variability for risk stratification of life-threatening arrhythmias., 22, 948-950.
- Postolache, O., Girão, P. S., Postolache, G. (2007). New approach on cardiac autonomic control estimation based on BCG processing. InVancouver, Canada, IEEE, 876-879.
- Postolache, O., Postolache, G., Girão, P. (2007). New device for assessment of autonomous nervous system functioning in psychophysiology. InWarsaw, Poland, IEEE, 1-5.
- Pinheiro, E. C., Postolache, O. (2008). Heart rate variability virtual sensor application in blood pressure assessment system. InInnsbruck, Austria, Acta Press, 79-82.
- Muehslteff, J., Espina, J., Alonso, M., Aubert, X., Falck, T. (2008). Wearable body sensor network for continuous context-related pulse arrival time monitoring. InInnsbruck, Austria, Acta Press, 378-383.
- Geddes, L. A., Voelz, M., James, S., Reiner, D. (1981). Pulse arrival time as a method of obtaining systolic and diastolic blood pressure indirectly., 19, 671-672.
- Ma, T., Zhang, Y. T. (2005). A correlation study on the variabilities in pulse transit time, blood pressure, and heart rate recorded simultaneously from healthy subjects. InShanghai, China, IEEE, 996-999.
- Chen, W., Kobayashi, T., Ichikawa, S., Takeuchi, Y., Togawa, T. (2000). Continuous estimation of systolic blood pressure using the pulse arrival time and intermittent calibration., 38 (5), 569-574.
- Sugo, Y., Tanaka, R., Soma, T., Kasuya, H., Sasaki, T., Sekiguchi, T., Hosaka, H., Ochiai, R. (1999). Comparison of the relationship between blood pressure and pulse wave transit times at different sites. InAtlanta, USA, IEEE, 222.
- Steptoe, A., Smuylan, H., Gribbin, B. (1976). Pulse wave velocity and blood pressure change: calibration and applications., 13 (5), 488-493.
- Gribbin, B., Steptoe, A., Sleight, P. (1976). Pulse wave velocity as a measure of blood pressure change., 13 (1), 86-90.
- Espina, J., Falck, T., Muehlsteff, J., Aubert, X. (2006). Wireless body sensor network for continuous cuff-less blood pressure monitoring. InBoston, USA, IEEE, 11-15.
- Pinheiro, E. C., Postolache, O., Girão, P. (2009). Pulse arrival time and ballistocardiogram application to blood pressure variability estimation. InCetraro, Italy, IEEE, 132-135.
- Kiu, Y., Poon, C., Zhang, Y. (2008). A hydrostatic calibration method for the design of wearable PAT-based blood pressure monitoring devices. InVancouver, Canada, IEEE, 1308-1310.
- Skinner, J., Anchin, J., Weiss, D. (2008). Nonlinear analysis of the heartbeats in public patient ECGs using an automated PD2i algorithm for risk stratification of arrhythmic death., 4 (2), 549-557.
- Yeragani, V. K., Srinivasan, K., Vempati, S., Pohl, R., Balon, R. (1993). Fractal dimension of heart rate time series: an effective measure of autonomic function., 75 (6), 2429-2438.
- Skinner, J., Pratt, C., Vybiral, T. (1993). A reduction in the correlation dimension of heartbeat intervals precedes imminent ventricular fibrillation in human subjects., 125 (3), 731-743.
- Vybiral, T., Skinner, J. (1993). The point correlation dimension of R-R Intervals predicts sudden cardiac death among high-risk patients. In, London, UK, IEEE, 257-260.
- Storella, R., Wood, H., Mills, K., Kanters, J., Højgaard, M., Holstein-Rathlou, N. (1998). Approximate entropy and point correlation dimension of heart rate variability in healthy subjects., 33 (4), 315-320.
- Yeragani, V., Sobolewski, E., Jampala, V., Kay, J., Yeragani, S., Igel, G. (1998). Fractal dimension and approximate entropy of heart period and heart rate: awake versus sleep differences and methodological issues., 95 (3), 295-301.
- Perkiömäki, J., Mäkikallio, T., Huikuri, H. (2005). Fractal and complexity measures of heart rate variability., 27 (2-3), 149-158.
- Richman, J., Moorman, J. (2000). Physiological time-series analysis using approximate entropy and sample entropy., 278 (6), 2039-2049.
- Rosso, O., Martin, M., Figliola, A., Keller, K., Plastino, A. (2006). EEG analysis using wavelet-based information tools., 153 (2), 163-182.
- Lunak, D. R., Bryngelson, R. S. (2006).U. S. Patent No. 7,052,465. Washington, D. C.: U. S. Patent and Trademark Office.
- Foo, J. Y. A., Lim, C. S. (2006). Pulse transit time as an indirect marker for variations in cardiovascular related reactivity., 14 (2), 97-108.
- Muehlsteff, J., Aubert, X., Schuett, M. (2006). Cuffless estimation of systolic blood pressure for short effort bicycle tests: the prominent role of the pre-ejection period. InNew York, USA, IEEE, 5088-5092.
- Payne, R. A., Symeonides, C. N., Webb, D. J., Maxwell, S. R. J. (2006). Pulse transit time measured from the ECG: an unreliable marker of beat-to-beat blood pressure., 100, 136-141.
- Pinheiro, E. C., Postolache, O., Girão, P. (2010). Theory and developments in an unobtrusive cardiovascular system representation: Ballistocardiography., 4, 201-216.
- Schroeder, M. (1991).New York, USA: W. H. Freeman.
- Costa, M., Goldberg, A. L., Peng, C. K. (2002). Multiscale entropy analysis of complex physiologic time series., 89 (6), 021906.
- Pincus, S. M. (1991). Approximate entropy as a measure of system complexity., 88, 2297-2301.
- Richman, J. S., Moorman, J. R. (2000). Physiological time-series analysis using approximate entropy and sample entropy., 278 (6), 2039-2049.
- Goldberger, A. L., Peng, C. K., Lipsitz, L. A. (2002). What is physiologic complexity and how does it change with aging and disease?, 23 (1), 23-26.
- Lekkala, J., Paajane, M. (1999). EMFi - new electret material for sensors and actuators. InDelphi, Greece, IEEE, 743-746.
- Strong, P. (1970).Beaverton, USA: Tektronix.
- Pinheiro, E. C., Postolache, O., Girão, P. (2010). Automatic wavelet detrending benefits to the analysis of cardiac signals acquired in a moving wheelchair. InBuenos Aires, Argentina, IEEE, 602-605.
DOI: https://doi.org/10.2478/v10048-010-0029-z | Journal eISSN: 1335-8871
Language: English
Page range: 166 - 175
Published on: Dec 21, 2010
Published by: Slovak Academy of Sciences, Institute of Measurement Science
In partnership with: Paradigm Publishing Services
Publication frequency: Volume open
Keywords:
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© 2010 E. Pinheiro, O. Postolache, P. Girão, published by Slovak Academy of Sciences, Institute of Measurement Science
This work is licensed under the Creative Commons License.