Elliptic Filter Based Noninvasive Blood Pressure Analyze with LabVIEW

Abstract

The blood in the vein is called blood pressure or tension. It depends on the amount of blood pumped by the heart
and the resistance of the vessels to this flow and the flexibility of the arterial walls. Very low values than
optimum blood pressure and very high values than normal blood pressure are important. With this aim,
Noninvasive Blood Pressure Analyze with LabVIEW offers an insight into us. LabVIEW is a graphical
programming language that uses a Dataflow model instead of sequential lines of text code. LabVIEW runs
principle of Data flow programming that allows multiple operations to work in parallel. So, designers spend less
time than a text based programming language. Application areas such as signal processing, image processing and
Data analysis are available. In this paper, LabVIEW- based Noninvasive Blood Pressure Analyze (NIBP) using
different Data and to obtain systolic/diastolic pressure. As a result of this, the current data are divided into
optimum blood pressure, normal blood pressure and prehypertension

Keywords

• Blood Pressure,Elliptic Filter,LabVIEW

References

1. 1. Ogedegbe, G.,, Pickering, T., (2010). Principles and techniques of blood pressure measurement. Cardiology Clinics. 28 (4), 571–586.
2. 2. Obrien, E., (2001). Blood pressure measurement is changing Heart. 85 (1): 3–5. doi:10.
3. 3. Materson, B.J., Garcia-Estrada, M.., Degraff, S.B., Preston, R.A., (2017). Prehypertension is Real and Can be Associated with Target Organ Damage, Journal of the American Society of Hypertension,doi.org/10.1016/j.jash.2017.09.005
4. 4. Kehtarnavaz, N, Mahotra, S., Digital Signal Processing Laboratory: LabVIEW-Based FPGA Implementation, pp.7.
5. 5. Aydın, S.G., Kaya, T., Güler, H., Wavelet-based study of valence–arousal model of emotions on EEG signals with LabVIEW, Brain Informatics, (3), pp.1-9.
6. 6. http://www.ni.com/white-paper/4752/en/
7. 7. Deshmukh, A., Gandole, Y., (2015). ECG Feature Extraction Using NI Lab-View Biomedical Workbench. International Journal of Recent Scientific Research 6(8), pp.5603-5607.
8. 8. Daniels, R.W., Approximation Methods for Electronic Filter Design. New York: McGraw-Hill.