Abstract
The paper is devoted to the algorithmic solution of quality control over the pneumatic blood pressure sensor positioning. Previously, this problem was solved by the operator based on his subjective assessment of the presence/absence of a pulse wave in the observed signal and its quality estimation. Recent studies have led us to a simple algorithm for automatically evaluating the accuracy of positioning. The algorithm is based on the value of the variability of the intervals of side peaks that the multiscale autocorrelation function can manifest as part of its structure. Since this value is closely related to such a characteristic of the signal as its quasi–periodicity, the algorithm essentially estimates the degree of periodicity of the signal, which is high in the presence of a pulse wave and small in its absence. In addition to the general principle of quasi–periodicity estimation much empirical information has been accumulated on the necessary preliminary normalization of the signal, the censorship of the side peaks to be considered, on the numerical values of the comparison thresholds, etc. The main ideas of the algorithm are illustrated by examples of processing real data obtained by positioning the developed pneumatic sensor.
The work is supported by the Russian Foundation for Basic Research (RFBR), grant N 18-29-02108 mk.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Antsiperov, V., Mansurov, G.: Wearable pneumatic sensor for non-invasive continuous arterial blood pressure monitoring. In: Rojas, I., Ortuño, F. (eds.) IWBBIO 2018. LNCS, vol. 10814, pp. 383–394. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-78759-6_35
Mansurov, G.K., et al.: Pneumatic sensor for continuous non-invasive measurement of arterial pressure. Invention patent RU2638712 (C1), bull 35, 15 December 2017
Mansurov, G.K., et al.: Monolithic three-chamber pneumatic sensor with integrated throttle channels for continuous non-invasive measurement of arterial pressure Invention patent RU2675066 (C1), bull 35, 14 December 2018
Antsiperov, V., Mansurov, G.: Positioning method for arterial blood pressure monitoring wearable sensor. In: Rojas, I., Valenzuela, O., Rojas, F., Ortuño, F. (eds.) IWBBIO 2019. LNCS, vol. 11465, pp. 405–414. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-17938-0_36
Antsiperov, V.: Multiscale correlation analysis of nonstationary signals containing quasi-periodic fragments. J. Commun. Technol. Electron. 53(1), 65–77 (2008). https://doi.org/10.1134/S1064226908010099
Hlawatsch, F., Auger, F. (eds.): Time-Frequency Analysis: Concepts and Methods. ISTE and Wiley, London (2008)
Jeong, J., Williams, W.J.: Kernel design for reduced interference distributions. IEEE Trans. Signal Process. 40(2), 402–412 (1992). https://doi.org/10.1109/78.124950
Antsiperov, V.E., Mansurov, G.K.: Arterial blood pressure monitoring by active sensors based on heart rate estimation and pulse wave pattern prediction. Pattern Recogn. Image Anal. 26(3), 533–547 (2016). https://doi.org/10.1134/S1054661816030019
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Antsiperov, V., Mansurov, G. (2020). Positioning Algorithm for Arterial Blood Pressure Pneumatic Sensor. In: Rojas, I., Valenzuela, O., Rojas, F., Herrera, L., Ortuño, F. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2020. Lecture Notes in Computer Science(), vol 12108. Springer, Cham. https://doi.org/10.1007/978-3-030-45385-5_13
Download citation
DOI: https://doi.org/10.1007/978-3-030-45385-5_13
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-45384-8
Online ISBN: 978-3-030-45385-5
eBook Packages: Computer ScienceComputer Science (R0)