Abstract
In this paper, we develop a novel application of independent component analysis (ICA) based auto-regression forecasting model(ICA-ARF). The method can noninvasively, continuously and conveniently derive ambulatory blood pressure (ABP) from the radial artery pressure waveform (RAPWF). To eliminate the effect of correlative factors in measurement, the ICA method is used to decomposite the raw signal and extract the independent component affected by blood pressure (BP). Based on the spectrum density of independent component, an auto-regression forecasting model is set up to derive BP. Experimental results show an excellent correlation and agreement with the BP measured by Omron electronic BP monitor (Type: HEM-7012). If the ICA-ARF is used, the the error can be reduced from 7.4mmHg to 2.55mmHg.
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He, L., Chen, Z., Zhang, Z. (2014). A Novel Method to Derive Ambulatory Blood Pressure from the Radial Pressure Waveform. In: Pan, L., Păun, G., Pérez-Jiménez, M.J., Song, T. (eds) Bio-Inspired Computing - Theories and Applications. Communications in Computer and Information Science, vol 472. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45049-9_28
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DOI: https://doi.org/10.1007/978-3-662-45049-9_28
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-45048-2
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