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Fuzzy Filtering for Physiological Signal Analysis
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DOI：10.1109/TFUZZ.2009.2038709.png)
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This study suggests the use of fuzzy-filtering algorithms to deal with the uncertainties associated to the analysis of physiological signals. The signal characteristics, for a given situation or physiological state, vary for an individual over time and also vary among the individuals with the same state. These random variations are due to the several factors related to the physiological behavior of individuals, which cannot be taken into account in the interpretation of signal characteristics. Our approach is to reduce the effect of random variations on the analysis of signal characteristics via filtering out randomness or uncertainty from the signal using a nonlinear fuzzy filter. Afuzzy-filtering algorithm, which is based on a modification of filtering algorithm of Kumar et al. [ M. Kumar, N. Stoll, and R. Stoll, IEEE Trans. Fuzzy Syst., vol. 17, no. 1, pp. 150-166, Feb. 2009], is proposed for an improved performance. The method is illustrated by studying the effect of head-up tilting on the heart-rate signal of 40 healthy subjects.
Keyword:
Features extraction
fuzzy filtering
head-up tilt (HUT) test
physiological signals
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11.9
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