Abstract
Nowadays medical equipment makes possible performing tests by patients themselves. These tests are usually health parameter measurements, like a glucose level or blood pressure. Though they are rather regularly performed, they are hardly used in patient’s state monitoring. These measurements are not suitable for interpretation by means of time series as they include few values and they are strongly influenced by actual living conditions or habits. The paper suggests an interpretation of series of measurements by means of fuzzy sets and next using a similarity measure of membership functions to disclose tendencies in the parameters’ change. It is shown for data available in the Internet that the proposed method can be used even for series of few measurements and that information extracted in such a way is qualitatively different from the classical method of moving average. The method can be used for multi-criteria self-monitoring of a patient, in future.
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This research was supported by statutory funds of the Institute of Electronics, Silesian University of Technology.
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Straszecka, E., Pander, T. (2021). Possible Use of Fuzzy Sets Similarity for Patient’s Parameters Observation. In: Atanassov, K., et al. Uncertainty and Imprecision in Decision Making and Decision Support: New Challenges, Solutions and Perspectives. IWIFSGN 2018. Advances in Intelligent Systems and Computing, vol 1081. Springer, Cham. https://doi.org/10.1007/978-3-030-47024-1_11
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DOI: https://doi.org/10.1007/978-3-030-47024-1_11
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