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Principal Component Analysis, Quantifying, and Filtering of Poincaré Plots for time series typal for E-health

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Health Informatics: A Computational Perspective in Healthcare

Part of the book series: Studies in Computational Intelligence ((SCI,volume 932))

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Abstract

This study deals with Poincaré Plots, which go a handy tool for visualizing and probing signals and records in medicine and E-health. The Poincaré Plot is a kind of recurrence graph as well as a scatter chart. It is also an embedding of a time series into 2D-space. We revised here the time-tested “ellipse fitting technique,” a popular method of the quantifying of Poincaré Plots, within more general Principal Components Analysis. The “ellipse fitting” turned out a simplified option of the Principal Components Analysis. We have framed the central approximation of the “ellipse fitting” and given the numeric gage of its reality. We have offered a new way of filtering the signal within Principal Components Analysis. At last, we have tested the abilities of both theories in case studies. The typal series for E-health were in use: a short series of ambulatory blood pressure tests and a more extended one for self-monitoring of blood glucose. The accuracy of the numeric descriptors of Poincaré Plots is almost the same with both theories. Still, the “ellipse fitting” may give a notable fault for the direction of the first Principal Component. Filtered Poincaré Plots keep the shapes of its originals, the descriptors’ values, and the fractal scaling law. However, the fractal dimension is a bit drop after the filtering.

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Authors and Affiliations

  1. Petro Mohyla Black Sea National University, 68 Desantnikov St., 10, Mykolayiv, 54003, Ukraine

    Gennady Chuiko, Olga Dvornik, Yevhen Darnapuk & Yaroslav Krainyk

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  1. Gennady Chuiko
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  2. Olga Dvornik
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  3. Yevhen Darnapuk
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  4. Yaroslav Krainyk
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Correspondence to Gennady Chuiko .

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Editors and Affiliations

  1. Department of Computer Science and Engineering, National Institute of Technology Silchar, Silchar, Assam, India

    Ripon Patgiri

  2. Department of Computer Science and Engineering, National Institute of Technology Silchar, Silchar, Assam, India

    Anupam Biswas

  3. Department of Computer Science and Engineering, National Institute of Technology Silchar, Silchar, Assam, India

    Pinki Roy

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Chuiko, G., Dvornik, O., Darnapuk, Y., Krainyk, Y. (2021). Principal Component Analysis, Quantifying, and Filtering of Poincaré Plots for time series typal for E-health. In: Patgiri, R., Biswas, A., Roy, P. (eds) Health Informatics: A Computational Perspective in Healthcare. Studies in Computational Intelligence, vol 932. Springer, Singapore. https://doi.org/10.1007/978-981-15-9735-0_4

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