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Dvornik, O. V.

Publications and source records attributed to Dvornik, O. V..

2 recordsLinked to original sources

"Devil's stairs", Poisson's Statistics, and Patient Sorting via Variabilities for Oxygenation: All from Arterial Blood Gas Data

This report deals with arterial oxygen saturation (SaO2) for healthy adults. A comparably small data set (20 persons) holds 3-minute records of SaO2. The sample rate was 200 Hz. The charts have the looks of a "devils stairs." A few (from 1 to 10) detectable oxygenation levels form the stairs treads, more or less long. "The risers" have two types (up and down), and all have virtually the same height, about 1 %. The inter-level shifts ( 0 to 42 switches per record) turned out a rare event at the actual sample rate. The number of switchings meets the Poisson distribution. There were found three visibly varied intensities for the switch-overs within the data set. Histograms also show the co-existing of no fewer than three subsets into the data set. The subsets differ by the intensity of switch-overs, amounts of possible levels, relative frequencies of most probable levels (modes), etcetera. In short, those all are diverse variability quantifiers. The higher variability subset has about 25 %, the lower one - 45%.

bioinformatics↗

Humans postural sways: non-Gauss, variability, and aging aspects of a data set mining

This report presents the results of data mining of a sample with two focus-groups. They have the same sizes: seven people into each one, random-wise picked up from the same data set. The trials of groups were idem. The postural swings, that is, the move of the center-of-pressure (COP), were recorded. Maple, a computer math system, has allowed us to apply the Principal Components Analysis, Statistical analysis, Kernel Density Estimations (KDE) for the probabilities. Poincare and Recurrence Plots were other tools for modern data mining. The non-Gauss features of the real distributions are not that to be neglect. They exist not only as outliers but as sharp kurtosis and skewness. Still, they are so far not enow to grave doubts to the Fractional Brownian model. We found some subtle aging hallmarks for focus-groups. First, the trend of variability descriptors to be bi-modal is sheerer for the older group. Second, the coefficients of correlations of the short-time variability index with other descriptors are clear age-related. 2012 ACM Subject ClassificationApplied computing [->] Life and medical sciences [->] Health informatics

bioinformatics↗