Data Analysis of Random Blood Measurements for Abnormal Condition Detection

Sokol, Yevgen, Shchapov, Pavel, Tomashevskyi, Roman, Veligorskyi, Oleksandr, Picking, Rich and Chakirov, Roustiam (2017) Data Analysis of Random Blood Measurements for Abnormal Condition Detection. In: 7th IEEE Int. Conference on Internet Technologies and Applications ITA-17, Wrexham, UK, 12-15 September 2017, Wrexham, UK.

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This paper discusses an approach of the abnormal condition detection of whole blood using piezo-synthetic effects in blood under dynamic external pressure. Three groups of samples having verified chemical and biological conditions were analysed to prove reliable detection: saline, whole blood and whole blood with colorectal cancer as an example of abnormal conditions. The procedure of a discrete differentiation process for obtained experimental data has been proposed as preliminary processing. Three information parameters have been selected to describe experimental data. Fischer F-statistics were used to determine the information content of the proposed information parameters. It has been proved that the proposed information parameters react on changing state of object under test and therefore can be effectively used for the abnormal condition detection.

Item Type: Conference or Workshop Item (Poster)
Divisions: Applied Science, Computing and Engineering
Depositing User: Hayley Dennis
Date Deposited: 19 Dec 2018 10:58
Last Modified: 19 Dec 2018 10:58

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