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The development of software for automated analysis of CGMS signals and electronic diaries

Keywords:

E.A. Pustozerov - Post-graduate Student, Assistant, Department of Biotechnical Systems, Saint Petersburg Electrotechnical University «LETI» E-mail: pustozerov.e@gmail.com P.V. Porova - Ph.D. (Med.), Head of a Laboratory, Federal Almazov North-West Medical Research Centre (St. Petersburg) E-mail: pvpopova@ya.ru Ya.A. Bolotko - Junior Research Scientist, Federal Almazov North-West Medical Research Centre (St. Petersburg) E-mail: yanabolotko@gmail.com Z.M. Yuldashev - Dr.Sc. (Eng.), Professor, Head of Department of Biotechnical Systems, Saint Petersburg Electrotechnical University «LETI» E-mail: yuld@mail.ru


The paper presents the development of the software for CGMS signals and electronic diaries data processing. Current software al-lows automatic matching and analysis of the data derived from CGMS signals and electronic diaries, interdependence analysis for different factors and blood glucose response and data representation in the form, convenient for the doctor, which should afford assistance in diabetes treatment. The structure of the system includes patient’s mobile device with pre-installed special software, which allows the user to keep a diary and forward it to the centralized server, continuous blood glucose monitoring system, which signals are also forwarded to the server and server software, which processes and presents the data. Server software performs initial signal processing and matching of diary records on different types of events related to peaks on BG signal (including food consumption, insulin injections, physical activity, sleep and urine ketones levels), data structuring and analysis as well as data representation in the form of standardized tables and graphs. In the following work additional software modules for more complex data analysis with machine learning techniques will be developed.
References:

 

  1. Popova P.V., Gerasimov A.S., Kravchuk E.N., Rjazanceva E.M., Cojj U.A., Dronova A.V., Nikolaeva P.A., Grineva E.N. Faktory riska gestacionnogo sakharnogo diabeta i ikh ispolzovanie s celju rannego ego vyjavlenija // Problemy zhenskogo zdorovja. 2013. T. 8. № 1. S. 5-11.
  2. Pustozerov E.A., JUldashev Z.M. Distancionnyjj monitoring sostojanija bolnykh sakharnym diabetom // Medicinskaja tekhnika. 2014. № 2. S. 15-18.
  3. Zeevi D. et al. Personalized Nutrition by Prediction of Glycemic Responses // Cell. 2015. V. 163. № 5.  R. 1079-1094.
  4. Pustozerov E.A., JUldashev Z.M. Sistema mHealth dlja informacionnojj podderzhki bolnogo sakharnym diabetom // Biotekhnosfera. 2013. № 1(25). S. 39-44.
  5. Tanenberg R., Bode B., Lane W., et al. Use of the Continuous Glucose Monitoring System to guide therapy in patients with insulin-treated diabetes: a randomized control trial // Mayo Clin Proc. 2004. V. 79. № 12. R. 1521-1526.
  6. Pustozerov E.A, Popova P.V. Mobilnoe prilozhenie dlja ocenki pishhevogo raciona i profilja glikemii: vozmozhnosti i perspektivy. Transljacionnaja medicina // Tezisy. Vseross. konf. s mezhdunar. uchastiem «Komandnyjj podkhod v sovremennojj ehndokrinologii». Sankt-Peterburg. 2016. S. 43.

 

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