Hypotension Investigation, Prospective Clinical Study

  • Ian Piper Southern General Hospital, Clinical Physics, Glasgow, Scotland
  • Alfonsas Vainoras Kaunas University of Technology and Lithuanian University of Health Sciences, Kaunas, Lithuania
  • Kristina Berskiene Kaunas University of Technology and Lithuanian University of Health Sciences, Kaunas, Lithuania
  • Rimtautas Ruseckas
  • Vidmantas Jurkonis
  • Liepa Bikulciene
  • Zenonas Navickas Kaunas University of Technology, Kaunas
  • Dovile Karaliene
  • Arminas Ragauskas Kaunas University of Technology, Kaunas, Lithuania
  • Mantas Deimantavicius
Keywords: Hypotension physiology, time series, Hankel atrices, rank, complexity profile.

Abstract

Hypotension occurring in the initial phase of resuscitation is significantly associated with increased mortality following brain injury, even when episodes are relatively short. A large amount of data exists in health care systems providing information on the major health indicators of patients in hospitals. It is believed that if enough of these data could be drawn together and analysed in a systematic way, then a system could be built that will trigger an alarm predicting the onset of a hypotensive event. In the paper the mathematical information algorithm based on the concept of the rank of a sequence is presented. For the analysis of hypotension physiology an application of a new algebraic method is proposed for real world time series analysis. Numerical experiments with a hypotension crisis prevention using arterial blood pressure time series are used to illustrate the potential of the proposed method. The algorithm for finding ranks of a sequence of the ECG parameters is presented in the paper in order to show complexity profiles. Experimental results show that presented in this paper method also can be used together with other hypotension prediction methods.

DOI: http://dx.doi.org/10.5755/j01.eie.22.2.13454

Published
2016-04-12
Section
ELECTRONIC MEASUREMENTS