DOI: https://doi.org/10.31071/kit2017.13.07

Inventory reference

ISSN 1812-7231 Klin.inform.telemed. Volume 12, Issue 13, 2017, Pages 53–63

Author(s)

Mayorov O. Yu.

Institution(s)

Kharkiv Medical Academy of Postgraduate Education

Institute of Medical Informatics and Telemedicine, LTD (Kharkiv)

Research Institute for Children and Adolescents Health Protection of the National Academy of Medical Sciences of Ukraine (Kharkiv)

Article title

Searching for methods for quantitative assessment of individual resistance to emotional stress in the norm and in pathology based on the analysis of heart rate variability. Factor model.

Abstract (resume)

Introduction: To diagnose the individual's resistance to emotional stress, quantitative assessment of not only the state of individual target-organs (heart, stomach, etc.) is necessary, but also systems that control the process of adaptation of the organism in the same conflict situations.

Objective of the study: Creation of a factor model based on heart rate variability (HRV).

Materials and methods: 129 practically healthy test subjects, male, 15-18 years old. To illustrate the effectiveness of the method, patients with dyslipoproteinemia (DLP) (53 patients) were used from a group of high risk for the development of atherosclerosis. Models of emotional stress: "anticipation stress" and "insuperable conflict situation" on the basis of unsuccessful operational activities.

Results. The technique of intellectual identification of R-peaks taking into account artifacts in conditions of free behavior is presented. The technique of interpolation correction of recording of RR-intervals with cardiac rhythm disturbances for subsequent correct correlation and spectral analysis is proposed. The shortcomings of the popular secondary HRV indices are analyzed. Noise-resistant secondary indices of HRV are presented: "anxiety index" (AI) and "type of anxiety reaction" (TARI), their physiological interpretation is substantiated. The necessity of creating new methods of nonlinear analysis for estimating fractal components of HRV is proved. It is a method of global reconstruction of dynamic HRV system and application of the local index of fractality in the analysis of short RR interval series in the assessment of heart rate variability.

Conclusion. A factor model of HRV parameters was developed and a physiological interpretation of the identified three main factors was given. Changes in the magnitude of isolated factors in a state of calm wakefulness and under conditions of modeling emotional stress in healthy subjects and patients with dyslipoproteinemia (DLP) were analyzed. The effectiveness of the proposed method is shown.

Keywords

emotional stress, individual resistance, heart rate variability (HRV), factor analysis

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