Using Time Series for Biomedical Signal Processing Under Uncertainties

The paper presents analysis of time series usage for the evaluation of biological systems’ functioning with a specific emphasis on applications in aviation and human factors. Analysis of the functional state of aviation operators is an important component of aviation safety. The paper concentrates on the visualization of the functional activity and dynamics of the organism as a biological system based on time data. Through the employment of recurrent plots, the identification of properties and mechanisms inherent to the biological system generating these series is facilitated. Changes in the state of the biological system are discernible by analyzing the visual structures of these plots, both topological and structural, thereby diminishing the informational uncertainty regarding the state of the biological object and supplementing it with an informative component. The nature of processes occurring within the biological system is indicated by the appearance of the recurrent plots, revealing the presence and impact of noise, states’ repetition and stagnation (laminarity), and the occurrence of abrupt state changes (extreme events). The stability of entire biological system functioning is assessable through the variability of heart rate, employing retrospective data for forecasting purposes. The necessity for intelligent analysis of biomedical data, particularly heart rate variability, in aviation contexts, is underscored by this analysis. The results of this study, employing multi-axis recurrence methods for the analysis of signals (time series) from the human cardiovascular system, are elucidated, providing crucial insights into human factors in aviation safety and performance.