Linear and nonlinear analyses of normal and fatigue heart rate variability signals for miners in high-altitude and cold areas

Abstract Background and Objective Fatigue is an important cause of operational errors, and human errors are the main cause of accidents. This study is an exploratory study in China. Field tests were conducted on heart rate variability (HRV) parameters and physiological indicators of fatigue among miners in high-altitude, cold and low-oxygen areas. This paper studies heart activity patterns during work fatigue in miners. Methods Fatigue affects both the sympathetic and parasympathetic nervous systems, and it is expressed as an abnormal pattern of HRV parameters. Thirty miners were selected as subjects for a field test, and HRV was extracted from 60 groups of electrocardiography (ECG) datasets as basic signals for fatigue analysis. Then, we analysed the HRV signals of the miners using linear (time domain and frequency domain) and nonlinear dynamics (Poincare plot and sample entropy (SampEn)), and a Pearson's correlation coefficient analysis and t-tests were performed on the measured indices. Results The results showed that the time-domain indices (SDNN, RMSSD, SDSD, pNN50, RRn, heart rate (HR), R-wave humps (RH)) and the coefficient of variation (CV)) and the frequency-domain indices (low frequency/high frequency (LF/HF), LFnorm and HFnorm) clearly changed after fatigue. These features were selected using a Poincare plot, sample entropy, Pearson's correlation coefficient and a t-test for further analysis. The fatigue characteristics and sensitivity parameters of miners in a high-altitude, cold and hypoxic environment were obtained. Conclusions This study provides deep insight into the use of linear and nonlinear fatigue characteristics to effectively and reliably identify miner fatigue. Furthermore, the study provides a reference for clinical studies of acute mountain sickness in high-altitude, cold and hypoxic environments.