2.6. HRV Calculation
This protocol is extracted from research article:
Can Heart Rate Variability (HRV) Be Used as a Biomarker of Thermal Comfort for Mine Workers?
Int J Environ Res Public Health, Jul 17, 2021; DOI: 10.3390/ijerph18147615

The HRV is usually analyzed by the time-domain method, spectral-domain method and nonlinear method. In this study, three methods were utilized to calculate the HRV indices summarized in Table 3. The time-domain HRV indices are easy to compute and simple. They can describe the beat-to-beat variability by using statistical techniques. In this group, the R-R interval and SDNN are the basic parameters of HRV. The R-R interval may be considered worthy of further study as an objective indication of the effect on people of the external environment [24]. It has relatively distinct discrimination between different cold and hot environments [18]. The SDNN is the standard deviation of the NN interval, which is the simplest variable of the HRV. The RMSSD represents the square root of the mean squared differences between successive RR intervals. The pNN20 represents the percentage of the RR consecutive pairs that differ by 20 milliseconds. The RMSSD and pNN20 are the most commonly used measures of heart rate interval difference, which estimate the high-frequency changes of heart rate, so they are highly correlated. Unlike the time-domain method, the spectral-domain method provides a greater understanding of heartbeat variation by decomposing the ECG into fundamental frequency components. Five indices of the frequency domain analysis method were selected, namely, the LF, HF, VLF, total power (TP) and LF/HF. The LF (0.04–0.15 Hz) changes with the change of thermal environment, [25,32] the HF (0.15–0.4 Hz) is generally considered to be the origin of the vagus nerve. The LF/HF, the ratio of low frequency component to the high frequency component, reflects the balance between sympathetic and parasympathetic nerves. It also considers to be related to human thermal comfort [21,25,26,27]. The VLF refers to the power in the frequency band below 0.04 Hz, which is related to human body temperature regulation. The SampEN is the probability that two sequences match if a new sample is added to the sequence. The VLF and SampEN were considered a good index of human thermal sensation [18]. Therefore, it is feasible to use these indices to study the relationship between workers and the thermal comfort associated with to underground mining environment.

Short Description of the Selected HRV Indices.

Note: The above indices were based on the 5-min segments.

ECG data were recorded continuously during the experiment. For each environmental condition, the human body needs to adapt to changes in the thermal environment for a certain time. During the stages of sitting or running, ECG data from the 10th–15th and the 20th–25th min were extracted for HRV analysis. After the data acquisition, the ECG was imported into the ECG viewer software for visual inspection to confirm that the recorded waveform has relatively high signal quality. Based on the QRS detection module, R wave can be automatically detected to reduce noise, baseline drift and other components, highlight peak and smooth near the peak. The second round of visual examination was performed to remove the misidentified peaks and ectopic pulsations. We confirmed that no ectopic pulsation occurred in these subjects. Finally, the continuous RR interval data are more than 256. HRV indices were calculated by Kubios Hrv3.3, a professional software developed by the University of Kuobios, Kuopio, Finland. An advanced detrended method was included in Kubios HRV software to remove the non-stationarity of the RR interval time series. This method works like a time-varying high pass filter. The data was smoothed according to the value of smoothing parameters. The bigger the smoothing parameter is, the lower the cut-off frequency of the filter is. In this process, the cut-off frequency was below the low frequency band (<0.04 Hz), ensuring that no part of the normal short-term HRV was removed. The Fourier transform (FFT) method was employed to calculate the power spectral density (PSD) of the R-R interval sequence in the spectrum domain analysis. The spectrum bands of analysis included VLF ranging from 0.00 to 0.04 Hz, low-frequency power (LF) ranging from 0.04 to 0.15 Hz, and high-frequency power (HF) ranging from 0.15 to 0.4 Hz.

Note: The content above has been extracted from a research article, so it may not display correctly.



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