## 2 Materials and Methods
### Data Collection and Pre-Processing
These times were recorded by means of SW which was part of the measurement system, based on the instructions from the instructor. Consequently, apart form RR interval time-series, the data contained also timestamps delimiting individual manoeuvres. Processing of such short RR interval time-series would significantly limit further analysis and options for data processing, e.g., by means of spectral analysis. Therefore, the processed time-series was extended to 210 s with respect to manoeuvre duration, i.e., if the manoeuvre initial time (\(t_{MS}\)) and end time (\(t_{ME}\)) are known, then the initial time (\(t_{NS}\)) and end time (\(t_{NE}\)) of the evaluated interval are given as:  
\[t_{NS}=t_{MS}-\frac{210-(t_{ME}-t_{MS})}{2}, \tag{1}\]  
\[t_{NE}=t_{ME}+\frac{210-(t_{ME}-t_{MS})}{2}, \tag{2}\]  
where all times are in seconds. The selection of such modified time interval was due to HRV matrices and norms for ultra-short term measurements [32; 33]. From these time-series, selected HRV indices were calculated. The selection of parameters used in this study was done considering the signal length. In general, a signal of a minimum 300 s is required for HRV indicies calculation, which is considered a gold standard for short-term recordings [28; 34; 35]. In case of shorter signals, such as in this study, it was not appropriate to use some standard parameters. Studies dealing with suitability of standard HRV parameters for shorter signals (ultra-short term recordings) essentially agree in one parameter of time analysis--root mean square of successive RR interval differences (RMSSD) [36; 37]. Usability of other parameters is at least arguable. In the case of standard deviation of NN intervals (SDNN, NN interval is synonymous for the RR interval) there are studies discouraging or not recommending its usage for ultra-short term recordings [37], but these studies work with 10 s records. Other studies indicate the possibility of its usage. [PERSON] and [PERSON] show high reproducibility between 150 s and 300 s signals [38]. Similar results are also presented by [PERSON] et al. for signals longer than 120 s [35]. Other parameters were discussed as rather not suitable for ultra-short term recordings, i.e., for the purpose of this study [39]. Descriptive statistics appeared also suitable. Most often, mean RR interval (Mean RR) parameter is used. This parameter seems also applicable for short-term recordings [34; 38; 39]. From other approaches, frequency analysis of RR intervals time-series is typically used. From the perspective of this analysis, HF (power spectral density at high-frequency band, 0.18-0.4 Hz) parameter appears the most suitable for ultra-short record [34]. Its standalone utilization, however, is not effective. In the case of LF (power spectral density at low-frequency band, 0.06-0.10 Hz) parameter, and the most important parameter--the LF/HF ratio, some studies indicate effectiveness from 120-150 s of record [28; 38]. By contrast, there are studies pronouncing frequency analysis unsuitable for ultra-short records and accept only the standard of 300 s as the minimal record length [40]. Due to this, frequency analysis was not considered in this study. For the purpose of ultra-short term heart rate variability (HRV) in the time domain, two parameters--RMSSD and SDNN--were calculated based on the RR intervals. Further, mean RR interval value (Mean RR) was computed. RMSSD parameter served the description of autonomic nervous system (ANS), consequently used as index of cardiac vagal control [41]. RMSSD value reflects the deviation between two heart rhythms, being the time domain measure for short-term variability monitoring, and heart rhythm high-frequency fluctuations [41; 42]. Calculation of RMSSD follows the knowledge of individual RR intervals (ms) with subsequent calculation of the squared difference of two consecutive RR intervals.