1.Evaluation of flight training progress using frequency-domain HRV parameters Presentation prepared for 57th International Congress of Space and Aviation Medicine by Zagreb Croatia 06-10 September 2009 Olaf Truszczynski Lukasz Dziuda Krzysztof Rozanowski Franciszek Skibniewski Mariusz Krej

2. Slide - - Introduction Fatigue and decrease in operational efficiency during flights pose a serious problem both in military and civil aviation. This can be observed not only in the case of pilots carrying out long-lasting flights and flight missions but also during short yet intensive missions. It can cause a loss of situational awareness, especially in pilots operating helicopters and transport aircraft on long missions. 3. Slide - - HRV analysis in flight training process Heart rate variability (HRV) is a measure of variations in heart rate (HR). It can be calculated by analyzing a time series of beat-to-beat intervals from the ECG signal. It is a non-invasive index of autonomic controls of the heart. In flight conditions, an HRV analysis can be useful in determining, for example, mental workload in pilots during particular phases of flight. 4. Slide - - Mechanism that underlies HRV This is, to a large extent, the activity of autonomic nervous system (ANS).HF(high frequencies) is an indicator of the parasympathetic division (responsible for slowing down) whereasLF(low frequencies) characterizes the sympathetic one (concerned with excitement and also involving a parasympathetic component). Both divisions are linked with each other. Stress, high environmental requirements, workload cause higher excitement and decrease in slowing down, which can be observed using HRV. This is why we actually should investigate what excites and what calms down and, basing on this knowledge, make hypotheses about changes in separate HRV bands. 5. Slide - - What HRV parameters mean? The higher the excitement, the higher theLF power(power within LF band) and the lower theHF power(power within HF band) whilst the higher breaking, relaxation, the higher theHF powerand the lower theLF power(this way the autonomic balance, i.e.LF / HFcan be considered). Likewise a higher heart rate (HR) is, to a large extent, a result of ANS activity. Higher excitement / workload / stress mean a higher HR. 6. Slide - - Aim of work

To determine the usefulness of HRV analysis in flight training process

To determine the interdependence between HRV parameters and flight performance

To verify the hypotheses on the assessment of the progress made during flight training

7. Slide - - Methods The study was carried out involving 25 student pilots of the Polish Air Force Academy being at the initial stage of their training on PZL130 Orlik aircraft.This stage was specified by repeatability of tasks consisting of basic flight elements performed within specific time regimes and with prescribed flight parameters.

Aviation tasks:

instructor flight - exercise 6

exam - exercise 8

unassisted flight - exercise 9

8. Slide - - Circuit parameters 9. Slide - - ECG recorder ECG signals were recorded using the A GATdevice for recording psychophysiological parameters, developed at the Military Institute of Aviation Medicine and used by the Polish Air Force. 10. Slide - - Flight recorder Performance parameters were recorded using the on-board flight recorder that delivers information about physical signals such as: acceleration altitude speed grade bank course 11. Slide - - Operation of ECG and flight recorders in the experiment 12. Slide - - Software Psychophysiological signals were analyzed using HRV Analysis Software 1.1 developed at the University of Kupio in Finland. Performance parameters were analyzed using Matlab. 13. Slide - - HRV parameters

ULF ultra-low frequencies (0.0005-0.003 Hz)

VLF very low frequencies (0.0035-0.04 Hz)

LF low frequencies (0.0405-0.15 Hz)

HF high frequencies (0.1505-0.4 Hz)

ULFP ower power within ULF band (ms 2 )

VLFP ower power within VLV band (ms 2 )

LFP ower power within LF band (ms 2 )

HFP ower power within HP band (ms 2 )

LF / HFLFP ower/HFP owercoefficient

Total Power total power (ms 2 )

DC constant component (ms 2 )

LFnorm normalised power within LF band (%)

14. Slide - - Performance parameters Vodch_sum mean value of 3 deviations from the required speed during flight Hodch_sum- mean value of 3 deviations from the required altitude during flight CoMean mean deviation from the required course during flight CTp time of flight (in seconds) beyond the required course during flight Rollmax maximal overgrad ingduring flight RollTptime of flight at overgrading 15. Slide - - Hypotheses

Pilots excitement should be lower before flight than during flight, which means that before flight theLF / HFvalue should be lower and theHFvalue higher

Pilots excitement should be higher during more demanding flights, so theLF / HFvalue should be higher and theHFvalue lower

The excitement in pilots should become lower and lower before subsequent flights

16. Slide - - Results

For each pilot, data for successive flights were analyzed and presented

Results for each flight consisted of:

• header with pilots number

• number of flight for each pilot

• number of measurement session

Three diagrams for each flight illustrating values for the following periods:

• restitution before flight (RBF) marked as 0

• following circuits marked as 1-7

• restitution after flight (RAF) marked as 8

were presented

17. Slide - - Methods of HRV analysis spectral_components_VLF: 0-0.04 Hz spectral_components_LF: 0.04-0.15 Hz spectral_components_HF: 0.15-04 Hz Detrending of RR series:Trend: Smoothn priors: Model: Eye; Alpha: 1000; Interpolation Rate of RR Series: 2 Hz Points in Freq Domain: 2048 AR Model Order: 14 spectral_components_VLF: 0-0.04 Hz spectral_components_LF: 0.04-0.15 Hz spectral_components_HF: 0.15-04 Hz Detrending of RR series:Trend: Smoothn priors: Model: Eye; Alpha: 1000; Interpolation Rate of RR Series: 2 Hz Points in Freq Domain: 2048 Window Width: 2048 Window Overlap: 512 AR Model Order: 14 HRV Analysis Software 1.1,method 2(AR auto correlation)HRV Analysis Software 1.1,method 1 FFT (fast fourier transformation) 18. Slide - - Example of results for pilot no.13 in his 3 rdflight 19. Slide - - Mean values ofLF / HFin subsequent circles An analysis ofthe resultsLH / HF =f(circle no.) shows that unlike in the case of a simpleHRparameter, which from one circle (circuit) to another has lower and lower values, it is hard to find certain regularities in the subjects behavior in the scope of their mental effort judged with this coefficient. 20. Slide - - Mean values ofLF / HFin subsequent circles during one flight An analysis of the results presented on the diagramLF / HF =f( c ircle no. in flight) demonstrates a quite considerable increase of theLF / HFcoefficient for successive circuits in a flight. The higher the number of circuits, the longer the time of the flight, the longer the period of subjecting the pilot to external factors (i.e. temperature, radiation, stress, fatigue), thus greater mental effort. The decrease in the value of coefficient for circles 6 and 7 is a result of the quite small trial. Flights with this number of circles were performed sporadically and are not a basis for reasoning. 21. Slide - - Mean values ofLF / HFin different mission type The results presented on the diagramLH / HF =f(mission type) confirm the pilots subjective opinions obtained with questionnaires, surveys and direct conversations. Despite the fact that the exercise is at each stage the same, the exam mobilizes for concentration and effort the most, even though it does not causes the highest stress (demonstrated by observing HR), which is the case in unassisted flights, i.e. exercise 9. 22. Slide - - Mean values ofLF norm The results of analysis of coefficientLFnormconfirm the conclusions presented above. It is worth considering the values of these variables determined in the period of restitution before (RBF) and after (RAF) flight. Expected values would be values lower than obtained during the flight itself. In this case only a slight decrease inLF / HF , andLFnormin RBF and RAF can be observed. This is due to conditions, in which the restitution period was carried out. Both RBF and RAF on the day of flight were during the process of preparing for the flight and discussing it later. This considerably disturbs the values of factors as they are not values of real restitution. 23. Slide - - Confirming hypotheses

Hypothesis 1 has been confirmed in 33 of the 62 analyzed flights.

Hypothesis 2 proved to be true in 48 of the 46 analyzed cases.

In the 3 rdhypothesis, which assumed that the excitement in pilots should become lower and lower before subsequent flights (theLF / HFvalues should gradually become lower and theHFvalues - higher before subsequent flights) , acomparison of mean values proved that this hypothesis was true. Moreover, a bigger change was observed between flights 1 and 5 than that between flights 1 and 2, which supports the hypothesis that the more flights a pilot conducts, the less excited he is going to be before the subsequent ones. This can be interpreted as reflection of the progress made during the training.

24. Slide - - Conclusion(1)

The presented analyses generally suggest the usefulness of applying an interpretation of the heart rate changes in pilots during flight trainings. This issue, however, needs further studies and incorporation of other cardiovascular indices (heart rate) and psychomotor factors (e.g. individual differences in temperament).

A development of good method for specifying flight performance accuracy seems to be significant.

25. Slide - - Conclusion(2)

Determining the optimal level of excitement related to flight for each pilot individually is an important issue as well. In other words, it is about determining that level of excitement, at which a pilot would conduct the flight in the most accurate way. The relation between the excitement level and flight performance has the shape of an inverted U.

26. Slide - - Thank you