In-flight Electrocardiography Monitoring in a Pilot During Cross Country Flight
Purpose: The diagnosis and management of cardiovascular diseases are important for pilots, as well as the assessment of workload. Heart rate variability (HRV) can be evaluated from electrocardiography (ECG) signals during flight phases to assess the activation of the autonomic nervous system. Me...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Aerospace Medical Association of Korea
2024-12-01
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| Series: | Hanggong uju uihakoeji |
| Subjects: | |
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| Summary: | Purpose: The diagnosis and management of cardiovascular diseases are important
for pilots, as well as the assessment of workload. Heart rate variability (HRV) can be
evaluated from electrocardiography (ECG) signals during flight phases to assess the
activation of the autonomic nervous system.
Methods: In this study, continuous ECG activity was recorded of one pilot who flied
as a pilot flying during a 4-hour long round trip using wearable ECG machine and was
analyzed with MATLAB (R2020b ver. 9.9, The Mathworks Inc.). Total flight was divided
into five phases: preflight, take off, cruise, landing, and postflight.
Results: Mean heart rate (HR) was lowest in the postflight phase (76 bpm), and
highest in the landing phase (86 bpm). Landing phase showed the highest values in
standard deviation of NN interval (59.3 ms), triangular index (11.7), and triangular
interpolation of NN interval (195 ms), while the postflight phase had highest root mean
square of successive difference (20.5 ms) and proportion of successive RR interval
(3.4 ms). As for frequency-domain metrics, the landing phase had the highest lowfrequency/
high-frequency ratio of 5.33. Among the non-linear HRV measures, the
landing phase presented the lowest SD1/SD2 ratio (0.15).
Conclusion: We observed the relative increase of mean HR and change of HRV in the
landing phase, indicating elevated sympathetic nervous tone. Further studies should
be considered to evaluate specific changes of ECG signals in flight phases and confirm
the clinical use of the MATLAB signal analysis tools. |
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| ISSN: | 1738-2548 2713-9972 |