Aircraft Pilots Workload Analysis: Heart Rate Variability Objective Measures and NASA-Task Load Index Subjective Evaluation

Autor: Andrea Alaimo; Antonio Esposito; Calogero Orlando; Andre Simoncini
Sprache: Englisch
Veröffentlicht: 2020
Quelle: Directory of Open Access Journals: DOAJ Articles
Online Zugang: https://www.mdpi.com/2226-4310/7/9/137
https://doaj.org/toc/2226-4310
doi:10.3390/aerospace7090137
2226-4310
https://doaj.org/article/ca727a83ef774c7e9b51449e0db90b14
https://doi.org/10.3390/aerospace7090137
https://doaj.org/article/ca727a83ef774c7e9b51449e0db90b14
Erfassungsnummer: ftdoajarticles:oai:doaj.org/article:ca727a83ef774c7e9b51449e0db90b14

Zusammenfassung

Workload and fatigue of aircraft pilots represent an argument of great interest in the framework of human factors and a pivotal point to be considered in aviation safety. 75% of aircraft accidents are related to human errors that, in most cases, are due to high level of mental workload and fatigue. There exist several subjective or objective metrics to quantify the pilots’ workload level, with both linear and nonlinear relationships reported in the literature. The main research objective of the present work is to analyze the relationships between objective and subjective workload measurements by looking for a correlation between metrics belonging to the subjective and biometric rating methods. More particularly, the Heart Rate Variability (HRV) is used for the objective analysis, whereas the NASA-TLX questionnaire is the tool chosen for the subjective evaluation of the workload. Two different flight scenarios were considered for the studies: the take-off phase with the initial climb and the final approach phase with the landing. A Maneuver Error Index (MEI) is also introduced to evaluate the pilot flight performance according to mission requirements. Both qualitative and quantitative correlation analyses were performed among the MEI, subjective and objective measurements. Monotonic relationships were found within the HRV indexes, and a nonlinear relationship is proposed among NASA-TLX and HRV indexes. These findings suggest that the relationship between workload, biometric data, and performance indexes are characterized by intricate patterns of nonlinear relationships.