Artificial Neural Network Analysis of Heart Rate under Cognitive Load in a Flight Simulator

M. Hannula, J. Koskelo, K. Huttunen, M. Sorri, and T. Leino (Finland)

Keywords

R-R interval, intelligent systems, heart rate analysis, and stress factors.

Abstract

Psychophysiological stress (PPS) affects heart rate variability (HRV) through the autonomic nervous system. In the present study, the applicability of artificial neural network (ANN) analysis in evaluating the cognitive workload that raises the PPS level of fighter pilots was explored using HRV data during a simulated F-18 Hornet flight. Electrocardiography (ECG) recordings and assessements of the cognitive load that induces psychophysiological stress were collected from 14 interceptor fighter pilots during a complex air battle in a simulator. Altogether 14 simulated air battles, containing 155 flight phases, were analyzed. The results of the analysis were encouraging; the Pearson’s correlation coefficients between the ECG data and the cognitive workload evaluated by an experienced flight instructor were between 0.66 and 0.69.

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