Retrospective Analysis of Pulse Wave Flattening for G-LOC Detection Using Automatic Computer Algorithm Methods

The possibility of G-induced loss of consciousness (G-LOC) is a key concern when flying modern, high-performance aircraft. Currently, there are no identification methods available based on physiological data. This study aimed to determine whether specific pulse wave changes could be reliably identified using automatic computer algorithms to detect impending G-LOC. The pulse waves of 86 people who experienced G-LOC in a human centrifuge were analysed alongside an age-, gender-, nationality-, training-, and anti-G-equipment-matched control group using computer algorithm methods to analyse possible longer reductions in the G-LOC group. Based on this data, the study showed that centrifuge profiles with a gradual “onset run” using AGSM resulted in longer pulse wave flattening around the G-LOC in the G-LOC group than in the matched control group. However, this could not be verified in human centrifuge runs with active flight profiles and higher onset rates. Unfortunately, this means that the method used here would not currently be applicable in actual flight. In the future, the possibility of creating an identification method could be extended by incorporating additional physiological data.