The complete paper explains how machine learning and physiology can be used to improve rig technical training by monitoring the operator’s stress, identifying key operations in which situational awareness is low, and targeting these operations with dedicated exercises. The developed methodology is based on a study of human psychological indicators captured through light biometric devices. These indicators are fed to a machine-learning algorithm that calculates a stress index for the observed operator. The model uses machine vision to identify key physiological parameters and a convolutional neural network to interpret them.
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