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Abstract
This paper research the influence of vital signs on the percentage of stress in people, in the context of artificial intelligence, specifically artificial neural networks. Currently there is an increasing interest in studying the conditioning factors of stress in people, process that has come to affect workers in the productive sectors in recent years. However, there is an interest in the percentage of stress of people and how it affects on the mood of the same, as a fundamental element in the individual's work performance. The central axis of this work is to evaluate the vital signs of pulse and respiration to estimate the percentage of stress present in the patient, in such a way as to allow an a priori assessment for a future medical diagnosis. The values of pulse and respiration are taken into account and an artificial neural network is executed to estimate the percentage of stress through a Bayesian process of processing medical variables.