Locomotion in virtual environments predicts cardiovascular responsiveness to subsequent stressful challenges

People differ in their susceptibility to stressors, but it is difficult to know a priori who has a higher vulnerability. Here, the authors show that machine learning algorithms applied to locomotor data from people’s exploration of virtual reality scenarios predicts heart rate variability to stress....

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Autores principales: João Rodrigues, Erik Studer, Stephan Streuber, Nathalie Meyer, Carmen Sandi
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2020
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Acceso en línea:https://doaj.org/article/35044ec9c1d346319326207e4e375cdf
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Sumario:People differ in their susceptibility to stressors, but it is difficult to know a priori who has a higher vulnerability. Here, the authors show that machine learning algorithms applied to locomotor data from people’s exploration of virtual reality scenarios predicts heart rate variability to stress.