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: | , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2020
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| Materias: | |
| 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. |
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