Generalisable machine learning models trained on heart rate variability data to predict mental fatigue

HIGHLIGHTS

• who: Andru00e1s Matuz from the DepartmentUniversity of have published the paper: Generalisable machine learning models trained on heart rate variability data to predict mental fatigue, in the Journal: Scientific Reports Scientific Reports
• what: Below, the authors report the most important findings. This model had a sensitivity of 72% and a specificity of 76%. The aim of this study was to determine the extent to which classification models and regression models trained on HRV data can detect a fatigue state and predict the level of subjective fatigue that results from prolonged performances of different cognitively demanding . . .
  

   

  

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