{"id":47737,"date":"2023-07-06T11:20:57","date_gmt":"2023-07-06T10:20:57","guid":{"rendered":"https:\/\/www.he-arc.ch\/?post_type=he-arc_publication&p=47737"},"modified":"2023-07-06T11:20:58","modified_gmt":"2023-07-06T10:20:58","slug":"relevant-physiological-indicators-for-assessing-workload-in-conditionally-automated-driving-through-three-class-classification-and-regression","status":"publish","type":"he-arc_publication","link":"https:\/\/www.he-arc.ch\/en\/publications\/relevant-physiological-indicators-for-assessing-workload-in-conditionally-automated-driving-through-three-class-classification-and-regression\/","title":{"rendered":"Relevant physiological indicators for assessing workload in conditionally automated driving, through three-class classification and regression"},"content":{"rendered":"\n
By : Quentin Meteier, Emmanuel de Salis, Marine Capallera, Marino Widmer, Leonardo Angelini, Omal Abou et al<\/p>\n\n\n\n
In : Frontiers in Computer Science<\/p>\n\n\n\n