Saara Suikkanen, Harri Pihlajamäki, Mickael Parviainen, Hannu Kautiainen, Ilkka Kiviranta
Prevalence of and Risk Factors for Back Pain Among Young Male Conscripts During Compulsory Finnish Military Service
Military medicine
transition industry 40 50 underscores need integrating humans manufacturing processes shifting focus towards customization personalization rather traditional mass production however human performance task execution may vary ensure high humanrobot teaming hrt performance crucial predict performance without negatively affecting task execution therefore predict performance indirectly significant factors affecting human performance engagement task load ie amount cognitive physical andor sensory resources required perform particular task must considered hence propose framework predict maximize hrt performance prediction task performance development phase methodology employs features extracted physiological data inputs labels predictionscategorized accurate performance inaccurate performance due highlow task loadare meticulously crafted using combination nasa tlx questionnaire records human performance quality control tasks application qlearning derive taskspecific weights task load indices structured approach enables deployment model exclusively rely physiological data predicting performance thereby achieving accuracy rate 9545 forecasting hrt performance maintain optimized hrt performance study introduces method dynamically adjusting robots speed case low performance strategic adjustment designed effectively balance task load thereby enhancing efficiency humanrobot collaboration