Detailed project information
Project Start Date: 1st December 2018
Project End Date: 31st May 2022
Project Duration: 42 months
Project Coordinator: Prof. Giulio Jacucci, University of Helsinki (FI)
HIT Scientific Coordinator: Prof. Luciano Gamberini
HIT Members and Staff: Prof. Anna Spagnolli, dott. Patrik Pluchino, dott. Chiara Rossato
Project number: 826266
Call (part) identifier: H2020-SC1-DTH-2018-1
Total Project Funding: 3 993 616,25 €
Partners: University of Helsinki, Aalto University, Human Inspired Technology Research Centre
(HIT - University of Padova), University of Trento, Finnish Institute of Occupational Health, Innovation
Sprint Sprl, Electrolux, BNP SRL., Idego, Etsimo.
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A new level of awareness for the cobot.

The Co-Adapt adaptive workstation (AAW) equipped with a collaborative robot (cobot) allows to tailor the workspace according to the actual workers' needs. Each working task imposes mental demands on the worker, but not all workers have the same amount of mental resources to meet those demands. Mental workload and stress influence workers' abilities critically, and the increase of mental workload and stress levels impact the workers' performance and well-being. Human body physiology and eye behaviour reflect these workload increments, thus by monitoring them it can be possible to infer the number of mental demands a human operator is experiencing. A series of physiological signals can be measured through wearable sensors to monitor workers' mental workload and stress levels. The Co-Adapt workstation ca be connected to the cobot and to sensors measuring physiological signals, such as heart rate (HR) and electrodermal activities (EDA), and eye behaviour, such as blinks and saccades, and pupil diameter. In this perspective, wireless physiological monitoring systems and eye-tracking glasses represent the means to make the workstation and the cobot “aware” of workers’ need, in an unobtrusive manner, thus without the need to distract them from the work. 

The age-related physiological declines characterizing senior workers require special care that the Co-Adapt workstation equipped with cobot and sensors can provide adaptively and in due time thanks to the continuous monitoring of operators' needs. 

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