Stress Measurement in Multi-tasking Decision Processes Using Executive Functions Analysis

Paletta, Lucas; Pszeida, Martin; Nauschnegg, Bernhard; Haspl, Thomas; Marton, Raphael

doi:10.1007/978-3-030-20473-0_33

Cited by 5 publications

References 15 publications

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Attention Analysis for Assistance in Assembly Processes

Paletta¹

2021

IFIP Advances in Information and Communication Technology

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Human attention processes play a major role in the optimization of human-machine interaction (HMI) systems. This work describes a suite of innovative components within a novel framework in order to assess the human factors state of the human operator primarily by gaze and in real-time. The objective is to derive parameters that determine information about situation awareness of the human collaborator that represents a central concept in the evaluation of interaction strategies in collaboration. The human control of attention provides measures of executive functions that enable to characterize key features in the domain of human-machine collaboration. This work presents a suite of human factors analysis components (the Human Factors Toolbox) and its application in the assembly processes of a future production line. Comprehensive experiments on HMI are described which were conducted with typical tasks including collaborative pick-and-place in a lab based prototypical manufacturing environment.

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Attention Analysis for Assistance in Assembly Processes

Paletta¹

2021

IFIP Advances in Information and Communication Technology

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Enhancing the Quality of Human-Robot Cooperation Through the Optimization of Human Well-Being and Productivity

Messeri

2022

Special Topics in Information Technology

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In human-robot interaction frameworks maximizing the team efficiency is crucial. However, it is also essential to mitigate the physical and cognitive workload experienced by the shop-floor worker during the collaborative task. In this chapter we first investigate the impact of the robot interaction role (whether being leader or follower during cooperation) on both the human physiological stress and production rate. Based on that, a game-theoretic approach is proposed to model the trade-off between the maximization of the human performance and the minimization of the human cognitive stress. Then, we describe a closed-loop robot control strategy that, based on the proposed game-theoretic model, enables the robot to simultaneously minimize the human cognitive stress and maximize his/her performance during cooperation, by adjusting its role. Eventually, a real-time task allocation strategy is proposed to both ensure the minimization of the human physical fatigue and the effectiveness of the production process. This method relies on a new sophisticated musculoskeletal model of the human upper-body. All these methodologies have been experimentally tested in realistic human-robot collaborative scenarios involving several volunteers and the ABB IRB 14000 dual-arm “YuMi" collaborative robot.

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