Biomechanical analysis on neurotypical and autism spectrum disorder people during human-cobot interaction

Abstract

Biomechanical analysis is essential for assessing subjects interacting with robotic setups and platforms. However, in industrial scenarios, workers’ biomechanics are assessed mainly through questionnaires and scales which provide limited objectivity. Very few studies analyzed the biomechanics of workers in multiple sessions, and no study assessed diverse populations of workers. Therefore, we collected tracking data from 14 neurotypical and 7 participants with autism spectrum disorder (ASD) performing assembly tasks in a lab-based industrial collaborative workcell. Human tracking data were acquired by an Azure Kinect and elaborated with a biomechanical model that allowed to compute human kinematics and dynamics. The biomechanics of neurotypical and ASD operators were compared across two working sessions. Both neurotypical and people characterized by ASD decreased torque and power in the second session with respect to the first one, indicating adaptation to the working activity. Interestingly, ASD people expended more energy than neurotypical, suggesting a higher risk of fatigue. Overall, ASD people performed similarly to neurotypical people from a biomechanical point of view. In this study, we showed a protocol for multisession biomechanical monitoring of workers during industrial human-robot collaboration tasks that can be employed in real scenarios and with ASD workers. This approach can be useful in human-robot collaboration to design minimum-fatigue collaborative tasks, support physical health, and improve ergonomics for workers.