[2212.14124] Joint Action is a Framework for Understanding Partnerships Between Humans and Upper Limb Prostheses Skip to main content Search Submit Donate Log in Search arXiv Press Enter to search · Advanced search Computer Science > Human-Computer Interaction arXiv:2212.14124 (cs) [Submitted on 28 Dec 2022] Title: Joint Action is a Framework for Understanding Partnerships Between Humans and Upper Limb Prostheses Authors: Michael R. Dawson , Adam S. R. Parker , Heather E. Williams , Ahmed W. Shehata , Jacqueline S. Hebert , Craig S. Chapman , Patrick M. Pilarski View a PDF of the paper titled Joint Action is a Framework for Understanding Partnerships Between Humans and Upper Limb Prostheses, by Michael R. Dawson and 6 other authors View PDF Abstract: Recent advances in upper limb prostheses have led to significant improvements in the number of movements provided by the robotic limb. However, the method for controlling multiple degrees of freedom via user-generated signals remains challenging. To address this issue, various machine learning controllers have been developed to better predict movement intent. As these controllers become more intelligent and take on more autonomy in the system, the traditional approach of representing the human-machine interface as a human controlling a tool becomes limiting. One possible approach to improve the understanding of these interfaces is to model them as collaborative, multi-agent systems through the lens of joint action. The field of joint action has been commonly applied to two human partners who are trying to work jointly together to achieve a task, such as singing or moving a table together, by effecting coordinated change in their shared environment. In this work, we compare different prosthesis controllers (proportional electromyography with sequential switching, pattern recognition, and adaptive switching) in terms of how they present the hallmarks of joint action. The results of the comparison lead to a new perspective for understanding how existing myoelectric systems relate to each other, along with recommendations for how to improve these systems by increasing the collaborative communication between each partner. Comments: Submitted to Frontiers in Neurorobotics Subjects: Human-Computer Interaction (cs.HC) ; Artificial Intelligence (cs.AI); Multiagent Systems (cs.MA); Robotics (cs.RO) Cite as: arXiv:2212.14124 [cs.HC] (or arXiv:2212.14124v1 [cs.HC] for this version) https://doi.org/10.48550/arXiv.2212.14124 Focus to learn more arXiv-issued DOI via DataCite Journal reference: 2024 10th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics (BioRob), 2024, pp. 605-611 Related DOI : https://doi.org/10.1109/BioRob60516.2024.10719838 Focus to learn more DOI(s) linking to related resources Submission history From: Michael Dawson Mr. [ view email ] [v1] Wed, 28 Dec 2022 23:27:32 UTC (778 KB) Full-text links: Access Paper: View a PDF of the paper titled Joint Action is a Framework for Understanding Partnerships Between Humans and Upper Limb Prostheses, by Michael R. 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