Ramadurai Sruthi, Gutierrez Christian, Jeong Heejin, Kim Myunghee
Mechanical and Industrial Engineering Department, College of Engineering, University of Illinois at Chicago, Chicago, IL, USA.
Computer Science Department, College of Engineering, University of Illinois at Chicago, Chicago, IL, USA.
IISE Trans Occup Ergon Hum Factors. 2024 Jan-Jun;12(1-2):97-111. doi: 10.1080/24725838.2023.2287015. Epub 2023 Dec 6.
OCCUPATIONAL APPLICATIONSAn understanding of fluency in human-robot teaming from a physiological standpoint is still incomplete. In our experimental study involving 24 participants, we designed a scenario for shared-space human-robot collaboration (HRC) for a material sorting task. When compared to a sequential mode of interaction, the simultaneous mode resulted in significantly higher perceptions of fluency and engagement, primarily by reducing human idle time. These observations were complemented by significant changes in physiological responses, such as ECG entropy and low frequency power. These responses could predict fluency and engagement with accuracies of 90 and 97%, respectively. Notably, the perception of fluency and preferred mode of interaction were influenced by individual preferences. Hence, it is crucial to consider both physiological responses and user preferences when designing HRC systems, to ensure a positive experience with the robot teammate and to foster engagement in long-term teamwork. Furthermore, these signals can be obtained using a single robust, low-cost, and comfortable sensor.
职业应用
从生理学角度对人机协作流畅性的理解仍不完整。在我们涉及24名参与者的实验研究中，我们设计了一个用于材料分拣任务的共享空间人机协作（HRC）场景。与顺序交互模式相比，同步模式主要通过减少人类空闲时间，使流畅性和参与度的感知显著更高。这些观察结果得到了生理反应显著变化的补充，如心电图熵和低频功率。这些反应分别能够以90%和97%的准确率预测流畅性和参与度。值得注意的是，流畅性感知和偏好的交互模式受个人偏好影响。因此，在设计HRC系统时，考虑生理反应和用户偏好至关重要，以确保与机器人队友有积极的体验，并促进长期团队合作中的参与度。此外，这些信号可以使用单个坚固、低成本且舒适的传感器获得。
