Recent studies have shown that gestures are useful indicators of understanding, learning, and memory retention. However, and specially in collaborative settings, current metrics that estimate task understanding often neglect the information expressed through gestures. This work introduces the physical instruction assimilation (PIA) metric, a novel approach to estimate task understanding by analyzing the way in which collaborators use gestures to convey, assimilate, and execute physical instructions. PIA estimates task understanding by inspecting the number of necessary gestures required to complete a shared task. PIA is calculated based on the multiagent gestural instruction comparer (MAGIC) architecture, a previously proposed framework to represent, assess, and compare gestures. To evaluate our metric, we collected gestures from collaborators remotely completing the following three tasks: block assembly, origami, and ultrasound training. The PIA scores of these individuals are compared against two other metrics used to estimate task understanding: number of errors and amount of idle time during the task. Statistically significant correlations between PIA and these metrics are found. Additionally, a Taguchi design is used to evaluate PIA's sensitivity to changes in the MAGIC architecture. The factors evaluated the effect of changes in time, order, and motion trajectories of the collaborators’ gestures. PIA is shown to be robust to these changes, having an average mean change of 0.45. These results hint that gestures, in the form of the assimilation of physical instructions, can reveal insights of task understanding and complement other commonly used metrics.

中文翻译：

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通过手势分析评估协作性身体任务

最近的研究表明，手势是理解，学习和记忆力的有用指标。但是，特别是在协作环境中，当前用于评估任务理解程度的指标通常会忽略通过手势表示的信息。这项工作介绍了物理指令吸收（PIA）度量标准，这是一种通过分析协作者使用手势传达，吸收和执行物理指令的方式来评估任务理解的新颖方法。PIA通过检查完成共享任务所需的必要手势的数量来估计任务的理解。PIA是基于多代理手势指令比较器（MAGIC）架构计算的，该架构是先前提出的表示，评估和比较手势的框架。要评估我们的指标，我们从协作者那里收集了手势，这些手势远程完成了以下三个任务：块体组装，折纸和超声训练。将这些人的PIA得分与用于评估任务理解的其他两个指标进行比较：错误数量和任务期间的空闲时间。发现了PIA与这些指标之间的统计上显着的相关性。此外，Taguchi设计用于评估PIA对MAGIC体系结构变化的敏感性。这些因素评估了协作者手势的时间，顺序和运动轨迹变化的影响。PIA显示出对这些变化的鲁棒性，其平均均值变化为0.45。这些结果表明，手势以物理指令的同化形式出现，