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Assessing task understanding in remote ultrasound diagnosis via gesture analysis
Pattern Analysis and Applications ( IF 3.9 ) Pub Date : 2021-09-13 , DOI: 10.1007/s10044-021-01027-2
Edgar Rojas-Muñoz 1 , Juan P. Wachs 2
Affiliation  

This work presents a gesture-based approach to estimate task understanding and performance during remote ultrasound tasks. Our approach is comprised of two main components. The first component uses the Multi-Agent Gestural Instruction Comparer (MAGIC) framework to represent and compare the gestures performed by collaborators. Through MAGIC, gestures can be compared based in their morphology, semantics, and pragmatics. The second component computes the Physical Instructions Assimilation (PIA) metric, a score representing how well are gestures being used to communicate and execute physical instructions. To evaluate our hypothesis, 20 participants performed a remote ultrasound task consisting of three subtasks: vessel detection, blood extraction, and foreign body detection. MAGIC’s gesture comparison approaches were compared against two other approaches based on how well they replicated human-annotated gestures matchings. Our approach outperformed the others, agreeing with the human baseline over 76% of the times. Subsequently, a correlation analysis was performed to compare PIA’s task understanding insights with those of three other metrics: error rate, idle time rate, and task completion percentage. Significant correlations (\(p\,\le \,0.04\)) were found between PIA and all the other metrics, positioning PIA as an effective metric for task understanding estimation. Finally, post-experiment questionnaires were used to subjectively evaluate the participants’ perceived understanding. The PIA score was found to be significantly correlated with the participants’ overall task understanding (\(p\le 0.05\)), hinting to the relation between the assimilation of physical instructions and self-perceived understanding. These results demonstrate that gestures an be used to estimate task understanding in remote ultrasound tasks, which can improve how these tasks are performed and assessed.



中文翻译:

通过手势分析评估远程超声诊断中的任务理解

这项工作提出了一种基于手势的方法来估计远程超声任务期间的任务理解和性能。我们的方法由两个主要部分组成。第一个组件使用多代理手势指令比较器 (MAGIC) 框架来表示和比较协作者执行的手势。通过 MAGIC,可以根据手势的形态、语义和语用来比较手势。第二个组件计算物理指令同化 (PIA) 指标,该分数表示使用手势进行通信和执行物理指令的效果如何。为了评估我们的假设,20 名参与者执行了一项远程超声任务,包括三个子任务:血管检测、血液提取和异物检测。MAGIC 的手势比较方法根据它们复制人工注释手势匹配的程度与其他两种方法进行了比较。我们的方法优于其他方法,超过 76% 的时间与人类基线一致。随后,进行了相关分析,将 PIA 的任务理解洞察力与其他三个指标的洞察力进行比较:错误率、空闲时间率和任务完成率。显着相关性(\(p\,\le \,0.04\) ) 被发现在 PIA 和所有其他指标之间,将 PIA 定位为任务理解估计的有效指标。最后,使用实验后问卷对参与者的感知理解进行主观评估。发现 PIA 分数与参与者的整体任务理解显着相关 ( \(p\le 0.05\) ),暗示了身体指令的同化与自我感知理解之间的关系。这些结果表明,手势可用于估计远程超声任务中的任务理解,这可以改进这些任务的执行和评估方式。

更新日期:2021-09-13
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