Surgical motion analysis using discriminative interpretable patterns
Surgical motion analysis using discriminative interpretable patterns
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DOI：
10.1016/j.artmed.2018.08.002
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发表时间：
2018-09-01
影响因子：
7.5
通讯作者：
Jannin, Pierre
中科院分区：
文献类型：
--
作者：
Forestier, Germain;Petitjean, Francois;Jannin, Pierre
目的：随着自动捕获设备的发展，手术运动分析越来越受到关注。在这种情况下，使用先进的手术培训系统，使手术学员的自动化评估成为可能。手术技能的自动化和定量评价是一个非常重要的步骤，在提高外科病人的护理材料和方法：在本文中，我们提出了一种方法，发现和排名的歧视性和可解释的模式，从记录的手术动作的手术实践。模式被定义为运动学数据中的一系列动作或事件，这些动作或事件一起区别于特定的姿势或技能水平。我们的方法是基于连续的运动学数据分解成一组重叠的手势表示字符串（袋的话），我们计算比较数值统计（TF-idf），使歧视手势发现通过其相对发生frequency.Results：我们进行了实验三个手术运动数据集。结果表明，所提出的方法识别的模式可以用来准确地分类个人的手势，技能水平和手术界面。我们还介绍了如何提供一个详细的反馈模式的受训者技能assessment.Conclusions：所提出的方法是一个有趣的除了现有的学习工具的手术，因为它提供了一种方法来获得反馈的练习的哪些部分已被用于分类的尝试是正确的或不正确的。
Objective: The analysis of surgical motion has received a growing interest with the development of devices allowing their automatic capture. In this context, the use of advanced surgical training systems makes an automated assessment of surgical trainee possible. Automatic and quantitative evaluation of surgical skills is a very important step in improving surgical patient care.Material and method: In this paper, we present an approach for the discovery and ranking of discriminative and interpretable patterns of surgical practice from recordings of surgical motions. A pattern is defined as a series of actions or events in the kinematic data that together are distinctive of a specific gesture or skill level. Our approach is based on the decomposition of continuous kinematic data into a set of overlapping gestures represented by strings (bag of words) for which we compute comparative numerical statistic (tf-idf) enabling the discriminative gesture discovery via its relative occurrence frequency.Results: We carried out experiments on three surgical motion datasets. The results show that the patterns identified by the proposed method can be used to accurately classify individual gestures, skill levels and surgical interfaces. We also present how the patterns provide a detailed feedback on the trainee skill assessment.Conclusions: The proposed approach is an interesting addition to existing learning tools for surgery as it provides a way to obtain a feedback on which parts of an exercise have been used to classify the attempt as correct or incorrect.