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Motion marker discovery from inertial body sensors for enhancing objective assessment of robotic surgical skills

机译:运动标记从惯性体传感器发现,用于提高机器人外科技能的客观评估

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Robotic surgery simulators are increasingly being used for education in several surgical specialties. However, the surgical skills assessment provided by the robotic simulator is only the statistical evaluation of the stimulus input from the surgeons to the hand and foot actuators, ignoring other body movements and postures that are critical to surgical performance. As a result, performance assessments to surgical experts are not significantly higher than those achieved by novices, and surgical residents do not get the meaningful feedback to improve their skills. In order to enhance the assessment of robotic surgical skills, we employed inertial body sensors and developed a novel motion marker discovery method to determine the differences in motion patterns between expert surgeons and novices on a robotic simulator (Mimic Technologies, Seattle, WA). 4 wireless inertial body sensor nodes capable of 6 degree of freedom sensing were unobtrusively attached to a subject on left wrist, right wrist, right upper arm, and left ankle and used to measure motion during a task. 6 experts and 26 novices participated and performed the Energy Dissection task. Preliminary findings suggested that training with inertial sensor nodes can enhance the robotic surgical training process in a limited amount of time.
机译:机器人手术模拟器被越来越多地用于教育的几个外科专业。然而,由机器人模拟器提供的手术技巧评估只能从医生的手和脚促动器的刺激输入的统计评估,忽略了其他的身体动作和那些对手术性能的关键姿势。其结果是,绩效评估手术专家并不比那些新手取得显著较高,手术的居民没有得到有意义的反馈,以提高他们的技能。为了增强的机器人手术技能评估,我们采用惯性体传感器和开发了一种新颖的运动标记发现的方法来确定在专家外科医生和新手之间运动模式在机器人模拟器的差异(模拟物技术,西雅图,WA)。 4无线惯性体传感器节点能够自由感测的6度被不显眼地附着于左手腕,右手腕,右上臂和左脚踝的受试者和在任务中用于测量运动。 6名专家和26名新手参与和执行的能源解剖任务。初步研究结果表明,培养具有惯性传感器节点可以提高机器人手术训练过程在有限的时间量。

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