Department of Computer Science, Johns Hopkins, Baltimore, Maryland, USA.
Department of Otolaryngology-Head & Neck Surgery, Johns Hopkins, Baltimore, Maryland, USA.
Otolaryngol Head Neck Surg. 2024 Jul;171(1):188-196. doi: 10.1002/ohn.714. Epub 2024 Mar 15.
Use microscopic video-based tracking of laryngeal surgical instruments to investigate the effect of robot assistance on instrument tremor.
Experimental trial.
Tertiary Academic Medical Center.
In this randomized cross-over trial, 36 videos were recorded from 6 surgeons performing left and right cordectomies on cadaveric pig larynges. These recordings captured 3 distinct conditions: without robotic assistance, with robot-assisted scissors, and with robot-assisted graspers. To assess tool tremor, we employed computer vision-based algorithms for tracking surgical tools. Absolute tremor bandpower and normalized path length were utilized as quantitative measures. Wilcoxon rank sum exact tests were employed for statistical analyses and comparisons between trials. Additionally, surveys were administered to assess the perceived ease of use of the robotic system.
Absolute tremor bandpower showed a significant decrease when using robot-assisted instruments compared to freehand instruments (P = .012). Normalized path length significantly decreased with robot-assisted compared to freehand trials (P = .001). For the scissors, robot-assisted trials resulted in a significant decrease in absolute tremor bandpower (P = .002) and normalized path length (P < .001). For the graspers, there was no significant difference in absolute tremor bandpower (P = .4), but there was a significantly lower normalized path length in the robot-assisted trials (P = .03).
This study demonstrated that computer-vision-based approaches can be used to assess tool motion in simulated microlaryngeal procedures. The results suggest that robot assistance is capable of reducing instrument tremor.
使用基于显微镜视频的喉外科器械跟踪技术，研究机器人辅助对器械震颤的影响。
实验性试验。
三级学术医疗中心。
在这项随机交叉试验中，从 6 名外科医生对尸体猪喉进行左、右侧声带切除术的 36 个视频中进行了记录。这些记录捕获了 3 种不同的情况：没有机器人辅助、使用机器人辅助剪刀和使用机器人辅助抓握器。为了评估工具震颤，我们采用了基于计算机视觉的工具跟踪算法。绝对震颤带功率和归一化路径长度被用作定量指标。Wilcoxon 秩和检验用于统计分析和试验之间的比较。此外，还进行了问卷调查，以评估机器人系统的易用性。
与徒手器械相比，使用机器人辅助器械时绝对震颤带功率显著降低（P = .012）。与徒手试验相比，归一化路径长度显著降低（P = .001）。对于剪刀，机器人辅助试验导致绝对震颤带功率（P = .002）和归一化路径长度（P < .001）显著降低。对于抓握器，绝对震颤带功率无显著差异（P = .4），但机器人辅助试验的归一化路径长度显著降低（P = .03）。
本研究表明，基于计算机视觉的方法可用于评估模拟微喉手术中的器械运动。结果表明，机器人辅助能够减少器械震颤。
