Zheng Yi, Leonard Grey, Tellez Juan, Zeh Herbert, Majewicz Fey Ann
Yi Zheng and Ann Majewicz Fey are with the Department of Mechanical Engineering, The University of Texas at Austin, Austin, TX 78712 USA.
Grey Leonard, Juan Tellez, Herbert Zeh and Ann Majewicz Fey are with the Department of Surgery, the University of Texas Southwestern Medical Center, Dallas, TX 75390 USA.
Int Symp Med Robot. 2021 Nov;2021. doi: 10.1109/ismr48346.2021.9661482. Epub 2022 Jan 3.
Increased levels of stress can impair surgeon performance and patient safety during surgery. The aim of this study is to investigate the effect of short term stressors on laparoscopic performance through analysis of kinematic data. Thirty subjects were randomly assigned into two groups in this IRB-approved study. The control group was required to finish an extended-duration peg transfer task (6 minutes) using the FLS trainer while listening to normal simulated vital signs and while being observed by a silent moderator. The stressed group finished the same task but listened to a period of progressively deteriorating simulated patient vitals, as well as critical verbal feedback from the moderator, which culminated in 30 seconds of cardiac arrest and expiration of the simulated patient. For all subjects, video and position data using electromagnetic trackers mounted on the handles of the laparoscopic instruments were recorded. A statistical analysis comparing time-series velocity, acceleration, and jerk data, as well as path length and economy of volume was conducted. Clinical stressors lead to significantly higher velocity, acceleration, jerk, and path length as well as lower economy of volume. An objective evaluation score using a modified OSATS technique was also significantly worse for the stressed group than the control group. This study shows the potential feasibility and advantages of using the time-series kinematic data to identify the stressful conditions during laparoscopic surgery in near-real-time. This data could be useful in the design of future robot-assisted algorithms to reduce the unwanted effects of stress on surgical performance.
压力水平升高会在手术过程中损害外科医生的表现并危及患者安全。本研究的目的是通过分析运动学数据来探究短期应激源对腹腔镜手术操作的影响。在这项经机构审查委员会批准的研究中，30名受试者被随机分为两组。对照组被要求在听着正常模拟生命体征并在一名安静的监督员观察的情况下，使用基础腹腔镜技能训练箱完成一项持续时间较长的移栓任务（6分钟）。应激组完成相同任务，但要听一段模拟患者生命体征逐渐恶化的声音，以及来自监督员的关键口头反馈，最终是30秒的心脏骤停和模拟患者的死亡。对于所有受试者，使用安装在腹腔镜器械手柄上的电磁跟踪器记录视频和位置数据。进行了一项统计分析，比较时间序列速度、加速度、加加速度数据，以及路径长度和容积经济性。临床应激源会导致速度、加速度、加加速度和路径长度显著更高，以及容积经济性更低。使用改良的客观结构化腹腔镜技能评估技术得出的客观评估分数，应激组也显著低于对照组。本研究表明，利用时间序列运动学数据近乎实时地识别腹腔镜手术中的应激状况具有潜在的可行性和优势。这些数据可能有助于未来机器人辅助算法的设计，以减少压力对手术操作的不良影响。
