Fujii Kenko, Salerno Antonino, Sriskandarajah Kumuthan, Kwok Ka-Wai, Shetty Kunal, Yang Guang-Zhong
Hamlyn Centre for Robotic Surgery, Imperial College London, SW7 2AZ, London, UK.
Rep U S. 2013 Nov 7;2013:3582-3589. doi: 10.1109/iros.2013.6696867.
This paper introduces a gaze contingent controlled robotic arm for laparoscopic surgery, based on gaze gestures. The method offers a natural and seamless communication channel between the surgeon and the robotic laparoscope. It offers several advantages in terms of reducing on-screen clutter and efficiently conveying visual intention. The proposed hands-free system enables the surgeon to be part of the robot control feedback loop, allowing user-friendly camera panning and zooming. The proposed platform avoids the limitations of using dwell-time camera control in previous gaze contingent camera control methods. The system represents a true hands-free setup without the need of obtrusive sensors mounted on the surgeon or the use of a foot pedal. Hidden Markov Models (HMMs) were used for real-time gaze gesture recognition. This method was evaluated with a cohort of 11 subjects by using the proposed system to complete a modified upper gastrointestinal staging laparoscopy and biopsy task on a phantom box trainer, with results demonstrating the potential clinical value of the proposed system.
本文介绍了一种基于注视手势的用于腹腔镜手术的注视视景控制机器人手臂。该方法在外科医生和机器人腹腔镜之间提供了自然且无缝的通信通道。在减少屏幕杂乱和有效传达视觉意图方面具有若干优势。所提出的免提系统使外科医生能够成为机器人控制反馈回路的一部分,实现用户友好的摄像头平移和缩放。所提出的平台避免了在先前的注视视景摄像头控制方法中使用停留时间摄像头控制的局限性。该系统代表了一种真正的免提设置,无需在外科医生身上安装侵入性传感器或使用脚踏板。隐马尔可夫模型(HMM)用于实时注视手势识别。通过使用所提出的系统,让11名受试者在模拟箱训练器上完成改良的上消化道分期腹腔镜检查和活检任务,对该方法进行了评估,结果证明了所提出系统的潜在临床价值。