King Rachel C, Atallah Louis, Lo Benny P L, Yang Guang-Zhong
Department of Computing, Imperial College London, London SW7 2AZ, UK.
IEEE Trans Inf Technol Biomed. 2009 Sep;13(5):673-9. doi: 10.1109/TITB.2009.2029614.
Laparoscopic surgery is a challenging task in minimally invasive surgery, which involves complex instrument control, extensive manual dexterity, and hand-eye coordination. This requires a greater attention to training and skills evaluation. In order to provide a more objective skills assessment method, this paper presents a wireless sensor platform for the capture of laparoscopic hand gesture data and a hidden-Markov-model-based analysis framework for optimal sensor selection and placement. Detailed experimental validation is provided to illustrate how the proposed method can be used to assess surgical performance improvement over repeated training.
腹腔镜手术是微创手术中的一项具有挑战性的任务，它涉及复杂的器械控制、广泛的手动灵活性和手眼协调能力。这就需要更加关注培训和技能评估。为了提供一种更客观的技能评估方法，本文提出了一个用于捕获腹腔镜手势数据的无线传感器平台以及一个基于隐马尔可夫模型的分析框架，用于优化传感器的选择和放置。文中提供了详细的实验验证，以说明所提出的方法如何用于评估重复训练后手术性能的提升。
