Enhancing Ultrasound Scanning Skills in a Leader-Follower Robotic System through Expert Hand Impedance Regulation.

IF 6.7 2区 医学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Baoshan Niu, Dapeng Yang, Le Zhang, Yiming Ji, Li Jiang, Hong Liu
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Abstract

Traditional breast cancer surgeries require collaboration between ultrasound (US) doctors and surgeons, making the procedure complex and treating physicians prone to fatigue. In leader-follower robotic surgery, a surgeon controls an US robotic arm and an instrument robotic arm with their left and right hands, enabling independent surgical performance. However, the lack of US scanning skills among surgeons, as well as the physical separation in leader-follower operations, can negatively impact both the scanning and surgical outcomes. This paper proposes a robot-assisted scheme based on dynamic arm impedance compensation (IC) that references expert arm stiffness to compensate for novice arm stiffness. The impedance compensator adjusts the compensation strategy according to the scanning area and scanning stage. The impedance force generator estimates the scanning direction via Kalman filtering and applies stiffness and damping forces in the vertical direction to suppress tremors and other involuntary movements. The experimental results revealed that during the coarse and fine scanning phases, the probe position variance decreased by 57.9% and 73.6%, the contact force variance decreased by 55.2% and 42.5%, and the US image confidence increased by 22.0% and 23.8%, respectively. Compared with traditional filtering compensation (FC) schemes, this approach reduces the average position variance and contact force variance by 32.0% and 25.3%, respectively, and increases confidence by 7.3%. In a no-compensation test, the IC training group outperformed the FC group. This scheme can assist leader-follower US scanning and rapidly improve surgical skills.

通过专家手阻抗调节提高领导-跟随机器人系统的超声扫描技能。
传统的乳腺癌手术需要超声(美国)医生和外科医生之间的合作,这使得手术过程复杂,治疗医生容易疲劳。在领导者-追随者机器人手术中,外科医生用左手和右手控制美国机械臂和仪器机械臂,实现独立手术。然而,外科医生缺乏美国扫描技能,以及在领导-跟随手术中的物理分离,会对扫描和手术结果产生负面影响。本文提出了一种基于动态臂阻抗补偿(IC)的机器人辅助方案,该方案参考专家臂刚度来补偿新手臂刚度。阻抗补偿器根据扫描区域和扫描阶段调整补偿策略。阻抗力发生器通过卡尔曼滤波估计扫描方向,并在垂直方向施加刚度和阻尼力来抑制震颤和其他非自主运动。实验结果表明,在粗扫描和细扫描阶段,探针位置方差分别减小了57.9%和73.6%,接触力方差分别减小了55.2%和42.5%,美国图像置信度分别增加了22.0%和23.8%。与传统滤波补偿(FC)方案相比,该方法将平均位置方差和接触力方差分别减小32.0%和25.3%,置信度提高7.3%。在无补偿测试中,IC训练组表现优于FC组。该方案可辅助先导-跟随超声扫描,快速提高手术技能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
IEEE Journal of Biomedical and Health Informatics
IEEE Journal of Biomedical and Health Informatics COMPUTER SCIENCE, INFORMATION SYSTEMS-COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
CiteScore
13.60
自引率
6.50%
发文量
1151
期刊介绍: IEEE Journal of Biomedical and Health Informatics publishes original papers presenting recent advances where information and communication technologies intersect with health, healthcare, life sciences, and biomedicine. Topics include acquisition, transmission, storage, retrieval, management, and analysis of biomedical and health information. The journal covers applications of information technologies in healthcare, patient monitoring, preventive care, early disease diagnosis, therapy discovery, and personalized treatment protocols. It explores electronic medical and health records, clinical information systems, decision support systems, medical and biological imaging informatics, wearable systems, body area/sensor networks, and more. Integration-related topics like interoperability, evidence-based medicine, and secure patient data are also addressed.
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