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Multi-Modal Haptic Feedback for Grip Force Reduction in Robotic Surgery

Ahmad Abiri, Jake Pensa, Anna Tao, Ji Ma, Yen‐Yi Juo, Syed J. Askari, James W. Bisley, Jacob Rosén, Erik Dutson, Warren S. Grundfest

发表年份
2019
引用次数
122
访问权限
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摘要

Minimally invasive robotic surgery allows for many advantages over traditional surgical procedures, but the loss of force feedback combined with a potential for strong grasping forces can result in excessive tissue damage. Single modality haptic feedback systems have been designed and tested in an attempt to diminish grasping forces, but the results still fall short of natural performance. A multi-modal pneumatic feedback system was designed to allow for tactile, kinesthetic, and vibrotactile feedback, with the aims of more closely imitating natural touch and further improving the effectiveness of HFS in robotic surgical applications and tasks such as tissue grasping and manipulation. Testing of the multi-modal system yielded very promising results with an average force reduction of nearly 50% between the no feedback and hybrid (tactile and kinesthetic) trials (p < 1.0E-16). The multi-modal system demonstrated an increased reduction over single modality feedback solutions and indicated that the system can help users achieve average grip forces closer to those normally possible with the human hand.

关键词

Kinesthetic learningHaptic technologyModality (human–computer interaction)Reduction (mathematics)Computer scienceModalSimulationModalitiesRoboticsRobot

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