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用于执行月球和远征手术的微型自主机器人的末端执行器接触和力检测。

End-Effector Contact and Force Detection for Miniature Autonomous Robots Performing Lunar and Expeditionary Surgery.

机构信息

Center for Advanced Surgical Technology, 986245 Nebraska Medical Center, Omaha, NE, 69818-6245, USA.

Department of Electrical and Computer Engineering, University of Nebraska-Lincoln, Lincoln, NE, 68588-0511, USA.

出版信息

Mil Med. 2021 Jan 25;186(Suppl 1):281-287. doi: 10.1093/milmed/usaa443.

Abstract

INTRODUCTION

The U.S. Space Force was stood up on December 20, 2019 as an independent branch under the Air Force consisting of about 16,000 active duty and civilian personnel focused singularly on space. In addition to the Space Force, the plans by NASA and private industry for exploration-class long-duration missions to the moon, near-earth asteroids, and Mars makes semi-independent medical capability in space a priority. Current practice for space-based medicine is limited and relies on a "life-raft" scenario for emergencies. Discussions by working groups on military space-based medicine include placing a Role III equivalent facility in a lunar surface station. Surgical capability is a key requirement for that facility.

MATERIALS AND METHODS

To prepare for the eventuality of surgery in space, it is necessary to develop low-mass, low power, mini-surgical robots, which could serve as a celestial replacement for existing terrestrial robots. The current study focused on developing semi-autonomous capability in surgical robotics, specifically related to task automation. Two categories for end-effector tissue interaction were developed: Visual feedback from the robot to detect tissue contact, and motor current waveform measurements to detect contact force.

RESULTS

Using a pixel-to-pixel deep neural network to train, we were able to achieve an accuracy of nearly 90% for contact/no-contact detection. Large torques were predicted well by a trained long short-term memory recursive network, but the technique did not predict small torques well.

CONCLUSION

Surgical capability on long-duration missions will require human/machine teaming with semi-autonomous surgical robots. Our existing small, lightweight, low-power miniature robots perform multiple essential tasks in one design including hemostasis, fluid management, suturing for traumatic wounds, and are fully insertable for internal surgical procedures. To prepare for the inevitable eventuality of an emergency surgery in space, it is essential that automated surgical robot capabilities be developed.

摘要

简介

美国太空部队于 2019 年 12 月 20 日成立,作为空军的一个独立分支,由约 16000 名现役和文职人员组成,专注于太空。除了太空部队,美国国家航空航天局(NASA)和私营企业计划进行探索级的月球、近地小行星和火星长期任务,这使得太空半自主医疗能力成为当务之急。目前基于太空的医学实践受到限制,并依赖于紧急情况下的“救生艇”方案。军事太空医学工作组的讨论包括在月球表面站放置一个相当于三级的设施。该设施的一个关键要求是手术能力。

材料与方法

为了应对太空手术的可能性,有必要开发出质量轻、功率低、微型手术机器人,作为现有地面机器人的太空替代品。本研究重点开发手术机器人的半自动能力,特别是与任务自动化相关的能力。开发了两种末端执行器与组织相互作用的类别:机器人的视觉反馈来检测组织接触,以及电机电流波形测量来检测接触力。

结果

使用逐像素深度神经网络进行训练,我们能够实现接触/无接触检测的近 90%的准确率。经过训练的长短期记忆递归网络可以很好地预测大扭矩,但该技术无法很好地预测小扭矩。

结论

在长期任务中,手术能力将需要人机协作与半自动手术机器人。我们现有的小型、轻量、低功率微型机器人在一个设计中执行多个基本任务,包括止血、流体管理、创伤性伤口缝合,并可完全插入进行内部手术。为了应对太空紧急手术的必然情况,必须开发自动化手术机器人的能力。

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