ReviewComputational intelligence and neuroscience2022
Human-Machine Interaction Methods for Minimally Invasive Surgical Robotic Arms.
Review in Computational intelligence and neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- [Research progress and technical analysis of dining robots].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2026Review
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Minimally invasive surgery has a smaller incision area than traditional open surgery, which can greatly reduce damage to the human body and improve the utilization of medical devices. However, minimally invasive surgery also has disadvantages such as limited flexibility and operational characteristics. The interactive minimally invasive surgical robot system not only improves the stability, safety, and accuracy of minimally invasive surgery but also introduces force feedback in controlling the surgical robot, which is a new development direction in the field of minimally invasive surgery. This paper reviews the development status of interactive minimally invasive surgical robotic systems and key technologies to achieve human-robot interaction and finally provides an outlook and summary of its development. Fuzzy theory and reinforcement learning are introduced into the parameter adjustment process of the variable guide control model, and a human-robot interaction method for minimally invasive surgical robot posture adjustment is proposed.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.