ArticleBioengineering (Basel, Switzerland)2025
An Arthroscopic Robotic System for Meniscoplasty with Autonomous Operation Ability.
Article in Bioengineering (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Meniscoplasty is a common surgical procedure used to treat meniscus tears. During the operation, there are often key challenges such as a limited visual field, a narrow operating space, and difficulties in controlling the resection range. Therefore, this study developed an arthroscopic robotic system with the ability of autonomous meniscus resection to achieve better surgical outcomes. To address the issue of limited visual fields during the operation, this study used the preoperative and intraoperative meniscus point cloud images for surgical navigation and proposed a novel cross-modal point cloud registration framework. After the registration was completed, the robotic system automatically generated a resection path that could maintain the crescent shape of the remaining meniscus based on the improved Rapidly Exploring Random Tree (RRT) path-planning algorithm in this study. Meanwhile, the Remote Center of Motion (RCM) constraint was introduced during the movement of the robot to enhance safety. In this study, the mean squared error of the preoperative-intraoperative meniscus point cloud registration was only 0.1964 mm
Indexed as
Identifiers
What OpenQuestion holds
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.