ArticleIEEE robotics and automation letters2025
Comparison of Classical, Neural Network and Hybrid Models for Hysteretic Single-tendon Catheter Kinematics.
Article in IEEE robotics and automation letters, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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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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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.
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Who cites it
3 citing papers in PubMed.
- Single twistable tendon-driven continuum robots.Nature communications · 2026Article
- Using Robotics to Improve Transcatheter Edge-to-Edge Repair of the Mitral Valve.IEEE robotics and automation letters · 2026Article
- A Modular Synthetic Data Generation Toolkit for Vision-Based Localization Models in Intraocular Robotic Microsurgery.Journal of medical robotics research · 2026Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
While robotic control of catheter motion can improve tip positioning accuracy, hysteresis arising from tendon friction and flexural deformation degrades kinematic modeling accuracy. In this paper, we compare the capabilities of three types of models for representing the forward and inverse kinematic maps of a clinical single-tendon cardiac catheter. Classical hysteresis models, neural networks and hybrid combinations of the two are included. Our results show that modeling accuracy is best when models are trained using motions corresponding to the anticipated clinical motions. For sinusoidal motions, recurrent neural network models provide the best performance. For point-to-point motions, however, a simple backlash model can provide comparable performance to a recurrent neural network.
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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.