通过梯度刚度设计，实现磁控导管在弯曲时稳定推进。
Stiffness Optimization for Concentrated Bending in Magnetically Actuated Catheters: Maintaining Steerability under Gradient Stiffness
- 采用分段梯度刚度与解耦推进-转向结构，优化导管刚度分布。
- 1.5毫米直径导管实现180°转向，弯曲半径3毫米，误差小于0.56毫米。
- 适合复杂分支路径导航，尤其适用于支气管等狭窄解剖结构。
磁控软性导管在实现高效推送力传输和近端集中弯曲以保证可操控性之间存在挑战：更高的轴向/弯曲刚度虽能提升力传递效率，但会降低可操控性；而较低刚度虽能实现大范围、近端集中的弯曲，但在压缩推送载荷下易发生扭结或屈曲。为解决这一权衡问题，本文提出一种刚度优化的多段磁控导管（SO-MAC），集成解耦的推进-转向机制与梯度刚度架构。在推进过程中，导管近端保持稳定的弯曲枢轴，远端被动自伸直以传输推进力，得益于优化的刚度分布及弹簧背骨对摩擦诱发扭结/屈曲的弹性恢复能力。在0–180°联合转向与推进过程中，枢轴位置保持稳定，远端尖端几乎沿直线朝目标方向前进。1.5毫米直径的SO-MAC实现了最大180°转向，10毫米处尖端弯曲半径为3毫米，平均形状误差为1.39 ± 0.56毫米，转向枢轴误差为0.35 ± 0.10毫米。在支气管仿体中的视觉反馈控制进一步验证了其在高度弯曲、分叉路径中稳健导航的能力。
原文摘要 · Abstract (English)
Achieving both efficient pushability (propulsion transmission) and proximally concentrated bending for steerability is challenging for magnetically actuated soft catheters: higher axial/bending stiffness improves force transmission but reduces steerability, whereas lower stiffness enables large, proximally concentrated bending yet increases kinking/buckling risk under compressive push loads. To address this trade-off, we propose a stiffness-optimized multi-segment magnetically actuated catheter (SO-MAC) that integrates a decoupled steering-advancement mechanism with a gradient-stiffness architecture. The SO-MAC concentrates bending about a stable proximal pivot during advancement while the distal section passively self-straightens to transmit propulsion, aided by the optimized stiffness distribution and elastic recovery of the spring backbone against friction-induced kinking/buckling. Over $0{-}180^{\circ}$ combined steering and advancement, the pivot remained stable and the distal tip advanced near-straight toward the target direction. A 1.5 mm-diameter SO-MAC achieved up to $180^{\circ}$ steering with a 3 mm bending radius at its 10 mm tip, with an average shape error of $1.39 \pm 0.56$ mm and a steering-pivot error of $0.35 \pm 0.10$ mm. Visual feedback control in a bronchial phantom further confirmed robust navigation through highly curved, bifurcating paths.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。