Biomimetic Octopus Suction Cup with Attachment Force Self-Sensing Capability for Cardiac Adhesion.

Soft robotics Pub Date : 2024-12-01 Epub Date: 2024-07-09 DOI:10.1089/soro.2023.0208
Ziwei Wang, Guangkai Sun, Xinwei Fan, Peng Xiao, Lianqing Zhu
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Abstract

This study develops a biomimetic soft octopus suction device with integrated self-sensing capabilities designed to enhance the precision and safety of cardiac surgeries. The device draws inspiration from the octopus's exceptional ability to adhere to various surfaces and its sophisticated proprioceptive system, allowing for real-time adjustment of adhesive force. The research integrates thin-film pressure sensors into the soft suction cup design, emulating the tactile capabilities of an octopus's sucker to convey information about the contact environment in real time. Signals from sensors within soft materials exhibiting complex strain characteristics are processed and interpreted using the grey wolf optimizer-back propagation (GWO-BP) algorithm. The tissue stabilizer is endowed with the self-sensing capabilities of biomimetic octopus suckers, and real-time feedback on the adhesion state is provided. The embedding location of the thin-film pressure sensors is determined through foundational experiments with flexible substrates, standard spherical tests, and biological tissue trials. The newly fabricated suction cups undergo compression pull-off tests to collect data. The GWO-BP algorithm model accurately identifies and predicts the suction cup's adhesion force in real time, with an error rate below 0.97% and a mean prediction time of 0.0027 s. Integrating this technology offers a novel approach to intelligent monitoring and attachment assurance during cardiac surgeries. Hence, the probability of potential cardiac tissue damage is reduced, with future applications for integrating intelligent biomimetic adhesive soft robotics.

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具有附着力自感应功能的仿生章鱼吸盘用于心脏粘附。
这项研究开发了一种具有集成自感功能的仿生软章鱼抽吸装置,旨在提高心脏手术的精确性和安全性。该装置从章鱼粘附在各种表面的卓越能力及其复杂的本体感觉系统中汲取灵感,可实时调整粘附力。研究将薄膜压力传感器集成到软吸盘设计中,模仿章鱼吸盘的触觉能力,实时传递接触环境的信息。使用灰狼优化器-反向传播(GWO-BP)算法处理和解释来自软材料内传感器的信号,这些软材料表现出复杂的应变特性。组织稳定器具有仿生章鱼吸盘的自感应能力,并能提供粘附状态的实时反馈。薄膜压力传感器的嵌入位置是通过柔性基底的基础实验、标准球形测试和生物组织试验确定的。对新制造的吸盘进行压缩拉脱试验,以收集数据。GWO-BP 算法模型能准确识别并实时预测吸盘的附着力,误差率低于 0.97%,平均预测时间为 0.0027 秒。因此,降低了潜在的心脏组织损伤概率,未来可应用于集成智能生物仿生粘附软机器人技术。
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