通过仿生和神经接口推进假手功能。

IF 3.7
Neurorehabilitation and neural repair Pub Date : 2025-06-01 Epub Date: 2025-04-24 DOI:10.1177/15459683251331593
Mohammad Haghani Dogahe, Mark A Mahan, Miqin Zhang, Somaye Bashiri Aliabadi, Alireza Rouhafza, Sahand Karimzadhagh, Alireza Feizkhah, Abbas Monsef, Mehryar Habibi Roudkenar
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引用次数: 0

摘要

背景与目的假手的发展正处于一个变革阶段,融合了仿生学和神经接口技术来重新定义功能和感觉反馈。本文探讨了仿生设计原理和神经接口技术(NIT)在提高假手能力方面的共生关系。方法从生物系统中汲取灵感,研究人员旨在通过创新的假肢设计来复制人手的复杂运动和能力。这一努力的核心是NIT,促进人工设备和人类神经系统之间的无缝通信。制造方法的最新进展推动了脑机接口的发展,通过解码神经活动来精确控制假手。结果人类手部的解剖复杂性强调了理解生物力学、神经解剖学和控制机制对于制作有效的假肢解决方案的重要性。此外,实现功能齐全的半机械人手的目标需要多学科方法和仿生设计来复制身体的固有能力。通过结合临床医生、组织工程师、生物工程师、电子和数据科学家的专业知识,下一代植入式装置不仅在解剖学和生物力学上准确,而且还提供直观的控制、感觉反馈和本体感觉,从而推动了当前假肢技术的界限。结论通过融合机器学习算法、生物机电原理和先进的外科技术,假手可以在恢复触觉和本体感觉的同时实现实时控制。这篇论文为假手的发展提供了新的途径,对增强假手的功能、耐用性和安全性具有潜在的意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Advancing Prosthetic Hand Capabilities Through Biomimicry and Neural Interfaces.

Background and ObjectivesProsthetic hand development is undergoing a transformative phase, blending biomimicry and neural interface technologies to redefine functionality and sensory feedback. This article explores the symbiotic relationship between biomimetic design principles and neural interface technology (NIT) in advancing prosthetic hand capabilities.MethodsDrawing inspiration from biological systems, researchers aim to replicate the intricate movements and capabilities of the human hand through innovative prosthetic designs. Central to this endeavor is NIT, facilitating seamless communication between artificial devices and the human nervous system. Recent advances in fabrication methods have propelled brain-computer interfaces, enabling precise control of prosthetic hands by decoding neural activity.ResultsAnatomical complexities of the human hand underscore the importance of understanding biomechanics, neuroanatomy, and control mechanisms for crafting effective prosthetic solutions. Furthermore, achieving the goal of a fully functional cyborg hand necessitates a multidisciplinary approach and biomimetic design to replicate the body's inherent capabilities. By incorporating the expertise of clinicians, tissue engineers, bioengineers, electronic and data scientists, the next generation of the implantable devices is not only anatomically and biomechanically accurate but also offer intuitive control, sensory feedback, and proprioception, thereby pushing the boundaries of current prosthetic technology.ConclusionBy integrating machine learning algorithms, biomechatronic principles, and advanced surgical techniques, prosthetic hands can achieve real-time control while restoring tactile sensation and proprioception. This manuscript contributes novel approaches to prosthetic hand development, with potential implications for enhancing the functionality, durability, and safety of the prosthetic limb.

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