神经功能康复:探讨神经肌肉重建技术的进展与挑战。

IF 5.9 2区 医学 Q2 CELL BIOLOGY
Neural Regeneration Research Pub Date : 2026-01-01 Epub Date: 2024-12-07 DOI:10.4103/NRR.NRR-D-24-00613
Chunxiao Tang, Ping Wang, Zhonghua Li, Shizhen Zhong, Lin Yang, Guanglin Li
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引用次数: 0

摘要

神经机器接口技术是一种开创性的方法,旨在解决由先天性疾病、创伤性损伤和神经系统疾病等疾病引起的神经功能障碍和残疾的复杂挑战。神经机接口技术与大脑或周围神经系统建立直接连接,恢复受损的运动、感觉和认知功能,显著提高患者的生活质量。本文综述了各种神经机接口技术的发展和整合,包括再生周围神经接口、靶向肌肉和感觉神经再生、激动-拮抗剂肌神经接口和脑机接口。柔性电子和生物工程的最新进展导致了更多生物相容性和高分辨率电极的发展,这提高了神经机器接口技术的性能和寿命。然而,重大的挑战仍然存在,如信号干扰,纤维组织封装,以及需要精确的解剖定位和重建。先进信号处理算法的集成,特别是那些利用人工智能和机器学习的算法,有可能提高神经信号解释的准确性和可靠性,这将使神经机器接口技术更加直观和有效。这些技术具有广泛而有影响力的临床应用,从假肢的运动恢复和感觉反馈到神经疾病治疗和神经康复。这篇综述表明,多学科合作将通过结合生物医学工程、临床外科和神经工程的见解来开发更复杂、更可靠的接口,在推进神经机器接口技术方面发挥关键作用。通过解决现有的限制和探索新的技术前沿,神经机器接口技术有可能彻底改变神经假肢和神经康复,有望增强神经损伤患者的活动性、独立性和生活质量。通过利用详细的解剖学知识和整合尖端的神经工程原理,研究人员和临床医生可以突破可能的界限,创造出越来越复杂和持久的假肢设备,为用户提供持续的好处。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Neural functional rehabilitation: Exploring neuromuscular reconstruction technology advancements and challenges.

Neural machine interface technology is a pioneering approach that aims to address the complex challenges of neurological dysfunctions and disabilities resulting from conditions such as congenital disorders, traumatic injuries, and neurological diseases. Neural machine interface technology establishes direct connections with the brain or peripheral nervous system to restore impaired motor, sensory, and cognitive functions, significantly improving patients' quality of life. This review analyzes the chronological development and integration of various neural machine interface technologies, including regenerative peripheral nerve interfaces, targeted muscle and sensory reinnervation, agonist-antagonist myoneural interfaces, and brain-machine interfaces. Recent advancements in flexible electronics and bioengineering have led to the development of more biocompatible and high-resolution electrodes, which enhance the performance and longevity of neural machine interface technology. However, significant challenges remain, such as signal interference, fibrous tissue encapsulation, and the need for precise anatomical localization and reconstruction. The integration of advanced signal processing algorithms, particularly those utilizing artificial intelligence and machine learning, has the potential to improve the accuracy and reliability of neural signal interpretation, which will make neural machine interface technologies more intuitive and effective. These technologies have broad, impactful clinical applications, ranging from motor restoration and sensory feedback in prosthetics to neurological disorder treatment and neurorehabilitation. This review suggests that multidisciplinary collaboration will play a critical role in advancing neural machine interface technologies by combining insights from biomedical engineering, clinical surgery, and neuroengineering to develop more sophisticated and reliable interfaces. By addressing existing limitations and exploring new technological frontiers, neural machine interface technologies have the potential to revolutionize neuroprosthetics and neurorehabilitation, promising enhanced mobility, independence, and quality of life for individuals with neurological impairments. By leveraging detailed anatomical knowledge and integrating cutting-edge neuroengineering principles, researchers and clinicians can push the boundaries of what is possible and create increasingly sophisticated and long-lasting prosthetic devices that provide sustained benefits for users.

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来源期刊
Neural Regeneration Research
Neural Regeneration Research CELL BIOLOGY-NEUROSCIENCES
CiteScore
8.00
自引率
9.80%
发文量
515
审稿时长
1.0 months
期刊介绍: Neural Regeneration Research (NRR) is the Open Access journal specializing in neural regeneration and indexed by SCI-E and PubMed. The journal is committed to publishing articles on basic pathobiology of injury, repair and protection to the nervous system, while considering preclinical and clinical trials targeted at improving traumatically injuried patients and patients with neurodegenerative diseases.
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