人类皮质脑和生物力学响应突然变化的外骨骼辅助行走。

IF 5.2 2区 医学 Q2 ENGINEERING, BIOMEDICAL
Seongmi Song;Courtney A. Haynes;J. Cortney Bradford
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引用次数: 0

摘要

机器人外骨骼已经取得了重大进展,但控制系统在提供与用户肌肉骨骼系统无缝对齐的辅助方面仍然面临挑战。为了增强用户与设备的互动,了解人类适应外骨骼辅助的神经机制是至关重要的。尽管大脑皮层活动在运动中起着至关重要的作用,但在行走时外骨骼辅助如何调节大脑皮层活动仍然知之甚少。本研究研究了外骨骼状态突变时的皮质动力学,以阐明大脑在步态适应中的作用。研究人员收集了21名健康成人在双侧踝关节外骨骼的跑步机上行走的EEG、运动学和肌肉活动数据。结果表明,额叶theta-band活动可以跟踪外骨骼状态的转变。适应在两步内发生,反映在额叶θ、α和β活动的变化,以及膝盖和脚踝运动范围和肌肉激活模式的变化。这些发现证明了EEG在外骨骼转换过程中对神经反应的敏感性,并强调了其在实现实时反馈以优化个性化辅助方面的潜在应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Human Cortical Brain and Biomechanical Responses to Abrupt Changes in Exoskeleton Assistance While Walking
Robotic exoskeletons have advanced significantly, yet control systems still face challenges in delivering assistance that seamlessly aligns with the user’s musculoskeletal system. To enhance user-device interaction, it is essential to understand the neural mechanisms underlying human adaptation to exoskeleton assistance. Although cortical brain activity plays a critical role in locomotion, how it is modulated by exoskeleton assistance while walking remains poorly understood. This study investigates cortical dynamics during abrupt exoskeleton state changes to clarify the brain’s role in gait adaptation. EEG, kinematic, and muscle activity data were collected from 21 healthy adults walking on a treadmill with bilateral ankle exoskeletons. Results reveal that frontal theta-band activity could track exoskeleton state transitions. Adaptations occurred within two strides, reflected in changes in frontal theta, alpha, and beta activity, along with variations in knee and ankle range of motion and muscle activation patterns. These findings demonstrate EEG’s sensitivity to neural responses during exoskeleton transitions and highlight its potential application for enabling real-time feedback to optimize personalized assistance.
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来源期刊
CiteScore
8.60
自引率
8.20%
发文量
479
审稿时长
6-12 weeks
期刊介绍: Rehabilitative and neural aspects of biomedical engineering, including functional electrical stimulation, acoustic dynamics, human performance measurement and analysis, nerve stimulation, electromyography, motor control and stimulation; and hardware and software applications for rehabilitation engineering and assistive devices.
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