Effects of Motor Preparation on Walking Ability in Active Ankle Dorsiflexion.

IF 3.2 Q2 CLINICAL NEUROLOGY
Hiroki Ito, Hideaki Yamaguchi, Ryosuke Yamauchi, Ken Kitai, Kazuhei Nishimoto, Takayuki Kodama
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引用次数: 0

Abstract

Background/objectives: This study aimed to examine the influence of brain activity during motor preparation on walking ability, focusing on motor control during active ankle dorsiflexion.

Methods: Participants were classified into high- and low-corticomuscular coherence (CMC), an index of neuromuscular control based on the median value. Biomechanical and neurophysiological indices of active ankle dorsiflexion and walking ability were compared between the two groups. Additionally, a machine learning model was developed to accurately predict the CMC classification using brain neural activity during motor preparation.

Results: The Cz-TA CMC (beta frequency band) during active ankle dorsiflexion successfully detected significant differences in the maximum dorsiflexion angle, inversion angular velocity, brain activity localization, and variations in Cz beta power values during the transition from motor preparation to execution. Furthermore, CMC identified significant differences in dorsiflexion angle changes after toe-off and inversion angles at initial contact during gait. A support-vector machine model predicting high or low CMC demonstrated high accuracy (Accuracy: 0.96, Precision: 0.92-1.00, Recall: 0.91-1.00, F1 Score: 0.95-0.96) during motor execution based on beta power values from -500 to 0 ms prior to the initiation of active ankle dorsiflexion (representing motor preparation).

Conclusions: These findings highlight that the motor preparation processes of the brain during active ankle dorsiflexion are involved in walking ability and can be used to predict it. This indicator is independent of disease severity and holds the potential to provide a clinically versatile evaluation method.

运动准备对踝关节主动背屈行走能力的影响。
背景/目的:本研究旨在研究运动准备过程中大脑活动对行走能力的影响,重点研究踝关节主动背屈时的运动控制。方法:参与者被分为高、低皮质肌相干性(CMC), CMC是一种基于中位数的神经肌肉控制指标。比较两组患者踝关节活动背屈和行走能力的生物力学和神经生理指标。此外,还开发了一个机器学习模型,利用运动准备过程中的脑神经活动准确预测CMC分类。结果:踝关节主动背屈时Cz- ta CMC (β频带)成功检测到最大背屈角度、倒置角速度、脑活动定位以及从运动准备到执行过渡期间Cz β功率值的变化。此外,CMC鉴定了脱趾后背屈角变化和步态初始接触时的倒置角的显著差异。在运动执行过程中,基于主动踝关节背屈开始前-500至0 ms(代表运动准备)的beta功率值,支持向量机模型预测高CMC或低CMC具有较高的准确性(准确度:0.96,精密度:0.92-1.00,召回率:0.91-1.00,F1评分:0.95-0.96)。结论:这些研究结果表明,踝关节主动背屈时大脑的运动准备过程与行走能力有关,并可用于预测行走能力。该指标独立于疾病严重程度,具有提供临床通用评估方法的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Neurology International
Neurology International CLINICAL NEUROLOGY-
CiteScore
3.70
自引率
3.30%
发文量
69
审稿时长
11 weeks
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