Exercise Science and Exercise Physiology Program, Kent State University, Kent, OH, USA.
Department of Physical Medicine and Rehabilitation, The University of Alabama at Birmingham, Birmingham, AL, USA.
Neurorehabil Neural Repair. 2024 Sep;38(9):693-704. doi: 10.1177/15459683241268556. Epub 2024 Aug 5.
Previous studies have established that increased Sample Entropy (SampEn) of cadence, a measure of non-linear variability, during dynamic cycling leads to greater improvements in motor function for individuals with Parkinson's disease (PD). However, there is significant variability in responses among individuals with PD due to symptoms and disease progression.
The aim of this study was to develop and test a paradigm for adapting a cycling exercise intervention using SampEn of cadence and rider effort to improve motor function.
Twenty-two participants were randomized into either patient-specific adaptive dynamic cycling (PSADC) or non-adaptive (NA) group. SampEn of cadence was calculated after each of the 12 sessions, and motor function was evaluated using the Kinesia test. Pearson's correlation coefficient was used to analyze the relationship between SampEn of cadence and motor function improvement. Multiple linear regression (MLR) was used to identify the strongest predictors of motor function improvement.
Pearson's correlation coefficient revealed a significant correlation between SampEn of cadence and motor function improvements ( = -.545, = .009), suggesting that higher SampEn of cadence led to greater motor function improvement. MLR demonstrated that SampEn of cadence was the strongest predictor of motor function improvement (β = -8.923, = -2.632, = .018) over the BMI, Levodopa equivalent daily dose, and effort.
The findings show that PSADC paradigm promoted a greater improvement in motor function than NA dynamic cycling. These data will be used to develop a predictive model to optimize motor function improvement after cycling in individuals with PD.
先前的研究已经证实，在动态骑行过程中，节奏的样本熵（SampEn）增加，这是一种衡量非线性可变性的指标，会导致帕金森病（PD）患者的运动功能得到更大的改善。然而，由于症状和疾病进展的不同，PD 患者之间的反应存在很大的差异。
本研究旨在开发和测试一种使用节奏的 SampEn 和骑手努力来适应骑行干预的范例，以改善运动功能。
22 名参与者被随机分配到患者特定自适应动态骑行（PSADC）或非自适应（NA）组。在 12 次骑行后，计算节奏的 SampEn，使用 Kinesia 测试评估运动功能。使用 Pearson 相关系数分析节奏的 SampEn 与运动功能改善之间的关系。使用多元线性回归（MLR）来确定运动功能改善的最强预测因子。
Pearson 相关系数显示，节奏的 SampEn 与运动功能改善之间存在显著相关性（r=-.545，p=0.009），表明较高的节奏的 SampEn 会导致更大的运动功能改善。MLR 表明，节奏的 SampEn 是运动功能改善的最强预测因子（β= -8.923，p= -2.632，p=0.018），超过了 BMI、左旋多巴等效日剂量和努力。
研究结果表明，PSADC 范例比 NA 动态骑行更能促进运动功能的改善。这些数据将用于开发一个预测模型，以优化 PD 患者骑行后运动功能的改善。
