Coordination and timing in repetitive movements have been intensively investigated in diverse experimental settings for understanding the underlying basic mechanisms in healthy controls. On this basic research side, there are mainly two theoretical models: the Wing-Kristofferson (WK) model and the Haken-Kelso-Bunz (HKB) model. On the clinical side of the research, several efforts have been spent on quantitatively assessing gait and other repetitive movements such as tapping, especially as an outcome measure of clinical trials in diverse neurological disorders. Nevertheless, Parkinson’s disease (PD) remains the predominant disorder in the clinical literature in this context, as the tremor activity and the changes in the gait are both common symptoms in PD. Although there are motion recording systems for data acquisition in clinical settings, the tools for analysis and quantification of the extracted time-series offered by these systems are severely restricted. Therefore, we introduce a toolbox which enables the analysis of repetitive movements within the framework of the two main theoretical models of motor coordination, which explicitly focuses on varying clinical and experimental settings such as self-paced vs. cued or uni-manual vs. bi-manual measurements. The toolbox contains particular pipelines for digital signal processing. Licensed under the GNU General Public License (GNU-GPL), the open source toolbox is freely available and can be downloaded from the Github link: https://github.com/MehmetEylemKirlangic/RepetitiveMovementAnalysis. We illustrate the application of the toolbox on sample experiments of gait and tapping with a control subject, as well as with a Parkinson’s patient. The patient has gone through a brain surgery for deep brain stimulation (DBS); hence, we present the results for both stimulation ON and stimulation OFF modes. Sample data are freely accessible at: https://github.com/MehmetEylemKirlangic/DATA.

中文翻译：

---

一个用于分析重复运动的Matlab工具箱：在步态和拍打实验中的应用。

重复运动中的协调和时间安排已在各种实验环境中进行了深入研究，以了解健康对照的基本基本机制。在基础研究方面，主要有两个理论模型：Wing-Kristofferson（WK）模型和Haken-Kelso-Bunz（HKB）模型。在研究的临床方面，已经花费了许多精力来定量评估步态和其他重复性动作，例如拍击，尤其是作为对各种神经系统疾病进行临床试验的结果指标。然而，在这种情况下，帕金森氏病（PD）仍然是临床文献中的主要疾病，因为震颤活动和步态变化都是PD的常见症状。尽管有运动记录系统可以在临床环境中采集数据，这些系统提供的用于分析和量化提取的时间序列的工具受到严格限制。因此，我们引入了一个工具箱，该工具箱可以在两个主要的运动协调性理论模型的框架内分析重复运动，该模型明确地专注于变化的临床和实验设置，例如自定速度，提示，单手或双向。 -手动测量。该工具箱包含用于数字信号处理的特定管道。开源工具箱是根据GNU通用公共许可证（GNU-GPL）许可的，可免费获得，并可从Github链接下载：https：//github.com/MehmetEylemKirlangic/RepetitiveMovementAnalysis。我们说明了该工具箱在步态和与对照对象拍打的示例实验中的应用，以及帕金森氏症患者。该患者已接受脑部手术以进行深部脑刺激（DBS）；因此，我们给出了刺激开和关模式的结果。样本数据可从以下网址免费访问：https：//github.com/MehmetEylemKirlangic/DATA。