Department of Electrical Engineering and Information Technology, University of Naples Federico II, 80125 Naples, Italy.
Institute of Care and Scientific Research of Telese of ICS Maugeri SPA SB, 82037 Telese Terme, Italy.
Sensors (Basel). 2022 Feb 22;22(5):1708. doi: 10.3390/s22051708.
The impact of neurodegenerative disorders is twofold; they affect both quality of life and healthcare expenditure. In the case of Parkinson's disease, several strategies have been attempted to support the pharmacological treatment with rehabilitation protocols aimed at restoring motor function. In this scenario, the study of upper limb control mechanisms is particularly relevant due to the complexity of the joints involved in the movement of the arm. For these reasons, it is difficult to define proper indicators of the rehabilitation outcome. In this work, we propose a methodology to analyze and extract an ensemble of kinematic parameters from signals acquired during a complex upper limb reaching task. The methodology is tested in both healthy subjects and Parkinson's disease patients (N = 12), and a statistical analysis is carried out to establish the value of the extracted kinematic features in distinguishing between the two groups under study. The parameters with the greatest number of significances across the submovements are duration, mean velocity, maximum velocity, maximum acceleration, and smoothness. Results allowed the identification of a subset of significant kinematic parameters that could serve as a proof-of-concept for a future definition of potential indicators of the rehabilitation outcome in Parkinson's disease.
神经退行性疾病的影响是双重的；它们既影响生活质量，又影响医疗保健支出。在帕金森病的情况下，已经尝试了几种策略来支持药物治疗，同时采用康复方案来恢复运动功能。在这种情况下，研究上肢控制机制特别重要，因为手臂运动涉及到关节的复杂性。出于这些原因，很难定义康复效果的适当指标。在这项工作中，我们提出了一种从复杂上肢运动任务中获取的信号中分析和提取运动学参数的方法。该方法在健康受试者和帕金森病患者（N=12）中进行了测试，并进行了统计分析，以确定提取的运动学特征在区分两组研究对象方面的价值。在子运动中具有最多显著意义的参数是持续时间、平均速度、最大速度、最大加速度和平滑度。结果确定了一组显著运动学参数，这些参数可以作为未来帕金森病康复效果潜在指标的概念验证。
