Russo Michela, Amboni Marianna, Pisani Noemi, Volzone Antonio, Calderone Danilo, Barone Paolo, Amato Francesco, Ricciardi Carlo, Romano Maria
Department of Electrical Engineering and Information Technology, University of Naples Federico II, 80125 Naples, Italy.
Center for Neurodegenerative Diseases (CEMAND), Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, 84131 Salerno, Italy.
Sensors (Basel). 2025 Jan 9;25(2):338. doi: 10.3390/s25020338.
Parkinson's disease (PD) is characterized by a slow, short-stepping, shuffling gait pattern caused by a combination of motor control limitations due to a reduction in dopaminergic neurons. Gait disorders are indicators of global health, cognitive status, and risk of falls and increase with disease progression. Therefore, the use of quantitative information on the gait mechanisms of PD patients is a promising approach, particularly for monitoring gait disorders and potentially informing therapeutic interventions, though it is not yet a well-established tool for early diagnosis or direct assessment of disease progression. Over the years, many studies have investigated the spatiotemporal parameters that are altered in the PD gait pattern, while kinematic and kinetic gait parameters are more limited. A scoping review was performed according to the PRISMA guidelines. The Scopus and PubMed databases were searched between 1999 and 2023. A total of 29 articles were included that reported gait changes in PD patients under different gait conditions: single free walking, sequential motor task, and dual task. The main findings of our review highlighted the use of optoelectronic systems for recording kinematic parameters and force plates for measuring kinetic parameters, due to their high accuracy. Most gait analyses in PD patients have been conducted at self-selected walking speeds to capture natural movement, although studies have also examined gait under various conditions. The results of our review indicated that PD patients experience alterations in the range of motion of the hip, knee, and ankle joints, as well as a reduction in the power generated/absorbed and the extensor/flexor moments. These findings suggest that the PD gait pattern may be more effectively understood using kinematic and kinetic parameters.
帕金森病(PD)的特征是步态缓慢、步幅短小、拖曳,这是由于多巴胺能神经元减少导致运动控制受限所致。步态障碍是整体健康、认知状态和跌倒风险的指标,并随疾病进展而增加。因此,利用帕金森病患者步态机制的定量信息是一种很有前景的方法,特别是用于监测步态障碍并可能为治疗干预提供依据,尽管它尚未成为早期诊断或直接评估疾病进展的成熟工具。多年来,许多研究调查了帕金森病步态模式中改变的时空参数,而运动学和动力学步态参数的研究则较为有限。根据PRISMA指南进行了一项范围综述。在1999年至2023年期间检索了Scopus和PubMed数据库。共纳入29篇报告帕金森病患者在不同步态条件下(单自由行走、连续运动任务和双任务)步态变化的文章。我们综述的主要发现强调了使用光电系统记录运动学参数和测力板测量动力学参数,因为它们具有很高的准确性。帕金森病患者的大多数步态分析都是在自选步行速度下进行的,以捕捉自然运动,尽管也有研究在各种条件下检查步态。我们综述的结果表明,帕金森病患者的髋关节、膝关节和踝关节的运动范围发生改变,同时产生/吸收的功率以及伸肌/屈肌力矩也有所降低。这些发现表明,使用运动学和动力学参数可能更有效地理解帕金森病步态模式。