Chulalongkorn Centre of Excellence for Parkinson's Disease & Related Disorders, Division of Neurology, Department of Medicine, Faculty of Medicine, Chulalongkorn University and King Chulalongkorn Memorial Hospital, Thai Red Cross Society, Bangkok, Thailand.
Department of Computer Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand.
J Parkinsons Dis. 2023;13(6):975-988. doi: 10.3233/JPD-230029.
Impaired dexterity is an early motor symptom in Parkinson's disease (PD) that significantly impacts the daily activity of patients; however, what constitutes complex dexterous movements remains controversial.
To explore the characteristics of finger dexterity in mild-to-moderate stage PD.
We quantitatively assessed finger dexterity in 48 mild-to-moderate stage PD patients and 49 age-matched controls using a simple alternating two-finger typing test for 15 seconds. Time-series analyses of various kinematic parameters with machine learning were compared between sides and groups.
Both the more and less affected hands of patients with PD had significantly lower typing frequency and slower typing velocity than the non-dominant and the dominant hands of controls (p = 0.019, p = 0.016, p < 0.001, p < 0.001). The slope of the typing velocity decreased with time, indicating a sequence effect in the PD group. A typing duration of 6 seconds was determined sufficient to discriminate PD patients from controls. Typing error, repetition, and repetition rate were significantly higher in the more affected hands of patients with PD than in the non-dominant hand of controls (p < 0.001, p = 0.03, p < 0.001). The error rate was constant, whereas the repetition rate was steep during the initiation of typing. A predictive model of the more affected hand demonstrated an accuracy of 70% in differentiating PD patients from controls.
Our study demonstrated complex components of impaired finger dexterity in mild-to-moderate stage PD, namely bradykinesia with sequence effects, error, and repetition at the initiation of movement, suggesting that multiple neural networks may be involved in dexterity deficits in PD.
在帕金森病(PD)中,动作不灵活是早期运动症状之一,严重影响患者的日常活动;然而,复杂的灵巧运动的构成仍存在争议。
探讨轻度至中度 PD 患者手指灵巧度的特点。
我们使用简单的交替双指打字测试对 48 名轻度至中度 PD 患者和 49 名年龄匹配的对照者进行 15 秒的手指灵巧度定量评估。使用机器学习对各种运动学参数的时间序列分析进行了比较。
PD 患者的双侧受累手打字频率明显低于对照组的非优势手和优势手(p = 0.019,p = 0.016,p < 0.001,p < 0.001),打字速度也较慢。打字速度随时间下降的斜率表明 PD 组存在序列效应。打字持续时间为 6 秒足以将 PD 患者与对照组区分开来。PD 患者双侧受累手的打字错误、重复和重复率明显高于对照组的非优势手(p < 0.001,p = 0.03,p < 0.001)。错误率保持不变,而在开始打字时重复率较高。更受累手的预测模型在区分 PD 患者和对照组方面的准确率为 70%。
我们的研究表明,在轻度至中度 PD 中存在手指灵巧度受损的复杂成分,即运动启动时出现的运动迟缓、错误和重复,提示在 PD 中灵巧度缺陷可能涉及多个神经网络。