Department of Anatomy, School of Biomedical Sciences, University of Otago, Dunedin 9054, New Zealand.
Medical Technologies Centre of Research Excellence, Auckland 1142, New Zealand.
Sensors (Basel). 2022 Feb 25;22(5):1827. doi: 10.3390/s22051827.
The Unified Parkinson's Disease Rating Scale (UPDRS) is a subjective Parkinson's Disease (PD) physician scoring/monitoring system. To date, there is no single upper limb wearable/non-contact system that can be used objectively to assess all UPDRS-III motor system subgroups (i.e., tremor (T), rigidity (R), bradykinesia (B), gait and posture (GP), and bulbar anomalies (BA)). We evaluated the use of a non-contact hand motion tracking system for potential extraction of GP information using forearm pronation-supination (P/S) motion parameters (speed, acceleration, and frequency). Twenty-four patients with idiopathic PD participated, and their UPDRS data were recorded bilaterally by physicians. Pearson's correlation, regression analyses, and Monte Carlo validation was conducted for all combinations of UPDRS subgroups versus motion parameters. In the 262,125 regression models that were trained and tested, the models within 1% of the lowest error showed that the frequency of P/S contributes to approximately one third of all models; while speed and acceleration also contribute significantly to the prediction of GP from the left-hand motion of right handed patients. In short, the P/S better indicated GP when performed with the non-dominant hand. There was also a significant negative correlation (with medium to large effect size, range: 0.3-0.58) between the P/S speed and the single BA score for both forearms and combined UPDRS score for the dominant hand. This study highlights the potential use of wearable or non-contact systems for forearm P/S to remotely monitor and predict the GP information in PD.
统一帕金森病评定量表 (UPDRS) 是一种主观的帕金森病 (PD) 医师评分/监测系统。迄今为止,尚无一种可用于客观评估所有 UPDRS-III 运动系统亚组(即震颤 (T)、僵硬 (R)、运动迟缓 (B)、步态和姿势 (GP) 和延髓异常 (BA))的上肢可穿戴/非接触系统。我们评估了使用非接触式手部运动跟踪系统从旋前-旋后 (P/S) 运动参数(速度、加速度和频率)中提取 GP 信息的潜力。24 名特发性 PD 患者参与了研究,他们的 UPDRS 数据由医生进行双侧记录。对所有 UPDRS 亚组与运动参数的组合进行了 Pearson 相关、回归分析和蒙特卡罗验证。在训练和测试的 262125 个回归模型中,模型误差最低的模型表明,P/S 频率对大约三分之一的模型有贡献;而速度和加速度也对从右利手患者的左手运动预测 GP 有显著贡献。简而言之,非优势手进行 P/S 时,更能指示 GP。P/S 速度与 BA 单项评分以及惯用手的前臂和综合 UPDRS 评分之间存在显著负相关(中等至较大效应量,范围:0.3-0.58)。本研究强调了使用可穿戴或非接触式系统进行前臂 P/S 以远程监测和预测 PD 中 GP 信息的潜力。