Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne NE2 4HH, UK.
Clinical Ageing Research Unit, Campus for Ageing and Vitality, Newcastle University, Newcastle upon Tyne NE4 5PL, UK.
Sensors (Basel). 2020 Sep 19;20(18):5377. doi: 10.3390/s20185377.
Parkinson's disease (PD) is a common neurodegenerative disorder resulting in a range of mobility deficits affecting gait, balance and turning. In this paper, we present: (i) the development and validation of an algorithm to detect turns during gait; (ii) a method to extract turn characteristics; and (iii) the classification of PD using turn characteristics. Thirty-seven people with PD and 56 controls performed 180-degree turns during an intermittent walking task. Inertial measurement units were attached to the head, neck, lower back and ankles. A turning detection algorithm was developed and validated by two raters using video data. Spatiotemporal and signal-based characteristics were extracted and used for PD classification. There was excellent absolute agreement between the rater and the algorithm for identifying turn start and end (ICC ≥ 0.99). Classification modeling (partial least square discriminant analysis (PLS-DA)) gave the best accuracy of 97.85% when trained on upper body and ankle data. Balanced sensitivity (97%) and specificity (96.43%) were achieved using turning characteristics from the neck, lower back and ankles. Turning characteristics, in particular angular velocity, duration, number of steps, jerk and root mean square distinguished mild-moderate PD from controls accurately and warrant future examination as a marker of mobility impairment and fall risk in PD.
帕金森病（PD）是一种常见的神经退行性疾病，导致一系列运动障碍，影响步态、平衡和转弯。在本文中，我们提出了：（i）一种用于检测步态中转弯的算法的开发和验证；（ii）一种提取转弯特征的方法；以及（iii）使用转弯特征对 PD 进行分类。37 名 PD 患者和 56 名对照者在间歇性行走任务中进行了 180 度转弯。头部、颈部、下背部和脚踝上都安装了惯性测量单元。开发了一种转弯检测算法，并使用视频数据由两名评估员进行验证。提取了时空和基于信号的特征，并用于 PD 分类。评估员和算法在识别转弯开始和结束时具有极好的绝对一致性（ICC≥0.99）。分类建模（偏最小二乘判别分析（PLS-DA））在对上肢和脚踝数据进行训练时，获得了最佳的准确率 97.85%。使用颈部、下背部和脚踝的转弯特征，实现了平衡的敏感性（97%）和特异性（96.43%）。转弯特征，特别是角速度、持续时间、步数、急动度和均方根，准确地区分了轻度至中度 PD 患者和对照组，可以作为 PD 患者运动障碍和跌倒风险的标志物进行进一步研究。
