Turning Detection During Gait: Algorithm Validation and Influence of Sensor Location and Turning Characteristics in the Classification of Parkinson's Disease.
Turning Detection During Gait: Algorithm Validation and Influence of Sensor Location and Turning Characteristics in the Classification of Parkinson's Disease.
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步态期间的转弯检测：帕金森病分类中传感器位置和转向特征的算法验证和影响。
DOI：
10.3390/s20185377
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发表时间：
2020-09-19
期刊：
影响因子：
--
通讯作者：
Alcock L
中科院分区：
文献类型：
--
作者：
Rehman RZU;Klocke P;Hryniv S;Galna B;Rochester L;Del Din S;Alcock L
帕金森病(PD)是一种常见的神经退行性疾病，导致一系列影响步态、平衡和转身的活动障碍。在本文中，我们介绍了：(I)步态中转弯检测算法的开发和验证；(Ii)转弯特征的提取方法；(Iii)利用转弯特征对PD进行分类。37名帕金森病患者和56名对照组在间歇性步行任务中进行了180度转弯。惯性测量单元安装在头部、颈部、下背部和脚踝上。开发了一种转弯检测算法，并通过两个评分器使用视频数据进行了验证。提取时空特征和基于信号的特征，并用于局部放电分类。评分者与识别转弯开始和结束的算法(ICC≥0.99)之间有很好的绝对一致性。分类模型(偏最小二乘判别分析)对上半身和踝关节数据的训练准确率最高，为97.85%。利用颈部、下背部和脚踝的转体特征，获得了平衡的敏感性(97%)和特异性(96.43%)。转身特征，特别是角速度、持续时间、步数、急转力和均方根，准确区分轻-中度PD和对照组，值得进一步检查，作为PD患者行动能力受损和跌倒风险的标志。
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.
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影响因子：
2.4
作者：
Crenna, P.;Carpinella, I.;Ferrarin, M.
通讯作者：
Ferrarin, M.
影响因子：
2.4
作者：
Hartmann, Antonia;Luzi, Susanna;de Bruin, Eling D.
通讯作者：
de Bruin, Eling D.
影响因子：
4.1
作者：
Lawson RA;Yarnall AJ;Duncan GW;Breen DP;Khoo TK;Williams-Gray CH;Barker RA;Collerton D;Taylor JP;Burn DJ;ICICLE-PD study group
通讯作者：
ICICLE-PD study group
影响因子：
3.6
作者：
Hulbert, Sophia;Ashburn, Ann;Verheyden, Geert
通讯作者：
Verheyden, Geert
影响因子：
8.6
作者：
Huxham, Frances;Baker, Richard;Iansek, Robert
通讯作者：
Iansek, Robert