Gulde Philipp, Hermsdörfer Joachim
Sports and Health Sciences, Technical University of Munich, Munich, Germany.
Front Neurol. 2018 Sep 12;9:615. doi: 10.3389/fneur.2018.00615. eCollection 2018.
Smoothness is a main characteristic of goal-directed human movements. The suitability of approaches quantifying movement smoothness is dependent on the analyzed signal's structure. Recently, activities of daily living (ADL) received strong interest in research on aging and neurorehabilitation. Such tasks have complex signal structures and kinematic parameters need to be adapted. In the present study we examined four different approaches to quantify movement smoothness in ADL. We tested the appropriateness of these approaches, namely the number of velocity peaks per meter (NoP), the spectral arc length (SAL), the speed metric (SM) and the log dimensionless jerk (LDJ), by comparing movement signals from eight healthy elderly (67.1a ± 7.1a) with eight healthy young (26.9a ± 2.1a) participants performing an activity of daily living (making a cup of tea). All approaches were able to identify group differences in smoothness (Cohen's d NoP = 2.53, SAL = 1.95, SM = 1.69, LDJ = 4.19), three revealed high to very high sensitivity (z-scores: NoP = 1.96 ± 0.55, SAL = 1.60 ± 0.64, SM = 3.41 ± 3.03, LDJ = 5.28 ± 1.52), three showed low within-group variance (NoP = 0.72, SAL = 0.60, SM = 0.11, LDJ = 0.71), two showed strong correlations between the first and the second half of the task execution (intra-trial Rs: NoP = 0.22 n.s., SAL = 0.33, SM = 0.36, LDJ = 0.91), and one was independent of other kinematic parameters (SM), while three showed strong models of multiple linear regression (Rs: NoP = 0.61, SAL = 0.48, LDJ = 0.70). Based on our results we make suggestion toward use examined smoothness measures. In total the log dimensionless jerk proved to be the most appropriate in ADL, as long as trial durations are controlled.
流畅性是人类目标导向运动的一个主要特征。量化运动流畅性的方法是否适用取决于所分析信号的结构。最近，日常生活活动（ADL）在衰老和神经康复研究中受到了强烈关注。此类任务具有复杂的信号结构，运动学参数需要进行调整。在本研究中，我们考察了四种不同的方法来量化ADL中的运动流畅性。我们通过比较八名健康老年人（67.1岁±7.1岁）和八名健康年轻人（26.9岁±2.1岁）在进行一项日常生活活动（泡茶）时的运动信号，测试了这些方法的适用性，即每米速度峰值数量（NoP）、谱弧长（SAL）、速度指标（SM）和对数无量纲加加速度（LDJ）。所有方法都能够识别出流畅性方面的组间差异（Cohen's d：NoP = 2.53，SAL = 1.95，SM = 1.69，LDJ = 4.19），三种方法显示出高到非常高的敏感性（z分数：NoP = 1.96 ± 0.55，SAL = 1.60 ± 0.64，SM = 3.41 ± 3.03，LDJ = 5.28 ± 1.52），三种方法显示出较低的组内方差（NoP = 0.72，SAL = 0.60，SM = 0.11，LDJ = 0.71），两种方法显示出任务执行前半段和后半段之间有强相关性（试验内Rs：NoP = 0.22无显著性差异，SAL = 0.33，SM = 0.36，LDJ = 0.91），一种方法与其他运动学参数无关（SM），而三种方法显示出强多元线性回归模型（Rs：NoP = 0.61，SAL = 0.48，LDJ = 0.70）。基于我们的结果，我们对所考察的流畅性测量方法的使用提出了建议。总体而言，只要试验持续时间得到控制，对数无量纲加加速度在ADL中被证明是最合适的。
