Feature Selection for Accelerometer-Based Posture Analysis in Parkinson's Disease
Feature Selection for Accelerometer-Based Posture Analysis in Parkinson's Disease
复制标题
DOI：
10.1109/titb.2011.2107916
复制
发表时间：
2011-05-01
影响因子：
--
通讯作者：
Chiari, Lorenzo
中科院分区：
文献类型：
--
作者：
Palmerini, Luca;Rocchi, Laura;Chiari, Lorenzo
帕金森病（PD）的主要症状之一是姿势不稳，安静站立姿势分析是PD临床评估的重要组成部分。本研究的目的是评估使用加速度计来表征早期轻度PD受试者姿势行为的可行性。20 PD和20个控制对象，下背部佩戴加速度计，进行了测试，在五个条件下，其特征在于感官和注意力干扰。从信号中计算出总共175个测量值，以量化身体摇摆的震颤、加速度和位移。实施特征选择以识别更好地表征PD和对照受试者的独特行为的措施的子集。它基于不同的分类器和嵌套交叉验证，以最大限度地提高选择对训练集变化的鲁棒性。三个特征的几个子集实现了低至5%的错误分类率。其中许多包括震颤相关的措施，在频域的posturalmeasure，和姿势位移措施。结果表明，定量姿势分析，使用一个单一的加速度计和一个简单的测试协议，可以提供有用的信息，以表征早期PD科目。该方案可能用于监测疾病的进展。
Posture analysis in quiet standing is a key component of the clinical evaluation of Parkinson's disease (PD), postural instability being one of PD's major symptoms. The aim of this study was to assess the feasibility of using accelerometers to characterize the postural behavior of early mild PD subjects. Twenty PD and 20 control subjects, wearing an accelerometer on the lower back, were tested in five conditions characterized by sensory and attentional perturbation. A total of 175 measures were computed from the signals to quantify tremor, acceleration, and displacement of body sway. Feature selection was implemented to identify the subsets of measures that better characterize the distinctive behavior of PD and control subjects. It was based on different classifiers and on a nested cross validation, to maximize robustness of selection with respect to changes in the training set. Several subsets of three features achieved misclassification rates as low as 5%. Many of them included a tremor-related measure, a posturalmeasure in the frequency domain, and a postural displacement measure. Results suggest that quantitative posture analysis using a single accelerometer and a simple test protocol may provide useful information to characterize early PD subjects. This protocol is potentially usable to monitor the disease's progression.