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首页> 外文会议>2016 IEEE Healthcare Innovation Point-Of-Care Technologies Conference >Gait monitoring system for patients with Parkinson's disease using wearable sensors
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Gait monitoring system for patients with Parkinson's disease using wearable sensors

机译：使用可穿戴式传感器的帕金森氏病患者步态监测系统

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The goal of this research is to develop a gait monitoring system for patients with Parkinson's disease (PD) using wearable sensors. To achieve this objective, the first step of our work is to identify the most significant features that would best distinguish between subjects with PD and healthy control subjects. Here, various gait features were extracted using data obtained from an online database (Physionet) and further analyzed to find the most significant features that would provide the best discrimination between the two groups. The statistical analysis of variance (ANOVA) test was conducted to differentiate the subjects based on the values of the mean and pattern classification was carried out using the Linear Discriminant Analysis (LDA) algorithm. The results show that a distinct set of gait features (step distance, stance and swing phases) contributed significantly in achieving a better classification accuracy rate.
机译：这项研究的目标是使用可穿戴传感器为帕金森氏病（PD）患者开发一种步态监测系统。为了实现这个目标，我们的工作的第一步是确定最重要的特征，这些特征可以最好地区分PD受试者和健康对照受试者。在这里，使用从在线数据库（Physionet）获得的数据来提取各种步态特征，并对其进行进一步分析，以找到能够在两组之间提供最佳区分的最重要特征。进行了方差统计分析（ANOVA）测试，以基于均值来区分受试者，并使用线性判别分析（LDA）算法进行了模式分类。结果表明，一组独特的步态特征（步距，姿势和挥杆阶段）显着有助于实现更好的分类准确率。

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