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首页> 美国卫生研究院文献>International Journal of Environmental Research and Public Health >Classification of Whole-Body Postural Discomfort Using Cluster Analysis
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Classification of Whole-Body Postural Discomfort Using Cluster Analysis

机译：使用聚类分析对全身姿势不适进行分类

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摘要

The objectives of this study were to evaluate the effect of gender and postures of the neck, trunk, and knee on overall postural discomfort, and to classify combined postures into different postural discomfort groups. A total of 95 participants (42 males and 53 females) performed 45 different static postures, which were a combination of 3 neck angles, 5 trunk angles, and 3 knee angles, and rated the perceived postural discomfort. Non-hierarchical K-means cluster analysis was employed to classify the 45 different combined postures into several postural discomfort groups. Postural discomfort was significantly affected by gender and postures of the neck, trunk, and knee (p < 0.001). Three clusters (high, medium, and low discomfort) were identified and the postural discomfort was significantly different between clusters (p < 0.001). The high discomfort group consisted of mostly males with high knee and trunk flexion angles and a moderate neck flexion angle. The low discomfort group was female-dominant with low neck and trunk flexion angles and a moderate knee flexion angle. The different flexibility (stiffness) of the joint motions between genders may affect the gender difference in postural discomfort. The knee and trunk postures were critical to the postural balance, which may affect the perception of whole-body discomfort. This result will be useful for developing and improving postural observation tools.
机译：本研究的目标是评估颈部，躯干和膝盖的性别和姿势对整体姿势不适的影响，并将综合姿势分类为不同的姿势不适群体。共有95名参与者（42名男性和53名女性）进行了45个不同的静态姿势，这是3个颈角，5个躯干角度和3个膝关节的组合，并评定了感知的姿势不适。非分级k均值集群分析用于将45种不同的组合姿势分类为几个姿势不适群体。姿势不适受颈部，躯干和膝关节的性别和姿势的显着影响（P <0.001）。鉴定了三种簇（高，培养基和低的不适），群集之间的姿势不适显着不同（P <0.001）。高度不适组由大多数膝关节和干屈曲角度和中等颈部屈曲角度组成的雄性。低不适群体是女性优势，具有低颈部和树干屈曲角度和适度的膝关节屈曲角度。性别之间的关节运动的不同灵活性（刚度）可能会影响姿势不适的性别差异。膝盖和干线姿势对姿势平衡至关重要，这可能影响全身不适的看法。该结果对于开发和改善姿势观察工具有用。

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