Fuzzy clustering of children with cerebral palsy based on temporal-distance gait parameters.
Fuzzy clustering of children with cerebral palsy based on temporal-distance gait parameters.
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DOI：
10.1109/86.650282
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发表时间：
1997-12-01
期刊：
影响因子：
--
通讯作者：
Vaughan, C L
中科院分区：
文献类型：
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作者：
O'Malley, M J;Abel, M F;Vaughan, C L
采用模糊聚类方法对88例痉挛型脑瘫患儿的时间-距离参数进行了分组。选择用于聚类的两个特征是步长和节奏，其使用基于68个神经系统完整儿童的群体的模型针对年龄和腿长进行归一化。使用神经系统完整的人口和集群有效性技术提供的信息，五个集群的脑瘫儿童。这五个集群中心代表了脑瘫儿童采用的不同行走策略。仅利用四个容易获得的参数-步幅，节奏，腿长和年龄-和少量的简单方程，就可以对任何患有痉挛性双瘫的儿童进行分类，并为五个聚类中的每一个生成个人的成员值。模糊聚类方法的临床实用性证明与手术前和手术后的测试数据与脑瘫（一个神经外科和一个骨科）的成员的五个集群的变化提供了一个客观的技术来衡量改善。该方法可用于研究其他临床实体，其中使用本文提供的算法建立不同的聚类中心。
Temporal-distance parameters for 88 children with the spastic diplegia form of cerebral palsy (CP) are grouped using the fuzzy clustering paradigm. The two features chosen for clustering are stride length and cadence which are normalized for age and leg length using a model based on a population of 68 neurologically intact children. Using information provided by the neurologically intact population and cluster validity techniques, five clusters for the children with cerebral palsy are identified. The five cluster centers represent distinct walking strategies adopted by children with cerebral palsy. Utilizing just four easily obtained parameters--stride length, cadence, leg length and age--and a small number of simple equations, it is possible to classify any child with spastic diplegia and to generate an individual's membership values for each of the five clusters. The clinical utility of the fuzzy clustering approach is demonstrated with pre- and post-operative test data for subjects with cerebral palsy (one neurosurgical and one orthopaedic) where changes in membership of the five clusters provide an objective technique for measuring improvement. This approach can be adopted to study other clinical entities where different cluster centers would be established using the algorithm provided here.