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An alternative of the sliding window approach in time series clustering of intracranial pressure for patients with traumatic brain injury

机译:脑外伤患者颅内压时间序列聚类中滑动窗口方法的替代方法

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In the paper, the controversial claim of the authors [3] that: “Clustering of time series subsequences, which are generated by the sliding window principle, is meaningless” is addressed and thoroughly tested. The test results confirmed the cited claim in respect with the synthetic pattern data, although, minor deviations depending on different window length have been obtained. For the retrospective set of real Intracranial Pressure (ICP) data acquired for the patients with the severe traumatic brain injury, we proposed an alternative of the sliding window approach consisting in the definition of specific segmentation of ICP records and in introducing six quantitative features. We show that clusterization in the corresponding feature vector space does not possess the property claimed by Keogh in [3].
机译:在本文中,作者[3]提出了有争议的主张:“通过滑动窗口原理生成的时间序列子序列的聚类是没有意义的”,并已对其进行了彻底的测试。测试结果证实了关于合成图案数据的引用权利要求,尽管已经获得了取决于不同窗长的微小偏差。对于严重颅脑外伤患者获得的真实颅内压(ICP)数据的回顾性研究,我们提出了一种滑动窗方法的替代方法,该方法包括定义ICP记录的特定分段并引入六个定量特征。我们表明,在相应的特征向量空间中的聚类不具有Keogh在[3]中声称的属性。

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