An alternative of the sliding window approach in time series clustering of intracranial pressure for patients with traumatic brain injury
Ivan Bajla, Radoslav Škoviera, Michal Teplan · 2017
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].