It is all kinds of data monitoring for ICU that are very important, on the one hand, it can provide reliable reference for medical personnel, so that they can care for critical patients in time, on the other hand, it also can avoid bringing trouble which is caused by instrument to severe patients. Through the mining technology of time series data ,this paper uses online segmentation algorithm of time series, establishing continuous monitoring data model for ICU and creating a time series Table, from the data of which, it can quickly extract monitoring data, and do real-time analysis. On this basis, this paper also puts forward an evaluation method for on-line segmentation algorithm performance , and also puts forward a kind of algorithm to speed up the time sequence segmentation recursion method, which can quickly extract the key components in the data, so as to accelerate the analysis on continuous monitoring data . Finally, through the continuous monitoring and analysis on the pressure of the severe patients who are inserted artificial airway balloon, this paper tests the reliability of the algorithm, and through the analysis and comparison with the data, it proves the quickness of algorithm, and provides a theoretical basis for analysis on continuous monitoring data for ICU.
Combining automated on-line segmentation and incremental clustering for whole body motions