Combining Multiple Concurrent Physiological Streams to Assessing Patients Condition

Multiple concurrent physiological streams generated by various medical devices play important roles in patient condition assessment. However, these physiological streams needto be analyzed together and output in real-time for preciseand timely controlling and management, which poses a non-trivial challenge to existing methods. This paper presents ourresearch on real-time assessing based on this kind of data.To address this problem, we first extract sketches from original data with the help of adaptive sampling and wave splittingalgorithm, then define scalable operators on sketches and propose MUNCA (MUlti-dimensional Nearest Center Analysis)to combine these multiple concurrent data together for anal-ysis. Experiments on real data demonstrate the effectiveness and efficiency of the proposed method.