Matching of quasi-periodic time series patterns by exchange of block-sorting signatures

We propose a novel method for quasi-periodic time series patterns matching, through signature exchange between the two patterns. The signature is obtained through sorting of the time series on magnitude. The advantage is that the difficult task of comparing the two patterns can be easily performed as a result of this exchange: The original time series is compared (point to point matching) to the reconstructed time series obtained through the reverse process, using the other time series signature. The matching is such that periods in one time series are put into correspondence with periods in the other time series, even if the time series is of different basic patterns and/or different lengths. The method is simple to implement and requires no parameters. It was compared to the very appreciated DTW algorithm on execution time, space and accuracy. Due to the quasi-periodic nature of the electrocardiogram, the tests were performed on ECG traces, selected from the Massachusetts Institute of Technology – Beth Israel Hospital (MITBIH) public database. Results show that the proposed method outperforms DTW on all aspects. This suggests that our method could be a good alternative to the classical DTW technique for quasi-periodic signals comparison. Specific applications are foreseen for our method: Novelty detection and person identification using ECG.