Permutation Complexity Measure Applied in Brain-Computer Interface Signal Analysis
Tong Qin-ye · Chuangan jishu xuebao · 2007
With the method of permutation partition, Lempel-Ziv complexity and new-defined Lattice complexity were applied to analyze signal of brain-computer interface. Because of the important modification made on permutation partitions of nonlinear time series, this coarse graining method now can be generally used on arbitrary series. In this study, the permutation partition and the common-used average partition were compared with each other, both accompanied by empirical mode decomposition. The results showed that the complexity measure based on permutation partition could do the job even more than the best result of average partition made on empirical mode decomposition. It confirmed that permutation complexity measure could be a useful new way to analyze brain data, especially under the occasion that rapidly processing was needed-brain-computer interface for instance.