The time-varying coherent analysis of medical signals

The study of neuron-synchronization of EEG signals can help us to understand the underlying cognitive processes. The cognitive and information processing take place in different brain regions. In order to investigate how these distributed brain regions are linked together and the information is exchanged, the coherent analysis is frequently used as a tool for studying the relationship between two channel EEG. EEG signals are often expressed as time-varying processes. For this purpose, this paper proposes a modern time-frequency method, which employs an alternative way for quantifying synchrony with both temporal and spectral resolution. This modern analysis method combines the wavelet transform. with the coherence. The wavelet coherent spectrum is defined and computed from the EEG data set such that the cross wavelet magnitude spectra serves to indicate the degree of coherence and the cross wavelet phase can be used to provide the direction of information flow between channels on different cortical regions. Several real EEG data are collected based on a cognitive target. It is observed from the cross wavelet magnitude spectra and the phase that there are obviously differences during identifying both Chinese and English sentences. The researches are helpful for the study of English and Chinese to the Chinese students.