Multiscale multidimensional recurrence quantitative analysis for analysing MEG signals in patients with schizophrenia
| Autor: | Jun Wang, Zhiwei Lv, Wenpo Yao, Wei Yan, Dengxuan Bai |
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| Rok vydání: | 2021 |
| Předmět: |
Computer science
business.industry Schizophrenia (object-oriented programming) 0206 medical engineering Biomedical Engineering Health Informatics Pattern recognition 02 engineering and technology Lorenz system behavioral disciplines and activities 020601 biomedical engineering 03 medical and health sciences Nonlinear system 0302 clinical medicine Chronic disease Quantitative analysis (finance) Potential biomarkers Signal Processing In patient Artificial intelligence Schizophrenia research business 030217 neurology & neurosurgery |
| Zdroj: | Biomedical Signal Processing and Control. 68:102586 |
| ISSN: | 1746-8094 |
| DOI: | 10.1016/j.bspc.2021.102586 |
| Popis: | Schizophrenia is a very serious chronic disease with very high hazards. Its pathogenesis is still unclear, and searching for its potential biomarkers has always been a popular issue in the field of schizophrenia research. Nonlinear dynamic analysis of magnetoencephalogram (MEG) signals in patients with schizophrenia is helpful to solve this problem. To quantitatively analyse multiscale recurrence information of MEG signals in patients with schizophrenia, this investigation propose a novel approach termed the multiscale multidimensional recurrence quantitative analysis (MsMdRQA). We first employed two sets of model series, which were generated by Lorenz and Rossler systems, to test the effectiveness of MsMdRQA in nonlinear analysis and to analyse the effects of dimension. Then we applied MsMdRQA to analyse MEG signals in schizophrenia. The test results suggest that both the Lorenz system and the Rossler system have different recurrence states at different scales; therefore, they effectively reflect the internal structure information of the Lorenz system and the Rossler system. Furthermore, we found that the recurrence values of the MEG signals in patients with schizophrenia were significantly lower (p |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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