Neural electrophysiological signal synchronization analysis using C-FFuzzyEn(PDF)
《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]
- Issue:
- 2023年第5期
- Page:
- 589-594
- Research Field:
- 医学信号处理与医学仪器
- Publishing date:
Info
- Title:
- Neural electrophysiological signal synchronization analysis using C-FFuzzyEn
- Author(s):
- HU Baohua1; ZHU Zongjun2; MU Jingsong3; JIN Feixiang1; LU Cuiping1; WANG Yong4
- 1. School of Advanced Manufacturing Engineering, Hefei University, Hefei 230601, China 2. Department of Acupuncture and Rehabilitation, the First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei 230031, China 3. Department of Rehabilitation Medicine, the First Affiliated Hospital of University of Science and Technology of China, Hefei 230001, China 4. School of Mechanical Engineering, Hefei University of Technology, Hefei 230009, China
- Keywords:
- Keywords: seizure cross fractional fuzzy entropy electrophysiological signal synchronization
- PACS:
- R318
- DOI:
- DOI:10.3969/j.issn.1005-202X.2023.05.011
- Abstract:
- Based on cross fuzzy entropy (C-FuzzyEn) and fractional calculus, cross fractional fuzzy entropy (C-FFuzzyEn) is proposed for analyzing the synchronization of coupled chaotic system and comparing the changes of EEG signal synchronization in healthy controls and epileptic patients. The results demonstrate that C-FFuzzyEn is superior to C-FuzzyEn in distinguishing models of different coupling degrees. In addition, compared with healthy controls, patients with epilepsy has lower C-FFuzzyEn during seizure activity, which is consistent with the synchronous firing of neurons during epileptic seizures. C-FFuzzyEn is better than C-FuzzyEn at distinguishing the synchronicity of EEG signals between brain regions in healthy controls and epileptic patients. C-FFuzzyEn can be used to analyze the synchronization of neural electrophysiological signals such as EEG signals.
Last Update: 2023-05-26