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作 者:胡保华 朱宗俊 穆景颂 金飞翔 鲁翠萍 王勇[4] HU Baohua;ZHU Zongjun;MU Jingsong;JIN Feixiang;LU Cuiping;WANG Yong(School of Advanced Manufacturing Engineering,Hefei University,Hefei 230601,China;Department of Acupuncture and Rehabilitation,the First Affiliated Hospital of Anhui University of Chinese Medicine,Hefei 230031,China;Department of Rehabilitation Medicine,the First Affiliated Hospital of University of Science and Technology of China,Hefei 230001,China;School of Mechanical Engineering,Hefei University of Technology,Hefei 230009,China)
机构地区:[1]合肥学院先进制造工程学院,安徽合肥230601 [2]安徽中医药大学第一附属医院针灸康复科,安徽合肥230031 [3]中国科学技术大学第一附属医院康复医学科,安徽合肥230001 [4]合肥工业大学机械工程学院,安徽合肥230009
出 处:《中国医学物理学杂志》2023年第5期589-594,共6页Chinese Journal of Medical Physics
基 金:国家自然科学基金(U1713210);安徽省科技重大专项(202103a07020009);合肥学院人才科研基金(21-22RC01)。
摘 要:基于传统互模糊熵,结合分数阶微积分提出分数阶互模糊熵(C-FFuzzyEn),并基于该算法分析混沌耦合系统的同步性,进行健康对照者和癫痫患者不同脑区脑电信号的耦合性对比。结果表明,与传统互模糊熵相比,C-FFuzzyEn提高了不同耦合度模型的区分能力;与健康对照者相比,癫痫患者在癫痫发作时不同通道脑电信号之间C-FFuzzyEn较小,与癫痫发作时各神经元同步放电现象相吻合;相比互模糊熵,C-FFuzzyEn区分健康对照者与癫痫患者脑区之间脑电信号同步性的效果更好。C-FFuzzyEn可应用于脑电信号等神经电生理信号的同步性分析。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.
分 类 号:R318[医药卫生—生物医学工程]
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