Composite multiscale coherence and application to functionalcorticomuscular coupling

作     者：Xiaoling Chen Ying Liu Shengcui Cheng Tingting Shen Huipeng Gao Peiguo Hou Ping Xie 

作者机构：Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei ProvinceInstitute of Electric EngineeringYanshan UniversityQinhuangdaoHebeiChina Key Laboratory of Measurement Technology and Instrumentation of Hebei ProvinceInstitute of Electric EngineeringYanshan UniversityQinhuangdaoHebeiChina 

出 版 物：《Medicine in Novel Technology and Devices》 (医学中新技术与新装备（英文）)

年 卷 期：2023年第19卷第3期

页      面：70-81页

学科分类：1002[医学-临床医学] 100210[医学-外科学(含：普外、骨外、泌尿外、胸心外、神外、整形、烧伤、野战外)] 10[医学] 

基　　金：funded by National Natural Science Foundation of China grant(U20A20192 and 62076216) Hebei Natural Science Foundation(F2022203002,F2021203033 and G2020203012) Cultivation Project for Basic Research and Innovation of Yanshan University(2021LGZD010) the Funding Program for Innovative Ability Training of graduate students of Hebei Provincial Department of Education under Grant CXZZSS2022123 Hebei Innovation Capability Improvement Plan Project(22567619H) 

主　　题：Coherence Composite multiscale Coarse graining Functional corticomuscular coupling 

摘      要：Though coherence, a classical method to describe the linear correlation between two time series, has wideranging applications, from economics to neuroscience, it fails to illustrate the inherently multi-time scalesbased correlations. In this paper, we proposed a multiscale-like coherence model, defined as composite multiscalecoherence (CMSC) by combining the kth coarse-grain processing with the coherence. We made a comparison withthe multiscale coherence (MSC) with coarse-grain process in numerical data to compare the sensitivity profiles tothe coupling strength, data length and white Gaussian noise. After that, we applied the proposed model to explorethe functional corticomuscular coupling (FCMC) by analyzing the correlation between the EEG and EMG *** results reflected that the CMSC method were sensitive to the coupling strength, data length and thewhite Gaussian noise, and presented more stability along the time scale compared to the MSC method. Ourapplication of CMSC methods on the EEG and EMG signals indicated that the FCMC was of multi-time scalecharacteristics and higher coherence mainly consisted in the alpha and beta bands at about scale 10, thoughsignificant area showed a gradual decline with the scale increasing. Further comparison indicated that bothmodels are equally effective to describe the multiscale characteristics of the FCMC at lower time scales, whilesome differences emerge at the high time scales. Both simulation and experimental data demonstrate the effectiveness of the proposed multiscale-like model to describe the multiscale correlation between two time series. Thisstudy extends the relative researches on the FCMC to the multi-time scale.