Dual-modal Physiological Feature Fusion-based Sleep Recognition Using CFS and RF Algorithm

作     者：Bing-Tao Zhang Xiao-Peng Wang Yu Shen Tao Lei 

作者机构：School of Electronic and Information EngineeringLanzhou Jiaotong UniversityLanzhou 730070China Key Laboratory of Opto-technology and Intelligent Conrtol Ministry of EducationLanzhou Jiaotong UniverstiyLanzhou 730070China School of Information Science and EngineeringLanzhou UniversityLanzhou 730000China College of Electronical and Information EngineeringShaanxi University of Science and TechnologyXi'an 710021China 

出 版 物：《International Journal of Automation and computing》 (国际自动化与计算杂志（英文版）)

年 卷 期：2019年第16卷第3期

页      面：286-296页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 0802[工学-机械工程] 0701[理学-数学] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by National Natural Science Foundation of China (Nos. 61761027 and 61461025) the Yong Scholar Fund of Lanzhou Jiaotong University (No. 2016004) the Teaching Reform Project of Lanzhou Jiaotong University (No. JGY201841) 

主　　题：Feature fusion mild difficulty in falling asleep(MDFA) decision support tool sleep issues optimal feature set 

摘      要：Research has demonstrated a significant overlap between sleep issues and other medical *** this paper,we consider mild difficulty in falling asleep(MDFA).Recognition of MDFA has the potential to assist in the provision of appropriate treatment plans for both sleep issues and related medical *** issue in the diagnosis of MDFA lies in *** address this issue,a decision support tool based on dual-modal physiological feature fusion which is able to automatically identify MDFA is proposed in this *** attention is given to the problem of how to extract candidate features and fuse dual-modal *** the identification of the optimal feature set,this study considers the correlations between each feature and class and evaluates correlations between the inter-modality ***,the recognition accuracy was measured using 10-fold cross *** experimental results for our method demonstrate improved *** highest recognition rate of MDFA using the optimal feature set can reach 96.22%.Based on the results of current study,the authors will,in projected future research,develop a real-time MDFA recognition system.