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

文献类型：期刊论文

作者Bing-Tao Zhang2,3,4; Xiao-Peng Wang4; Yu Shen4
刊名International Journal of Automation and Computing
出版日期2019
卷号16期号:3页码:286-296
关键词Feature fusion mild difficulty in falling asleep (MDFA) decision support tool sleep issues optimal feature set.
ISSN号1476-8186
DOI10.1007/s11633-019-1171-1
英文摘要Research has demonstrated a significant overlap between sleep issues and other medical conditions. In 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 conditions. An issue in the diagnosis of MDFA lies in subjectivity. To 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 study. Special attention is given to the problem of how to extract candidate features and fuse dual-modal features. Following the identification of the optimal feature set, this study considers the correlations between each feature and class and evaluates correlations between the inter-modality features. Finally, the recognition accuracy was measured using 10-fold cross validation. The experimental results for our method demonstrate improved performance. The 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.
源URL[http://ir.ia.ac.cn/handle/173211/42338]  
专题自动化研究所_学术期刊_International Journal of Automation and Computing
作者单位1.College of Electronical and Information Engineering, Shaanxi University of Science and Technology, Xi′an 710021, China
2.School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, China
3.Key Laboratory of Opto-technology and Intelligent Conrtol Ministry of Education, Lanzhou Jiaotong Universtiy, Lanzhou 730070, China
4.School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
推荐引用方式
GB/T 7714		 Bing-Tao Zhang,Xiao-Peng Wang,Yu Shen. Dual-modal Physiological Feature Fusion-based Sleep Recognition Using CFS and RF Algorithm[J]. International Journal of Automation and Computing,2019,16(3):286-296.
APA Bing-Tao Zhang,Xiao-Peng Wang,&Yu Shen.(2019).Dual-modal Physiological Feature Fusion-based Sleep Recognition Using CFS and RF Algorithm.International Journal of Automation and Computing,16(3),286-296.
MLA Bing-Tao Zhang,et al."Dual-modal Physiological Feature Fusion-based Sleep Recognition Using CFS and RF Algorithm".International Journal of Automation and Computing 16.3(2019):286-296.

入库方式： OAI收割

来源：自动化研究所

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