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Automated anxiety detection using probabilistic binary pattern with ECG signals.

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第一作者： Mehmet,Baygin

第一单位： Department of Computer Engineering, Faculty of Engineering and Architecture, Erzurum Technical University, Erzurum, Turkey.

作者： Mehmet,Baygin ^[1] ; Prabal Datta,Barua ^[2] ; Sengul,Dogan ^[3] ; Turker,Tuncer ^[4] ; Tan Jen,Hong ^[5] ; Sonja,March ^[6] ; Ru-San,Tan ^[7] ; Filippo,Molinari ^[8] ; U Rajendra,Acharya ^[9]

作者单位： Department of Computer Engineering, Faculty of Engineering and Architecture, Erzurum Technical University, Erzurum, Turkey. ^[1] School of Business (Information System), University of Southern Queensland, Australia. ^[2] Department of Digital Forensics Engineering, College of Technology, Firat University, 23119, Elazig, Turkey. Electronic address: sdogan@firat.edu.tr. ^[3] Department of Digital Forensics Engineering, College of Technology, Firat University, 23119, Elazig, Turkey. ^[4] Data Science and Artificial Intelligence Lab, Singapore General Hospital, Singapore. ^[5] Centre for Health Research, University of Southern Queensland, Australia; School of Psychology and Wellbeing, University of Southern Queensland, Australia. ^[6] Department of Cardiology, National Heart Centre Singapore, Singapore; Duke-NUS Medical School, Singapore. ^[7] Biolab, PolitoBIOMed Lab, Department of Electronics and Telecommunications, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Turin, Italy. ^[8] Centre for Health Research, University of Southern Queensland, Australia; School of Mathematics, Physics and Computing, University of Southern Queensland, Springfield, Australia. ^[9]

关键词 ECG signal classification ECG-based mood detection Feature engineering Probabilistic binary pattern combinational majority voting

医学主题词人类(Humans);心电描记术(Electrocardiography);小波分析(Wavelet Analysis);算法(Algorithms);焦虑(Anxiety);焦虑症(Anxiety Disorders);信号处理, 计算机辅助(Signal Processing, Computer-Assisted)

DOI 10.1016/j.cmpb.2024.108076

PMID 38422891

发布时间 2024-03-18

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