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    Sleep apnea detection from single-lead ECG using features based on ECG -derived respiration (EDR) signals

    , Article IRBM ; Volume 39, Issue 3 , 2018 , Pages 206-218 ; 19590318 (ISSN) Janbakhshi, P ; Shamsollahi, M. B ; Sharif University of Technology
    Elsevier Masson SAS  2018
    Abstract
    Background and objective: One of the important applications of non-invasive respiration monitoring using ECG signal is the detection of obstructive sleep apnea (OSA). ECG-derived respiratory (EDR) signals, contribute to useful information about apnea occurrence. In this paper, two EDR extraction methods are proposed, and their application in automatic OSA detection using single-lead ECG is investigated. Methods: EDR signals are extracted based on new respiration-related features in ECG beats morphology, such as ECG variance (EDRVar) and phase space reconstruction area (EDRPSR). After evaluating the EDRs by comparing them to a reference respiratory signal, they are used in an automatic OSA... 

    Extraction of Respiratory Information from ECG and Application on the
    Apnea Detection

    , M.Sc. Thesis Sharif University of Technology Janbakhshi, Parvaneh (Author) ; Shamsollahi, Mohammad Bagher (Supervisor)
    Abstract
    Respiration signal is one of the biological information required to monitor patient respiratory activities. Noninvasive respiratory monitoring is an extensive field of research, which has seen widespread interest for several years. It is well known that the respiratory activity influences electrocardiographic measurements (ECG) in various ways. Therefore, different signal processing techniques have been developed for extracting this respiratory information from the ECG, namely ECG derived respiratory (EDR). Potential advantages of such techniques are their low cost, high convenience and the ability to simultaneously monitor cardiac and respiratory activity. One of the aims of this thesis is... 

    ECG-derived respiration estimation from single-lead ECG using gaussian process and phase space reconstruction methods

    , Article Biomedical Signal Processing and Control ; Volume 45 , 2018 , Pages 80-90 ; 17468094 (ISSN) Janbakhshi, P ; Shamsollahi, M. B ; Sharif University of Technology
    Elsevier Ltd  2018
    Abstract
    Respiratory activity influences electrocardiographic measurements (ECG) in various ways. Therefore, extraction of respiratory information from ECG, namely ECG-derived respiratory (EDR), can be used as a promising noninvasive method to monitor respiration activity. In this paper, an automatic EDR extraction system using single-lead ECG is proposed. Respiration effects on ECG are categorized into two different models: additive and multiplicative based models. After selection of a proper model for each subject using a proposed criterion, gaussian process (GP) and phase space reconstruction area (PSRArea) are introduced as new methods of EDR extraction for additive and multiplicative models,...