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  • Open Access

    ARTICLE

    Automatic Sleep Staging Algorithm Based on Random Forest and Hidden Markov Model

    Junbiao Liu1, 6, Duanpo Wu2, 3, Zimeng Wang2, Xinyu Jin1, *, Fang Dong4, Lurong Jiang5, Chenyi Cai6

    CMES-Computer Modeling in Engineering & Sciences, Vol.123, No.1, pp. 401-426, 2020, DOI:10.32604/cmes.2020.08731

    Abstract In the field of medical informatics, sleep staging is a challenging and timeconsuming task undertaken by sleep experts. According to the new standard of the American Academy of Sleep Medicine (AASM), the stages of sleep are divided into wakefulness (W), rapid eye movement (REM) and non-rapid eye movement (NREM) which includes three sleep stages (N1, N2 and N3) that describe the depth of sleep. This study aims to establish an automatic sleep staging algorithm based on the improved weighted random forest (WRF) and Hidden Markov Model (HMM) using only the features extracted from double-channel EEG signals. The WRF classification model… More >

  • Open Access

    ARTICLE

    Analysis of OSA Syndrome from PPG Signal Using CART-PSO Classifier with Time Domain and Frequency Domain Features

    N. Kins Burk Sunil1, *, R. Ganesan2, B. Sankaragomathi3

    CMES-Computer Modeling in Engineering & Sciences, Vol.118, No.2, pp. 351-375, 2019, DOI:10.31614/cmes.2018.04484

    Abstract Obstructive Sleep Apnea (OSA) is a respiratory syndrome that occurs due to insufficient airflow through the respiratory or respiratory arrest while sleeping and sometimes due to the reduced oxygen saturation. The aim of this paper is to analyze the respiratory signal of a person to detect the Normal Breathing Activity and the Sleep Apnea (SA) activity. In the proposed method, the time domain and frequency domain features of respiration signal obtained from the PPG device are extracted. These features are applied to the Classification and Regression Tree (CART)-Particle Swarm Optimization (PSO) classifier which classifies the signal into normal breathing signal… More >

  • Open Access

    ARTICLE

    Individualized Design of the Ventilator Mask based on the Residual Concentration of CO2

    Zhiguo Zhang1,*, Zhenxiao Li2, Yifei Zhang3, Zhenze Wang4, Minzhou Luo1

    CMES-Computer Modeling in Engineering & Sciences, Vol.117, No.2, pp. 157-167, 2018, DOI:10.31614/cmes.2018.04067

    Abstract OSAHS (Obstructive Sleep Apnea Hypopnea Syndrome) is a respiratory disease mainly characterized by limited and repeated pauses of breathing in sleep. Currently, the optimal treatment is to apply CPAP (Continuous Positive Airway Pressure) ventilation on the upper airway of the patient through a household respiratory machine. However, if the ventilator mask is designed improperly, it might cause the residue and repeated inhalation of CO2, which will exert an adverse impact on the therapeutic effect. Present research numerically analyzed the CO2 transportation inside a commercial ventilator mask (Mirage SoftGel, ResMed, Australia) based on the reconstructed 3D numerical model of a volunteer's… More >

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