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  • Open Access

    ARTICLE

    Turbulent Kinetic Energy of Flow during Inhale and Exhale to Characterize the Severity of Obstructive Sleep Apnea Patient

    W. M. Faizal1,*, C. Y. Khor1, Muhammad Nooramin Che Yaakob1, N. N. N. Ghazali2, M. Z. Zainon2, Norliza Binti Ibrahim3, Roziana Mohd Razi4

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 43-61, 2023, DOI:10.32604/cmes.2023.022716

    Abstract This paper aims to investigate and present the numerical investigation of airflow characteristics using Turbulent Kinetic Energy (TKE) to characterize the upper airway with obstructive sleep apnea (OSA) under inhale and exhale breathing conditions. The importance of TKE under both breathing conditions is that it show an accurate method in expressing the severity of flow in sleep disorder. Computational fluid dynamics simulate the upper airway’s airflow via steady-state Reynolds-averaged Navier-Stokes (RANS) with k–ω shear stress transport (SST) turbulence model. The three-dimensional (3D) airway model is created based on the CT scan images of an actual patient, meshed with 1.29 million… More > Graphic Abstract

    Turbulent Kinetic Energy of Flow during Inhale and Exhale to Characterize the Severity of Obstructive Sleep Apnea Patient

  • Open Access

    ARTICLE

    Neural Cryptography with Fog Computing Network for Health Monitoring Using IoMT

    G. Ravikumar1, K. Venkatachalam2, Mohammed A. AlZain3, Mehedi Masud4, Mohamed Abouhawwash5,6,*

    Computer Systems Science and Engineering, Vol.44, No.1, pp. 945-959, 2023, DOI:10.32604/csse.2023.024605

    Abstract Sleep apnea syndrome (SAS) is a breathing disorder while a person is asleep. The traditional method for examining SAS is Polysomnography (PSG). The standard procedure of PSG requires complete overnight observation in a laboratory. PSG typically provides accurate results, but it is expensive and time consuming. However, for people with Sleep apnea (SA), available beds and laboratories are limited. Resultantly, it may produce inaccurate diagnosis. Thus, this paper proposes the Internet of Medical Things (IoMT) framework with a machine learning concept of fully connected neural network (FCNN) with k-nearest neighbor (k-NN) classifier. This paper describes smart monitoring of a patient’s… More >

  • Open Access

    ARTICLE

    Computational Analysis of Airflow in Upper Airway under Light and Heavy Breathing Conditions for a Realistic Patient Having Obstructive Sleep Apnea

    W. M. Faizal1,2, N. N. N. Ghazali2,*, C. Y. Khor1, M. Z. Zainon2, Irfan Anjum Badruddin3,4,*, Sarfaraz Kamangar4, Norliza Binti Ibrahim5, Roziana Mohd Razi6

    CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.2, pp. 583-604, 2021, DOI:10.32604/cmes.2021.015549

    Abstract Background: Obstructive sleep apnea is a sleeping disorder that has troubled a sizeable population. There is an active area of research on obstructive sleep apnea that intends to better understand airflow behaviors and therefore treat patients more effectively. This paper aims to investigate the airflow characteristics of the upper airway in an obstructive sleep apnea (OSA) patient under light and heavy breathing conditions by using Turbulent Kinetic Energy (TKE), an accurate method in expressing the flow concentration mechanisms of sleeping disorders. It is important to visualize the concentration of flow in the upper airway in order to identify the severity… More >

  • Open Access

    ARTICLE

    Sleep Apnea Monitoring System Based on Commodity WiFi Devices

    Xiaolong Yang1, Xin Yu1, Liangbo Xie1,*, Hao Xue2, Mu Zhou1, Qing Jiang1

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2793-2806, 2021, DOI:10.32604/cmc.2021.016298

    Abstract To address the limitations of traditional sleep monitoring methods that highly rely on sleeping posture without considering sleep apnea, an intelligent apnea monitoring system is designed based on commodity WiFi in this paper. By utilizing linear fitting and wavelet transform, the phase error of channel state information (CSI) of the receiving antenna is eliminated, and the noise of the signal amplitude is removed. Moreover, the short-time Fourier transform (STFT) and sliding window method are combined to segment received wireless signals. Finally, several important statistical characteristics are extracted, and a back propagation (BP) neural network model is built to identify apnea… More >

  • Open Access

    ARTICLE

    Multifactorial Disease Detection Using Regressive Multi-Array Deep Neural Classifier

    D. Venugopal1, T. Jayasankar2,*, N. Krishnaraj3, S. Venkatraman4, N. B. Prakash5, G. R. Hemalakshmi5

    Intelligent Automation & Soft Computing, Vol.28, No.1, pp. 27-38, 2021, DOI:10.32604/iasc.2021.015205

    Abstract Comprehensive evaluation of common complex diseases associated with common gene mutations is currently a hot area of human genome research into causative new developments. A multi-fractal analysis of the genome is performed by placing the entire DNA sequence into smaller fragments and using the chaotic game representation and systematic methods to calculate the general dimensional spectrum of each fragment. This is a time consuming process as it uses floating point to represent large data sets and requires processing time. The proposed Regressive Multi-Array Deep Neural Classifier (RMDNC) system is implemented to reduce the computation time, it is called a polymorphic… 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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