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  • Open Access


    What Is the Place of the Healthcare Professionals in Adherence to Online Therapeutic Programs for Insomnia? Some Responses from the Sleep-4-All-1 Study and Sleep-4-All-2.0 Study Protocol

    Quelle est la place des professionnels de santé dans l’adhésion aux programmes thérapeutiques en ligne de l’insomnie ? Éléments de réflexion issus de l’étude Sleep-4-All-1 et protocole de l’étude Sleep-4-All-2.0

    D. Boinon, C. Charles, L. Fasse, J. Journiac, G. Pallubicki, E. Guerdoux-Ninot, G. Ninot, A. Couillet, J.-B. Le Provost, J. Savard, S. Dauchy

    Psycho-Oncologie, Vol.16, No.1, pp. 173-181, 2022, DOI:10.3166/pson-2022-0179

    Abstract Cognitive behavioral therapy for insomnia (CBTI) remains difficult to access for patients with cancer. Its digitalization seem like a promising solution to benefit as many people as possible. The feasibility of a Quebec CBTI program was thus demonstrated in France, while revealing the limits of a self-help remote program for patients with cancer. The challenge remains to better understand with the Sleep-4-All-2.0 protocol study the role of healthcare professionals in supporting patients in this type of program.

    La thérapie cognitivocomportementale de l’insomnie (TCC-I) demeure difficile d’accès pour les patients atteints de cancer. Sa digitalisation semble une solution prometteuse… More >

  • Open Access


    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


    Competitive Multi-Verse Optimization with Deep Learning Based Sleep Stage Classification

    Anwer Mustafa Hilal1,*, Amal Al-Rasheed2, Jaber S. Alzahrani3, Majdy M. Eltahir4, Mesfer Al Duhayyim5, Nermin M. Salem6, Ishfaq Yaseen1, Abdelwahed Motwakel1

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1249-1263, 2023, DOI:10.32604/csse.2023.030603

    Abstract Sleep plays a vital role in optimum working of the brain and the body. Numerous people suffer from sleep-oriented illnesses like apnea, insomnia, etc. Sleep stage classification is a primary process in the quantitative examination of polysomnographic recording. Sleep stage scoring is mainly based on experts’ knowledge which is laborious and time consuming. Hence, it can be essential to design automated sleep stage classification model using machine learning (ML) and deep learning (DL) approaches. In this view, this study focuses on the design of Competitive Multi-verse Optimization with Deep Learning Based Sleep Stage Classification (CMVODL-SSC) model using Electroencephalogram (EEG) signals.… More >

  • Open Access


    The Effect of Sleep on Workplace Interpersonal Conflict: The Mediating Role of Ego Depletion

    Mei Chen, Haoran Dong, Yang Luo, Hui Meng*

    International Journal of Mental Health Promotion, Vol.24, No.6, pp. 901-916, 2022, DOI:10.32604/ijmhp.2022.020006

    Abstract This study aimed to investigate the relationship between sleep and workplace interpersonal conflict and the role of ego depletion as the mediating mechanism. A survey was conducted daily for two weeks using an experience sampling method. A sample of 79 employees from the East Coast of China was collected. A multilevel regression analysis was conducted to test the proposed hypotheses. Results indicated that higher sleep quantity was associated with lower daily ego depletion at noon and lower workplace interpersonal conflict. Moreover, ego depletion mediated the effects of sleep quantity on workplace interpersonal conflict. The findings identified the adverse effects of… More >

  • Open Access


    Physical exercise, Sedentary Behaviour, Sleep and Depression Symptoms in Chinese Young Adults During the COVID-19 Pandemic: A Compositional Isotemporal Analysis

    Jianjun Su1, Enxiu Wei1, Cain Clark2, Kaixin Liang3, Xiaojiao Sun4,*

    International Journal of Mental Health Promotion, Vol.24, No.5, pp. 759-769, 2022, DOI:10.32604/ijmhp.2022.020152

    Abstract Numerous studies links movement activity (e.g., physical activity, sedentary behavior [SB], and sleep) with mental health or illness indicators during the COVID-19 pandemic; however, research has typically examined time-use behaviors independently, rather than considering daily activity as a 24-hour time-use composition. This cross-sectional study aimed to use compositional isotemporal analysis to estimate the association between reallocation of time-use behaviors and depression symptoms in young adults in China. Participants (n = 1475; 68.0% of female; 20.7 [1.60] years) reported their time spent in moderate to vigorous physical activity (MVPA), light physical activity (LPA), SB, and sleep. Replacing SB with sleep, LPA,… More >

  • Open Access


    Optimal Sparse Autoencoder Based Sleep Stage Classification Using Biomedical Signals

    Ashit Kumar Dutta1,*, Yasser Albagory2, Manal Al Faraj1, Yasir A. M. Eltahir3, Abdul Rahaman Wahab Sait4

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 1517-1529, 2023, DOI:10.32604/csse.2023.026482

    Abstract The recently developed machine learning (ML) models have the ability to obtain high detection rate using biomedical signals. Therefore, this article develops an Optimal Sparse Autoencoder based Sleep Stage Classification Model on Electroencephalography (EEG) Biomedical Signals, named OSAE-SSCEEG technique. The major intention of the OSAE-SSCEEG technique is to find the sleep stage disorders using the EEG biomedical signals. The OSAE-SSCEEG technique primarily undergoes preprocessing using min-max data normalization approach. Moreover, the classification of sleep stages takes place using the Sparse Autoencoder with Smoothed Regularization (SAE-SR) with softmax (SM) approach. Finally, the parameter optimization of the SAE-SR technique is carried out… More >

  • Open Access


    Application Progress of Aromatherapy in Perioperative Patients

    Yuezi Liao1,2,*, Xing Liu1,2, Mengqin Zhang1,2, Hao Hua3

    Journal of Intelligent Medicine and Healthcare, Vol.1, No.1, pp. 1-10, 2022, DOI:10.32604/jimh.2022.029848

    Abstract Aromatherapy is a sort of natural therapy for body maintenance using essential oils and vegetable oils extracted from natural plants. It belongs to the category of homeopathy. Aromatherapy combines the dual functions of art and treatment, comprehensively considers the needs of human physiology and psychology, and is widely used in the field of medical care. Aromatherapy is one of the complementary and alternative treatments extensively studied at home and abroad. It has a relieving effect on postoperative pain, sleep disturbance, nausea, vomiting and preoperative anxiety, and is an important intervention in perioperative care. A large number of research data show… More >

  • Open Access


    Base Station Energy Management in 5G Networks Using Wide Range Control Optimization

    J. Premalatha*, A. SahayaAnselin Nisha

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 811-826, 2023, DOI:10.32604/iasc.2023.026523

    Abstract The traffic activity of fifth generation (5G) networks demand for new energy management techniques that is dynamic deep and longer duration of sleep as compared to the fourth generation (4G) network technologies that demand always for varied control and data signalling based on control base station (CBS) and data base station (DBS). Hence, this paper discusses the energy management in wireless cellular networks using wide range of control for twice the reduction in energy conservation in non-standalone deployment of 5G network. As the new radio (NR) based 5G network is configured to transmit signal blocks for every 20 ms, the proposed… More >

  • Open Access


    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


    Meeting 24-h Movement Guidelines is Related to Better Academic Achievement: Findings from the YRBS 2019 Cycle

    Shaoying Liu1,2,#, Qian Yu3,#, Md Mahbub Hossain4, Scott Doig5, Ran Bao6, Yaping Zhao7, Jin Yan8,*, Xun Luo3, Jiaxuan Yang3, Arthur F. Kramer9,10, Liye Zou3

    International Journal of Mental Health Promotion, Vol.24, No.1, pp. 13-24, 2022, DOI:10.32604/IJMHP.2021.017660

    Abstract This research is designed to investigate the relationship between the 24-h movement guidelines (24-HMG) and self-reported academic achievement (AA) using nationally representative data derived from the 2019 U.S. National Youth Risk Behaviour Survey. A multiple-stage cluster sampling procedure has been adopted to ensure a representative sample (N = 9127 adolescents; mean age = 15.7 years old; male% = 49.8%). Logistic regression has been adopted to obtain the odds ratio (OR) regarding the associations between adherence to 24-HMG and AA while controlling for ethnicity, body mass index, sex and age. The prevalence of meeting the 24-h movement guidelines in isolation and… More >

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