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  • Open Access

    REVIEW

    Wearable Healthcare and Continuous Vital Sign Monitoring with IoT Integration

    Hamed Taherdoost1,2,3,4,*

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 79-104, 2024, DOI:10.32604/cmc.2024.054378 - 15 October 2024

    Abstract Technical and accessibility issues in hospitals often prevent patients from receiving optimal mental and physical health care, which is essential for independent living, especially as societies age and chronic diseases like diabetes and cardiovascular disease become more common. Recent advances in the Internet of Things (IoT)-enabled wearable devices offer potential solutions for remote health monitoring and everyday activity recognition, gaining significant attention in personalized healthcare. This paper comprehensively reviews wearable healthcare technology integrated with the IoT for continuous vital sign monitoring. Relevant papers were extracted and analyzed using a systematic numerical review method, covering various More >

  • Open Access

    ARTICLE

    A Novel Efficient Patient Monitoring FER System Using Optimal DL-Features

    Mousa Alhajlah*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6161-6175, 2023, DOI:10.32604/cmc.2023.032505 - 28 December 2022

    Abstract Automated Facial Expression Recognition (FER) serves as the backbone of patient monitoring systems, security, and surveillance systems. Real-time FER is a challenging task, due to the uncontrolled nature of the environment and poor quality of input frames. In this paper, a novel FER framework has been proposed for patient monitoring. Preprocessing is performed using contrast-limited adaptive enhancement and the dataset is balanced using augmentation. Two lightweight efficient Convolution Neural Network (CNN) models MobileNetV2 and Neural search Architecture Network Mobile (NasNetMobile) are trained, and feature vectors are extracted. The Whale Optimization Algorithm (WOA) is utilized to More >

  • Open Access

    ARTICLE

    Automated Patient Discomfort Detection Using Deep Learning

    Imran Ahmed1, Iqbal Khan1, Misbah Ahmad1, Awais Adnan1, Hanan Aljuaid2,*

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2559-2577, 2022, DOI:10.32604/cmc.2022.021259 - 07 December 2021

    Abstract The Internet of Things (IoT) has been transformed almost all fields of life, but its impact on the healthcare sector has been notable. Various IoT-based sensors are used in the healthcare sector and offer quality and safe care to patients. This work presents a deep learning-based automated patient discomfort detection system in which patients’ discomfort is non-invasively detected. To do this, the overhead view patients’ data set has been recorded. For testing and evaluation purposes, we investigate the power of deep learning by choosing a Convolution Neural Network (CNN) based model. The model uses confidence… More >

  • Open Access

    ARTICLE

    Machine Learning Applied to Problem-Solving in Medical Applications

    Mahmoud Ragab1,2, Ali Algarni3, Adel A. Bahaddad4, Romany F. Mansour5,*

    CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2277-2294, 2021, DOI:10.32604/cmc.2021.018000 - 21 July 2021

    Abstract Physical health plays an important role in overall well-being of the human beings. It is the most observed dimension of health among others such as social, intellectual, emotional, spiritual and environmental dimensions. Due to exponential increase in the development of wireless communication techniques, Internet of Things (IoT) has effectively penetrated different aspects of human lives. Healthcare is one of the dynamic domains with ever-growing demands which can be met by IoT applications. IoT can be leveraged through several health service offerings such as remote health and monitoring services, aided living, personalized treatment, and so on.… More >

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