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  • Open Access

    REVIEW

    A Systematic Review on the Internet of Medical Things: Techniques, Open Issues, and Future Directions

    Apurva Sonavane1, Aditya Khamparia2,*, Deepak Gupta3

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1525-1550, 2023, DOI:10.32604/cmes.2023.028203

    Abstract IoT usage in healthcare is one of the fastest growing domains all over the world which applies to every age group. Internet of Medical Things (IoMT) bridges the gap between the medical and IoT field where medical devices communicate with each other through a wireless communication network. Advancement in IoMT makes human lives easy and better. This paper provides a comprehensive detailed literature survey to investigate different IoMT-driven applications, methodologies, and techniques to ensure the sustainability of IoMT-driven systems. The limitations of existing IoMT frameworks are also analyzed concerning their applicability in real-time driven systems or applications. In addition to… More >

  • Open Access

    ARTICLE

    Computing and Implementation of a Controlled Telepresence Robot

    Ali A. Altalbe1,2,*, Aamir Shahzad3, Muhammad Nasir Khan4

    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 1569-1585, 2023, DOI:10.32604/iasc.2023.039124

    Abstract The development of human-robot interaction has been continuously increasing for the last decades. Through this development, it has become simpler and safe interactions using a remotely controlled telepresence robot in an insecure and hazardous environment. The audio-video communication connection or data transmission stability has already been well handled by fast-growing technologies such as 5G and 6G. However, the design of the physical parameters, e.g., maneuverability, controllability, and stability, still needs attention. Therefore, the paper aims to present a systematic, controlled design and implementation of a telepresence mobile robot. The primary focus of this paper is to perform the computational analysis… More >

  • Open Access

    ARTICLE

    DeepGan-Privacy Preserving of HealthCare System Using DL

    Sultan Mesfer Aldossary*

    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 2199-2212, 2023, DOI:10.32604/iasc.2023.038243

    Abstract The challenge of encrypting sensitive information of a medical image in a healthcare system is still one that requires a high level of computing complexity, despite the ongoing development of cryptography. After looking through the previous research, it has become clear that the security issues still need to be looked into further because there is room for expansion in the research field. Recently, neural networks have emerged as a cost-effective and effective optimization strategy in terms of providing security for images. This revelation came about as a result of current developments. Nevertheless, such an implementation is a technique that is… More >

  • Open Access

    ARTICLE

    A Novel Krill Herd Based Random Forest Algorithm for Monitoring Patient Health

    Md. Moddassir Alam1, Md Mottahir Alam2, Muhammad Moinuddin2,3, Mohammad Tauheed Ahmad4, Jabir Hakami5, Anis Ahmad Chaudhary6, Asif Irshad Khan7, Tauheed Khan Mohd8,*

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4553-4571, 2023, DOI:10.32604/cmc.2023.032118

    Abstract Artificial Intelligence (AI) is finding increasing application in healthcare monitoring. Machine learning systems are utilized for monitoring patient health through the use of IoT sensor, which keep track of the physiological state by way of various health data. Thus, early detection of any disease or derangement can aid doctors in saving patients’ lives. However, there are some challenges associated with predicting health status using the common algorithms, such as time requirements, chances of errors, and improper classification. We propose an Artificial Krill Herd based on the Random Forest (AKHRF) technique for monitoring patients’ health and eliciting an optimal prescription based… More >

  • Open Access

    ARTICLE

    Advance IoT Intelligent Healthcare System for Lung Disease Classification Using Ensemble Techniques

    J. Prabakaran1,*, P. Selvaraj2

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 2141-2157, 2023, DOI:10.32604/csse.2023.034210

    Abstract In healthcare systems, the Internet of Things (IoT) innovation and development approached new ways to evaluate patient data. A cloud-based platform tends to process data generated by IoT medical devices instead of high storage, and computational hardware. In this paper, an intelligent healthcare system has been proposed for the prediction and severity analysis of lung disease from chest computer tomography (CT) images of patients with pneumonia, Covid-19, tuberculosis (TB), and cancer. Firstly, the CT images are captured and transmitted to the fog node through IoT devices. In the fog node, the image gets modified into a convenient and efficient format… More >

  • Open Access

    ARTICLE

    Teamwork Optimization with Deep Learning Based Fall Detection for IoT-Enabled Smart Healthcare System

    Sarah B. Basahel1, Saleh Bajaba2, Mohammad Yamin3, Sachi Nandan Mohanty4, E. Laxmi Lydia5,*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1353-1369, 2023, DOI:10.32604/cmc.2023.036453

    Abstract The current advancement in cloud computing, Artificial Intelligence (AI), and the Internet of Things (IoT) transformed the traditional healthcare system into smart healthcare. Healthcare services could be enhanced by incorporating key techniques like AI and IoT. The convergence of AI and IoT provides distinct opportunities in the medical field. Fall is regarded as a primary cause of death or post-traumatic complication for the ageing population. Therefore, earlier detection of older person falls in smart homes is required to improve the survival rate of an individual or provide the necessary support. Lately, the emergence of IoT, AI, smartphones, wearables, and so… More >

  • Open Access

    ARTICLE

    Sensor-Based Gait Analysis for Parkinson’s Disease Prediction

    Sathya Bama B*, Bevish Jinila Y

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2085-2097, 2023, DOI:10.32604/iasc.2023.028481

    Abstract Parkinson’s disease is identified as one of the key neurodegenerative disorders occurring due to the damages present in the central nervous system. The cause of such brain damage seems to be fully explained in many research studies, but the understanding of its functionality remains to be impractical. Specifically, the development of a quantitative disease prediction model has evolved in recent decades. Moreover, accelerometer sensor-based gait analysis is accepted as an important tool for recognizing the walking behavior of the patients during the early prediction and diagnosis of Parkinson’s disease. This type of minimal infrastructure equipment helps in analyzing the Parkinson’s… More >

  • Open Access

    ARTICLE

    Telepresence Robots and Controlling Techniques in Healthcare System

    Fawad Naseer1,*, Muhammad Nasir Khan1, Zubair Nawaz2, Qasim Awais3

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6623-6639, 2023, DOI:10.32604/cmc.2023.035218

    Abstract In this era of post-COVID-19, humans are psychologically restricted to interact less with other humans. According to the world health organization (WHO), there are many scenarios where human interactions cause severe multiplication of viruses from human to human and spread worldwide. Most healthcare systems shifted to isolation during the pandemic and a very restricted work environment. Investigations were done to overcome the remedy, and the researcher developed different techniques and recommended solutions. Telepresence robot was the solution achieved by all industries to continue their operations but with almost zero physical interaction with other humans. It played a vital role in… More >

  • Open Access

    ARTICLE

    IoMT-Based Healthcare Framework for Ambient Assisted Living Using a Convolutional Neural Network

    Waleed T. Al-Sit1, Nidal A. Al-Dmour2, Taher M. Ghazal3,4,*, Ghassan F. Issa3

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6867-6878, 2023, DOI:10.32604/cmc.2023.034952

    Abstract In the age of universal computing, human life is becoming smarter owing to the recent developments in the Internet of Medical Things (IoMT), wearable sensors, and telecommunication innovations, which provide more effective and smarter healthcare facilities. IoMT has the potential to shape the future of clinical research in the healthcare sector. Wearable sensors, patients, healthcare providers, and caregivers can connect through an IoMT network using software, information, and communication technology. Ambient assisted living (AAL) allows the incorporation of emerging innovations into the routine life events of patients. Machine learning (ML) teaches machines to learn from human experiences and to use… More >

  • Open Access

    ARTICLE

    IoT-Deep Learning Based Activity Recommendation System

    Sharmilee Kannan1,*, R. U. Anitha2, M. Divayapushpalakshmi3, K. S. Kalaivani4

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 2001-2016, 2023, DOI:10.32604/csse.2023.031965

    Abstract The rising use of mobile technology and smart gadgets in the field of health has had a significant impact on the global community. Health professionals are increasingly making use of the benefits of these technologies, resulting in a major improvement in health care both in and out of clinical settings. The Internet of Things (IoT) is a new internet revolution that is a rising research area, particularly in health care. Healthcare Monitoring Systems (HMS) have progressed rapidly as the usage of Wearable Sensors (WS) and smartphones have increased. The existing framework of conventional telemedicine’s store-and-forward method has some issues, including… More >

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