Fog Computing Service in the Healthcare Monitoring System for Managing the Real-Time Notification

ICT in Nursing and Patient Healthcare Management: Scoping Review and Case Studies

Over the past few decades, Information and Communication Technologies (ICT) have revolutionized the fields of nursing and patient healthcare management. This scoping review and the accompanying case studies shed light on the extensive scope and impact of ICT in these critical healthcare domains. The scoping review explores the wide array of ICT tools employed in nursing care and patient healthcare management. These tools encompass electronic health records systems, mobile applications, telemedicine solutions, remote monitoring systems, and more. This article underscores how these technologies have enhanced the efficiency, accuracy, and accessibility of clinical information, contributing to improved patient care. ICT revolution has revitalized nursing care and patient management, improving the quality of care and patient satisfaction. This review and the accompanying case studies emphasize the ongoing potential of ICT in the healthcare sector and call for further research to maximize its benefits.

Fog-Based Smart Cardiovascular Disease Prediction System Powered by Modified Gated Recurrent Unit

The ongoing fast-paced technology trend has brought forth ceaseless transformation. In this regard, cloud computing has long proven to be the paramount deliverer of services such as computing power, software, networking, storage, and databases on a pay-per-use basis. The cloud is a big proponent of the internet of things (IoT), furnishing the computation and storage requisite to address internet-of-things applications. With the proliferating IoT devices triggering a continual data upsurge, the cloud-IoT interaction encounters latency, bandwidth, and connectivity restraints. The inclusion of the decentralized and distributed fog computing layer amidst the cloud and IoT layer extends the cloud's processing, storage, and networking services close to end users. This hierarchical edge-fog-cloud model distributes computation and intelligence, yielding optimal solutions while tackling constraints like massive data volume, latency, delay, and security vulnerability. The healthcare domain, warranting time-critical functionalities, can reap benefits from the cloud-fog-IoT interplay. This research paper propounded a fog-assisted smart healthcare system to diagnose heart or cardiovascular disease. It combined a fuzzy inference system (FIS) with the recurrent neural network model's variant of the gated recurrent unit (GRU) for pre-processing and predictive analytics tasks. The proposed system showcases substantially improved performance results, with classification accuracy at 99.125%. With major processing of healthcare data analytics happening at the fog layer, it is observed that the proposed work reveals optimized results concerning delays in terms of latency, response time, and jitter, compared to the cloud. Deep learning models are adept at handling sophisticated tasks, particularly predictive analytics. Time-critical healthcare applications reap benefits from deep learning's exclusive potential to furnish near-perfect results, coupled with the merits of the decentralized fog model, as revealed by the experimental results.

Wearable Sensors for Healthcare: Fabrication to Application

This paper presents a substantial review of the deployment of wearable sensors for healthcare applications. Wearable sensors hold a pivotal position in the microelectronics industry due to their role in monitoring physiological movements and signals. Sensors designed and developed using a wide range of fabrication techniques have been integrated with communication modules for transceiving signals. This paper highlights the entire chronology of wearable sensors in the biomedical sector, starting from their fabrication in a controlled environment to their integration with signal-conditioning circuits for application purposes. It also highlights sensing products that are currently available on the market for a comparative study of their performances. The conjugation of the sensing prototypes with the Internet of Things (IoT) for forming fully functioning sensorized systems is also shown here. Finally, some of the challenges existing within the current wearable systems are shown, along with possible remedies.