AIMC Topic: Monitoring, Physiologic

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An ensemble of deep representation learning with metaheuristic optimisation algorithm for critical health monitoring using internet of medical things.

Scientific reports
The Internet of Things (IoT) plays a significant part in the healthcare field. The growth of smart devices, smart sensors, and advanced lightweight communication protocols has created an opportunity to connect medical devices for monitoring biomedica...

IoT enabled health monitoring system using rider optimization algorithm and joint process estimation.

Scientific reports
The timely detection of abnormal health conditions is crucial in achieving successful medical intervention and enhancing patient outcomes. Despite advances in health monitoring, existing methods often struggle with achieving high accuracy, sensitivit...

Tackling inter-subject variability in smartwatch data using factorization models.

Scientific reports
Smartwatches enable longitudinal and continuous data acquisition. This has the potential to remotely monitor (changes) of the health of users. However, differences among subjects (inter-subject variability) limit a model to generalize to unseen subje...

On-Mask Magnetoelastic Sensor Network for Self-Powered Respiratory Monitoring.

ACS nano
Respiratory monitoring is crucial because it provides key insights into a person's health and physiological conditions. Conventional respiratory sensing is significantly challenged by the presence of water vapor in exhaled breath. An on-mask magnetoe...

A hybrid fog-edge computing architecture for real-time health monitoring in IoMT systems with optimized latency and threat resilience.

Scientific reports
The advancement of the Internet of Medical Things (IoMT) has transformed healthcare delivery by enabling real-time health monitoring. However, it introduces critical challenges related to latency and, more importantly, the secure handling of sensitiv...

Synergizing Nanosensor-Enhanced Wearable Devices with Machine Learning for Precision Health Management Benefiting Older Adult Populations.

ACS nano
Population aging presents significant health challenges and socioeconomic burdens globally, driving an increased demand for precision health management. In the era of big data, the exponential growth of health information is accelerating advances in ...

Design and analysis of TwinCardio framework to detect and monitor cardiovascular diseases using digital twin and deep neural network.

Scientific reports
World Health Organization (WHO) estimates 17.9 million deaths globally every year due to Cardiovascular Disease or CVD, which includes an array of disorders of the heart and blood vessels, that includes coronary heart disease, cerebrovascular disease...

Fused federated learning framework for secure and decentralized patient monitoring in healthcare 5.0 using IoMT.

Scientific reports
Federated Learning (FL) enables artificial intelligence frameworks to train on private information without compromising privacy, which is especially useful in the medical and healthcare industries where the knowledge or data at hand is never enough. ...

Enhancing remote patient monitoring with AI-driven IoMT and cloud computing technologies.

Scientific reports
The rapid advancement of the Internet of Medical Things (IoMT) has revolutionized remote healthcare monitoring, enabling real-time disease detection and patient care. This research introduces a novel AI-driven telemedicine framework that integrates I...

Dual smart sensor data-based deep learning network for premature infant hypoglycemia detection.

Scientific reports
In general, deficient birth weight neonates suffer from hypoglycemia, and this can be quite disadvantageous. Like oxygen, glucose is a building block of life and constitutes the significant share of energy produced by the fetus and the neonate during...