AIMC Topic: Monitoring, Physiologic

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Fully Wearable Devices for Real-Time Health Monitoring and Multimodal Sensing in Nanomedicine Using Multiplexed Green Biofuels.

Nano letters
Fully wearable devices are crucial for real-time health monitoring, but existing devices often lack stable power, on-site signal processing, and multimodal sensing. To overcome these limitations, we introduce the first self-powered and fully wearable...

A skin-interfaced wireless wearable device and data analytics approach for sleep-stage and disorder detection.

Proceedings of the National Academy of Sciences of the United States of America
Accurate identification of sleep stages and disorders is crucial for maintaining health, preventing chronic conditions, and improving diagnosis and treatment. Direct respiratory measurements, as key biomarkers, are missing in traditional wrist- or fi...

IoT-enabled real-time health monitoring system for adolescent physical rehabilitation.

Scientific reports
This study aims to develop an intelligent system leveraging Internet of Thing (IoT) technology to enhance the precision of youth physical training monitoring and improve training outcomes. A wearable device incorporating Micro Electro Mechanical Syst...

Oxygen Uptake Prediction for Timely Construction Worker Fatigue Monitoring Through Wearable Sensing Data Fusion.

Sensors (Basel, Switzerland)
The physical workload evaluation of construction activities will help to prevent excess physical fatigue or overexertion. The workload determination involves measuring physiological responses such as oxygen uptake (VO) while performing the work. The ...

CLEAR-Shock: Contrastive LEARning for Shock.

IEEE journal of biomedical and health informatics
Shock is a life-threatening condition characterized by generalized circulatory failure, which can have devastating consequences if not promptly treated. Thus, early prediction and continuous monitoring of physiological signs are essential for timely ...

Real-time health monitoring by examining the role of next-generation elements in a medical app.

Computers in biology and medicine
The healthcare sector is undergoing a profound transformation driven by the rapid rise in healthcare applications (mHealth apps), which are becoming integral to how patients manage their health. This paper examines the role of next-generation technol...

A comparative study of neural network architectures for vital signs monitoring based on the national early warning systems (NEWS).

Health informatics journal
The study aims to assess the efficacy of various neural network architectures in predicting the National Early Warning Systems (NEWS) score, using vital signs, to enhance early warning and monitoring in clinical settings. A comparative evaluation o...

SEISMIC-HF 1: key findings from AHA24 and implications for remote cardiac monitoring.

Heart failure reviews
While there is continued progress in developing therapies for patients with heart failure, the condition results in significant morbidity and a sizeable economic impact on our society. Recent advances in wearable sensors combined with machine learnin...

Multiscale activity recognition algorithms to improve cross-subjects performance resilience in rehabilitation monitoring systems.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: This study introduces multiscale feature learning to develop more robust and resilient activity recognition algorithms, aimed at accurately tracking and quantifying rehabilitation exercises while minimizing performance dispa...

Improved security for IoT-based remote healthcare systems using deep learning with jellyfish search optimization algorithm.

Scientific reports
With an increased chronic disease and an ageing population, remote health monitoring is a substantial method to enhance the care of patients and decrease healthcare expenses. The Internet of Things (IoT) presents a promising solution for remote healt...