AIMC Topic: Monitoring, Physiologic
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A comparative study of neural network architectures for vital signs monitoring based on the national early warning systems (NEWS).
Health informatics journal
Apr 25, 2025
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...
Multiscale activity recognition algorithms to improve cross-subjects performance resilience in rehabilitation monitoring systems.
Computer methods and programs in biomedicine
Apr 23, 2025
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
Apr 17, 2025
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...
Tidal Volume Monitoring via Surface Motions of the Upper Body-A Pilot Study of an Artificial Intelligence Approach.
Sensors (Basel, Switzerland)
Apr 10, 2025
The measurement of tidal volumes via respiratory-induced surface movements of the upper body has been an objective in medical diagnostics for decades, but a real breakthrough has not yet been achieved. The improvement of measurement technology throug...
Randomized Trial on Electroacupuncture for Recovery of Postoperative Gastrointestinal Function Based on Long-Term Monitoring Device.
Annals of surgical oncology
Apr 4, 2025
BACKGROUND: This research aimed to explore the efficacy and safety of electroacupuncture in promoting the recovery of postoperative gastrointestinal function and to discuss the potential mechanism on the basis of heart rate variability (HRV).
Monitoring effort and respiratory drive in patients with acute respiratory failure.
Current opinion in critical care
Apr 4, 2025
PURPOSE OF REVIEW: Accurate monitoring of respiratory drive and inspiratory effort is crucial for optimizing ventilatory support during acute respiratory failure. This review evaluates current and emerging bedside methods for assessing respiratory dr...
Machine learning-based non-invasive continuous dynamic monitoring of human core temperature with wearable dual temperature sensors.
Physiological measurement
Apr 3, 2025
Due to the growing demand for personal health monitoring in extreme environments, continuous monitoring of core temperature has become increasingly important. Traditional monitoring methods, such as mercury thermometers and infrared thermometers, may...
Transforming Healthcare: Intelligent Wearable Sensors Empowered by Smart Materials and Artificial Intelligence.
Advanced materials (Deerfield Beach, Fla.)
Apr 1, 2025
Intelligent wearable sensors, empowered by machine learning and innovative smart materials, enable rapid, accurate disease diagnosis, personalized therapy, and continuous health monitoring without disrupting daily life. This integration facilitates a...
False Crisis Alarms in Cardiopulmonary Monitoring:: Identification, Causes, and Clinical Implications.
Critical care nursing clinics of North America
Mar 26, 2025
The systematic annotation of crisis alarms reveals a high number of false alarms for both ventricular tachycardia and asystole, which are best identified by inspecting simultaneous multilead electrocardiographs. Among the few true crisis alarms, 11 w...
The future of artificial intelligence in cardiovascular monitoring.
Current opinion in critical care
Mar 24, 2025
PURPOSE OF REVIEW: Cardiovascular monitoring is essential for managing hemodynamic instability and preventing complications in critically ill patients. Conventional monitoring approaches are limited by predefined thresholds, dependence on clinician e...
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