AIMC Topic: Monitoring, Physiologic

Clear Filters Showing 81 to 90 of 386 articles

mmWave-RM: A Respiration Monitoring and Pattern Classification System Based on mmWave Radar.

Sensors (Basel, Switzerland)
Breathing is one of the body's most basic functions and abnormal breathing can indicate underlying cardiopulmonary problems. Monitoring respiratory abnormalities can help with early detection and reduce the risk of cardiopulmonary diseases. In this s...

Development of an Automated Free Flap Monitoring System Based on Artificial Intelligence.

JAMA network open
IMPORTANCE: Meticulous postoperative flap monitoring is essential for preventing flap failure and achieving optimal results in free flap operations, for which physical examination has remained the criterion standard. Despite the high reliability of p...

Research on Monitoring Assistive Devices for Rehabilitation of Movement Disorders through Multi-Sensor Analysis Combined with Deep Learning.

Sensors (Basel, Switzerland)
This study aims to integrate a convolutional neural network (CNN) and the Random Forest Model into a rehabilitation assessment device to provide a comprehensive gait analysis in the evaluation of movement disorders to help physicians evaluate rehabil...

Wearable ECG Device and Machine Learning for Heart Monitoring.

Sensors (Basel, Switzerland)
With cardiovascular diseases (CVD) remaining a leading cause of mortality, wearable devices for monitoring cardiac activity have gained significant, renewed interest among the medical community. This paper introduces an innovative ECG monitoring syst...

A Novel AI Approach for Assessing Stress Levels in Patients with Type 2 Diabetes Mellitus Based on the Acquisition of Physiological Parameters Acquired during Daily Life.

Sensors (Basel, Switzerland)
Stress is the inherent sensation of being unable to handle demands and occurrences. If not properly managed, stress can develop into a chronic condition, leading to the onset of additional chronic health issues, such as cardiovascular illnesses and d...

Energy-efficient dynamic sensor time series classification for edge health devices.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Time series data plays a crucial role in the realm of the Internet of Things Medical (IoMT). Through machine learning (ML) algorithms, online time series classification in IoMT systems enables reliable real-time disease dete...

A deep learning approach for generating intracranial pressure waveforms from extracranial signals routinely measured in the intensive care unit.

Computers in biology and medicine
Intracranial pressure (ICP) is commonly monitored to guide treatment in patients with serious brain disorders such as traumatic brain injury and stroke. Established methods to assess ICP are resource intensive and highly invasive. We hypothesized tha...

Position-Aware Indoor Human Activity Recognition Using Multisensors Embedded in Smartphones.

Sensors (Basel, Switzerland)
Composite indoor human activity recognition is very important in elderly health monitoring and is more difficult than identifying individual human movements. This article proposes a sensor-based human indoor activity recognition method that integrate...

The Cooperation Between Nurses and a New Digital Colleague "AI-Driven Lifestyle Monitoring" in Long-Term Care for Older Adults: Viewpoint.

JMIR nursing
Technology has a major impact on the way nurses work. Data-driven technologies, such as artificial intelligence (AI), have particularly strong potential to support nurses in their work. However, their use also introduces ambiguities. An example of su...

Emergency Response Person Localization and Vital Sign Estimation Using a Semi-Autonomous Robot Mounted SFCW Radar.

IEEE transactions on bio-medical engineering
The large number and scale of natural and man-made disasters have led to an urgent demand for technologies that enhance the safety and efficiency of search and rescue teams. Semi-autonomous rescue robots are beneficial, especially when searching inac...