AIMC Topic: Monitoring, Physiologic

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[Intelligent Monitoring System Based on Computer Vision and Artificial Intelligence].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation Jan 30, 2025
To ensure the quality of care for inpatients in ophthalmic hospitals, address the complex and variable conditions of postoperative patients, and conduct more comprehensive, accurate and real-time monitoring of patients, an intelligent monitoring syst...
Monitoring, Physiologic Artificial Intelligence Algorithms Humans
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Revolutionizing health monitoring: Integrating transformer models with multi-head attention for precise human activity recognition using wearable devices.

Technology and health care : official journal of the European Society for Engineering and Medicine Jan 1, 2025
BACKGROUND: A daily activity routine is vital for overall health and well-being, supporting physical and mental fitness. Consistent physical activity is linked to a multitude of benefits for the body, mind, and emotions, playing a key role in raising...
Humans Neural Networks, Computer Monitoring, Physiologic Activities of Daily Living Human Activities Algorithms Deep Learning Wearable Electronic Devices
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A Respiratory Signal Monitoring Method Based on Dual-Pathway Deep Learning Networks in Image-Guided Robotic-Assisted Intervention System.

The international journal of medical robotics + computer assisted surgery : MRCAS Dec 1, 2024
BACKGROUND: Percutaneous puncture procedures, guided by image-guided robotic-assisted intervention (IGRI) systems, are susceptible to disruptions in patients' respiratory rhythm due to factors such as pain and psychological distress.
Monitoring, Physiologic Robotic Surgical Procedures Neural Networks, Computer Humans Surgery, Computer-Assisted Algorithms Respiration Deep Learning
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Bridging Gaps with Generative AI: Enhancing Hypertension Monitoring Through Patient and Provider Insights.

Studies in health technology and informatics Aug 22, 2024
This study introduces a Generative Artificial Intelligence (GenAI) assistant designed to address key challenges in Remote Patient Monitoring (RPM) for hypertension. After a comprehensive needs assessment from clinicians and patients, we identified pi...
Health Knowledge, Attitudes, Practice Hypertension Monitoring, Physiologic Reproducibility of Results Surveys and Questionnaires Stakeholder Participation Patient Participation Needs Assessment Natural Language Processing Physician-Patient Relations Telemedicine Humans Digital Health Physicians Evidence Gaps
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[Application of Photoplethysmography Combined with Deep Learning in Postoperative Monitoring of Flaps].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation Jul 30, 2024
OBJECTIVE: Photoelectric volumetric tracing (PPG) exhibits high sensitivity and specificity in flap monitoring. Deep learning (DL) is capable of automatically and robustly extracting features from raw data. In this study, we propose combining PPG wit...
Embolism Rabbits Neural Networks, Computer Deep Learning Animals Postoperative Period Photoplethysmography Monitoring, Physiologic Surgical Flaps
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Comparing Artificial Intelligence-Based Versus Conventional Endotracheal Tube Monitoring Systems in Clinical Practice.

Studies in health technology and informatics Jul 24, 2024
Endotracheal tube dislodgement is a common patient safety incident in clinical settings. Current clinical practices, primarily relying on bedside visual inspections and equipment checks, often fail to detect endotracheal tube displacement or dislodge...
Cross-Over Studies Intubation, Intratracheal Artificial Intelligence Deep Learning Monitoring, Physiologic Humans
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Enhancing Non-Contact Heart Rate Monitoring: An Intelligent Multi-ROI Approach with Face Masking and CNN-Based Feature Adaptation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Heart rate (HR) estimation from facial video streams has emerged in the recent years as a promising method of unobtrusive vitals monitoring. Conventional non-contact HR monitoring algorithms like POS, CHROM, ICA are often applied to a single region o...
Algorithms Humans Reproducibility of Results Neural Networks, Computer Male Face Monitoring, Physiologic Heart Rate
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Minimally invasive monitor of cardiac output based on the machine-learning analysis of the pulse contour of the peripheral arterial pressure.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
In the hemodynamic management of anesthetized patients during surgical operation, minimally invasive and accurate cardiac output (CO) monitoring is strongly required. We have developed a CO monitor based on the machine-learning analysis of the pulse ...
Dogs Arterial Pressure Cardiac Output Monitoring, Physiologic Machine Learning Blood Pressure Animals
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HRV-based Monitoring of Neonatal Seizures with Machine Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
With the rapid development of machine learning (ML) in biomedical signal processing, ML-based neonatal seizure detection using heart rate variability (HRV) parameters extracted from the electrocardiogram (ECG) has gained increasing interest. In this ...
Heart Rate Infant, Newborn Monitoring, Physiologic Sensitivity and Specificity Humans Electrocardiography Seizures Male Machine Learning Signal Processing, Computer-Assisted Support Vector Machine Female
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Computer vision-inspired contrastive learning for self-supervised anomaly detection in sensor-based remote healthcare monitoring.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Sensor-based remote healthcare monitoring is a promising approach for timely detection of adverse health events such as falls or infections in people living with dementia (PLwD) in the home, and reducing preventable hospital admissions. Current anoma...
Humans Machine Learning Algorithms Dementia Supervised Machine Learning Monitoring, Physiologic Remote Sensing Technology
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