AIMC Topic: Monitoring, Physiologic

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Clinical Assessment of a Lightweight CNN Model for Real-Time Atrial Fibrillation Prediction in Continuous Wearable 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
Atrial Fibrillation (AFib) represents a prevalent cardiac arrhythmia associated with substantial risk for affected individuals. The integration of wearable devices, coupled with advanced predictive models, opens pathways for non-invasive and real-tim...
Atrial Fibrillation Middle Aged Wearable Electronic Devices Monitoring, Physiologic Electrocardiography, Ambulatory Electrocardiography Neural Networks, Computer Female Male Humans
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Advancements in Continuous Glucose Monitoring: Integrating Deep Learning and ECG Signal.

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
This paper presents a novel approach to noninvasive hyperglycemia monitoring utilizing electrocardiograms (ECG) from an extensive database comprising 1119 subjects. Previous research on hyperglycemia or glucose detection using ECG has been constraine...
Signal Processing, Computer-Assisted Continuous Glucose Monitoring Deep Learning Blood Glucose Hyperglycemia Monitoring, Physiologic Electrocardiography Neural Networks, Computer Algorithms Humans
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A Deep-Learning-Based Approach for Delirium Monitoring in ICU Patients Using Thermograms.

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
Patients in the ICU frequently suffer from delirium, which can delay their recovery and may cause significant distress. Despite standardized scoring systems, its diagnosis and classification however, remain largely subjective and are subject to intra...
Humans Neural Networks, Computer Intensive Care Units Delirium Thermography Deep Learning Monitoring, Physiologic
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Wireless Earphone-based Real-Time Monitoring of Breathing Exercises: A Deep Learning Approach.

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
Several therapy routines require deep breathing exercises as a key component and patients undergoing such therapies must perform these exercises regularly. Assessing the outcome of a therapy and tailoring its course necessitates monitoring a patient'...
Humans Wireless Technology Breathing Exercises Monitoring, Physiologic Algorithms Signal Processing, Computer-Assisted Deep Learning
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Differential Private Federated Transfer Learning for Mental Health Monitoring in Everyday Settings: A Case Study on Stress Detection.

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
Mental health conditions, prevalent across various demographics, necessitate efficient monitoring to mitigate their adverse impacts on life quality. The surge in data-driven methodologies for mental health monitoring has underscored the importance of...
Monitoring, Physiologic Privacy Mental Health Stress, Psychological Humans Machine Learning Algorithms
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Integrating Remote Patient Monitoring Data into Machine Learning Models for Predicting Emergency Department Utilization.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 1, 2024
The integration of Remote Patient Monitoring (RPM) data into risk stratification models has emerged as a promising approach for improving healthcare delivery and patient outcomes. In this work, we explore the integration of RPM features - including a...
Monitoring, Physiologic Machine Learning Emergency Service, Hospital Humans Electronic Health Records Remote Patient Monitoring
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IoT-based incubator monitoring and machine learning powered alarm predictions.

Technology and health care : official journal of the European Society for Engineering and Medicine Jan 1, 2024
BACKGROUND: Incubators, especially the ones for babies, require continuous monitoring for anomaly detection and taking action when necessary.
Internet of Things Humidity Clinical Alarms Wireless Technology Cloud Computing Mobile Applications Monitoring, Physiologic Infant, Newborn Temperature Neural Networks, Computer Machine Learning Humans Incubators, Infant Algorithms
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[Wearable devices: Perspectives on assessing and monitoring human physiological status].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Dec 25, 2023
This review article aims to explore the major challenges that the healthcare system is currently facing and propose a new paradigm shift that harnesses the potential of wearable devices and novel theoretical frameworks on health and disease. Lifestyl...
Artificial Intelligence Wearable Electronic Devices Humans Monitoring, Physiologic
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Handling Class Imbalance in Machine Learning-based Prediction Models: A Case Study in Asthma Management.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2023
A data-driven prediction tool has the potential to provide early warning of an asthma attack and improve asthma management and outcomes. Most previous machine learning (ML)-based studies for asthma attack prediction have reported a severe class imbal...
Logistic Models Algorithms Monitoring, Physiologic Quality of Life Humans Machine Learning
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Face-Free Chest Detection Using Convolutional Neural Networks for Non-Contact Respiration 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, 2023
Non-contact methods for monitoring respiration face limitations when it comes to selecting the chest region of interest. The semi-automatic method, which requires the user to select the chest region in the first frame, is not suitable for real-time a...
Respiration Monitoring, Physiologic Face Neural Networks, Computer
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