AIMC Topic: Photoplethysmography

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Exploiting heart rate variability for driver drowsiness detection using wearable sensors and machine learning.

Scientific reports Jul 10, 2025
Driver drowsiness is a critical issue in transportation systems and a leading cause of traffic accidents. Common factors contributing to accidents include intoxicated driving, fatigue, and sleep deprivation. Drowsiness significantly impairs a driver'...
Algorithms Female Adult Humans Machine Learning Accidents, Traffic Heart Rate Automobile Driving Sleep Stages Male Wearable Electronic Devices Photoplethysmography
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Evolving Blood Pressure Estimation: From Feature Analysis to Image-Based Deep Learning Models.

Journal of medical systems Jul 9, 2025
Traditional cuffless blood pressure (BP) estimation methods often require collecting physiological signals, such as electrocardiogram (ECG) and photoplethysmography (PPG), from two distinct body sites to compute metrics like pulse transit time (PTT) ...
Signal Processing, Computer-Assisted Blood Pressure Electrocardiography Pulse Wave Analysis Humans Blood Pressure Determination Deep Learning Photoplethysmography
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Dual smart sensor data-based deep learning network for premature infant hypoglycemia detection.

Scientific reports Jul 2, 2025
In general, deficient birth weight neonates suffer from hypoglycemia, and this can be quite disadvantageous. Like oxygen, glucose is a building block of life and constitutes the significant share of energy produced by the fetus and the neonate during...
Humans Algorithms Female Infant, Newborn Monitoring, Physiologic Deep Learning Hypoglycemia Blood Glucose Infant, Premature Photoplethysmography
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Channel attention pyramid network for remote physiological measurement.

Scientific reports Jul 2, 2025
Remote photoplethysmography (rPPG) is an emerging contactless physiological parameter detection method utilizing cameras, showing great promise as a forefront technology for remote health assessment. While traditional rPPG methods have substantially ...
Humans Deep Learning Photoplethysmography Monitoring, Physiologic Video Recording
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Cuff-less blood pressure monitoring via PPG signals using a hybrid CNN-BiLSTM deep learning model with attention mechanism.

Scientific reports Jul 1, 2025
Blood pressure (BP) serves as a fundamental indicator of cardiovascular health, measuring the force exerted by circulating blood against arterial walls during each heartbeat. This paper introduces an advanced deep learning framework for precise, non-...
Deep Learning Wearable Electronic Devices Photoplethysmography Female Male Middle Aged Blood Pressure Determination Blood Pressure Signal Processing, Computer-Assisted Humans Neural Networks, Computer
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Machine-learning guided differentiation between photoplethysmography waveforms of supraventricular and ventricular origin.

Computer methods and programs in biomedicine Apr 20, 2025
BACKGROUND: It is unclear, whether photoplethysmography (PPG) waveforms from wearable devices can differentiate between supraventricular and ventricular arrhythmias. We assessed, whether a neural network-based classifier can distinguish the origin of...
Signal Processing, Computer-Assisted Heart Ventricles Tachycardia, Supraventricular Adolescent Photoplethysmography Electrocardiography Machine Learning Male Female Young Adult Humans Middle Aged Aged Neural Networks, Computer Adult
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Diabetes: Non-Invasive Blood Glucose Monitoring Using Federated Learning with Biosensor Signals.

Biosensors Apr 16, 2025
Diabetes is a growing global health concern, affecting millions and leading to severe complications if not properly managed. The primary challenge in diabetes management is maintaining blood glucose levels (BGLs) within a safe range to prevent compli...
Humans Blood Glucose Biosensing Techniques Neural Networks, Computer Machine Learning Federated Learning Photoplethysmography Diabetes Mellitus Blood Glucose Self-Monitoring
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Parallel convolutional neural networks for non-invasive cardiac hemodynamic estimation: integrating uncalibrated PPG signals with nonlinear feature analysis.

Physiological measurement Mar 31, 2025
Understanding cardiac hemodynamic status (CHS) is essential for accurate cardiovascular health assessment, as it is governed by key parameters such as cardiac output (CO), systemic vascular resistance (SVR), and arterial compliance (AC). This study a...
Deep Learning Female Convolutional Neural Networks Signal Processing, Computer-Assisted Photoplethysmography Humans Male Adult Heart Neural Networks, Computer Middle Aged Nonlinear Dynamics Hemodynamics
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Machine Learning-Based VO Estimation Using a Wearable Multiwavelength Photoplethysmography Device.

Biosensors Mar 24, 2025
The rate of oxygen consumption, which is measured as the volume of oxygen consumed per mass per minute (VO) mL/kg/min, is a critical metric for evaluating cardiovascular health, metabolic status, and respiratory function. Specifically, VO is a powerf...
Wearable Electronic Devices Photoplethysmography Female Oxygen Consumption Adult Humans Male Machine Learning Algorithms
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Machine learning analysis of integrated ABP and PPG signals towards early detection of coronary artery disease.

Scientific reports Mar 12, 2025
Every year, Coronary Artery Disease (CAD) claims lives of over a million people. CAD occurs when the coronary arteries, responsible for supplying oxygenated blood to the heart, get occluded due to plaque deposits on their inner walls. The most critic...
Early Diagnosis Arterial Pressure Blood Pressure Signal Processing, Computer-Assisted Coronary Artery Disease Male Humans Middle Aged Machine Learning Photoplethysmography Female Aged
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