Výsledky vyhledávání - "Cardenas, Diego"

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Optimizing Photoplethysmography-Based Sleep Staging Models by Leveraging Temporal Context for Wearable Devices Applications

Autor: Quino, Joseph A. P., Cardenas, Diego A. C., Toledo, Marcelo A. F., Dias, Felipe M., Ribeiro, Estela, Krieger, Jose E., Gutierrez, Marco A.

Accurate sleep stage classification is crucial for diagnosing sleep disorders and evaluating sleep quality. While polysomnography (PSG) remains the gold standard, photoplethysmography (PPG) is more practical due to its affordability and widespread us

Externí odkaz: http://arxiv.org/abs/2410.00693

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Exploring the limitations of blood pressure estimation using the photoplethysmography signal

Autor: Dias, Felipe M., Cardenas, Diego A. C., Toledo, Marcelo A. F., Oliveira, Filipe A. C., Ribeiro, Estela, Krieger, Jose E., Gutierrez, Marco A.

Hypertension, a leading contributor to cardiovascular morbidity, underscores the need for accurate and continuous blood pressure (BP) monitoring. Photoplethysmography (PPG) presents a promising approach to this end. However, the precision of BP estim

Externí odkaz: http://arxiv.org/abs/2404.16049

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A machine-learning sleep-wake classification model using a reduced number of features derived from photoplethysmography and activity signals

Autor: Almeida, Douglas A., Dias, Felipe M., Toledo, Marcelo A. F., Cardenas, Diego A. C., Oliveira, Filipe A. C., Ribeiro, Estela, Krieger, Jose E., Gutierrez, Marco A.

Sleep is a crucial aspect of our overall health and well-being. It plays a vital role in regulating our mental and physical health, impacting our mood, memory, and cognitive function to our physical resilience and immune system. The classification of

Externí odkaz: http://arxiv.org/abs/2308.05759

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Machine Learning-Based Diabetes Detection Using Photoplethysmography Signal Features

Autor: Oliveira, Filipe A. C., Dias, Felipe M., Toledo, Marcelo A. F., Cardenas, Diego A. C., Almeida, Douglas A., Ribeiro, Estela, Krieger, Jose E., Gutierrez, Marco A.

Diabetes is a prevalent chronic condition that compromises the health of millions of people worldwide. Minimally invasive methods are needed to prevent and control diabetes but most devices for measuring glucose levels are invasive and not amenable f

Externí odkaz: http://arxiv.org/abs/2308.01930

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Quality Assessment of Photoplethysmography Signals For Cardiovascular Biomarkers Monitoring Using Wearable Devices

Autor: Dias, Felipe M., Toledo, Marcelo A. F., Cardenas, Diego A. C., Almeida, Douglas A., Oliveira, Filipe A. C., Ribeiro, Estela, Krieger, Jose E., Gutierrez, Marco A.

Photoplethysmography (PPG) is a non-invasive technology that measures changes in blood volume in the microvascular bed of tissue. It is commonly used in medical devices such as pulse oximeters and wrist worn heart rate monitors to monitor cardiovascu

Externí odkaz: http://arxiv.org/abs/2307.08766

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