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

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

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

Explainable artificial intelligence in deep learning-based detection of aortic elongation on chest X-ray images.

Autor: Ribeiro E; Heart Institute (InCor), Clinics Hospital University of Sao Paulo Medical School (HCFMUSP), Av. Dr. Enéas Carvalho de Aguiar, 44 - Cerqueira César, São Paulo, SP 05403-900, Brazil.; University of Sao Paulo Medical School (FMUSP), Av. Dr. Arnaldo, 455 - Cerqueira César, Pacaembu, SP 01246-903, Brazil., Cardenas DAC; Heart Institute (InCor), Clinics Hospital University of Sao Paulo Medical School (HCFMUSP), Av. Dr. Enéas Carvalho de Aguiar, 44 - Cerqueira César, São Paulo, SP 05403-900, Brazil., Dias FM; Heart Institute (InCor), Clinics Hospital University of Sao Paulo Medical School (HCFMUSP), Av. Dr. Enéas Carvalho de Aguiar, 44 - Cerqueira César, São Paulo, SP 05403-900, Brazil.; Polytechnique School, University of Sao Paulo (POLI USP), Av. Prof. Luciano Gualberto, 380 - Butantã, São Paulo, SP 05508-010, Brazil., Krieger JE; Heart Institute (InCor), Clinics Hospital University of Sao Paulo Medical School (HCFMUSP), Av. Dr. Enéas Carvalho de Aguiar, 44 - Cerqueira César, São Paulo, SP 05403-900, Brazil., Gutierrez MA; Heart Institute (InCor), Clinics Hospital University of Sao Paulo Medical School (HCFMUSP), Av. Dr. Enéas Carvalho de Aguiar, 44 - Cerqueira César, São Paulo, SP 05403-900, Brazil.; University of Sao Paulo Medical School (FMUSP), Av. Dr. Arnaldo, 455 - Cerqueira César, Pacaembu, SP 01246-903, Brazil.; Polytechnique School, University of Sao Paulo (POLI USP), Av. Prof. Luciano Gualberto, 380 - Butantã, São Paulo, SP 05508-010, Brazil.

Publikováno v: European heart journal. Digital health [Eur Heart J Digit Health] 2024 Jun 25; Vol. 5 (5), pp. 524-534. Date of Electronic Publication: 2024 Jun 25 (Print Publication: 2024).