Estela Ribeiro

According to our database, Estela Ribeiro authored at least 7 papers between 2023 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2024

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

Joseph A. P. Quino, Diego A. C. Cardenas, Marcelo A. F. Toledo, Felipe Meneguitti Dias, Estela Ribeiro, José Eduardo Krieger, Marco A. Gutierrez

CoRR, 2024

Exploring the limitations of blood pressure estimation using the photoplethysmography signal.

Felipe Meneguitti Dias, Diego Armando Cardona Cárdenas, Marcelo A. F. Toledo, Filipe A. C. Oliveira, Estela Ribeiro, José Eduardo Krieger, Marco A. Gutierrez

CoRR, 2024

2023

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

Douglas A. Almeida, Felipe Meneguitti Dias, Marcelo A. F. Toledo, Diego Armando Cardona Cárdenas, Filipe A. C. Oliveira, Estela Ribeiro, José Eduardo Krieger, Marco A. Gutierrez

CoRR, 2023

Machine Learning-Based Diabetes Detection Using Photoplethysmography Signal Features.

Filipe A. C. Oliveira, Felipe Meneguitti Dias, Marcelo A. F. Toledo, Diego Armando Cardona Cárdenas, Douglas A. Almeida, Estela Ribeiro, José Eduardo Krieger, Marco A. Gutierrez

CoRR, 2023

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

Felipe Meneguitti Dias, Marcelo A. F. Toledo, Diego Armando Cardona Cárdenas, Douglas A. Almeida, Filipe A. C. Oliveira, Estela Ribeiro, José Eduardo Krieger, Marco A. Gutierrez

CoRR, 2023

Artificial Intelligence-Driven Screening System for Rapid Image-Based Classification of 12-Lead ECG Exams: A Promising Solution for Emergency Room Prioritization.

Felipe Meneguitti Dias, Estela Ribeiro, Ramon Alfredo Moreno, Adèle Helena Ribeiro, Nelson Samesima, Carlos Alberto Pastore, José Eduardo Krieger, Marco A. Gutierrez

IEEE Access, 2023

Developing a Machine Learning Pipeline for Predicting Neurological Outcomes in Comatose Cardiac Arrest Survivors Using Continuous EEG Data.

Quenaz B. Soares, Felipe Meneguitti Dias, Estela Ribeiro, José Eduardo Krieger, Marco A. Gutierrez

Proceedings of the Computing in Cardiology, 2023