3 results match your criteria: "Federal University of ABC Center of Mathematics Computing and Cognition[Affiliation]"
Geometric neural network based on phase space for BCI-EEG decoding.
J Neural Eng
October 2024
Athena Project team, Inria, 2004 route des luciioles, Sophia Antipolis, 06902, FRANCE.
\textbf{Objective:} The integration of Deep Learning (DL) algorithms on brain signal analysis is still in its nascent stages compared to their success in fields like Computer Vision. This is particularly true for BCI, where the brain activity is decoded to control external devices without requiring muscle control. Electroencephalography (EEG) is a widely adopted choice for designing BCI systems due to its non-invasive and cost-effective nature and excellent temporal resolution.
View Article and Find Full Text PDFTen sessions of transcranial direct current stimulation for chronic chikungunya arthralgia: study protocol for a randomised clinical trial.
BMJ Open
October 2022
Graduate Program in Health Science, Federal University of Rio Grande do Norte, Natal, Brazil
Article Synopsis
- The chikungunya virus is causing a significant public health issue in Brazil, particularly in the Northeast region, where chronic pain affects over 60% of infected individuals for years.
- This study aims to test the effectiveness of transcranial direct current stimulation (tDCS) in reducing pain and improving muscle strength, functionality, and quality of life in those suffering from chronic arthralgia through a structured clinical trial.
- The trial involves 40 participants randomized to receive either active or sham tDCS treatment over 10 sessions, with evaluations at multiple intervals to track changes in pain levels and other health outcomes.
Modelling the COVID-19 pandemic in context: an international participatory approach.
BMJ Glob Health
December 2020
Centre for Mathematics, Computation and Cognition, Federal University of ABC Center of Mathematics Computing and Cognition, Santo Andre, São Paulo, Brazil.
Article Synopsis
- The SARS-CoV-2 pandemic has overwhelmed health systems and altered the way scientific evidence is shared and published, leading to rapid dissemination of information.
- Decision-makers faced significant challenges implementing containment measures due to a lack of empirical data, increasing reliance on predictive mathematical models, especially in high-income countries.
- The COVID-19 Modelling (CoMo) Consortium was created as a participatory approach to bridge the gap in access to modeling insights for policymakers in low-income and middle-income countries, fostering collaboration among experts and local health authorities.