César Teixeira

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Associate Professor

Faculdade de Ciências da Universidade de Lisboa

Portugal

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About

César Teixeira is an Associate Professor at Universidade de Coimbra Faculdade de Ciências e Tecnologia in Portugal. His research focuses on areas including pupillography, machine learning applications for epileptic seizure prediction, and multimodal imaging studies in cognitive assessment. He has published recent articles examining optimal methodologies in EEG analysis, digital communication solutions for individuals with Amyotrophic Lateral Sclerosis, and computational methods relevant to syphilis. His contributions enhance the understanding of neural mechanisms and their implications for technology and health.

Recent Grants

Grant: Close

Towards Realistic Epileptic Seizure Prediction: dealing with long-term concept drifts and data-labeling uncertainty RECoD

Open Date: 2021-01-01

Close Date: 2023-12-31

Grant: Close

Wearable Electronics for Effective Lung Monitoring

Open Date: 2019-01-01

Close Date: 2022-06-30

Grant: Close

Wearable Electronics for Effective Lung Monitoring

Open Date: 2019-01-01

Close Date: 2022-06-01

Grant: Close

LookAfterRisk - Dynamic risk assessment using home-mobile technologies for the management of myocardial infarction patients.

Open Date: 2018-07-01

Close Date:

Grant: Close

BASE - Biofeedback Augmented Software Engineering.

Open Date: 2018-07-01

Close Date:

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Lorena Petrella

Invited Assistant Professor

University of Coimbra

PORTUGAL

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Paulo de Carvalho

Professor Catedrático

Universidade do Porto Faculdade de Economia

PORTUGAL

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Mauro Pinto

Invited Assistant Professor

University of Coimbra

PORTUGAL

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Antonio Dourado

(Full) Professor

University of Coimbra

PORTUGAL

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Paulo Gil

Universidade de Aveiro

PORTUGAL

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César Teixeira

Research Interests

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About

Recent Grants

Articles (20)

Optimal frequency bands for pupillography for maximal correlation with HRV

EEG as a potential ground truth for the assessment of cognitive state in software development activities: A multimodal imaging study

Comparison between epileptic seizure prediction and forecasting based on machine learning

Classifier combination supported by the sleep-wake cycle improves EEG seizure prediction performance

Concept-drifts adaptation for machine learning EEG epilepsy seizure prediction

EEG epilepsy seizure prediction: the post-processing stage as a chronology

On the accuracy of code complexity metrics: A neuroscience-based guideline for improvement

Computational methods applied to syphilis: where are we, and where are we going?

Digital Alternative Communication for Individuals with Amyotrophic Lateral Sclerosis: What We Have

Digital Alternative Communication for Individuals with Amyotrophic Lateral Sclerosis: What We Have

How Reliable Are Ultra-Short-Term HRV Measurements during Cognitively Demanding Tasks?

EPIC: Annotated epileptic EEG independent components for artifact reduction

Automatic segmentation and classification of mice ultrasonic vocalizations

On the clinical acceptance of black-box systems for EEG seizure prediction

Ensemble Deep Neural Network for Automatic Classification of EEG Independent Components

Ensemble Deep Neural Network for Automatic Classification of EEG Independent Components

A personalized and evolutionary algorithm for interpretable EEG epilepsy seizure prediction

Biomedical signals and machine learning in amyotrophic lateral sclerosis: a systematic review

Heart rate variability analysis for the identification of the preictal interval in patients with drug-resistant epilepsy

National registry for amyotrophic lateral sclerosis: a systematic review for structuring population registries of motor neuron diseases

Collaborators (10)

Henrique Madeira

Pedro Martins

Joao Duraes

Marco Simões

Matthias Dümpelmann

Lorena Petrella

Paulo de Carvalho

Mauro Pinto

Antonio Dourado

Paulo Gil

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