Patrícia J. Bota

Orcid: 0000-0002-0514-7517

According to our database1, Patrícia J. Bota authored at least 14 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Exploring Retrospective Annotation in Long-Videos for Emotion Recognition.
IEEE Trans. Affect. Comput., 2024

BioSPPy: A Python toolbox for physiological signal processing.
SoftwareX, 2024

Benchmarking of Sensor Configurations and Measurement Sites for Out-of-the-Lab Photoplethysmography.
Sensors, 2024

2023
Impact of sampling rate and interpolation on photoplethysmography and electrodermal activity signals' waveform morphology and feature extraction.
Neural Comput. Appl., March, 2023

EmotiphAI: a biocybernetic engine for real-time biosignals acquisition in a collective setting.
Neural Comput. Appl., March, 2023

Group Synchrony for Emotion Recognition Using Physiological Signals.
IEEE Trans. Affect. Comput., 2023

2022
A dissimilarity-based approach to automatic classification of biosignal modalities.
Appl. Soft Comput., 2022

Acting emotions: physiological correlates of emotional valence and arousal dynamics in theatre.
Proceedings of the IMX '22: ACM International Conference on Interactive Media Experiences, Aveiro, Portugal, June 22, 2022

2021
Smartphone-based Content Annotation for Ground Truth Collection in Affective Computing.
Proceedings of the IMX '21: ACM International Conference on Interactive Media Experiences, 2021

2020
TSFEL: Time Series Feature Extraction Library.
SoftwareX, 2020

Emotion Assessment Using Feature Fusion and Decision Fusion Classification Based on Physiological Data: Are We There Yet?
Sensors, 2020

A Wearable System for Electrodermal Activity Data Acquisition in Collective Experience Assessment.
Proceedings of the 22nd International Conference on Enterprise Information Systems, 2020

2019
A Semi-Automatic Annotation Approach for Human Activity Recognition.
Sensors, 2019

A Review, Current Challenges, and Future Possibilities on Emotion Recognition Using Machine Learning and Physiological Signals.
IEEE Access, 2019


  Loading...