Automated Author Profile

Federico Sukno

Current S-Index

0.3

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

0.3

Average Dataset Index per dataset

Total Datasets

1

Total datasets for this author

Average FAIR Score

53.9%

Average FAIR Score per dataset

Total Citations

0

Total citations to the author's datasets

Total Mentions

0

Total mentions of the author's datasets

S-Index Interpretation

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

"CAST-Phys"

"The Contactless Affective States Through Physiological Signals Database (CASTPhys) is a high-quality, multimodal dataset specifically developed for remote emotion recognition using both facial and physiological indicators. It features a diverse range of physiological signals, including photoplethysmography (PPG), electrodermal activity (EDA), and respiration rate (RR), along with high-resolution, uncompressed facial video recordings that support remote signal recovery. The dataset contains 1,080 facial videos alongside the corresponding physiological data collected from 60 participants, each of whom annotated 18 emotional video stimuli using self-reported valence and arousal ratings."

Authors

  • Joaquim Comas Martínez ;
  • Alexander Joel Vera ;
  • Xavier Vives ;
  • Eleonora De Filippi ;
  • Federico Sukno ;
  • Alexandre Pereda
0 Citations0 Mentions54% FAIR0.3 Dataset Index
10.21227/bc86-aa672025