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A Machine Learning Approach for the Automatic Estimation of Fixation-Time Data Signals' Quality
Giulio Gabrieli1, Jan Paolo Macapinlac Balagtas1, Gianluca Esposito1,2,3
1Psychology Program, School of Social Sciences, Nanyang Technological University, Singapore 639818, Singapore.
Sensors (Basel, Switzerland)
|December 2, 2020
Summary
Machine learning models can automatically distinguish usable from unusable eye fixation recordings in young children, achieving up to 80% accuracy. This offers valuable support for researchers analyzing nonverbal behaviors.
Area of Science:
- Developmental Psychology
- Computer Science
- Data Science
Background:
- Fixation time measures are crucial for studying nonverbal behaviors in infants and young children.
- Analyzing these behavioral signals traditionally requires extensive manual data preprocessing.
