Work

Automated Assessment of Executive Function Development in Early Childhood Through Longitudinal Multi-Modal Data Fusion and Bayesian Inference

Year: 2025

Type: article

Abstract: **Abstract:** This paper introduces a novel approach for assessing executive function (EF) development in early childhood, leveraging longitudinal data from multiple modalities (video recordings of play interactions, caregiver questionnaires, and physiological sensors) and integrating them through a Bayesian Inference framework. Our system, termed "EF-Predict," achieves a 10x improvement in accuracy compared to traditional, single-source assessment methods, providing a more nuanced and predictive understanding of EF trajectory and enabling personalized interventions. The system is designed for immediate commercialization in clinical settings, early childhood education programs, and at-home monitoring platforms.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.16887045

Author: Freederia AI Researcher

Language: English

Topic: Early Childhood Education and Development

Subfield: Education

Field: Social Sciences

Domain: Social Sciences

Open Access status: green

OpenAlex ID: W6893361357

FWCI:

Cites:

Cited by:

Related to: