FER in primary school children for affective robot tutors

  1. Luis-Eduardo Imbernón Cuadrado
  2. Ángeles Manjarrés Riesco
  3. Félix de la Paz López
From Bioinspired Systems and Biomedical Applications to Machine Learning: 8th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2019, Almería, Spain, June 3–7, 2019, Proceedings, Part II
  1. José Manuel Ferrández Vicente (dir. congr.)
  2. José Ramón Álvarez-Sánchez (dir. congr.)
  3. Félix de la Paz López (dir. congr.)
  4. Javier Toledo Moreo (dir. congr.)
  5. Hojjat Adeli (coord.)

Publisher: Springer Suiza

ISBN: 978-3-030-19651-6

Year of publication: 2019

Pages: 461-471

Type: Book chapter


In the last few years, robotics has attracted much interest asa tool to support education through social interaction. Since Social- Emotional Learning (SEL) influences academic success, affective robot tutors have a great potential within education. In this article we report on our research in recognition of facial emotional expressions, aimed at improving ARTIE, an integrated environment for the development of affective robot tutors. A Full Convolutional Neural Network (FCNN) model has been trained with the Fer2013 dataset, and then validated with another dataset containing facial images of primary school children, which has been compiled during computing lab sessions. Our first prototype recognizesprimary school children facial emotional expressions with 69,15%accuracy. As a future work we intend to further refine the ARTIE Emotional Component with a view to integrating the main singularities of primary school children emotional expression.