Authors:
Suyan Zhang
1
;
Xin Dong
2
;
Yan Feng
1
;
Li Chen
3
;
Guanghui Huang
1
and
Jianhua Zhang
4
Affiliations:
1
Faculty of Humanities and Arts, Macau University of Science and Technology, Avenida Wai Long, Macao, China
;
2
Department of Engineering Science, Macau University of Science and Technology, Avenida Wai Long, Macao, China
;
3
School of Creative Media, City University of Hong Kong, Kowloon Tong, Hong Kong, China
;
4
Medical Engineering Technology and Data Mining Institute, Zhengzhou University, 100 Science Avenue, Zhengzhou, China
Keyword(s):
Deep Learning, Data Analysis, Art Therapy, Expression Therapy, Mosaic Art, Mental Health Assessment.
Abstract:
Contemporary children’s mental health has emerged as a focal point of societal concern, particularly given that children are in the foundational stages of physical and psychological development. The exploration of children’s mental health through expressive art therapies, including art therapy, has attracted widespread attention. First, we conduct mosaic art classes for 50 students at a primary school in Henan Province, China, collect students’ works, and test the students’ psychological status according to the mental health scale. Subsequently, we categorize the artworks into positive and negative types, combine them with various deep neural network models to classify the student works, and analyse the correlation between colors, brightness, and student psychological states in the works, aiming to provide a theoretical model for student mental health assessment. Finally, we found that the ResNet model achieved an accuracy of 76% in the artwork classification task. Brightness in stud
ent works cannot be a representative factor of psychological states, whereas the role of color (yellow, blue, green, brown) was particularly prominent. Through this study, we conclude that color in artistic expression has potential value for the mental health of primary school students, providing scientific evidence and theoretical support for contemporary children’s mental health through expressive therapy.
(More)