The Intervention of Music Education on Students’ Mental Health Based on Fuzzy Computing

Abstract

Music is an important way for people to express and communicate their thoughts and feelings. It not only has the functions of cultivating sentiment, developing intelligence, and promoting personality development but also has an energetic function on the spiritual fitness of pupils. As an important part of quality education in schools, music education has become a pioneer in the implementation of psychological intervention for students. Music education can cultivate sentiment and lively and optimistic mood by emotional images conveyed through various music and has a special role that cannot be replaced by other disciplines. However, the current music education in schools only focuses on the dissemination of music knowledge and there is no research on which type of music can effectively interfere with students’ mental health. In order to be able to choose music that is effective for students’ mental health intervention in music education, this paper will study the intervention research of music education on students’ mental health based on fuzzy computing. This paper extracts the musical features such as average pitch, average pitch intensity, melody direction, pitch stability value, rhythm intensity, and beat, uses fuzzy computing to classify music, determines which types of music can improve students’ mental health, and uses experiments to verify the validity of this research. The consequences of the research show that choosing effective music to intervene in students’ mental health can greatly improve students’ mental health problems. The scores of students’ psychological status after the intervention are 0.73 times of those before the intervention. It demonstrates the validity of the study.