This paper presents an in-depth study and analysis of the application of the Gestalt theory to music psychotherapy for piano. The paper focuses on how to apply the “whole and part” and “epiphany” perspectives of the Gestalt learning theory to singing and music appreciation lessons. In addition, the Gestalt school’s ideas of developing creative thinking, creating problematic situations, and transferring learning were demonstrated through the implementation of teaching cases. There are differences in the effects of different music on the distribution of body surface temperature; there are differences in the effects of yang music on the Directing Vessel compared to the effects of yin music on the Directing Vessel, and the effects are following the hierarchical model of thinking; there are individual differences in the magnitude of the effects of the same music on the body surface temperature of different people, and the identification of music needs to be combined with the three factors. The wavelet energy entropy (WEE) characteristics of EEG signals were extracted as the input of the designed and optimized deep belief network model, and the average emotional classification accuracy of EEG signals in the left and right brain regions could be obtained as 84.20% and 83.07%, respectively, under the condition of distinguishing brain regions and different music environments. Compared with the classification accuracies of DBN, restricted Boltzmann machine (RBM), and K nearest neighbor (kNN) algorithms in mixed music environments, the classification effects were improved by about 3.49%, 12.89%, and 7.24%. Relying on the ability-poor theory and Weiner attribution theory, different types of secondary school students, their psychological characteristics, and their causes were pointed out. Combined with the psychological characteristics, the case study illustrates the positive effect of music therapy on psychological support.