This paper presents an in-depth analysis and study of the role of piano performance in alleviating psychological trauma in people with psychological isolation disorder. In this paper, we designed a music modulation system based on EEG signals of people with isolation disorder and designed an interface with real-time emotion recognition. MATLAB is responsible for data processing and classification, while Python is responsible for communication and real-time transmission between modules, EEG signal collection, and processing. For the EEG signals in the DEAP emotion database, a Butterworth bandpass filter is used to denoise the signals, and then, a wavelet packet decomposition reconstruction is used to remove the artifacts and complete the preprocessing of the signals. Finally, the support vector machine with optimized parameters of the genetic algorithm was used to classify the positive, neutral, and negative samples with 89.23% accuracy. In this study, all subjects were divided into experimental and control groups by experimentally measuring the changes in heart rate, skin electrical conduction, skin temperature, and EEG signals before and after the experimental group, and statistical analysis was also performed on the data tabulation of the experimental and control groups. The experimental results proved that piano playing has a significant effect on relieving the psychological trauma of people with psychological isolation disorder when the training frequency of piano playing therapy reaches a certain intensity. This study provides a certain theoretical basis for clinical, educational, and health services.