Abstract: Emotion recognition is an important research direction in the fields of artificial intelligence and human-computer interaction. It has significant implications for enhancing user experience and the intelligence of applications. Emotion recognition based on multimodal physiological data has become a research hotspot in recent years due to the objectivity and diversity of its data sources, which enable more accurate capture of an individual's emotional state. Firstly, the basic concepts of affective computing and emotion representation models are introduced. Secondly, emotion recognition methods based on physiological data are summarized. Then, the focus shifts to the process of emotion recognition based on multimodal physiological data, including physiological data preprocessing, traditional machine learning methods, and deep learning methods. Finally, the main challenges faced by emotion recognition based on multimodal physiological data are analyzed, and future prospects are discussed.