Thanks to the miniaturization and flexibility of various sensors, wearables have been broadly applied in many areas, such as sports science, medical informatics, rehabilitation, etc. Researchers are eager to deeply exploit the potential of the wearable sensors and fuse multimodal information, which can actually put theory into practice. However, the integration is usually tough in terms of application. The current challenge is how to find the balance between providing abundant biofeedback and reducing the number of sensors (i.e., avoiding movement constraints). In this paper, we propose to develop a multimodal wearable system that can monitor and acquire multi-source signals in real-time for the alpine skiers; and also, we plan to build a platform where the multimodal information will be fused for further analysis of their performance in the alpine ski slalom. The proposed system will be designed and developed based on a two-chain biomechanical model to reach the balance and provide an optimal solution by using only six IMUs. This paper mainly focuses on exploring the detailed usage of the two-chain biomechanical model and introducing the architecture of the real-time multimodal wearable system. By performing a preliminary experiment, it has been demonstrated that multiple IMUs can work simultaneously in the same coordinate system with high consistency. The Pearson correlation coefficient and the Bland-Altman plot were generated as the validation and support.