Sit-to-Stand (STS) is one of the most frequent movements in people’s daily life. For patients with muscle weakness or paraplegia, exoskeleton assistance is an effective way to resume their ability to STS. And STS is a dynamic process of movement, so the torque of exoskeleton is gradually constructed. Therefore, analysis of the STS process is an important foundation for exoskeleton assist human to stand. In previous studies, most used methods based on mode recognition to determine the phase of the STS. However, pattern recognition methods are poorly interpretable and are affected by training samples and human motion variability. In this paper, based on the dynamic stability analysis of STS movement, we proposed a phase estimation algorithm that considers velocity variation. Six healthy volunteers were recruited in the experiment. The effectiveness of the method mentioned was verified by comparing the changes of XCOM and COM. This model-based method has better interpretability and provides a new means to analyze STS movement.