This paper studies a human motion analysis system for limb status assessment and motion posture correction. Firstly, to address the problems such as occlusion that are prone to occur during human motion, this paper introduces deformable attention and generative adversarial networks based on Transformer for optimal human key point location detection. Secondly, using the proposed algorithm, this paper designs a motion analysis system by combining the limb space constraint relationship of human posture and knowledge related to body posture analysis. Finally, through testing on public datasets and in real scenarios, this paper evaluates the feasibility of the proposed algorithm and system from both qualitative and quantitative perspectives in experiments. The experimental results prove that the detection accuracy of the algorithm in this paper can reach up to 937% on public datasets; in the tests on real scenes, the algorithm and the motion analysis system designed in this paper can effectively solve the common problems such as occlusion in human posture recognition, and show the multidimensional analysis results of human motion posture through the visualization system.