The recent advancements in the field of human motion analysis and sports technique feedback are significantly enhancing the precision and efficiency of monitoring and correcting human movements. Researchers are increasingly focusing on integrating artificial intelligence, edge computing, and IoT technologies to develop real-time, cost-effective, and accurate systems for posture correction, gait analysis, and sports technique feedback. These systems are not only improving the performance of athletes and individuals with prostheses but also broadening the accessibility of advanced sports science technologies to a wider audience. Notably, the use of deep learning algorithms and hierarchical attention mechanisms in pose estimation models is leading to more robust and accurate real-time feedback systems, even in complex and dynamic environments. Additionally, the incorporation of process-aware information in human activity recognition is enhancing the contextual understanding and accuracy of these systems. These innovations are paving the way for more intelligent and adaptive sports and health management systems.