用动作捕捉+烟花特效激励用户做广播体操，效果显著提升。
Dance of Fireworks: An Interactive Broadcast Gymnastics Training System Based on Pose Estimation
- 通过手机摄像头实时分析姿势，动态生成烟花动画反馈
- 4轮训练后关节角度误差从21.3°降至9.8°，参与率达93.4%
- 无需专业设备，适合办公室等久坐场景长期使用
本研究提出Dance of Fireworks系统，利用移动设备摄像头与轻量级姿态估计（PoseNet/TensorFlow Lite）技术，实时提取人体关键点并计算关节角度，与标准动作对比提供即时纠正反馈。为提升参与意愿，系统将用户动作参数（如关节角度、速度）映射为可定制的烟花动画，动作越准确，视觉效果越丰富。136名参与者实验显示，经过四轮训练，平均关节角度误差由21.3°降至9.8°（p < 0.01），93.4%用户认为其有效促进锻炼，85.4%称赞其娱乐性。系统无需预设动作模板或专用硬件，可无缝融入办公环境。未来将优化姿态识别精度、降低延迟，并增加多人互动与音乐同步功能。该方案为久坐人群提供了低成本、高参与度的运动激励方案。
原文摘要 · Abstract (English)
This study introduces Dance of Fireworks, an interactive system designed to combat sedentary health risks by enhancing engagement in radio calisthenics. Leveraging mobile device cameras and lightweight pose estimation (PoseNet/TensorFlow Lite), the system extracts body keypoints, computes joint angles, and compares them with standardized motions to deliver real-time corrective feedback. To incentivize participation, it dynamically maps users' movements (such as joint angles and velocity) to customizable fireworks animations, rewarding improved accuracy with richer visual effects. Experiments involving 136 participants demonstrated a significant reduction in average joint angle errors from 21.3 degrees to 9.8 degrees (p < 0.01) over four sessions, with 93.4 percent of users affirming its exercise-promoting efficacy and 85.4 percent praising its entertainment value. The system operates without predefined motion templates or specialised hardware, enabling seamless integration into office environments. Future enhancements will focus on improving pose recognition accuracy, reducing latency, and adding features such as multiplayer interaction and music synchronisation. This work presents a cost-effective, engaging solution to promote physical activity in sedentary populations.
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