中国医疗设备2025，Vol.40Issue(10)：37-43,7.DOI:10.3969/j.issn.1674-1633.20250249
八段锦运动场景下的手部关键点检测算法研究
Research on Hand Key Point Detection Algorithm in Baduanjin Motion Scenarios
摘要
Abstract
Objective To design a hand key point detection algorithm for the intelligent guidance and evaluation system of Baduanjin,in order to solve a series of challenging problems such as occlusion,complex action details and mobile deployment.Methods Based on the YOLOv8n-pose model,a hand key point detection algorithm YOLO-BDJ-Hands for the Baduanjin scene was proposed.The separation enhanced attention module was introduced to learn the adaptive weight attention of hand occlusion region.The receptive field expansion module was used to increase the receptive field range and enhance the ability to detect hand detail features at different scales.Results On the Baduanjin hand key point dataset,the detection precision and recall rate of the YOLO-BDJ-Hands algorithm were 0.912 and 0.901 respectively.The number of model params was 3.1 M,which was 9%less than that of the original model.The floating point operations was 9.5 B,which could meet the requirements of mobile deployment.Conclusion The YOLO-BDJ-Hands algorithm proposed in this study has high robustness and generalization performance,basically achieving model lightweighting,facilitating deployment and application on mobile terminals,and can provide effective technical support for the subsequent development and promotion of the intelligent guidance and evaluation system of Baduanjin.关键词
八段锦/手部关键点检测/注意力机制/多尺度特征/轻量化/YOLOv8Key words
Baduanjin/hand key point detection/attention mechanism/multi-scale features/lightweight/YOLOv8分类
医药卫生引用本文复制引用
万璐,孙兆才,李翔,魏本征..八段锦运动场景下的手部关键点检测算法研究[J].中国医疗设备,2025,40(10):37-43,7.基金项目
国家自然科学基金(62372280 （）
62402297) （）
山东省自然科学基金(2023QF094 （）
2024MF139) （）
青岛市科技惠民示范专项(23-2-8-smjk-2-nsh) （23-2-8-smjk-2-nsh）
齐鲁健康与卫生领军人才计划项目 （）
山东省青年科技人才托举工程 （）
山东中医药大学科学研究基金重点项目(KYZK2024Z07). （KYZK2024Z07）
