沈阳航空航天大学学报2026，Vol.43Issue(1)：63-72,10.DOI:10.3969/j.issn.2095-1248.2026.01.009
基于人体姿态估计的健身运动评估系统
Fitness exercise evaluation system based on human posture estimation
摘要
Abstract
In order to solve the problem that the current fitness exercise evaluation systems provided poor evaluation information and involved high computational complexity,a fitness exercise evaluation system based on human posture estimation was proposed.The system utilized the built-in camera of mobile phones or tablet computers,combined with human pose estimation algorithms,action recognition algorithms,and action evaluation algorithms to achieve intelligent and effective evaluation of users'fitness exercises.Firstly,the MediaPipe algorithm was used to estimate the human posture and obtain the human joint bone data.Then,it was fed into the proposed SCBT-GCN network for action recognition.Based on kinematic principles,a series of evaluation methods had been designed which evaluate joint angles,symmetry,trajectory characteristics,and movement fluency.Finally,corresponding targeted movement assessment algorithms were invoked based on the identified action categories to detect and evaluate abnormal fitness movements,thereby forming a fitness action evaluation system with strong intelligence and high real-time performance.Experimental results show that the system has an accuracy of 98.6%in action recognition,which can detect abnormal actions in real time and score fitness actions offline,demonstrating high practical value.关键词
人体姿态估计/动作识别/动作评估/ST-GCN/高斯混合模型Key words
human posture estimation/action recognition/action evaluation/ST-GCN/Gaussian mixture model分类
信息技术与安全科学引用本文复制引用
冯雅迪,姬晓飞,田舒文,王竹筠..基于人体姿态估计的健身运动评估系统[J].沈阳航空航天大学学报,2026,43(1):63-72,10.基金项目
国家自然科学基金(项目编号:62003224). （项目编号:62003224）
