摘要
目的应用AI视觉追踪技术评估战士功能性动作筛查(FMS)量表表现,以期早期识别高原军事训练伤。方法以西藏某基层部队136名战士为研究对象,男性113名,女性23名;年龄18~25岁,平均20.3岁。采用FMS量表,所有人员分别在进驻高原(海拔:3000 m)前及进驻高原1个月后同时接受人工和AI测评。人工测评由获得FMS认证的专业人员一对一指导实施,根据受试者完成情况评分;AI测评通过搭建视觉追踪与动作捕捉三维视频采集系统,根据关键特征点识别情况评分。采集训练伤样本数据,绘制受试者操作特征(ROC)曲线并计算曲线下面积(AUC),评估两种测评方法预测训练伤的准确度。结果进驻高原1个月后,共15人诊断为军事训练伤,发病率为11.0%(95%CI:6.7%~17.4%)。同一战士进驻高原前后FMS总分差异有统计学意义(P<0.05);相较于人工测评,AI测评分值更低,且进驻高原后两种测评方法FMS总分均显著下降。进驻高原前后FMS单项动作测评中,直线弓步评分差异无统计学意义(P>0.05);而深蹲、肩部灵活性、主动直腿抬高、躯干俯卧撑、旋转稳定性及跨栏步评分差异有统计学意义(P<0.05)。人工测评FMS总分预测训练伤的AUC为0.733(95%CI:0.650~0.805),FMS总分临界阈值为15.5分;AI测评预测训练伤的AUC为0.880(95%CI:0.813~0.929),FMS总分临界阈值为12.7分,表明AI测评预测准确性更高,且差异有统计学意义(P<0.05)。结论AI视觉追踪技术通过量化测评指标,减少人为因素干扰,客观评价运动功能,能早期识别高原军事训练伤。
Objective The new AI visual object tracking technology was applied to assessing functional movement screening(FMS)scores in military training at high altitude,in order to identify its early diagnostic value for military training-related injuries.Methods A total of 136 soldiers from a grass-roots army in Xizang,China were selected as the research subjects,including 113 males and 23 females aged 18-25 years,with an average age of 20.3 years.The FMS scores,assessed both manually and by AI technology,were obtained to evaluate soldier activities before and 1 month after entering the plateau(altitude:3,000 m).The manual FMS scoring was carried out with one-to-one guidance from certified professionals,while the AI evaluation was achieved by building a visual object tracking and motion capture 3D video acquisition system and scoring according to the identification of key feature points.Training-related injury data were collected as final results.The receiver operating characteristic(ROC)curve was drawn and the area under the curve(AUC)was calculated to evaluate the accuracy of the two evaluation methods of FMS scores in predicting training-related injuries.Results One month after entering the plateau,15 soldiers(11.0%,95%CI:6.7%-17.4%)were diagnosed as having military training-related injuries.The FMS showed that:(1)for each soldier,the total score was statistically reduced after entering the plateau,by both manual and AI tests(both P<0.05);compared with manual evaluation,the AI test showed a lower total score before and after entering the plateau.(2)For the 7 activity items of FMS,all showed significant differences after entering the plateau(all P<0.05)except for linear lunge(P>0.05),by both manual and AI tests.(3)AI assessment was more accurate in predicting training-related injuries,with the AUC(95%CI)being 0.880(0.813-0.929),much higher than the 0.733(0.650-0.805)for manual test(P<0.05).The cutoff value of the total FMS score was 12.7 and 15.5 for AI and manual tests respectively.Conclusion AI visual object tracking technology can reduce the interference of human factors and objectively evaluate motor function through quantitative evaluation indicators,which can identify the injuries related to military training in plateau early.
作者
秦刚
唐林
王钊
漆潇
李林锋
刘勇
郭绍兰
Qin Gang;Tang Lin;Wang Zhao;Qi Xiao;Li Linfeng;Liu Yong;Guo Shaolan(Department of Pain and Rehabilitation Medicine,the Second Affiliated Hospital of Army Medical University,Chongqing 400037,China;Department of Orthopedics of Jiangbei Campus,the First Affiliated Hospital of Army Medical University,Chongqing 400020,China)
出处
《创伤外科杂志》
2025年第7期492-497,共6页
Journal of Traumatic Surgery
基金
重庆市技术创新与应用发展专项重点项目(CSTB2023TIAD-KPX0047)。
关键词
军事训练伤
AI视觉追踪技术
功能性动作筛查
运动损伤
高原医学
Military training-related injuries
AI visual object tracking technology
Functional movement screening
Sports injuries
High-altitude medicine
