收稿日期: 2021-09-17
网络出版日期: 2022-08-16
基金资助
福州市卫健委创新团队项目(2018-S-wt3);福建省创伤骨科急救与康复临床医学研究中心项目(2020Y2014);福州市临床重点专科建设项目经费资助(201912001)
The application of a cardiopulmonary resuscitation training software based on posture recognition technology in students of a higher vocational nursing college
目的 验证基于姿势识别技术的心肺复苏培训软件在高职护理专业学生心肺复苏操作教学的效果。 方法 选取某卫生职业技术学校2019级2个班级护理专业学生为研究对象,A班为试验组(n=38),在常规教学的基础上使用基于姿势识别技术的心肺复苏培训软件进行辅助教学;B班为对照组(n=49),采用常规演示法进行操作指导。共进行1次理论培训和2次操作培训,分别于3次培训后,使用除颤器所带的反馈仪采集学生胸外按压考核数据,比较两组胸外按压合格率,评价学生的教学满意度。 结果 广义估计方程结果显示,试验组第2、3次培训后的胸外按压操作综合合格率均高于对照组,组间差异有统计学意义(Wald χ2=16.976,P<0.001);两组第2、3次培训后的综合合格率均高于第1次培训后,差异有统计学意义(Wald χ2=48.580,P<0.001)。试验组满意度达100%,对照组为96%。 结论 基于姿势识别技术的心肺复苏培训软件可动态识别并反馈学生胸外按压时的肩、肘、手的动作形态、按压频率与深度,并采用节拍提示标准范围内的按压节律,可起到规范操作姿势、频率的作用,能有效提高学生对胸外按压技能的掌握程度,提高教学满意度。
林洁 , 王惠珠 , 向月 , 吴玉环 , 吴风霞 , 谢伙生 . 基于姿势识别技术的自主研发心肺复苏培训软件在高职护理专业教学中的应用[J]. 中华护理教育, 2022 , 19(8) : 699 -703 . DOI: 10.3761/j.issn.1672-9234.2022.08.006
Objective To examine the effects of a self-developed CPR training software based on posture recognition technology in students of a higher vocational nursing college. Methods Nursing students in 2 classes of Grade 2019 in a higher vocational nursing college were recruited in the study. Students in class A were assigned to the experimental group(n=38) and the cardiopulmonary resuscitation training software based on gesture recognition technology was used in this group. Students in class B were assigned to the control group(n=49) and the routine demonstration was used. One theoretical training and 2 skills training were conducted. After 3 training sessions,the feedback device of the defibrillator was used to collect the assessment data of the chest compressions. The qualified rates of chest compressions were compared between the two groups. Students’ satisfaction with teaching was also evaluated. Results The generalized estimating equation showed that the comprehensive qualified rates of chest compression operation in the experimental group after the second and third training sessions were higher than those in the control group(Wald χ2=16.976,P<0.001). The comprehensive pass rates after the second and third training were higher than those after the first training(Wald χ2=48.580,P<0.001). The satisfaction rate of students in the experimental group was 100% while it was 96% of students in the control group. Conclusion The self-developed CPR software based on posture recognition technology can dynamically recognize and provide feedback to the action form,pressing frequency and depth of the students’ shoulders,elbows,and hands during chest compression. Besides,it uses the beat to prompt the pressing rate within the standard range. The software can play a role in standardizing operation posture and frequency,and can effectively improve students’ mastery of the skills and improve their satisfaction level.
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