ISSN 1672-9234 CN 11-5289/R
Responsible Institution:China Association for Science and Technology
Publishing:Chinese Nursing Journals Publishing House Co.,Ltd.
Sponsor:Chinese Nursing Association
Source journal for Chinese Science Citation Database
China Academic Journals Full-text Database
China Core Journal Alternative Database
Chinese Science and Technical Journal Database

Chinese Journal of Nursing Education ›› 2022, Vol. 19 ›› Issue (8): 699-703.doi: 10.3761/j.issn.1672-9234.2022.08.006

• Nursing Education • Previous Articles     Next Articles

The application of a cardiopulmonary resuscitation training software based on posture recognition technology in students of a higher vocational nursing college

LIN Jie(),WANG Huizhu(),XIANG Yue,WU Yuhuan,WU Fengxia,XIE Huosheng   

  • Received:2021-09-17 Online:2022-08-15 Published:2022-08-16
  • Contact: Huizhu WANG E-mail:6830046@qq.com;381790830@qq.com

Abstract:

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.

Key words: Education,Nursing, Cardiopulmonary Resuscitation, Posture recognition, Human-computer interaction