A Semi-Physical Simulation System for Evaluation of Cardiopulmonary Resuscitation Mechanical Compression Parameters Based on Fracture Risk and Blood Perfusion
High-quality cardiopulmonary resuscitation (CPR) is a critical determinant of survival following cardiac arrest. In recent years, mechanical compression has become increasingly prevalent in the emergency management of cardiac arrest. The settings of key compression parameters strongly influence the effectiveness of chest compression. This study developed a semi-physical simulation platform and evaluation criteria to assess the optimal parameters for CPR. A multi-spring system was designed to simulate the risk of sternal fractures during chest compression. Additionally, a blood flow model was constructed to simulate blood perfusion. The evaluation criteria, which include quantifying sternal fracture risk and blood perfusion, are used to calculate the compression effect by inputting the compression force and depth data into the evaluation model. (Analysis of Variance)ANOVA analysis demonstrated statistically significant impacts of different compression parameters on compression outcomes. The results demonstrated that the mechanical waveform data more accurately reflected the compression dynamics encountered in real-world CPR circumstances. The trapezoidal compression waveform demonstrated clear superiority over triangle and sine waveforms, enhancing blood circulation. This study’s exploration of the trapezoidal waveform fills a gap in the AHA guidelines. In addition to the waveform, the study confirmed that a compression depth of 50 mm and a frequency of 120 compressions per minute yielded the most effective hemodynamic outcomes. These findings validated and expanded upon the AHA guidelines, offering a novel and comprehensive approach to optimising CPR effectiveness, improving both patient survival rates and the quality of mechanical resuscitation.
Authors
- Peng Zhao (ORCID: https://orcid.org/0000-0002-3815-1248)
- Jiefeng Xu (ORCID: https://orcid.org/0000-0001-5597-0838)
- Yifeng Pan (ORCID: https://orcid.org/0009-0003-6664-9531)
- Yufeng Hu (ORCID: https://orcid.org/0000-0002-9416-262X)
- Mao Zhang (ORCID: https://orcid.org/0000-0001-7919-8213)
- Y. Chen (ORCID: https://orcid.org/0009-0003-1400-1346)
Institutions
- Second Affiliated Hospital of Zhejiang University (CN)
- Zhejiang University (CN)
Publication Details
- Journal
- IEEE Sensors Journal
- Published
- 2025-08-25
- DOI
- https://doi.org/10.1109/jsen.2025.3589561
- Primary Topic
- Cardiac Arrest and Resuscitation
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Key Research and Development Program of China