研发一种无需假设完全胸廓回弹的 CPR 中实时反馈按压的算法。
Development of a real-time feedback algorithm for chest compression during CPR without assuming full chest decompression.
机构信息
Biomedical Engineering Research Group, Department of Mechanical and Mechatronic Engineering, Stellenbosch University, Private Bag X1, Matieland 7602, South Africa.
Biomedical Engineering Research Group, Department of Mechanical and Mechatronic Engineering, Stellenbosch University, Private Bag X1, Matieland 7602, South Africa.
出版信息
Resuscitation. 2014 Jun;85(6):820-5. doi: 10.1016/j.resuscitation.2014.03.003. Epub 2014 Mar 13.
OBJECTIVES
To evaluate the performance of a real-time feedback algorithm for chest compression (CC) during cardiopulmonary resuscitation (CPR), which provides accurate estimation of the CC depth based on dual accelerometer signal processing, without assuming full CDC. Also, to explore the influence of incomplete chest decompression (CDC) on the CC depth estimation performance.
METHODS
The performance of a real-time feedback algorithm for CC during CPR was evaluated by comparison with an offline algorithm using adult CPR manikin CC data obtained under various conditions.
RESULTS
The real-time algorithm, using non-causal baselining, delivered comparable CC depth estimation accuracy to the offline algorithm on both soft and hard back support surfaces. In addition, for both algorithms incomplete CDC led to underestimation of the CC depth.
CONCLUSIONS
CPR feedback systems which utilize an assumption of full CDC may be unreliable especially in long duration CPR events where rescuer fatigue can strongly influence CC quality. In addition, these systems may increase the risk of thoracic and abdominal injury during CPR since rescuers may apply excessive compression forces due to underestimation of the CC depth when incomplete CDC occurs. Hence, there is a strong need for CPR feedback systems to accurately measure CDC in order to improve their clinical effectiveness.
目的
评估一种基于双加速计信号处理的实时反馈算法在心肺复苏（CPR）期间的胸外按压（CC）性能，该算法可根据实际情况准确估计 CC 深度，而无需假设完全的胸部回弹（CDC）。此外，还探索了不完全的胸部回弹（CDC）对 CC 深度估计性能的影响。
方法
通过比较使用成人 CPR 模型在各种条件下获得的 CC 数据的离线算法，评估了 CPR 期间 CC 的实时反馈算法的性能。
结果
在软、硬背板支撑表面上，使用非因果基线的实时算法与离线算法相比，提供了可比的 CC 深度估计准确性。此外，对于这两种算法，不完全的 CDC 都会导致 CC 深度的低估。
结论
使用完全 CDC 假设的 CPR 反馈系统可能不可靠，特别是在长时间 CPR 事件中，救援人员的疲劳可能强烈影响 CC 质量。此外，由于不完全的 CDC 会导致 CC 深度的低估，这些系统可能会增加 CPR 期间胸部和腹部损伤的风险，因为救援人员可能会因 CC 深度的低估而施加过大的按压力量。因此，强烈需要 CPR 反馈系统来准确测量 CDC，以提高其临床效果。
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