Development of a smart backboard system for real-time feedback during CPR chest compression on a soft back support surface

The quality of cardiopulmonary resuscitation (CPR) is often inconsistent and frequently fails to meet recommended guidelines. One promising approach to address this problem is for clinicians to use an active feedback device during CPR. However, one major deficiency of existing feedback systems is that they fail to account for the displacement of the back support surface during chest compression (CC), which can be important when CPR is performed on a soft surface. In this study we present the development of a real-time CPR feedback system based on an algorithm which uses force and dual-accelerometer measurements to provide accurate estimation of the CC depth on a soft surface, without assuming full chest decompression. Based on adult CPR manikin tests it was found that the accuracy of the estimated CC depth for a dual accelerometer feedback system is significantly better (7.3% vs. 24.4%) than for a single accelerometer system on soft back support surfaces, in the absence or presence of a backboard. In conclusion, the algorithm used was found to be suitable for a real-time, dual accelerometer CPR feedback application since it yielded reasonable accuracy in terms of CC depth estimation, even when used on a soft back support surface.