A Feasibility Study for Measuring Accurate Chest Compression Depth and Rate on Soft Surfaces Using Two Accelerometers...

Area of Science:

• Biomedical Engineering
• Emergency Medicine
• Cardiopulmonary Resuscitation Technology

Background:

• Accelerometer-based cardiopulmonary resuscitation (CPR) feedback devices are common.
• Existing devices overestimate chest compression depth on soft surfaces, potentially leading to ineffective resuscitation.
• Accurate depth measurement is crucial for effective CPR.

Purpose of the Study:

• To evaluate a novel algorithm for CPR compression depth and rate measurement using dual accelerometers.
• To assess the algorithm's performance in a simulated resuscitation environment with varying surfaces.
• To address the limitations of current devices in soft surface scenarios.

Main Methods:

• A manikin was used for compressions on foam and sprung mattresses, with and without a backboard.
• Two accelerometers were placed on the manikin's chest and back.
• A new algorithm calculated sternal-spinal displacement by subtracting mattress displacement from total chest displacement, derived from spectral analysis of acceleration data.

Main Results:

• The system demonstrated a median unsigned error of 2.1 mm (4.4%) for compression depth.
• Depth measurement errors varied between mattress types (foam: 2.4 mm, sprung: 1.7 mm) and backboard use.
• Median error for compression rate was 0.9 cpm (1.0%), with no significant differences across conditions.

Conclusions:

• The dual-accelerometer system provides accurate CPR feedback on compression depth and rate, even on soft surfaces.
• The algorithm effectively compensates for mattress displacement, overcoming a key limitation of current devices.
• This technology can improve the quality of CPR delivered in challenging environments.