An Interface Between Pre-existing CPR Performance Measurement Devices and CPR Performance Assessment and Visualization Applications

C12470: Interface between CPR performance measurement devices and performance assessment and visualization applications

Novelty:

A computer software platform with accompanying hardware to provide accurate and clinically realistic quality CPR (QCPR) feedback.

Value Proposition:

The American Heart Association CPR guidelines include metrics that place importance on the quality of the resuscitative effort. QCPR metrics, which include chest compression depth, rate, and recoil, are measured in practice by QCPR-capable clinical monitors to provide real-time and post-event performance feedback. Presently, pre-existing QCPR sensors that provide objective feedback only work with specific clinical monitors and defibrillators, which are usually too expensive to allot for training alone. The majority of CPR training, therefore, is completed with minimal or no objective feedback regarding the rate, depth, or recoil of chest compressions. Poor feedback during training is correlated to inferior clinical performance. This system addresses limitations of using actual clinical devices during training by emulating the clinical device interface, while using clinical QCPR sensors to provide data on chest compression quality. Additional advantages of this technology include:

Technical Details:

Johns Hopkins researchers have developed a system to interface pre-existing CPR performance measurement devices with customizable CPR performance assessment and visualization applications. First, a hardware component continuously samples from the accelerometer output of the QCPR sensor. From this acceleration data, the real-time position is calculated via linear estimation and filtering. Compressions are identified from position data, and the compression rate, depth, and recoil characteristics are recorded. These recorded compression characteristics can be displayed as real-time QCPR feedback for individual chest compressions and/or sets of chest compressions based on American Heart Association CPR Guidelines. This feedback is displayed on a PC, laptop, or tablet for individualized, data-driven CPR training. Other input sensors (e.g. Xbox Kinnect, position sensor) may be used instead of an accelerometer-based QCPR sensor.

Looking for Partners:

To develop and commercialize the technology as a tool for CPR and basic life support training and education.

Stage of Development:

Prototype to be tested in nurse education programs at the Johns Hopkins Hospital

Data Availability:

Prototype