University of Pittsburgh researchers have developed Signal-Guided Chest Compression CPR (SGCC-CPR), an automatic chest compression device utilizing biological feedback to improve the efficacy of cardiopulmonary resuscitation (CPR) during out of hospital cardiac arrest (OHCA).
Description
Out-of-hospital cardiac arrest (OHCA) is one of the leading causes of mortality in the United States. Early and efficient CPR, involving chest compressions and rescue breaths to continue oxygenation of vital organs along with electrical defibrillation provides the best chance of patient survival. However, survival from OHCA is less than 10%. This device aims to improve the effectiveness of chest compressions through automation of the process and adjusting compressions in response to physiological feedback has the potential to improve the effectiveness of CPR and survival rates.
Applications
· Prehospital care
· In-Hospital care
· Nursing home and community care
Advantages
Traditionally, manual CPR has been provided by healthcare providers. More recently, automatic compression devices have been increasingly used to provide consistent and effective chest compression removing the risk of fatigue. However, the limitation of these devices is that they apply the same rate of compression and depth to all patients, regardless of patient chest size or other physiological features.
SGCC-CPR has been designed to tailor compression rate and depth to patients based on factors including diameter and compliance of the chest. Using devices already found in healthcare settings, parameters can be adjusted during active CPR compression to improve the physiological response. The depth and rate of compressions is optimized through monitoring key physiological variables like blood pressure and ECG analysis. This novel device is the first known automatic compression device known to incorporate biological feedback allowing for personalized compression based on physiological feedback, unlike the current one-size-fits-all approach.
Invention Readiness
A fully functioning prototype has been developed. In a proof-of-concept animal study, biosignals derived from arterial pressure and ECG waveforms were used to control the rate and depth of chest compressions. Using an algorithm, compressions were adjusted to optimize these biosignals. All animals showed improvement in biosignals. Further work is required to optimize this device, explore the inclusion of other biosignals including tissue oxygenation levels, and begin human studies.
IP Status
https://patents.google.com/patent/US20160317385A1
