Cardiac arrest is a leading cause of death in the United States. Despite 40 years of teaching resuscitation techniques and pre-hospital system development to provide pre-hospital medical care rapidly, mortality remains high. It has recently been recognized that not performing chest compressions for relatively short periods of time during resuscitation may be responsible for a significant percentage of the high mortality. Resuscitation guidelines call for the stopping of chest compressions for the determination of the presence or absence of a carotid pulse by healthcare personnel when performing cardiopulmonary resuscitation, yet performance of pulse checks is time consuming and the results are often incorrect. LifeWave has developed an ultra-wideband radar sensor capable of detecting cardiac motion. We propose to develop the software algorithms that will allow this device to quickly determine whether or not a patient's cardiac motion is consistent with a palpable carotid pulse. This Phase 1 grant application has 2 specific aims: 1) Develop an algorithm that uses LifeWave's ultra-wideband radar signal to differentiate between the presence and absence of mechanical heart motion equivalent to the presence or absence of a palpable carotid pulse. We will use the radar sensor to record from animals with a range of heart rates and levels of cardiac contractility. We will use signal processing and statistical techniques to develop an algorithm that identifies whether or not the amount of cardiac motion present is consistent with the presence of a palpable carotid pulse (systolic blood pressure > 60 mmHg). We hypothesize that we will be able to differentiate between the presence and absence of a carotid pulse with 95% sensitivity and 70% specificity from 5 seconds of recorded data. 2) Show that the combination of the LifeWave medical radar and the signal processing algorithm developed in specific aim 1 can determine the mechanical heart motion associated with the presence or absence of a palpable carotid pulse during resuscitation of an animal model of sudden cardiac arrest. We hypothesize that by using the algorithm developed in specific aim 1, we will be able to differentiate between the presence and absence of a palpable carotid pulse with 95% sensitivity and 70% specificity from 5 seconds of data recording. Accomplishment of these two specific aims will show the ability of our ultra-wideband radar device to detect cardiac motion during resuscitation from cardiac arrest and prepare us for a phase II application and the development of a stand-alone radar monitor. Cardiac arrest is a leading cause of death in the United States. Despite 40 years of teaching resuscitation techniques and pre-hospital system development to provide pre-hospital medical care rapidly, mortality remains high. We propose to develop a radar-based pulse detection device that will decrease the amount of time spent performing pulse checks during resuscitation and not spent performing chest compressions. We hope that this device will improve survival following cardiac arrest.
Thesaurus Terms: cardiopulmonary resuscitation, cardiovascular function, computer program /software, patient monitoring device, pulse pressure wave blood pressure, disease /disorder model, heart rate, inhibitor /antagonist, mathematical model, oscillatory blood flow, statistics /biometry, ventricular fibrillation blood flow measurement, swine, time resolved data
