Wouter Herman Peeters

Detection of a spontaneous pulse in photoplethysmograms during automated cardiopulmonary resuscitation in a porcine model

INTRODUCTION Reliable, non-invasive detection of return of spontaneous circulation (ROSC) with minimal interruptions to chest compressions would be valuable for high-quality cardiopulmonary resuscitation (CPR). We investigated the potential of photoplethysmography (PPG) to detect the presence of a spontaneous pulse during automated CPR in an animal study. METHODS Twelve anesthetized pigs were instrumented to monitor circulatory and respiratory parameters. Here we present the simultaneously recorded PPG and arterial blood pressure (ABP) signals. Ventricular fibrillation was induced, followed by 20 min of automated CPR and subsequent defibrillation. After defibrillation, pediatric-guidelines-style life support was given in cycles of 2 min. PPG and ABP waveforms were recorded during all stages of the protocol. Raw PPG waveforms were acquired with a custom-built photoplethysmograph controlling a commercial reflectance pulse oximetry probe attached to the nose. ABP was measured in the aorta. RESULTS In nine animals ROSC was achieved. Throughout the protocol, PPG and ABP frequency content showed strong resemblance. We demonstrate that (1) the PPG waveform allows for the detection of a spontaneous pulse during ventilation pauses, and that (2) frequency analysis of the PPG waveform allows for the detection of a spontaneous pulse and the determination of the pulse rate, even during ongoing chest compressions, if the pulse and compression rates are sufficiently distinct. CONCLUSIONS These results demonstrate the potential of PPG as a non-invasive means to detect pulse presence or absence, as well as pulse rate during CPR.

Photoplethysmography-Based Algorithm for Detection of Cardiogenic Output During Cardiopulmonary Resuscitation

Detecting return of spontaneous circulation (ROSC) during cardiopulmonary resuscitation (CPR) is challenging, time consuming, and requires interrupting chest compressions. Based on automated-CPR porcine data, we have developed an algorithm to support ROSC detection, which detects cardiogenic output during chest compressions via a photoplethysmography (PPG) signal. The algorithm can detect palpable and impalpable spontaneous pulses. A compression-free PPG signal which estimates the spontaneous pulse waveform, was obtained by subtracting the compression component, modeled by a harmonic series. The fundamental frequency of this series was the compression rate derived from the transthoracic impedance signal measured between the defibrillation pads. The amplitudes of the harmonic components were obtained via a least mean-square algorithm. The frequency spectrum of the compression-free PPG signal was estimated via an autoregressive model, and the relationship between the spectral peaks was analyzed to identify the pulse rate (PR). Resumed cardiogenic output could also be detected from a decrease in the baseline of the PPG signal, presumably caused by a redistribution of blood volume to the periphery. The algorithm indicated cardiogenic output when a PR or a redistribution of blood volume was detected. The algorithm indicated cardiogenic output with 94% specificity and 69% sensitivity compared to the retrospective ROSC detection of nine clinicians. Results showed that ROSC detection can be supported by combining the compression-free PPG signal with an indicator based on the detected PR and redistribution of blood volume.

On algorithms for calculating arterial pulse pressure variation during major surgery

OBJECTIVE Arterial pulse pressure variation (PPV) is widely used for predicting fluid responsiveness and supporting fluid management in the operating room and intensive care unit. Available PPV algorithms have been typically validated for fluid responsiveness during episodes of hemodynamic stability. Yet, little is known about the performance of PPV algorithms during surgery, where fast changes of the blood pressure may affect the robustness of the presented PPV value. This work provides a comprehensive understanding of how various existing algorithmic designs affect the robustness of the presented PPV value during surgery, and proposes additional processing for the pulse pressure signal before calculating PPV. APPROACH We recorded arterial blood pressure waveforms from 23 patients undergoing major abdominal surgery. To evaluate the performance, we designed three clinically relevant metrics. Main results and Significance: The results show that all algorithms performed well during episodes of hemodynamic stability. Moreover, it is demonstrated that the proposed processing helps improve the robustness of PPV during the entire course of surgery.