Characterizing cardiorespiratory interaction in preterm infants across sleep states using visibility graph analysis.

Cardiorespiratory interaction (CRI) has been intensively studied in adult sleep, yet not in preterm infants, in particular across different sleep states including wake (W), active sleep (AS), and quiet sleep (QS). The aim of this study was to quantify the interaction between cardiac and respiratory activities in different sleep states of preterm infants. The postmenstrual age (PMA) of preterm infants was also taken into consideration. The CRI during sleep was analyzed using a visibility graph (VG) method, enabling the nonlinear analysis of CRI in a complex network. For each sleep state, parameters quantifying various aspects of the CRI characteristics from constructed VG network including mean degree (Dm) and its variability (Dsd), clustering coefficient (CCm) and its variability (CCsd), assortativity coefficient (AC), and complexity (DSE) were extracted from the CRI networks. The interaction effect of sleep state and PMA was found to be statistically significant on all CRI parameters except for AC and DSE. The main effect between sleep state and CRI parameters was statistically significant except for CCm, and that between PMA and CRI parameters was statistically significant except for DSE. In conclusion, the CRI of preterm infants is associated with sleep states and PMA in general. For preterm infants with a larger PMA, CRI has a more clustered pattern during different sleep states, where QS shows a more regular, stratified, and stronger CRI than other states. In the future, these parameters can be potentially used to separate sleep states in preterm infants.NEW & NOTEWORTHY The interaction between cardiac and respiratory activities is investigated in preterm infant sleep using an advanced nonlinear method (visibility graph) and some important characteristics are shown to be significantly different across sleep states, which has not been studied before.

On detection of spontaneous pulse by photoplethysmography in cardiopulmonary resuscitation.

OBJECTIVE: This work investigates the potential of photoplethysmography (PPG) to detect a spontaneous pulse from the finger, nose or ear in order to support pulse checks during cardiopulmonary resuscitation (CPR). METHODS: In a prospective single-center cross-sectional study, PPG signals were acquired from cardiac arrest victims who underwent CPR. The PPG signals were analyzed and compared to arterial blood pressure (ABP) signals as a reference during three distranaisco; Date: 2/2/2020; Time:18:44:23inct phases of CPR: compression pauses, on-going compressions and at very low arterial blood pressure. Data analysis was based on a qualitative subjective visual description of similarities of the frequency content of PPG and ABP waveform. RESULTS: In 9 patients PPG waveforms corresponded to ABP waveforms during normal blood pressures. During ABP in the clinically challenging range of 60 to 90 mmHg and during chest compressions and pauses, PPG continued to resemble ABP, as both signals showed similar frequency components as a result of chest compressions as well as cardiac activity. Altogether 1199 s of PPG data in compression pauses were expected to show a spontaneous pulse, of which 732 s (61%) of data were artifact-free and showed the spontaneous pulse as visible in the ABP. CONCLUSIONS: PPG signals at all investigated sites can indicate pulse presence at the moment the heart resumes beating as verified via the ABP signal. Therefore, PPG may provide decision support during CPR, especially related to preventing and shortening interruptions for unnecessary pulse checks. This could have impact on CPR outcome and should further be investigated.

Reduction of Periodic Motion Artifacts in Photoplethysmography.

Periodic motion artifacts affect photoplethysmography (PPG) signals in activities of daily living (ADL), cardiopulmonary exercise testing (CPX), and cardiopulmonary resuscitation (CPR). This hampers measurement of interbeat intervals (IBIs) and oxygen saturation (SpO 2 ). Our objective was to develop a generic algorithm to remove periodic motion artifacts, recovering artifact-reduced PPG signals for beat-to-beat analysis. METHODS: The algorithm was retrospectively evaluated on forehead PPG signals measured while walking on a treadmill. The step rate was tracked in a motion reference signal via a second-order generalized integrator with a frequency-locked loop. Two reference signals were compared: sensor motion relative to the skin ( ∆x[n]) measured via self-mixing interferometry and head motion ( av[n] ) measured via accelerometry. The step rate was used in a quadrature harmonic model to estimate the artifacts. Quadrature components need only two coefficients per frequency leading to a short filter and prevent undesired frequency-shifted components in the artifact estimate. Subtracting the estimate from the measured signal reduced the artifacts. RESULTS: Compared to ∆x[n] , av[n] had a better signal-to-noise ratio and more consistently contained a component at the step rate. Artifact reduction was effective for distinct step rate and pulse rate, since the artifact-reduced signals provided more stable IBI and SpO 2 measurements. CONCLUSION: Accelerometry provided a more reliable motion reference signal. The proposed algorithm can be of significance for monitoring in ADL, CPX, or CPR, by providing artifact-reduced PPG signals for improved IBI and SpO 2 measurements during periodic motion.

Towards an algorithm for automatic accelerometer-based pulse presence detection during cardiopulmonary resuscitation.

Manual palpation is still the gold standard for assessment of pulse presence during cardiopulmonary resuscitation (CPR) for professional rescuers. However, this method is unreliable, time-consuming and subjective. Therefore, reliable, quick and objectified assessment of pulse presence in cardiac arrest situations to assist professional rescuers is still an unmet need. Accelerometers may present a promising sensor modality as pulse palpation technology for which pulse detection at the carotid artery has been demonstrated to be feasible. This study extends previous work by presenting an algorithm for automatic, accelerometer-based pulse presence detection at the carotid site during CPR. We show that accelerometers might be helpful in automated detection of pulse presence 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.

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.

Reducing motion artifacts in photoplethysmograms by using relative sensor motion: phantom study.

Currently, photoplethysmograms (PPGs) are mostly used to determine a patient's blood oxygenation and pulse rate. However, PPG morphology conveys more information about the patient's cardiovascular status. Extracting this information requires measuring clean PPG waveforms that are free of artifacts. PPGs are highly susceptible to motion, which can distort the PPG-derived data. Part of the motion artifacts are considered to result from sensor-tissue motion and sensor deformation. It is hypothesized that these motion artifacts correlate with movement of the sensor with respect to the skin. This hypothesis has been proven true in a laboratory setup. In vitro PPGs have been measured in a skin perfusion phantom that is illuminated by a laser diode. Optical motion artifacts are generated in the PPG by translating the laser diode with respect to the PPG photodiode. The optical motion artifacts have been reduced significantly in vitro, by using a normalized least-mean-square algorithm with only a single coefficient that uses the laser's displacement as a reference for the motion artifacts. Laser displacement has been measured accurately via self-mixing interferometry by a compact laser diode with a ball lens integrated into the package, which can be easily integrated into a commercial sensor.