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Background: Lower body negative Pressure (LBNP)-induced hypovolemia is simulating acute hemorrhage by sequestrating blood into lower extremities. Bioelectrical Impedance Analysis (BIA) is based on the electrical properties of biological tissues, as electrical current flows along highly conductive body tissues (such as blood). Changes in blood volume will lead to changes in bioimpedance. This study aims to study changes in upper (UL) and lower (LL) extremities bioimpedance during LBNP-induced hypovolemia. Methods: This was a prospective observational study of healthy volunteers who underwent gradual LBNP protocol which consisted of 3-minute intervals: at baseline, -15, -30, -45, -60 mmHg, then recovery phases at -30 mmHg and baseline. The UL&LL extremities bioimpedance were measured and recorded at each phase of LBNP and the percentage changes of bioimpedance from baseline were calculated and compared using student's t-test. A P-value of < 0.05 was considered significant. Correlation between relative changes in UL&LL bioimpedance and estimated blood loss (EBL) from LBNP was calculated using Pearson correlation. Results: 26 healthy volunteers were enrolled. As LBNP-induced hypovolemia progressed, there were a significant increase in UL bioimpedance and a significant decrease in LL bioimpedance. During recovery phases (where blood was shifted from the legs to the body), there were a significant increase in LL bioimpedance and a reduction in UL bioimpedance. There were significant correlations between estimated blood loss from LBNP model with UL (R = 0.97) and LL bioimpedance (R = − 0.97). Conclusion: During LBNP-induced hypovolemia, there were reciprocal changes in UL&LL bioimpedance. These changes reflected hemodynamic compensatory mechanisms to hypovolemia. [ABSTRACT FROM AUTHOR]

Develop a signal quality index (SQI) for the widely available peripheral venous pressure waveform (PVP). We focus on the quality of the cardiac component in PVP. We model PVP by the adaptive non-harmonic model. When the cardiac component in PVP is stronger, the PVP is defined to have a higher quality. This signal quality is quantified by applying the synchrosqueezing transform to decompose the cardiac component out of PVP, and the SQI is defined as a value between 0 and 1. A database collected during the lower body negative pressure experiment is utilized to validate the developed SQI. All signals are labeled into categories of low and high qualities by experts. A support vector machine (SVM) learning model is trained for practical purpose. The developed signal quality index coincide with human experts' labels with the area under the curve 0.95. In a leave-one-subject-out cross validation (LOSOCV), the SQI achieves accuracy 0.89 and F1 0.88, which is consistently higher than other commonly used signal qualities, including entropy, power and mean venous pressure. The trained SVM model trained with SQI, entropy, power and mean venous pressure could achieve an accuracy 0.92 and F1 0.91 under LOSOCV. An exterior validation of SQI achieves accuracy 0.87 and F1 0.92; an exterior validation of the SVM model achieves accuracy 0.95 and F1 0.96. The developed SQI has a convincing potential to help identify high quality PVP segments for further hemodynamic study. This is the first work aiming to quantify the signal quality of the widely applied PVP waveform. [ABSTRACT FROM AUTHOR]

The photoplethysmographic (PPG) waveform contains hemodynamic information in its oscillations. We provide a new method for quantitative study of the waveform morphology and its relationship to the hemodynamics. A data adaptive modeling of the waveform shape is used to describe the PPG waveforms recorded from ear and finger. Several indices, based on the phase and amplitude information of different harmonics, are proposed to describe the PPG morphology. The proposed approach is illustrated by analyzing PPG waveforms recorded during a lower body negative pressure (LBNP) experiment. Different phase and amplitude dynamics are observed during the LBNP experiment. Specifically, we observe that the phase difference between the high order harmonics and fundamental components change more significantly when the PPG signal is recorded from the ear than the finger at the beginning of the study. In contrast, the finger PPG amplitude changes more when compared to the ear PPG during the recovery period. A more complete harmonic analysis of the PPG appears to provide new hemodynamic information when used during a LBNP experiment. We encourage other investigators who possess modulated clinical waveform data (e.g. PPG, arterial pressure, respiratory, and autonomic) to re-examine their data, using phase information and higher harmonics as a potential source of new insights into underlying physiologic mechanisms. [ABSTRACT FROM AUTHOR]

We introduce a recently developed nonlinear-type time-frequency analysis tool, synchrosqueezing transform (SST), to quantify complicated and noisy physiological waveform that has time-varying amplitude and frequency. We apply it to analyze a peripheral venous pressure (PVP) signal recorded during a seven hours aortic valve replacement procedure. In addition to showing the captured dynamics, we also quantify how accurately we can estimate the instantaneous heart rate from the PVP signal. [ABSTRACT FROM AUTHOR]

From home to intensive care units, innovations in pulse oximetry are susceptible to improve the monitoring and management of patients developing acute respiratory failure, and particularly those with the coronavirus disease 2019 (COVID-19). They include self-monitoring of oxygen saturation (SpO2) from home, continuous wireless SpO2 monitoring on hospital wards, and the integration of SpO2 as the input variable for closed-loop oxygen administration systems. The analysis of the pulse oximetry waveform may help to quantify respiratory efforts and prevent intubation delays. Tracking changes in the peripheral perfusion index during a preload-modifying maneuver may be useful to predict preload responsiveness and rationalize fluid therapy. [ABSTRACT FROM AUTHOR]

During shoulder surgery, patients typically are placed in the beach chair position. In rare cases, this positioning has resulted in devastating outcomes of postoperative cerebral ischemia (Cullen and Kirby in APSF Newsl 22(2):25-27, ; Munis in APSF Newsl 22(4):82-83, ). This study presents a method to noninvasively and continuously hemodynamically monitor patients during beach chair positioning by using the photoplethysmograph signal recorded from a commercial pulse oximeter. Twenty-nine adults undergoing shoulder surgery were monitored before and after beach chair positioning with electrocardiogram, intermittent blood pressure, end tidal carbon dioxide, and photoplethysmograph via Nellcor finger pulse oximeter. Fast Fourier transform (FFT) was used to perform frequency-domain analysis on the photoplethysmograph (PPG) signal for data segments taken 80-120 s before and after beach chair positioning. The amplitude density of respiration-associated PPG oscillations was quantified measuring the height of the FFT peak at respiratory frequency. Results were reported as (median, interquartile range) and statistical analysis was performed using Wilcoxon sign rank test. Data were also collected when vasoactive drugs phenylephrine and ephedrine were used to maintain acceptable mean arterial pressure during a case. With beach chair positioning, all subjects who did not receive vasoactive drugs showed an increase in the FFT amplitude density of respiration-associated PPG oscillations ( p < 0.0001) without change in pulse-associated PPG oscillations. The PPG was more accurate at monitoring the change to beach chair position than blood pressure or heart rate. With vasoactive drugs, pulse-associated PPG oscillations decreased only with phenylephrine while respiration-associated oscillations did not change. Frequency domain analysis of the PPG signal may be a better tool than traditional noninvasive hemodynamic parameters at monitoring patients during beach chair position surgery. [ABSTRACT FROM AUTHOR]

Since the discovery of anesthetic agents, patient monitoring has been considered one of the core responsibilities of the anesthesiologist. As depicted in Robert Hinckley's famous painting, The First Operation with Ether, one observes William Thomas Green Morton carefully watching over his patient. Since its founding in 1905, 'Vigilance' has been the motto of the American Society of Anesthesiologists (ASA). Over a hundred years have passed, and one would think we would be clear regarding what we are watching for and how we should be watching. On the contrary, the introduction of new technology and outcome research is requiring us to re-examine our fundamental assumptions regarding what is and what is not important in the care of the patient. A vast majority of anesthesiologists would refuse to proceed with an anesthetic without the presence of a pulse oximeter. On the other hand, outcome studies have failed to demonstrate an improvement in patient care with their use. For that matter, it can be argued that outcome studies have yet to demonstrate an unambiguous role for any monitor of any type (i.e. blood pressure cuff or ECG), as outcome studies may fail to capture rare events. Because of the increased safety that has been attributed to pulse oximetry, it is unlikely that further studies can or will be conducted. As we enter a new era of clinical monitoring, with an emphasis on noninvasive cardiovascular monitoring, it might be of benefit to examine the role of the pulse oximeter in clinical care. This article reviews the available evidence for pulse oximetry. Further, it discusses contemporary issues, events, and perceptions that may help to explain how and why pulse oximetry may have been adopted as a standard of care despite the lack of supportive. Lastly, it discusses less obvious benefits of pulse oximetry that may have further implications on the future of anesthesia care and perhaps even automated anesthesia. [ABSTRACT FROM AUTHOR]

Introduction: Our study sought to explore changes in photoplethysmographic (PPG) waveform param- eters, during lower body negative pressure (LBNP) which simulated hypovolemia, in spontaneously breathing volunteers. We hypothesize that during progressive LBNP; there will be a preservation of ear PPG parameters and a decrease in finger PPG parameters.Methods: With IRB approval, 11 volunteers underwent a LBNP protocol at baseline, 30, 75, and 90 mm Hg (or until the subject became symptomatic). Subjects were monitored with finger and ear pulse oximeter probes, an ECG, and a finger arterial blood pressure monitor. The square root of the mean of the squared differences between adjacent NN intervals (RMSSD) which is the time domain analysis of the heart rate variability (HRV) was measured. PPG waveforms were analyzed for height, area, width 50, maximum and minimum slope. Data are presented as median and inter-quartile range. Friedman ANOVA and Wilcoxon tests were used to identify changes in hemo- dynamic and PPG parameters, P < 0.017 was considered statistically significant.Results: There were no significant changes in the blood pressure variables at LBNP(30), but at and beyond LBNP(75), the decreases in systolic, mean and pulse pressure were significant as was the increase in diastolic pressure. Heart rate increased significantly at LBNP(30), reaching a maximum of 75.4% above baseline at the symptomatic phase while RMSSD showed significant reduction at LBNP(75). Finger PPG height, area, width 50, and maximum slope decreased significantly at LBNP(30) and during symptomatic phase they showed a reduction of 59.4, 76.9, 27.4 and 51.6%, respectively. Ear PPG height, area, width 50 and maximum slope did not change significantly until the LBNP(75), reached. During symptomatic phase, the respective declines reached 39.3, 61.0, 21.4 and 34.9%.Conclusion: PPG waveform parameters may prove to be sensitive and specific as early indicators of blood loss. These PPG changes were observed before profound decreases in arterial blood pressure. The relative sparing of central cutaneous blood flow is consistent with the increased parasympathetic innervation of central structures. [ABSTRACT FROM AUTHOR]

Objective: The photoplethysmographic (PPG) waveforms are modulated by the respiratory, cardiac and autonomic nervous system. Lower body negative pressure (LBNP) has been used as an experimental tool to simulate loss of central blood volume in humans. The aim of our research is to understanding PPG waveform changes during progressive hypovolemia.Methods: With IRB approval, 11 volunteers underwent a LBNP protocol at baseline, 30, 75, and 90 mmHg (or until the subject became symptomatic). Subjects were monitored with finger and ear pulse oximeter probes, ECG, and finger arterial blood pressure monitor (FABP). Heart rate variability (HRV) was analyzed to high frequency (HRV-HF) (0.12-0.4 Hz) and low frequency (HRV-LF) (0.04-0.12 Hz). Frequency analysis of PPG waveforms were computed to low (0.04-0.11 Hz) frequency (PPG-LF), intermediate (0.12-0.18 Hz) frequency (PPG-IF), respiratory (0.19-0.3 Hz) frequency (PPG-Resp.) and cardiac (0.75-2.5 Hz) frequency (PPG-Cardiac)during different phases of LBNP protocolResults: Heart rate increased significantly while systolic, mean and pulse pressure of the FABP declined slowly together with significant reductions in HRV-HF (0.12-0.4 Hz) and HRV-LF (0.04-0.12 Hz) power at LBNP(75). There was significant reduction in finger PPG-Cardiac modulation which is consistent with the reduction in the pulse pressure of the FABP. As the LBNP progress there was shift in the amplitude density of the ear PPG-Cardiac to PPG-Resp. Oscillation as an evidence of progressive hypovolemia with reduction in pulse pressure and increase in the respiratory induced variations. At LBNP(75), there were significant increased (>140% increase from the baseline) in ear PPG-IF (0.12-0.18 Hz) in the meantime HRV-HF showed significant reduction (>89%) from the baseline. At the symptomatic phase; there was a shift in ear PPG-IF to PPG-Resp. With an increase in the ear PPG-Resp. Modulation to ≥175% from the baselineConclusion: The pulse oximeter waveform contains a complex mixture of the effect of cardiac, venous, autonomic, and respiratory systems on the central and peripheral circulation. The occurrence of autonomic modulation needs to be taken into account when studying signals that have their origins from central sites (e.g. ear and forehead). [ABSTRACT FROM AUTHOR]

Objective: We investigate the hypothesis that the photoplethysmograph (PPG) waveform can be analyzed to infer regional venous oxygen saturation.Methods: Fundamental to the successful isolation of the venous saturation is the identification of PPG characteristics that are unique to the peripheral venous system. Two such characteristics have been identified. First, the peripheral venous waveform tends to reflect atrial contraction. Second, ventilation tends to move venous blood preferentially due to the low pressure and high compliance of the venous system. Red (660 nm) and IR (940 nm) PPG waveforms were collected from 10 cardiac surgery patients using an esophageal PPG probe. These waveforms were analyzed using algorithms written in Mathematica. Four time-domain saturation algorithms (ArtSat, VenSat, ArtInstSat, VenInstSat) and four frequency-domain saturation algorithms (RespDC, RespAC, Cardiac, and Harmonic) were applied to the data set.Results: Three of the algorithms for calculating venous saturation (VenSat, VenInstSat, and RespDC) demonstrate significant difference from ArtSat (the conventional time-domain algorithm for measuring arterial saturation) using the Wilcoxon signed-rank test with Bonferroni correction (p < 0.0071).Conclusions: This work introduces new algorithms for PPG analysis. Three algorithms (VenSat, VenInstSat, and RespDC) succeed in detecting lower saturation blood. The next step is to confirm the accuracy of the measurement by comparing them to a gold standard (i.e., venous blood gas). [ABSTRACT FROM AUTHOR]

Heart rate variability (HRV), extracted from an electrocardiogram, is known to be a noninvasive indicator reflecting the dynamic interplay between perturbations to cardiovascular function and the dynamic response of the cardiovascular regulatory system. Photoplethysmography (PPG) is a noninvasive method to monitor arterial oxygen saturation on a continuous basis. Given the rich cardiovascular information in the PPG signal, and the ubiquity and simplicity of pulse oximetry, we are investigating the feasibility of acquiring dynamics pertaining to the autonomic nervous system from PPG waveforms. To do this, we are quantifying PPG variability (PPGV). Detailed algorithmic approaches for extracting accurate PPGV signals are presented. We compare PPGV to HRV by computing time and frequency domain parameters often associated with HRV measurements, as well as approximate entropy calculations. Our results demonstrate that the parameters of PPGV are highly correlated with the parameters of HRV. Thus, our results indicate that PPGV could be used as an alternative measurement of HRV. [ABSTRACT FROM AUTHOR]

Abstract Objective  The objective of this study was to determine the relationship between systemic vascular resistance (SVR), finger & ear photoplethysmographic measurements in 14 adult patients undergoing coronary artery bypass grafting (CABG). Methods  Patients were monitored with photoplethysmographs of the finger and ear and continuous cardiac output (QT) via thermodilution catheter. The relationship between SVR, finger plethysmographic amplitude, width and ear plethysmographic amplitude, width was assessed with linear regression. Results  The finger plethysmographic amplitude had a low correlation r value = −0.15, while finger plethysmographic width had a better correlation r value = 0.56. The correlation between SVR and ear plethysmographic amplitude and width were −0.24 and 0.62 respectively. Using receiver operating characteristic analysis the ear plethysmographic width had both better sensitivity and specificity than the finger plethysmographic width in identifying high and low SVR. Using a multiple regression analysis, SVR was estimated from the pulse oximeter waveforms: SVR calculated = 27.27  (3978.53 � Ear pulse oximeter width) − (8.91 � Ear pulse oximeter area)  (1986.3 � Finger pulse oximeter width). Bland–Altman analysis was used the bias was 29.8 dynes s cm−5, standard deviation was 587.3, upper and lower limit of agreement were 1204.45, and −1144.8 dynes s cm−5 respectively. Conclusion  The data indicate that pulse width of finger and ear plethysmographic tracing are more sensitive to changes in SVR than the other indices. An appreciation of changes in pulse width may provide valuable evidence with respect to changes in peripheral vascular tone. [ABSTRACT FROM AUTHOR]

Objective. It has been widely appreciated that ventilation-induced variations in systolic blood pressure during mechanical ventilation correlate with changes in intravascular volume. The present study assessed whether alterations in volume status likewise can be detected with noninvasive monitoring (ear plethysmograph) in non-intubated subjects (awake volunteers). Methods. Eight healthy adults were monitored with EKG, noninvasive blood pressure, an unfiltered ear plethysmograph, and a respiratory force transduction belt before (PRE) and after (POST) withdrawal of 450 ml of blood from an antecubital vein. Spectral-domain analysis was used to determine the peak ventilatory frequency and the power of the associated variation in the ear plethysmographic tracing; Interphase differences in the respiration-induced plethysmographic variations were assessed by Wilcoxon signed rank test. In addition, the changes in the ear plethysmographic tracing were compared to changes in heart rate and blood pressure. Results. There was a significant increase in respiratory-associated oscillations at the respiratory frequency between the PRE and POST phases (p = 0.012). These changes were detected despite lack of changes in heart rate or blood pressure. Conclusions. Respiration-induced changes of the ear plethysmographic waveform during spontaneous ventilation increase significantly as a consequence of withdrawal of approximately one unit of blood in healthy volunteers. [ABSTRACT FROM AUTHOR]

Objective. We report the off-line calculation of the vascular complianceof the finger and suggest the continuous on-line use of this methodology asan aid to monitoring the peripheral vascular resistance. This method consistsof the simultaneous analysis of the waveform signals from the pulse oximetermonitors and the arterial pressure as indicators of “volume” andpressure respectively to continuously calculate the vascular“compliance” (volume change per unit pressure change). This shouldbe seen as a “relative compliance” as the pulse plethysmographsignal is not calibrated. This new methodology allows for continuousmonitoring of peripheral vascular compliance as a beat-to-beat indicator ofperipheral vascular resistance. The vaso-constrictors, phenylephrine andephedrine, were shown to decrease the compliance as predicted. Methods. Thearterial pressure and pulse oximeter waveforms were obtained during routineanesthetic care. The waveforms were collected with a computer data-acquisitionsystem and then analyzed “off-line” as an indirect indicator oftotal vascular tone. Demographic and clinical information including drugadministration were recorded. Results. A case report is presented using thisnew form of analysis. Vascular compliance changes induced by phenylephrine andephedrine were studied. A dose response curve of peripheral vascularcompliance to phenylephrine was generated from these data. Conclusions. Byplotting the pulse oximeter waveforms versus the arterial waveforms, multiplevolume versus pressure (relative compliance) loops were obtained. Analysis ofthese loops may assist in the monitoring of vascular compliance. [ABSTRACT FROM AUTHOR]

In the original publication of the article, the section heading "Conclusion" was placed before the sentence "The assessment of changes in cardiac output..." in page 2 instead of the sentence "From home to ICUs, innovations in..." in the last paragraph of the page 2. The correct section is given below: [ABSTRACT FROM AUTHOR]