A cardiovascular mathematical model of graded head-up tilt.

A lumped parameter model of the cardiovascular system has been developed and optimized using experimental data obtained from 13 healthy subjects during graded head-up tilt (HUT) from the supine position to [Formula: see text]. The model includes descriptions of the left and right heart, direct ventricular interaction through the septum and pericardium, the systemic and pulmonary circulations, nonlinear pressure volume relationship of the lower body compartment, arterial and cardiopulmonary baroreceptors, as well as autoregulatory mechanisms. A number of important features, including the separate effects of arterial and cardiopulmonary baroreflexes, and autoregulation in the lower body, as well as diastolic ventricular interaction through the pericardium have been included and tested for their significance. Furthermore, the individual effect of parameter associated with heart failure, including LV and RV contractility, baseline systemic vascular resistance, pulmonary vascular resistance, total blood volume, LV diastolic stiffness and reflex gain on HUT response have also been investigated. Our fitted model compares favorably with our experimental measurements and published literature at a range of tilt angles, in terms of both global and regional hemodynamic variables. Compared to the normal condition, a simulated congestive heart failure condition produced a blunted response to HUT with regards to the percentage changes in cardiac output, stroke volume, end diastolic volume and effector response (i.e., heart contractility, venous unstressed volume, systemic vascular resistance and heart rate) with progressive tilting.

Estimation of cardiac output and total peripheral resistance in preterm infants by arterial waveform analysis.

This study investigated whether arterial blood pressure waveform analysis could be useful for estimating left ventricular outflow (LVO) and total peripheral resistance (TPR) in preterm infants. A cohort of 27 infants were studied, with 89 measurements of left ventricular outflow (LVO) using Doppler echocardiography and arterial pressure using catheters, performed in 0, 12, 24 and 36 hours after birth. TPR was computed as mean arterial pressure divided by LVO. The diastolic decay rate (1/τ) was obtained via fitting an exponential function to the last one third of each arterial pulse, with the mean rate computed from 50 pulses selected from each infant. This decay rate was considered to be inversely related to TPR while positively related to LVO. The results of regression analysis have confirmed that the diastolic decay rate had significant positive and negative relationships with LVO and TPR respectively(r = 0.383, P = 0.0002 and r = -0.379, P = 0.0002 respectively). These preliminary results demonstrated the potential utility of arterial pressure waveform analysis for estimating LVO and TPR in preterm infants, but more advanced multi-parameter models may be needed to improve accuracy of the estimation.

Detrended fluctuation analysis of blood pressure in preterm infants with intraventricular hemorrhage.

Very preterm infants are at high risk of death and serious permanent brain damage, as occurs with intraventricular hemorrhage (IVH). Detrended fluctuation analysis (DFA) that quantifies the fractal correlation properties of physiological signals has been proposed as a potential method for clinical risk assessment. This study examined whether DFA of the arterial blood pressure (ABP) signal could derive markers for the identification of preterm infants who developed IVH. ABP data were recorded from a prospective cohort of 30 critically ill preterm infants in the first 1-3 h of life, 10 of which developed IVH. DFA was performed on the beat-to-beat sequences of mean arterial pressure (MAP), systolic blood pressure (SBP) and pulse interval, with short-term exponent (α1, for timescale of 4-15 beats) and long-term exponent (α2, for timescale of 15-50 beats) computed accordingly. The IVH infants were found to have higher short-term scaling exponents of both MAP and SBP (α1 = 1.06 ± 0.18 and 0.98 ± 0.20) compared to the non-IVH infants (α1 = 0.84 ± 0.25 and 0.78 ± 0.25, P = 0.017 and 0.038, respectively). The results have demonstrated that fractal dynamics embedded in the arterial pressure waveform could provide useful information that facilitates early identification of IVH in preterm infants.

Spontaneous fluctuations in the peripheral photoplethysmographic waveform: roles of arterial pressure and muscle sympathetic nerve activity.

Assessment of spontaneous slow waves in the peripheral blood volume using the photoplethysmogram (PPG) has shown potential clinical value, but the physiological correlates of these fluctuations have not been fully elucidated. This study addressed the contribution of arterial pressure and muscle sympathetic nerve activity (MSNA) in beat-to-beat PPG variability in resting humans under spontaneous breathing conditions. Peripheral PPG waveforms were measured from the fingertip, earlobe, and toe in young and healthy individuals (n = 13), together with the arterial pressure waveform, electrocardiogram, respiration, and direct measurement of MSNA by microneurography. Cross-spectral coherence analysis revealed that among the PPG waveforms, low-frequency fluctuations (0.04-0.15 Hz) in the ear PPG had the highest coherence with arterial pressure (0.71 ± 0.15) and MSNA (0.44 ± 0.18, with a peak of 0.71 ± 0.16 at 0.10 ± 0.03 Hz). The normalized midfrequency powers (0.08-0.15 Hz), with an emphasis on the 0.1-Hz region, were positively correlated between MSNA and the ear PPG (r = 0.77, P = 0.002). Finger and toe PPGs had lower coherence with arterial pressure (0.35 ± 0.10 and 0.30 ± 0.11, respectively) and MSNA (0.33 ± 0.10 and 0.26 ± 0.10, respectively) in the LF band but displayed higher coherence between themselves (0.54 ± 0.09) compared with the ear (P < 0.001), which may suggest the dominance of regional vasomotor activities and a common sympathetic influence in the glabrous skin. These findings highlight the differential mechanisms governing PPG waveform fluctuations across different body sites. Spontaneous PPG variability in the ear includes a major contribution from arterial pressure and MSNA, which may provide a rationale for its clinical utility.

Recent advances in the monitoring and control of haemodynamic variables during haemodialysis: a review.

The human body possesses a unique set of organs that are responsible for providing homeostatic balance to the body's fluids. Of these, the kidneys regulate fluid and electrolyte balance in order to maintain the intracellular and extracellular fluid volumes and ion composition within tight limits. When kidneys fail to function normally, fluid is retained and several ions and solutes accumulate. The consequences may be life threatening. Many kidney failure patients rely on haemodialysis (HD) as a life sustaining therapy to remove the waste products and excess fluid from the circulating blood. HD is based on the principle of diffusion of solutes and ultrafiltration of fluid across a semi-permeable membrane. Fluid removal during HD results in relative hypovolaemia during which the stability of a patient relies on compensatory mechanisms to maintain blood pressure (BP). The major compensatory mechanisms include sympathetic nervous system activation of peripheral vasoconstriction together with modest heart rate acceleration to ensure the haemodynamic stability of the patient. Over the years, many monitoring tools have been developed in the hope of predicting intra-dialytic hypotensive episodes. Similarly many methods have been utilized to prevent dialysis-induced complications: ultrafiltration and dialysate sodium profiling, varying ultrafiltration based on frequent BP measurements, etc. This paper provides a comprehensive review of those monitoring and control tools. It starts with a brief introduction to human kidneys and dialysis for non-specialized readers. The paper then reviews the monitoring tools that have been applied to assess the physiological response of patients during HD. This is followed by control techniques used to prevent dialysis-induced complications.

Spectral analysis of systemic and cerebral cardiovascular variabilities in preterm infants: relationship with clinical risk index for babies (CRIB).

Frequency spectrum analysis of circulatory signals has been proposed as a potential method for clinical risk assessment of preterm infants by previous studies. In this study, we examined the relationships between various spectral measures derived from systemic and cerebral cardiovascular variabilities and the clinical risk index for babies (CRIB II). Physiological data collected from 17 early low birth weight infants within 1-3 h after birth were analysed. Spectral and cross-spectral analyses were performed on heart rate variability, blood pressure variability and cerebral near-infrared spectroscopy measures such as oxygenated and deoxygenated haemoglobins (HbO(2) and HHb) and tissue oxygenation index (TOI). In addition, indices related to cardiac baroreflex sensitivity and cerebral autoregulation were derived from the very low, low- and mid-frequency ranges (VLF, LF and MF). Moderate correlations with CRIB II were identified from mean arterial pressure (MAP) normalized MF power (r = 0.61, P = 0.009), LF MAP-HHb coherence (r = 0.64, P = 0.006), TOI VLF percentage power (r = 0.55, P = 0.023) and LF baroreflex gain (r = -0.61, P = 0.01 after logarithmic transformation), with the latter two parameters also highly correlated with gestational age (r = -0.75, P = 0.0005 and r = 0.70, P = 0.002, respectively). The relationships between CRIB II and various spectral measures of arterial baroreflex and cerebral autoregulation functions have provided further justification for these measures as possible markers of clinical risks and predictors of adverse outcome in preterm infants.

The effect of ventricular assist devices on cerebral blood flow and blood pressure fractality.

Biological signals often exhibit self-similar or fractal scaling characteristics which may reflect intrinsic adaptability to their underlying physiological system. This study analysed fractal dynamics of cerebral blood flow in patients supported with ventricular assist devices (VAD) to ascertain if sustained modifications of blood pressure waveform affect cerebral blood flow fractality. Simultaneous recordings of arterial blood pressure and cerebral blood flow velocity using transcranial Doppler were obtained from five cardiogenic shock patients supported by VAD, five matched control patients and five healthy subjects. Computation of a fractal scaling exponent (α) at the low-frequency time scale by detrended fluctuation analysis showed that cerebral blood flow velocity exhibited 1/f fractal scaling in both patient groups (α = 0.95 ± 0.09 and 0.97 ± 0.12, respectively) as well as in the healthy subjects (α = 0.86 ± 0.07). In contrast, fluctuation in blood pressure was similar to non-fractal white noise in both patient groups (α = 0.53 ± 0.11 and 0.52 ± 0.09, respectively) but exhibited 1/f scaling in the healthy subjects (α = 0.87 ± 0.04, P < 0.05 compared with the patient groups). The preservation of fractality in cerebral blood flow of VAD patients suggests that normal cardiac pulsation and central perfusion pressure changes are not the integral sources of cerebral blood flow fractality and that intrinsic vascular properties such as cerebral autoregulation may be involved. However, there is a clear difference in the fractal scaling properties of arterial blood pressure between the cardiogenic shock patients and the healthy subjects.

Identification of high-risk acute coronary syndromes by spectral analysis of ear photoplethysmographic waveform variability.

There is a need for robust techniques for early and accurate diagnosis of acute coronary syndromes (ACSs), to avoid inappropriate discharge of patients. This study examined the use of frequency spectrum analysis of heart rate variability (HRV) and photoplethysmogram (PPG) waveform variability for the identification of high-risk ACS patients defined by an elevated cardiac troponin level. The study cohort comprised a convenience sample of adult patients presenting to the emergency department of the Prince of Wales Hospital over a 4 month period complaining of non-traumatic chest pain. Valid electrocardiogram (ECG) and earlobe PPG waveforms together with troponin I test results were obtained from 52 patients at presentation, 4 of which were troponin I positive (Trop 0+). Frequency spectrum analysis was performed on the beat-to-beat HRV and PPG waveform variability (PPGV). The Trop 0+ were found to have significantly higher normalized mid-frequency power (MF(nu)) in HRV (P = 0.017), PPG amplitude variability (P = 0.009) and the cross-spectrum of HRV and PPGV (P = 0.001), which were attributed to reflex sympathetic response to myocardial ischemia. MF(nu) of PPG amplitude had the best overall performance in detecting Trop 0+, with ROC area under the curve of 0.93. The results demonstrate the potential use of ear PPG waveform to identify high-risk heart disease patients, and further highlight the utility of frequency spectrum analysis of PPGV in critical care.

Multivariate classification of systemic vascular resistance using photoplethysmography.

Systemic vascular resistance (SVR) classification is useful for the diagnosis and prognosis of critical pathophysiological conditions, with the ability to identify patients with abnormally high or low SVR of immense clinical value. In this study, a supervised classifier, based on Bayes' rule, is employed to classify a heterogeneous group of intensive care unit patients (N = 48) as being below (SVR < 900 dyn s cm(-5)), within (900 ⩽ SVR ⩽ 1200 dyn s cm(-5)) or above (SVR > 1200 dyn s cm(-5)) the clinically accepted range for normal SVR. Features derived from the finger photoplethysmogram (PPG) waveform and other routine cardiovascular measurements (heart rate and mean arterial pressure) were used as inputs to the classifier. In the construction of the classifier model, two techniques were used to approximate the class conditional probability densities--a single Gaussian distribution model (also known as discriminant analysis) and a non-parametric model using the Parzen window kernel density estimation method. An exhaustive feature search was performed to select a feature subset that maximized the performance indicator, Cohen's kappa coefficient (κ). The Gaussian model with multiple features achieved the best overall kappa coefficient (κ = 0.57), although the results from the non-parametric model were comparable (κ = 0.51). The optimum subset in the Gaussian model consisted of PPG waveform variability features, including the low-frequency to high-frequency ratio (LF/HF) and the normalized mid-frequency power (MF(NU)), in addition to the PPG pulse wave features, such as pulse width, peak-to-notch time, reflection index, and notch time ratio. The classifier performed particularly well in discriminating low SVR, with a sensitivity of 85%, specificity of 86%, positive predictive value of 88% and a negative predictive value of 82%. The results highlight the feasibility of deploying a multivariate statistical approach of SVR classification in the clinical setting, simply using a non-invasive and easy-to-measure PPG waveform signal.

Determinants of human cerebral pressure-flow velocity relationships: new insights from vascular modelling and Ca²âº channel blockade.

The fundamental determinants of human dynamic cerebral autoregulation are poorly understood, particularly the role of vascular compliance and the myogenic response. We sought to 1) determine whether capacitive blood flow associated with vascular compliance and driven by the rate of change in mean arterial blood pressure (dMAP/dt) is an important determinant of middle cerebral artery velocity (MCAv) dynamics and 2) characterise the impact of myogenic blockade on these cerebral pressure-flow velocity relations in humans. We measured MCAv and mean arterial pressure (MAP) during oscillatory lower body negative pressure (n =8) at 0.10 and 0.05 Hz before and after cerebral Ca²âº channel blockade (nimodipine). Pressure-flow velocity relationships were characterised using transfer function analysis and a regression-based Windkessel analysis that incorporates MAP and dMAP/dt as predictors of MCAv dynamics. Results show that incorporation of dMAP/dt accounted for more MCAv variance (R² 0.80-0.99) than if only MAP was considered (R2 0.05-0.90). The capacitive gain relating dMAP/dt and MCAv was strongly correlated to transfer function gain (0.05 Hz, r =0.93, P<0.01; 0.10 Hz, r =0.91, P<0.01), but not to phase or coherence. Ca²âº channel blockade increased the conductive gain relation between MAP and MCAv (P<0.05), and reduced phase at 0.05 Hz (P<0.01). Capacitive and transfer function gain were unaltered. The findings suggest capacitive blood flow is an important determinant of cerebral haemodynamics that bears strong relations to some metrics of dynamic cerebral autoregulation derived from transfer function analysis, and that Ca²âº channel blockade enhances pressure-driven resistive blood flow but does not alter capacitive blood flow. the causes and effects of cerebrovascular diseases such as stroke and dementia.

Fingertip photoplethysmographic waveform variability and systemic vascular resistance in intensive care unit patients.

Low frequency variability in the fingertip photoplethysmogram (PPG) waveform has been utilized for inferring sympathetic vascular control, but its relationship with a quantitative measure of vascular tone has not been established. In this study, we examined the association between fingertip PPG waveform variability (PPGV) and systemic vascular resistance (SVR) obtained from thermodilution cardiac output (CO) and intra-arterial pressure measurements in 48 post cardiac surgery intensive care unit patients. Among the hemodynamic measurements, both CO (P < 0.05) and SVR (P < 0.0001) had statistically significant relationships with the normalized low frequency power (LF(nu)) of PPGV. The LF(nu) of baseline PPGV had moderate but significant positive correlation with SVR (r = 0.54, P < 0.0001), and a value below 52.5 nu was able to identify SVR < 900 dyn s cm⁻5 with sensitivity of 59% and specificity of 95%. The results have provided quantitative evidence to confirm the link between fingertip PPGV and sympathetic vascular control. Suppression of LF vasomotor waves leading to dominance of respiration-related HF fluctuations in the fingertip circulation was a specific (though not sensitive) marker of systemic vasodilatation, which could be potentially utilized for the assessment of critical care patients.

Identification and control for automated regulation of hemodynamic variables during hemodialysis.

This paper proposes a novel model-based control methodology for a computer-controlled hemodialysis system, designed to maintain the hemodynamic stability of end-stage renal failure patients undergoing fluid removal during hemodialysis. The first objective of this paper is to introduce a linear parameter varying system to model the hemodynamic response of patients during hemodialysis. Ultrafiltration rate (UFR) and dialysate sodium concentration (DSC) are imposed as the inputs, and the model computes the relative blood volume (RBV), percentage change in heart rate ( ∆HR), and systolic blood pressure (SBP) during the course of hemodialysis. The model parameters were estimated based on data collected from 12 patients undergoing 4 profiled hemodialysis sessions. The modeling results demonstrated that the proposed model could be useful for estimating the individual patient's hemodynamic behavior during hemodialysis. Based on the model, the second objective is to implement a computer-controlled hemodialysis system for the regulation of RBV and HR during hemodialysis while maintaining SBP within stable range. The proposed controller is based on a model predictive control approach utilizing pre-defined constraints on the control inputs (UFR and DSC) as well as the output (SBP). The designed control system was experimentally verified on four patients. The results demonstrated that the proposed computer-controlled hemodialysis system regulated the RBV and HR of the patients according to individual reference profiles with an average mean square error of 0.24% and 2.6%, respectively, and thus can be potentially useful for ensuring the stability of patients undergoing hemodialysis by avoiding sudden changes in hemodynamic variables.

Contribution of arterial Windkessel in low-frequency cerebral hemodynamics during transient changes in blood pressure.

The Windkessel properties of the vasculature are known to play a significant role in buffering arterial pulsations, but their potential importance in dampening low-frequency fluctuations in cerebral blood flow has not been clearly examined. In this study, we quantitatively assessed the contribution of arterial Windkessel (peripheral compliance and resistance) in the dynamic cerebral blood flow response to relatively large and acute changes in blood pressure. Middle cerebral artery flow velocity (MCA(V); transcranial Doppler) and arterial blood pressure were recorded from 14 healthy subjects. Low-pass-filtered pressure-flow responses (<0.15 Hz) during transient hypertension (intravenous phenylephrine) and hypotension (intravenous sodium nitroprusside) were fitted to a two-element Windkessel model. The Windkessel model was found to provide a superior goodness of fit to the MCA(V) responses during both hypertension and hypotension (R² = 0.89 ± 0.03 and 0.85 ± 0.05, respectively), with a significant improvement in adjusted coefficients of determination (P < 0.005) compared with the single-resistance model (R² = 0.62 ± 0.06 and 0.61 ± 0.08, respectively). No differences were found between the two interventions in the Windkessel capacitive and resistive gains, suggesting similar vascular properties during pressure rise and fall episodes. The results highlight that low-frequency cerebral hemodynamic responses to transient hypertension and hypotension may include a significant contribution from the mechanical properties of vasculature and, thus, cannot solely be attributed to the active control of vascular tone by cerebral autoregulation. The arterial Windkessel should be regarded as an important element of dynamic cerebral blood flow modulation during large and acute blood pressure perturbation.

Cerebral near-infrared spectroscopy analysis in preterm infants with intraventricular hemorrhage.

Near-infrared spectroscopy (NIRS) for cerebral circulation monitoring has gained popularity in the neonatal intensive care setting, with studies showing the possibility of identifying preterm infants with intraventricular hemorrhage (IVH) by transfer function analysis of arterial blood pressure (BP) and NIRS measures. In this study, we examined a number of NIRS-derived measures in a cohort of preterm infants with IVH (n = 5) and without IVH (n = 12) within 1-3 hours after birth. The IVH infants were found to have significantly higher tissue oxygenation index (TOI), lower fractional tissue oxygen extraction (FTOE) and lower coherence between arterial BP and deoxygenated hemoglobin (HHb) in the very low frequency range (VLF, 0.02-0.04 Hz). Further studies with larger sample size are warranted for a more complete understanding of the clinical utility of these NIRS measures for early identification of IVH infants.

Photoplethysmographic variability analysis in critical care--current progress and future challenges.

The concept of early goal-directed therapy emphasizes the need for early diagnosis and intervention to achieve better therapeutic outcomes in critical care. There has been rapidly growing interest in the use of the photoplethysmogram (PPG), also known as the "pulse oximetry waveform", as a noninvasive diagnostic tool in this clinical setting. The peripheral PPG exhibits beat-to-beat variability driven by physiological mechanisms such as respiration and sympathetic vascular activity. This paper provides an overview of the current progress towards the application of PPG waveform variability (PPGV) in emergency and intensive care. Studies to date have demonstrated the potential value of PPGV for assessing a range of pathophysiological conditions including blood loss, sepsis and low systemic vascular resistance. Translation of research findings into clinical practice poses several future challenges, including the need for large scale validation studies with appropriate measurement systems, more robust solutions to signal quality issues (such as motion artifacts), and better physiological understanding of the information-rich PPGV.

Peripheral photoplethysmography variability analysis of sepsis patients.

Sepsis is associated with impairment in autonomic regulatory function. This work investigates the application of heart rate and photoplethysmogram (PPG) waveform variability analysis in differentiating two categories of sepsis, namely systemic inflammatory response syndrome (SIRS) and severe sepsis. Electrocardiogram-derived heart period (RRi) and PPG waveforms, measured from fingertips (Fin-PPG) and earlobes (Ear-PPG), of Emergency Department sepsis patients (n = 28) with different disease severity, were analysed by spectral technique, and were compared to control subjects (n = 10) in supine and 80° head-up tilted positions. Analysis of covariance (ANCOVA) was applied to adjust for the confounding factor of age. Low-frequency (LF, 0.04-0.15 Hz), mid-frequency (MF, 0.09-0.15 Hz) and high-frequency (HF, 0.15-0.60 Hz) powers were computed. The normalised MF power in Ear-PPG (MFnu(Ear)) was significantly reduced in severe sepsis patients with hyperlactataemia (lactate > 2 mmol/l), compared to SIRS patients (P < 0.05). Moreover, in a group of normal controls, MFnu(Ear) was not altered by head-up tilting (P > 0.05), suggesting that there may be a link between 0.1 Hz ear blood flow oscillation and tissue metabolic changes in sepsis, in addition to autonomic factors. The study highlighted the value of PPG spectral analysis in the non-invasive assessment of peripheral vascular regulation in sepsis patients, with potential implications in monitoring the progression of sepsis.

Linear parameter varying system based modeling of hemodynamic response to profiled hemodialysis.

This paper proposes a novel linear parameter varying (LPV) system to model the hemodynamic response of end-stage renal failure patients to profiled hemodialysis (PHD). Ultrafiltration rate (UFR) and dialysate sodium concentration (Na) are imposed as the control inputs and the model computes the relative blood volume (RBV), percentage change in heart rate (ΔDHR(%)) and percentage change in systolic blood pressure (ΔDSBP(%)) during the course of hemodialysis. Model parameters are estimated using least squares approach based on data collected from 12 patients where each patient underwent 4 profile hemodialysis sessions. Parameter identification based on four profiled sessions of the same patient revealed an average mean square error of 0.11 for RBV, 0.24 for ΔDHR and 0.43 for ΔDSBP. The results provided a good model to estimate the individual patient's hemodynamic behavior during hemodialysis. The developed model can play a vital role in designing a robust control system to automatically regulate the UFR and Na while maintaining the hemodynamic variables within stable range.

Respiration-induced changes in ear photoplethysmography relates to relative blood volume during hemodialysis.

Renal failure patients provide a good model of fluid overload with the process of hemodialysis leading to central hypovolemia. This study aims to assess if hemodialysis induces identifiable changes in ear photoplethysmographic waveform variability (PPGV). The results are based on data collected from 10 kidney failure patients undergoing regular hemodialysis; classified as either fluid removal or non-fluid removal patients. Six minutes of continuous photoplethysmography (PPG) signals were recorded at pre-dialysis, end of dialysis and at regular intervals of 20 minutes during hemodialysis. Baseline and amplitude variabilities were derived from the PPG waveform. Frequency spectrum analysis was applied to these variability signals and spectral powers were then calculated from low frequency (LF), mid frequency (MF) and high frequency (HF) bands. The results indicate that in fluid removal patients, LF (p = 0.04), MF (p = 0.03) and HF (p = 0.0003) powers of amplitude ear PPGV (expressed in mean-scaled units) showed a significant increase at the end of dialysis compared to pre-dialysis. No significant change was observed in non-fluid removal patients. A moderate correlation was found between relative blood volume (RBV) and HF power (median R = 0.64, p 〈 0.05). This study suggests that ear PPG may be a suitable monitor of the systemic circulation and can provide a non-invasive tool to detect blood volume loss.

Classification of low systemic vascular resistance using photoplethysmogram and routine cardiovascular measurements.

Low systemic vascular resistance (SVR) can be a useful indicator for early diagnosis of critical pathophysiological conditions such as sepsis, and the ability to identify low SVR from simple and noninvasive physiological signals is of immense clinical value. In this study, an SVR classification system is presented to recognize the occurrence of low SVR, among a heterogenous group of patients (N = 48), based on the use of routine cardiovascular measurements and features extracted from the finger photoplethysmogram (PPG) as inputs to a quadratic discriminant classifier. An exhaustive feature search was performed to identify a near optimum feature subset. Cohen's kappa coefficient (κ) was used as a performance measure to compare candidate feature sets. The classifier using the following combination of features performed best (κ = 0.56, sensitivity = 96.30%, positive predictivity = 92.31%): normalized low-frequency power (LFNU) derived from PPG, ratio of low-frequency power to high-frequency power (LF/HF) of the PPG variability signal, and the ratio of mean arterial pressure to heart rate (MAP/HR). Classifiers that used either LF(NU) (κ = 0.43), LF/HF (κ = 0.37) or MAP/HR (κ = 0.43) alone showed inferior performance. Discrimination of patients with and without low SVR can be achieved with reasonable accuracy using multiple features derived from the PPG combined with routine cardiovascular measurements.