Abstract: A system and method are disclosed for detecting a vasoactive agent in patient's bloodstream. In one embodiment, an input signal is received that is associated with arterial blood pressure. A change of an arterial blood pressure parameter over time is determined. A vasoactive agent is then automatically detected using the determined change. In another embodiment, a waveform associated with an arterial blood pressure signal can be received. A parameter associated with the received waveform is calculate. Then the calculated parameter can be used to determine the presence of a vasoactive agent. In yet another embodiment, detection of a vasoactive agent in any of the other embodiments can be used in a calculation of a hemodynamic parameter, such as cardiac output, stroke volume, systemic vascular resistance, stroke volume variation, cardiac index, stroke volume index, systemic vascular resistance index, vascular compliance, and vascular tone.

Abstract: The present application concerns detecting catheter proximity to a blood-vessel wall and blood-vessel wall artifacts associated therewith. In one embodiment, a light source, in a catheter, can be used to project light into the blood vessel. An intensity associated with at least one light wavelength that interacted with blood can be measured. Based on the measured intensity, a determination can be made regarding blood-vessel wall artifacts due to the catheter tip proximity to a blood-vessel wall. Feedback can be provided to the clinician in order to assist the clinician in adjusting the catheter to optimize signal quality and minimize artifacts due to the blood-vessel wall.

Abstract: A system and method are disclosed for detecting a vasoactive agent in patient's bloodstream. In one embodiment, an input signal is received that is associated with arterial blood pressure. A change of an arterial blood pressure parameter over time is determined. A vasoactive agent is then automatically detected using the determined change. In another embodiment, a waveform associated with an arterial blood pressure signal can be received. A parameter associated with the received waveform is calculate. Then the calculated parameter can be used to determine the presence of a vasoactive agent. In yet another embodiment, detection of a vasoactive agent in any of the other embodiments can be used in a calculation of a hemodynamic parameter, such as cardiac output, stroke volume, systemic vascular resistance, stroke volume variation, cardiac index, stroke volume index, systemic vascular resistance index, vascular compliance, and vascular tone.

Abstract: A cardiovascular parameter such as cardiac output is estimated from a current pressure waveform data set without needing to directly measure blood flow or arterial compliance. The general shape of an input flow waveform over one beat-to-beat cycle is assumed (or computed), and then the parameters of a flow-to-pressure model, if not pre-determined, are determined using system identification techniques. In one embodiment, the parameters thus determined are used to estimate a current peripheral resistance, which is used not only to compute an estimate of the cardiovascular parameter, but also to adjust the shape of the input flow waveform assumed during at least one subsequent beat-to-beat cycle. Another embodiment does not require computation of the peripheral resistance and still another embodiment computes a flow estimate from an optimized identification of the parameters defining the assumed input flow waveform.

Abstract: Methods for detecting parameters in cardiac output related waveforms are described. The methods include methods for detecting individual heart beat cycles in a cardiac output related waveform, methods for detecting an error in an assigned starting point for an individual heart beat cycle in a cardiac output related waveform, methods for detecting a dichrotic notch for an individual heart beat cycle in a cardiac output related waveform, and methods for detecting an error in an assigned dichrotic notch for an individual heart beat cycle in a cardiac output related waveform. The identification of these parameters is important for a clinician as these parameters form the basis for the calculation of many other cardiac output related parameters.

Abstract: The present application concerns detecting catheter proximity to a blood-vessel wall and blood-vessel wall artifacts associated therewith. In one embodiment, a light source, in a catheter, can be used to project light into the blood vessel. An intensity associated with at least one light wavelength that interacted with blood can be measured. Based on the measured intensity, a determination can be made regarding blood-vessel wall artifacts due to the catheter tip proximity to a blood-vessel wall. Feedback can be provided to the clinician in order to assist the clinician in adjusting the catheter to optimize signal quality and minimize artifacts due to the blood-vessel wall.

Abstract: The present application relates to continuous measurement of total hemoglobin (tHb) in whole blood. In one embodiment, different wavelengths are used for normalization of the spectral intensity and calculation of the total hemoglobin. In particular, for normalization, a first wavelength is used wherein the wavelength is substantially insensitive to changes in levels of hemoglobin and oxygen saturation. For calculation of the total hemoglobin, a second wavelength is used. The second wavelength is sensitive to changes in levels of hemoglobin, but substantially insensitive to changes in levels of oxygen saturation. In another embodiment, a continuous measurement can be made using two wavelengths that are both sensitive to oxygen saturation, but they both are equally sensitive. In other words, the normalized intensities associated with the two wavelengths change equal amounts with equal changes in oxygen saturation levels.

Abstract: Methods for detecting parameters in cardiac output related waveforms are described. The methods include methods for detecting individual heart beat cycles in a cardiac output related waveform, methods for detecting an error in an assigned starting point for an individual heart beat cycle in a cardiac output related waveform, methods for detecting a dichrotic notch for an individual heart beat cycle in a cardiac output related waveform, and methods for detecting an error in an assigned dichrotic notch for an individual heart beat cycle in a cardiac output related waveform. The identification of these parameters is important for a clinician as these parameters form the basis for the calculation of many other cardiac output related parameters.

Abstract: Methods for detecting parameters in cardiac output related waveforms are described. The methods include methods for detecting individual heart beat cycles in a cardiac output related waveform, methods for detecting an error in an assigned starting point for an individual heart beat cycle in a cardiac output related waveform, methods for detecting a dichrotic notch for an individual heart beat cycle in a cardiac output related waveform, and methods for detecting an error in an assigned dichrotic notch for an individual heart beat cycle in a cardiac output related waveform. The identification of these parameters is important for a clinician as these parameters form the basis for the calculation of many other cardiac output related parameters.

Abstract: Methods for determining a cardiovascular parameter, e.g., a parameter reflecting fluid or volume responsiveness, using a modified waveform dataset are described. The waveform dataset corresponds to a signal, for example, from an arterial blood pressure, or any signal proportional to, or derived from the arterial pressure signal. These methods involve identifying individual cardiac cycles in the waveform dataset, measuring the waveform characteristics for the individual cycles, then determining if the individual cardiac cycles are regular cardiac cycles or irregular cardiac cycles. Once any irregular cardiac cycles are detected, a respiratory parameter is measured. Next, a modified waveform dataset containing the waveform characteristics of the regular cardiac cycles and the waveform characteristics of the irregular cardiac cycles is created wherein the waveform characteristics of the irregular cardiac cycles are replaced with estimated waveform characteristics.

Abstract: Methods for monitoring cardiovascular conditions, i.e., hyperdynamic circulation, vasodilation, vasoconstriction, or central-to-peripheral arterial pressure decoupling conditions are described. These methods involve measuring a central signal proportional to or a function of the subject's heart activity and a peripheral signal proportional to or a function of a signal related to the central signal. Then calculating a time difference between features in the central and peripheral signals representing the same heart event. The cardiovascular condition is indicated if the time difference is greater or lower than a threshold value, if the time difference is greater or lower than a threshold value over a specified period of time, or if there is a significant statistical change in the times over the specified time period. These methods can alert a user that a subject is experiencing the cardiovascular condition, which can enable a clinician to appropriately provide treatment to the subject.

Abstract: Methods for monitoring central-to-peripheral arterial pressure decoupling, i.e., hyperdynamic conditions, are described. These methods involve the comparison of parameters calculated from multivariate statistical models established for both subjects experiencing normal hemodynamic conditions and subjects experiencing hyperdynamic conditions, in which central- to peripheral decoupling may occur. The difference or ratio between the parameters calculated using the two multivariate statistical models provides a continual indication of the level of decoupling as well as indicating peripheral decoupling when a threshold value is exceeded. These methods can be used to both alert a user to the fact that a subject is experiencing peripheral decoupling and provide accurate arterial tone measurements, which enable the calculation of accurate values for other parameters, such as stroke volume and cardiac output.

Abstract: Methods for monitoring central-to-peripheral arterial pressure decoupling, i.e., hyperdynamic or vasodilation conditions are described. These methods involve the comparison of parameters such as impedance, compliance, and pressure that can be determined from flow and pressure measurements at central aortic and peripheral arterial locations. The relationship between the parameters at the central aortic and peripheral arterial locations provides an indication of central-to-peripheral arterial pressure decoupling. These methods can be alert a user that a subject is experiencing central-to-peripheral arterial pressure decoupling, which can enable a clinician to appropriately provide treatment to the subject.

Abstract: Methods for measuring a cardiovascular parameter in a subject regardless of whether the subject is experiencing normal hemodynamic or abnormal hemodynamic conditions are described. These methods involve the determination of whether a subject is experiencing normal hemodynamic conditions or abnormal hemodynamic conditions, then applying an appropriate model to subject data to determine a cardiovascular parameter for the subject. Multivariate Boolean models are used to establish if the subject is experiencing normal hemodynamic or abnormal hemodynamic conditions, then multivariate statistical models are used to calculate the appropriate cardiovascular parameter. Having correct cardiovascular parameters for a subject experiencing abnormal hemodynamic conditions, for example, enables the calculation of accurate values for treatment relevant parameters, such as, cardiac output and stroke volume.

Abstract: Methods for detecting parameters in cardiac output related waveforms are described. The methods include methods for detecting individual heart beat cycles in a cardiac output related waveform, methods for detecting an error in an assigned starting point for an individual heart beat cycle in a cardiac output related waveform, methods for detecting a dichrotic notch for an individual heart beat cycle in a cardiac output related waveform, and methods for detecting an error in an assigned dichrotic notch for an individual heart beat cycle in a cardiac output related waveform. The identification of these parameters is important for a clinician as these parameters form the basis for the calculation of many other cardiac output related parameters.

Abstract: Multivariate statistical models for the detection of vascular conditions, methods for creating such multivariate statistical models, and methods for the detection of vascular condition in a subject using the multivariate statistical models are described. The models are created based on arterial pressure waveform data from a first group of subjects that were experiencing a particular vascular condition and a second group of subjects that were not experiencing the same vascular condition. The multivariate statistical models are set up to provide different output values for each set of input data. Thus, when data from a subject under observation is input into the model, the relationship of the model output value to the established output values for the two groups upon which the model was established will indicate whether the subject is experiencing the vascular condition.

Abstract: Methods for determining a cardiovascular parameter reflecting fluid or volume changes and for detecting arrhythmia are disclosed. These methods involve receiving a waveform dataset corresponding to an arterial blood pressure, pulseox, Doppler ultrasound or bioimpedance signal and analyzing the waveform to detect irregular cardiac cycles. Irregular cardiac cycles are detected, for example, by comparing parameters of individual cardiac cycles to the parameters of other or average cardiac cycles. If any irregular cardiac cycles are present, their effect is compensated for to form a modified waveform dataset. Once any irregular cardiac cycles are compensated for, a cardiovascular parameter reflecting fluid or volume changes using the modified waveform dataset is calculated. In the method for determining arrhythmia, if the number of irregular cardiac cycles exceeds a predetermined arrhythmia threshold, a user such as a medical professional is notified.

Abstract: A cardiovascular parameter such as cardiac output is estimated from a current pressure waveform data set without needing to directly measure blood flow or arterial compliance. The general shape of an input flow waveform over one beat-to-beat cycle is assumed (or computed), and then the parameters of a flow-to-pressure model, if not pre-determined, are determined using system identification techniques. In one embodiment, the parameters thus determined are used to estimate a current peripheral resistance, which is used not only to compute an estimate of the cardiovascular parameter, but also to adjust the shape of the input flow waveform assumed during at least one subsequent beat-to-beat cycle. Another embodiment does not require computation of the peripheral resistance and still another embodiment computes a flow estimate from an optimized identification of the parameters defining the assumed input flow waveform.

Abstract: A cardiovascular parameter such as cardiac output is estimated from a current pressure waveform data set without needing to directly measure blood flow or arterial compliance. The general shape of an input flow waveform over one beat-to-beat cycle is assumed (or computed), and then the parameters of a flow-to-pressure model, if not pre-determined, are determined using system identification techniques. In one embodiment, the parameters thus determined are used to estimate a current peripheral resistance, which is used not only to compute an estimate of the cardiovascular parameter, but also to adjust the shape of the input flow waveform assumed during at least one subsequent beat-to-beat cycle. Another embodiment does not require computation of the peripheral resistance and still another embodiment computes a flow estimate from an optimized identification of the parameters defining the assumed input flow waveform.

Abstract: Methods for the detection of vascular conditions such as vasodilation in a subject are described. The methods involve receiving a signal corresponding to an arterial blood pressure and calculating one or more cardiovascular parameters from the arterial blood pressure. The cardiovascular parameters are calculated using factors impacted by vascular conditions such as vasodilation. Factors impacted by these vascular conditions include the area under the systolic portion of the arterial blood pressure signal, the duration of systole, and the ratio of the duration of the systole to the duration of the diastole. By monitoring cardiovascular parameters that are calculated using factors impacted by vascular conditions such as vasodilation for changes indicating the vascular conditions, such vascular conditions can be detected.