Abstract: A system includes a hardware unit that stores signal distortion detection code. The code causes the system to execute steps of a method for evaluating the fit and placement of a hemodynamic sensor. The method includes obtaining hemodynamic data from the hemodynamic sensor and determining an arterial pressure waveform based on the hemodynamic data. A distortion score is determined based on one or more features extracted from the arterial pressure waveform and a weighting module. The method includes selectively invoking a sensory alarm based on a comparison of the distortion score to a predetermined criterion or predetermined criteria.

Abstract: Systems and methods for computer-assisted analysis of pulmonary capillary wedge pressure (PCWP) measurement acquisition in an individual are provided. Various systems and methods measure a wedge pressure via a pulmonary catheter and determine the quality of the wedge pressure measurement. In some instances, systems and methods utilize a trained computational model to assess PCWP quality. Systems and methods are also directed to determining transitions between a wedge and non-wedge positions, which may utilize fuzzy logic to identify such transitions based on a one or more hemodynamic features.

Abstract: A system for monitoring arterial pressure of a patient determines a score that is predictive of responsiveness of the patient to a therapy. Sensed hemodynamic data representative of an arterial pressure waveform of the patient are received by a hemodynamic monitor. Magnitude data and trend data are derived from the hemodynamic data. The score that is predictive of the responsiveness of the patient to the therapy is determined based on the magnitude data and the trend data of the hemodynamic parameter. A representation of the score is output.

Abstract: Systems and methods identify respiration signals in a patient, which can be important for monitoring respiratory health. A respiration signal can be extracted based on data within a physiological waveform, such as a blood pressure waveform, a blood flow waveform, an electrocardiogram, or a plethysmogram. The physiological waveform can be filtered to identify and extract the respiration signal, which can be utilized to construct a capnogram waveform. A respiration rate can be calculated from the respiration signal or from the constructed capnogram waveform.

Abstract: A system for determining an endotype of hypotension of a patient can include a hemodynamic sensor and a converter. The system can receive, from the hemodynamic sensor, an analog hemodynamic sensor signal from the patient. The system can convert, using the converter, the analog hemodynamic sensor signal to an arterial pressure signal waveform and extract from the arterial pressure signal waveform a plurality of heart health parameters. Using a deep learning model, the system can encode the plurality of heart health parameters into one or more latent space heart health parameters. The system can generate a location in latent space of the arterial pressure signal waveform and determine a relative location of the arterial pressure signal waveform in latent space. Based on the relative location, the system can determine the endotype of hypotension of the patient and display an alert indicating the endotype of hypotension.

Abstract: A system having a processor obtain a digital hemodynamic data from a hemodynamic sensor, obtain one or more vital sign parameters characterizing vital sign data from the digital hemodynamic data, derive differential parameters based on the one or more vital sign parameters, generate combinatorial parameters using the one or more vital sign parameters and the differential parameters, determine a risk score corresponding to a probability of a future hypotension event for the living subject based on a weighted combination of a plurality of hypotension profiling parameters including the one or more vital sign parameters characterizing vital sign data, the differential parameters and the combinatorial parameters, and invoke a sensory alarm if the risk score satisfies a predetermined risk criterion.

Abstract: A system disclosed herein includes a hardware processor and a predictive risk model training software code stored in a system memory. The hardware processor executes the software code to receive vital sign data of a population of subjects including positive and negative subjects with respect to a health state, to define data sets for use in training a predictive risk model, to transform the vital sign data to parameters characterizing the vital sign data, and to obtain differential parameters based on those parameters. The hardware processor executes the software code to further generate combinatorial parameters using the parameters and the differential parameters, to analyze the parameters, the differential parameters, and the combinatorial parameters to identify a reduced set of parameters correlated with the health state, to identify a predictive set of parameters enabling prediction of the health state for a living subject, and to compute predictive risk model coefficients.

Abstract: A method for monitoring arterial pressure of a patient and detecting nociception of the patient includes receiving, by a hemodynamic monitor, sensed hemodynamic data representative of an arterial pressure waveform of the patient. A hardware processor of the hemodynamic monitor performs waveform analysis of the sensed hemodynamic data to calculate a plurality of signal measures of the sensed hemodynamic data. The hardware processor of the hemodynamic monitor calculates cross-correlational association measurements between each of the signal measures. The cross-correlational association measurements are outputted to a user interface. The cross-correlational association measurements are monitored for bursts in the cross-correlational association measurements. A nociception event of the patient is detected when a burst in one or more of the cross-correlational association measurements is outputted to the user interface.

Abstract: A system for monitoring arterial pressure of a patient determines a score that is predictive of responsiveness of the patient to a therapy. Sensed hemodynamic data representative of an arterial pressure waveform of the patient are received by a hemodynamic monitor. Magnitude data and trend data are derived from the hemodynamic data. The score that is predictive of the responsiveness of the patient to the therapy is determined based on the magnitude data and the trend data of the hemodynamic parameter. A representation of the score is output.

Abstract: A system having a processor obtain a digital hemodynamic data from a hemodynamic sensor, obtain one or more vital sign parameters characterizing vital sign data from the digital hemodynamic data, derive differential parameters based on the one or more vital sign parameters, generate combinatorial parameters using the one or more vital sign parameters and the differential parameters, determine a risk score corresponding to a probability of a future hypotension event for the living subject based on a weighted combination of a plurality of hypotension profiling parameters including the one or more vital sign parameters characterizing vital sign data, the differential parameters and the combinatorial parameters, and invoke a sensory alarm if the risk score satisfies a predetermined risk criterion.

Abstract: A method and apparatus for determining a subject's autoregulation function state is provided. The method includes: continuously sensing a tissue region of a subject with a tissue oximeter to produce first signals representative of at least one tissue oxygenation parameter during a period of time; continuously measuring a blood pressure level of the subject during the period of time to produce second signals representative of the subject's blood pressure during the period of time; determining a presence of a confounding factor that affects the sensed tissue oxygenation parameter in a manner independent of an autoregulation function of the subject, the determination using the first signals; using the first and second signals to determine an autoregulation function state of the subject when the absence of the confounding factor is determined. The method may include determining an at least one of an LLA or a ULA of a subject's autoregulation function state.

Abstract: A method for determining a post-induction score that represents a prediction that a patient will experience a hypotensive event after beginning an administration of anesthesia is disclosed herein that includes receiving, by a hemodynamic monitor prior to the administration of anesthesia on the patient, sensed hemodynamic data representative of an arterial pressure waveform of the patient. The method further includes extracting, by the hemodynamic monitor, at least one waveform feature from the sensed hemodynamic data. Additionally, the method includes determining, by the hemodynamic monitor based on the at least one waveform feature, the post-induction score that represents the likelihood that the patient will experience a hypotensive event after beginning the administration of anesthesia. Finally, the post-induction score is displayed.

Abstract: A hemodynamic monitoring system monitors arterial blood pressure of a patient and provides a warning to medical personnel of a predicted future hypotension event of the patient. Waveform analysis is performed on sensed hemodynamic data representative of an arterial pressure waveform of the patient to determine a plurality of hypotension profiling parameters predictive of a future hypotension event for the patient. A set of transformed hypotension profiling parameters is generated based on the hypotension profiling parameters and mean and standard deviation values of the hypotension profiling parameters at a standard mean arterial pressure (MAP) threshold for hypotension and an adjusted MAP threshold for hypotension. A risk score representing a probability of a future hypotension event for the patient is determined based on the set of transformed hypotension profiling parameters. A sensory alarm is invoked to produce a sensory signal in response to the risk score satisfying a predetermined risk criterion.

Abstract: A hemodynamic monitoring system monitors arterial blood pressure of a patient and provides a warning to medical personnel of a predicted future hypotension event of the patient. Sensed hemodynamic data representative of an arterial pressure waveform of the patient are received by a hemodynamic monitor. The received hemodynamic data is offset, based on a difference between a standard mean arterial pressure (MAP) threshold for hypotension and an adjusted MAP threshold for hypotension, to produce adjusted hemodynamic data. Waveform analysis of the adjusted hemodynamic data is performed, and a risk score representing a probability of a future hypotension event for the patient is determined based on the waveform analysis. A sensory alarm is invoked to produce a sensory signal in response to the risk score satisfying a predetermined risk criterion.

Abstract: There are provided systems and methods for performing mean arterial pressure (MAP) derived prediction of future hypotension. Such a system includes a hardware unit including a hardware processor and a system memory, a hypotension prediction software code stored in the system memory, and a sensory alarm. The hardware processor is configured to execute the hypotension prediction software code to receive MAP data of the living subject, and to transform the MAP data to one or more parameters predictive of a future hypotension event of the living subject. The hardware processor is further configured to execute the hypotension prediction software code to determine a risk score of the living subject corresponding to the probability of the future hypotension event based on at least some of the one or more parameters, and to invoke the sensory alarm if the risk score of the living subject satisfies a predetermined risk criteria.

Abstract: A system for monitoring arterial pressure of a patient determines a score that is predictive of responsiveness of the patient to a therapy. Sensed hemodynamic data representative of an arterial pressure waveform of the patient are received by a hemodynamic monitor. Magnitude data and trend data are derived from the hemodynamic data. The score that is predictive of the responsiveness of the patient to the therapy is determined based on the magnitude data and the trend data of the hemodynamic parameter. A representation of the score is output.

Abstract: There are provided systems and methods for performing mean arterial pressure (MAP) derived prediction of future hypotension. Such a system includes a hardware unit including a hardware processor and a system memory, a hypotension prediction software code stored in the system memory, and a sensory alarm. The hardware processor is configured to execute the hypotension prediction software code to receive MAP data of the living subject, and to transform the MAP data to one or more parameters predictive of a future hypotension event of the living subject. The hardware processor is further configured to execute the hypotension prediction software code to determine a risk score of the living subject corresponding to the probability of the future hypotension event based on at least some of the one or more parameters, and to invoke the sensory alarm if the risk score of the living subject satisfies a predetermined risk criteria.

Abstract: A system disclosed herein includes a hardware processor and a predictive risk model training software code stored in a system memory. The hardware processor executes the software code to receive vital sign data of a population of subjects including positive and negative subjects with respect to a health state, to define data sets for use in training a predictive risk model, to transform the vital sign data to parameters characterizing the vital sign data, and to obtain differential parameters based on those parameters. The hardware processor executes the software code to further generate combinatorial parameters using the parameters and the differential parameters, to analyze the parameters, the differential parameters, and the combinatorial parameters to identify a reduced set of parameters correlated with the health state, to identify a predictive set of parameters enabling prediction of the health state for a living subject, and to compute predictive risk model coefficients.

Abstract: A system having a processor obtain a digital hemodynamic data from a hemodynamic sensor, obtain one or more vital sign parameters characterizing vital sign data from the digital hemodynamic data, derive differential parameters based on the one or more vital sign parameters, generate combinatorial parameters using the one or more vital sign parameters and the differential parameters, determine a risk score corresponding to a probability of a future hypotension event for the living subject based on a weighted combination of a plurality of hypotension profiling parameters including the one or more vital sign parameters characterizing vital sign data, the differential parameters and the combinatorial parameters, and invoke a sensory alarm if the risk score satisfies a predetermined risk criterion.

Abstract: A system having a processor obtain a digital hemodynamic data from a hemodynamic sensor, obtain one or more vital sign parameters characterizing vital sign data from the digital hemodynamic data, derive differential parameters based on the one or more vital sign parameters, generate combinatorial parameters using the one or more vital sign parameters and the differential parameters, determine a risk score corresponding to a probability of a future hypotension event for the living subject based on a weighted combination of a plurality of hypotension profiling parameters including the one or more vital sign parameters characterizing vital sign data, the differential parameters and the combinatorial parameters, and invoke a sensory alarm if the risk score satisfies a predetermined risk criterion.