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: According to one implementation, a medical device includes a display, a blood pressure sensor for sensing an arterial blood pressure of a patient and for generating a blood pressure signal, an analog-to-digital converter (ADC) for receiving the blood pressure signal and for converting the blood pressure signal to blood pressure data in digital form, and a hardware processor for executing an aortic stenosis diagnostic software code. The hardware processor executes the aortic stenosis diagnostic software code to receive the blood pressure data from the ADC, and to identify parameters indicative of aortic stenosis in the patient, based on the blood pressure data. The hardware processor further executes the aortic stenosis diagnostic software code to classify the severity of aortic stenosis in the patient based on an exponential function of the parameters.

Abstract: A health monitoring unit includes a hardware processor, a memory, a display, and a graphical user interface (GUI) stored in the memory. The GUI is executed by the processor to provide a selection screen enabling a user to select parameters for viewing on the display from among health parameters of a living subject being tracked by the health monitoring unit. The GUI also presents a main screen showing the parameters selected by the user, the main screen including an icon for communicating a hypotension probability index (HPI) status of the living subject. In addition, the GUI overlays an alarm screen as a pop-up on the display if the HPI of the living subject satisfies a predetermined risk criteria, and enables the user to access an HPI diagnostic screen showing values for a subset of the health parameters identified as predictive of a future hypotension event for the living subject.

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: 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 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: Disclosed is an apparatus, system, and method for utilizing a pressure transducer simulator that is configured for use with a pressure sensor device and a patient monitoring device. The pressure transducer simulator may be configured to generate a simulation of the output of an analog pressure sensing device to be compatible with the patient monitoring device. The simulation may be based upon a pressure signal received from the pressure sensor device. In one embodiment, the pressure transducer simulator includes a digital potentiometer that is configured to generate an analog signal based upon the pressure signal received from the pressure sensor device and wherein the digital potentiometer is configured to transmit the analog signal to the patient monitoring device.

Abstract: There is provided a biomedical sensing system and a method for its use. Such a system includes a diagnostic sensor configured to sense a physiological metric of a living subject via contact with the living subject, and to generate a diagnostic signal corresponding to the physiological metric. In addition, the system includes a motion sensor situated proximate the diagnostic sensor and configured to sense a motion corresponding to a motion of the diagnostic sensor during sensing of the physiological metric. The system also includes an analysis unit including a processor, and a memory storing a motion correction module. The processor is configured to receive the diagnostic signal and the motion signal, and to execute the motion correction module from the memory to adaptively filter the diagnostic signal using the motion signal to produce a motion compensated diagnostic signal.

Abstract: Disclosed is an apparatus, system, and method for utilizing a pressure transducer simulator that is configured for use with a pressure sensor device and a patient monitoring device. The pressure transducer simulator may be configured to generate a simulation of the output of an analog pressure sensing device to be compatible with the patient monitoring device. The simulation may be based upon a pressure signal received from the pressure sensor device. In one embodiment, the pressure transducer simulator includes a digital potentiometer that is configured to generate an analog signal based upon the pressure signal received from the pressure sensor device and wherein the digital potentiometer is configured to transmit the analog signal to the patient monitoring device.

Abstract: Embodiments of the disclosure are directed to methods, apparatuses, and computer program products for determining a hemodynamic parameter. An exemplary method comprises: receiving data associated with at least one heart beat; calculating a first standard deviation for at least a portion of the data; interpolating a second standard deviation for at least a second portion of the data; and determining the hemodynamic parameter based on the first standard deviation and the second standard deviation.

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: A method and apparatus for determining a cardiovascular parameter including receiving an input signal corresponding to an arterial blood pressure measurement over an interval that covers at least one cardiac cycle, determining a propagation time of the input signal, determining at least one statistical moment of the input signal, and determining an estimate of the cardiovascular parameter using the propagation time and the at least one statistical moment.

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: Embodiments include methods and apparatus for determining whether a neurological event has occurred in a subject. An apparatus includes at least one sensor adapted to sense electroencephalogram signals from the subject. The apparatus also includes an electroencephalogram acquisition module adapted to receive the electroencephalogram signals from at least one sensor, and a processing and analysis module adapted to receive signals from the electroencephalogram acquisition module and determine changes in neurological function using entropy analysis.