Abstract: A method for determining an efficacy of cardiopulmonary resuscitation (CPR) includes receiving a plethysmography signal from an oximetry sensor and an electrocardiogram (ECG) signal from an ECG sensor at a processor associated with a patient monitor, the oximetry sensor, or the ECG sensor. The method includes determining a first indicator related to the efficacy of CPR based on the plethysmography signal, using the processor. The method also includes determining a second indicator related to the efficacy of CPR based on the ECG signal, using the processor. The method further includes combining the first indicator and the second indicator to determine a combination metric indicative of the efficacy of CPR, using the processor.

Abstract: A medical monitoring system includes an oximetry sensor having a light emitter positioned to emit light into a patient and a photodetector positioned to generate a plethysmography signal. The system includes a monitor having a processor configured to receive the plethysmography signal from the oximetry sensor and to identify a non-cardiac pulse based on a first pulse shape metric, the non-cardiac pulse being generated by the administration of cardiopulmonary resuscitation (CPR) to the patient. The processor is also configured to measure an oxygen saturation of the patient from the identified non-cardiac pulse and to output the measured oxygen saturation to a visual display.

Abstract: Methods and systems are provided for determining fluid administration. The system may determine fluid administration based on the fluid responsiveness and regional oxygen saturation of a subject. The system may receive the fluid responsiveness and regional oxygen saturation from external sources or may determine one or both based on received physiological signals. In some embodiments, the system may determine whether to administer fluid based on the fluid responsiveness and regional oxygen saturation. In some embodiments, the system may determine the amount of fluid to administer based on the fluid responsiveness and regional oxygen saturation. In some embodiments, the system may determine the effectiveness of fluid administration. In some embodiments, the system may provide an indication of the determined fluid administration so that a care-giver can implement the appropriate fluid administration. In some embodiments, the system may control the fluid administration based on its determination.

Abstract: A method for monitoring autoregulation includes, using a processor, receiving a blood pressure signal and an oxygen saturation signal from a patient. The method also includes determining a linear correlation between the blood pressure signal and the oxygen saturation signal and determining a significance value associated with the linear correlation. The method further includes providing a signal indicative of the patient's autoregulation status to an output device based on the linear correlation and the significance value.

Abstract: Methods and systems are provided for determining fluid administration. The system may determine fluid administration based on the fluid responsiveness and regional oxygen saturation of a subject. The system may receive the fluid responsiveness and regional oxygen saturation from external sources or may determine one or both based on received physiological signals. In some embodiments, the system may determine whether to administer fluid based on the fluid responsiveness and regional oxygen saturation. In some embodiments, the system may determine the amount of fluid to administer based on the fluid responsiveness and regional oxygen saturation. In some embodiments, the system may determine the effectiveness of fluid administration. In some embodiments, the system may provide an indication of the determined fluid administration so that a care-giver can implement the appropriate fluid administration. In some embodiments, the system may control the fluid administration based on its determination.

Abstract: A system may include a photoplethysmograph (PPG) sensor configured to be secured to a patient and to generate a PPG signal for the patient. The system may also include a motion sensor configured to generate a motion signal indicative of motion of the patient. Further, the system may include a controller configured to receive the PPG signal from the PPG sensor and the motion signal from the motion sensor, to analyze the motion signal to detect motion of the patient, and to deactivate the at least one emitter of the PPG sensor based on the analysis of the motion signal when motion of the patient is detected.

Abstract: A method for monitoring autoregulation includes receiving a blood pressure signal and an oxygen saturation signal, determining a phase difference between the blood pressure signal and the oxygen saturation signal, and determining a patient's autoregulation status based at least in part on a phase difference between the blood pressure signal and the oxygen saturation signal.

Abstract: Methods, systems, and devices for measuring respiratory parameters from an ECG device are described. The method may include receiving an electrocardiogram (ECG) signal associated with a patient. The method may further include detecting a change in modulation of the ECG signal between a first portion of the ECG signal and a second portion of the ECG signal. The method may further include determining a change in respiratory effort of the patient based at least in part on the change in modulation.

Abstract: A method for monitoring autoregulation includes using a processor for receiving blood pressure data and oxygen saturation data from a patient, fitting a dynamic model to the blood pressure data and the oxygen saturation data to determine one or more parameters of the dynamic model indicative of autoregulation, and determining the patient's autoregulation status based on the one or more parameters.

Abstract: Systems and methods provided relate to patient sensors and/or patient monitors that recognize and/or identify a patient with physiological signals obtained from the sensor. A scalogram may be produced by applying a wavelet transform for the physiological signals obtained from the sensor. The scalogram may be a three dimensional model (having time, scale, and magnitude) from which certain physiological information may be obtained. For example, unique human physiological characteristics, also known as biometrics, may be determined from the scalograms. More specifically, monitoring the changes in the morphology of the photoplethysmographic (PPG) waveform transforms (e.g., scalogram) may determine patient-specific information that may be used to recognize and/or identify the patient, and that may be used to determine a proper or improper association between the patient and the wireless sensor and/or patient monitor.

Abstract: Systems and methods are provided for storing and recalling metrics associated with physiological signals. It may be determined that the value of a monitored physiological metric corresponds to a stored value. In such cases, a patient monitor may determine that a calibration is not desired. In some cases, a patient monitor may recall calibration parameters associated with the stored value if it determined that the stored value corresponds to the monitored metric value.

Abstract: Systems, methods, sensors, and software for providing enhanced measurement and detection of patient pain response are provided herein. In a first example, a measurement system is provided that includes a capacitive system configured to measure a capacitance signal of tissue of the patient using a capacitive sensor applied to the tissue of the patient. The measurement system also includes a patient monitor configured to measure an electrical signal representing brain activity of the patient using a brain activity sensor applied to the tissue of the patient. The measurement system also includes a processing system configured to determine pain metrics based at least on the capacitance signal and the electrical signal, and determine a pain response of the patient based at least on the pain metrics and pain calibration information for the patient.

Abstract: Systems, methods, sensors, and software for providing enhanced measurement and detection of patient pain response are provided herein. In a first example, a measurement system is provided that includes a capacitive system configured to measure a capacitance signal of tissue of the patient using a capacitive sensor proximate to the tissue of the patient. The measurement system also includes a patient monitor configured to measure an electrical signal representing brain activity of the patient. The measurement system also includes a processing system configured to determine pain metrics based at least on the capacitance signal and the electrical signal, and determine a pain response of the patient based at least on the pain metrics and pain calibration information for the patient.

Abstract: Methods and systems are presented for determining physiological information in a physiological monitor. A physiological signal (e.g., an EEG signal) received from a subject is wavelet transformed and first and second related features that vary in scale over time are identified in the transformed signal. First and second coupled ridges of the respective first and second related features may also be identified in the transformed signal. A non-stationary relationship parameter is determined and is indicative of the relationship between the first and second features and/or between the first and second ridges. Physiological information, which may be indicative of a level of awareness of a subject, is determined based on the non-stationary relationship parameter.

Abstract: Systems and methods provided relate to patient sensors and/or patient monitors that recognize and/or identify a patient with physiological signals obtained from the sensor. A scalogram may be produced by applying a wavelet transform for the physiological signals obtained from the sensor. The scalogram may be a three dimensional model (having time, scale, and magnitude) from which certain physiological information may be obtained. For example, unique human physiological characteristics, also known as biometrics, may be determined from the scalograms. More specifically, monitoring the changes in the morphology of the photoplethysmographic (PPG) waveform transforms (e.g., scalogram) may determine patient-specific information that may be used to recognize and/or identify the patient, and that may be used to determine a proper or improper association between the patient and the wireless sensor and/or patient monitor.

Abstract: Systems and methods provided relate to patient sensors and/or patient monitors that recognize and/or identify a patient with physiological signals obtained from the sensor. A scalogram may be produced by applying a wavelet transform for the physiological signals obtained from the sensor. The scalogram may be a three dimensional model (having time, scale, and magnitude) from which certain physiological information may be obtained. For example, unique human physiological characteristics, also known as biometrics, may be determined from the scalograms. More specifically, monitoring the changes in the morphology of the photoplethysmographic (PPG) waveform transforms (e.g., scalogram) may determine patient-specific information that may be used to recognize and/or identify the patient, and that may be used to determine a proper or improper association between the patient and the wireless sensor and/or patient monitor.

Abstract: Methods and systems are presented for determining physiological information in a physiological monitor. A physiological signal (e.g., an EEG signal) received from a subject is wavelet transformed and first and second related features that vary in scale over time are identified in the transformed signal. First and second coupled ridges of the respective first and second related features may also be identified in the transformed signal. A non-stationary relationship parameter is determined and is indicative of the relationship between the first and second features and/or between the first and second ridges. Physiological information, which may be indicative of a level of awareness of a subject, is determined based on the non-stationary relationship parameter.

Abstract: A physiological monitoring system may receive a sensor signal from a physiological sensor. The system may determine a first and second change metric based on the sensor signal, and may determine a venous signal based on the change metrics. In some embodiments, the sensor signal may be a photoplethysmograph signal that includes both arterial and venous information. By subtracting a second change metric from a first change metric, arterial contributions may be substantially removed, resulting in a signal primarily comprising venous information. The venous signal may be indicative of changes in the venous blood, and may be used to determine a physiological parameter, for example, blood pressure. The venous signal may also be used to trigger an event, for example, calibration of a blood pressure measurement.

Abstract: Systems and method for utilizing energy harvesting techniques to power a battery-less wireless medical sensor to perform intermittent operations are disclosed. The systems may include one or more sensing components configured to generate data related to one or more physiological parameters by performing intermittent measurements on a patient. The systems and method may include wireless communication circuitry configured to wirelessly transmit the data to a monitor. The monitor may be configured to operate with the battery-less wireless medical sensor or may download required operational algorithms if needed. The intermittent measurement and transmission may be asynchronously executed. The systems and method may include a processing device configured to determine when to perform the intermittent measurement and transmit data based at least upon a power source energy level, a rate at which to perform the intermittent measurement and transmit data, a prioritization, or a triggering event.

Abstract: The present invention relates to physiological signal processing, and in particular to methods and systems for processing physiological signals to predict a fluid responsiveness of a patient. A medical monitor for monitoring a patient includes an input receiving a photoplethysmograph (PPG) signal representing light absorption by a patient's tissue. The monitor also includes a perfusion status indicator indicating a perfusion status of the PPG signal, and a fluid responsiveness predictor (FRP) calculator programmed to calculate an FRP value based on a respiratory variation of the PPG signal. The FRP calculator applies a correction factor based on the perfusion status indicator.