Abstract: A physiological monitoring system may process a physiological signal such a photoplethysmograph signal from a subject. The system may determine physiological information, such as a physiological rate, from the physiological signal. The system may use search techniques and qualification techniques to determine one or more initialization parameters. The initialization parameters may be used to calculate and qualify a physiological rate. The system may use signal conditioning to reduce noise in the physiological signal and to improve the determination of physiological information. The system may use qualification techniques to confirm determined physiological parameters. The system may also use autocorrelation techniques, cross-correlation techniques, fast start techniques, and/or reference waveforms when processing the physiological signal.

Abstract: A physiological monitoring system may process a physiological signal such a photoplethysmograph signal from a subject. The system may determine physiological information, such as a physiological rate, from the physiological signal. The system may use search techniques and qualification techniques to determine one or more initialization parameters. The initialization parameters may be used to calculate and qualify a physiological rate. The system may use signal conditioning to reduce noise in the physiological signal and to improve the determination of physiological information. The system may use qualification techniques to confirm determined physiological parameters. The system may also use autocorrelation techniques, cross-correlation techniques, fast start techniques, and/or reference waveforms when processing the physiological signal.

Abstract: A physiological monitoring system may determine physiological information, such as physiological rate information, from a physiological signal. The system may determine a first metric value indicative of a physiological classification based on the physiological signal. An algorithm setting may be determined based on the physiological classification. The system may determine a second metric value indicative of a different physiological classification based on the physiological signal. A different algorithm may be determined based on the different physiological classification. The algorithm setting may, for example, affect the amount of filtering applied to the physiological signal.

Abstract: A physiological monitoring system may determine physiological information, such as physiological rate information, from a physiological signal. The system may receive a calculated value indicative of a physiological rate. The system may determine a value indicative of noise in the physiological signal and adjust at least one criterion for qualifying or disqualifying the calculated value based on the value indicative of noise. The criterion may, for example, be a threshold and the threshold may be adjusted based on the value indicative of noise. The system may qualify or disqualify the calculated value based on the at least one adjusted criterion.

Abstract: Embodiments of the present disclosure relate to a system and method for non-invasively determining a cardiac output of a patient that may include a photoacoustic sensor and a determination of oxygen uptake of the patient. Specifically, a signal from a photoacoustic sensor may be used to determine a mixed venous and an arterial oxygen saturation of the patient. The parameters of mixed venous and arterial oxygen saturation in conjunction with oxygen uptake may be used to calculate cardiac output using the Fick method.

Abstract: A physiological monitoring system may determine physiological information, such as physiological rate information, from a physiological signal. The system may generate a difference signal based on the physiological signal. The system may determine positive areas associated with positive regions of the difference signal and negative areas associated with negative regions of the difference signal. The system may determine area ratios based on adjacent positive and negative regions of the difference signal. The system may determine an algorithm setting based on the area ratios. The algorithm setting may, for example, affect the amount of filtering applied to the physiological signal.

Abstract: A system is provided including a respiratory detection module, a circulatory detection module, and an analysis module. The respiratory detection module is configured to detect respiratory information representative of respiration of a patient. The circulatory detection module configured to detect circulatory information representative of circulation of the patient. The analysis module is configured to obtain a respiratory waveform based at least in part on the respiratory information, obtain a circulatory waveform based at least in part on the circulatory information, combine the respiratory waveform and the circulatory waveform to provide a mixed waveform, and isolate a portion of the mixed waveform to identify a respiratory responsiveness waveform representative of an effect of the respiration of the patient on the mixed waveform.

Abstract: A physiological monitoring system may determine physiological information, such as physiological rate information, from a physiological signal. The system may receive a calculated value indicative of a physiological rate. The system may determine difference values between a first collection of values of the physiological signal and another collection of corresponding value of the physiological signal spaced from the first collection based on the calculated value. The system may sum the difference values, and qualify or disqualify the calculated value based on the sum. The difference values may have positive and negative values, or the system may calculate an absolute value of each difference value prior to summing. The sum may be compared to a threshold to determine whether to qualify or disqualify the calculated value.

Abstract: A physiological monitoring system may determine physiological information, such as physiological rate information, from a physiological signal. The system may determine a skew metric based on the physiological signal. The system may determine an algorithm setting based on a reference relationship between the determined skew metric and a value indicative of a physiological rate. The algorithm setting may, for example, affect the amount of filtering applied to the physiological signal.

Abstract: A physiological monitoring system may determine physiological information, such as physiological rate information, from a physiological signal. The system may apply a bandpass filter to the physiological signal to assist in the determination of the physiological information. The system may determine a value indicative of a physiological rate and a metric based on the physiological signal. The system may select one or more settings, such as the center frequency and bandwidth, of the bandpass filter based on the rate and based on the metric, and apply the bandpass filter to the physiological signal.

Abstract: A system is provided including a cardiac output monitor configured to be operatively connected to a detection module that obtains electrocardiogram (ECG) signals from the patient. The monitor includes an axis analysis module and a cardiac output module. The axis analysis module is configured to obtain ECG axis information including information corresponding to at least one ECG axis of a patient. The axis analysis module is also configured to determine ECG axis change information corresponding to a change in the ECG axis information of the patient. The cardiac output analysis module is configured to determine a change in cardiac output using the ECG axis change information.

Abstract: The disclosure relates generally to a method and a system for acquiring patient parameters of a plurality of patient parameter relationship expressions and performing an automated spontaneous breathing trial. In the event of a successful trial, constructive notice of the success is provided.

Abstract: A method for configuring communication with medical devices includes a receiving, at a configuration interface, a first input indicative of first configuration parameters for a first medical device from a user and a second input indicative of second configuration parameters for a second medical device from the user. The first configuration parameters include at least one of a frequency parameter, a selection parameter, a compression parameter, an output parameter, and a port parameter. The method further includes receiving, at the configuration interface, first patient parameters from the first medical device and second patient parameters from the second medical device. The method further includes transmitting a first selected subset of the first patient parameters based on the first configuration parameters and transmitting a second selected subset of the second patient parameters based on the second configuration parameters.

Abstract: A system is configured to determine cardiac output of a patient. The system may include a first sub-system configured to detect a first physiological signal, and a second sub-system configured to detect a second physiological signal that differs from the first physiological signal. The first and second sub-systems may be separate and distinct from one another. The system may also include a cardiac output determination module that is configured to determine the cardiac output based, at least in part, on the first and second physiological signals.

Abstract: A system for determining stroke volume of an individual. The system includes a skew-determining module that is configured to calculate a first derivative of photoplethysmogram (PPG) signals of the individual. The first derivative forms a derivative waveform. The skew-determining module is configured to determine a skew metric of the first derivative, wherein the skew metric is indicative of a morphology of at least one pulse wave detected from blood flow of the individual in the derivative waveform. The system also includes an analysis module that is configured to determine a stroke volume of the individual. The stroke volume is a function of the skew metric of the first derivative.

Abstract: A system to determine a resting heart rate (HR) of an individual. The system may include a monitor that is configured to be operatively connected to a sensor that obtains physiological signals from an individual. The monitor is configured to receive the physiological signals from the sensor. The monitor may include a validation module that is configured to analyze the physiological signals to identify valid heart beats from the physiological signals. The monitor may also include a rate-determining module that is configured to determine an HR signal that is based on the valid heart beats. The HR signal includes a series of data points. The monitor may also include an analysis module that is configured to analyze the HR signal and identify baseline data points from the series of data points. The analysis module is configured to calculate the resting HR based on the baseline data points.

Abstract: The disclosure relates generally to a method and a system for acquiring patient parameters and indicating the status of patient parameter relationship expressions for a selected breathing stage from a plurality of breathing stages.

Abstract: A system is configured to determine a fluid responsiveness index of a patient from a physiological signal. The system may include a sensor configured to be secured to an anatomical portion of the patient, and a monitor operatively connected to the sensor. The sensor is configured to sense a physiological characteristic of the patient. The monitor is configured to receive a physiological signal from the sensor. The monitor may include an index-determining module configured to determine the fluid responsiveness index through formation of a ratio of one or both of amplitude or frequency modulation of the physiological signal to baseline modulation of the physiological signal.

Abstract: A patient monitoring system includes monitoring service that receives parameter values from a number of data sources. A status model manager facilitates creation of a clinical status model that includes conditions defining relationships between parameters and thresholds. The status model manager evaluates the clinical status model based on the parameter values to determine a clinical status of a patient.

Abstract: A physiological monitoring system may use photoacoustic sensing to determine physiological information of a subject. The photoacoustic monitoring system may use a light source, such as a modulated continuous wave laser diode, to provide a frequency modulated photonic signal (e.g., a chirp signal) to the subject. An acoustic detector may be used to detect an acoustic pressure signal from the subject. The acoustic pressure signal may include two components corresponding to two wavelengths of light in the photonic signal. A signal ratio may be calculated based on the two components. The photoacoustic monitoring system may use the signal ratio to calculate one or more absorption coefficients. The photoacoustic monitoring system may use the one or more absorption coefficients to determine additional physiological information such as hemoglobin concentration, blood oxygen saturation, and temperature.