Abstract: According to embodiments, systems and methods are provided for filtering a signal. A first reference signal may be generated according to a signal model and a second reference signal may be generated by analyzing a continuous wavelet transform of a signal. The first and second reference signals may then both be applied to an input signal to filter the input signal according to the components of both of the reference signals.

Abstract: According to embodiments, systems and methods are provided that use continuous wavelet transforms and basis functions to provide an optimized system for the determination of physiological information. In an embodiment, the basis functions may be used to refine an area of interest in the signal in frequency or in time, and the continuous wavelet transform may be used to identify a maxima ridge in the scalogram at scales with characteristic frequencies proximal to the frequency or frequencies of interest. In another embodiment, a wavelet transform may be used to identify regions of a signal with the morphology of interest while basis functions may be used to focus on these regions to determine or filter information of interest. In yet another embodiment, basis functions and continuous wavelet transforms may be used concurrently and their results combined to form optimized information or a confidence metric for determined physiological information.

Abstract: In some embodiments, systems and methods for identifying a low perfusion condition are provided by transforming a signal using a wavelet transform to generate a scalogram. A pulse band and adjacent marker regions in the scalogram are identified. Characteristics of the marker regions are used to detect the existence of a lower perfusion condition. If such a condition is detected, an event may be triggered, such as an alert or notification.

Abstract: In some embodiments, systems and methods for identifying a low perfusion condition are provided by transforming a signal using a wavelet transform to generate a scalogram. A pulse band and adjacent marker regions in the scalogram are identified. Characteristics of the marker regions are used to detect the existence of a lower perfusion condition. If such a condition is detected, an event may be triggered, such as an alert or notification.

Abstract: According to embodiments, non-corrupted signal segments are detected by a data modeling processor implementing an artificial neural network. The neural network may be trained to detect artifact in the signal (e.g., a PPG signal or some wavelet representation of a PPG signal) and gate valid signal segments for use in determining physiological parameters, such as, for example, pulse rate, oxygen saturation, pulse rate, respiration rate, and respiratory effort. When an artifact is detected, previously received known-good signal segments may be buffered and replace the signal segment or segments containing artifact. A regression analysis may also be performed in order to extrapolate new data from previously received known-good signal segments. In this way, more accurate and reliable physiological parameters may be determined.

Abstract: The present disclosure relates to monitoring a characteristic respiration rate of a patient based at least in part on a suitable time period that either precedes or follows a triggering event, such as a clinician/patient interaction, where the triggering event may negatively impact the physiological parameter. In some embodiments, physiological parameter values falling between one or more pre-set thresholds may be used to derive the characteristic physiological parameter. In some embodiments, monitoring the respiration rate may provide additional information about the patient's status. In some embodiments, confidence measures may be associated with, or may be used to analyze features of the patient signal to derive information about, the characteristic respiration rate. The patient signal used to derive a patient's respiration rate may be of an oscillatory nature or may include oscillatory features that may be analyzed to derive a characteristic respiration rate.

Abstract: According to embodiments, a pulse band region is identified in a wavelet scalogram of a physiological signal (e.g., a plethysmograph or photoplethysmograph signal). Components of the scalogram at scales larger than the identified pulse band region are then used to determine a baseline signal in wavelet space. The baseline signal may then be used to normalize the physiological signal. Physiological information may be determined from the normalized signal. For example, oxygen saturation may be determined using a ratio of ratios or any other suitable technique.

Abstract: According to embodiments, techniques for estimating scalogram energy values in a wedge region of a scalogram are disclosed. A pulse oximetry system including a sensor or probe may be used to receive a photoplethysmograph (PPG) signal from a patient or subject. A scalogram, corresponding to the obtained PPG signal, may be determined. In an arrangement, energy values in the wedge region of the scalogram may be estimated by calculating a set of estimation locations in the wedge region and estimating scalogram energy values at each location. In an arrangement, scalogram energy values may be estimated based on an estimation scheme and by combining scalogram values in a vicinity region. In an arrangement, the vicinity region may include energy values in a resolved region of the scalogram and previously estimated energy values in the wedge region of the scalogram. In an arrangement, one or more signal parameters may be determined based on the resolved and estimated values of the scalogram.

Abstract: According to an embodiment, techniques for estimating scalogram energy values in a wedge region of a scalogram are disclosed. A pulse oximetry system including a sensor or probe may be used to receive a photoplethysmograph (PPG) signal from a patient or subject. A scalogram, corresponding to the obtained PPG signal, may be determined. In an approach, energy values in the wedge region of the scalogram may be estimated by performing convolution-based or convolution-like operations on the obtained PPG signal, or a transformed version thereof, and the scalogram may be updated according to the estimated values. In an approach, a deskewing technique may be used to align data prior to adding the data to the scalogram. In an approach, one or more signal parameters may be determined based on the resolved and estimated values of the scalogram.

Abstract: Methods and systems are disclosed for analyzing multiple scale bands in the scalogram of a physiological signal in order to obtain information about a physiological process. An analysis may be performed to identify multiple scale bands that are likely to contain the information sought. Each scale band may be assessed to determine a band quality, and multiple bands may be combined based on the band quality. Information about a physiological process may determined based on the combined band. In an embodiment, analyzing multiple scale bands in a scalogram arising from a wavelet transformation of a photoplethysmograph signal may yield clinically relevant information about, among other things, the blood oxygen saturation of a patient.

Abstract: A method and system for measuring fluid responsiveness of a patient is disclosed. Information related to fluid responsiveness of a patient may be derived from a PPG signal, for example, by analyzing the PPG signal transformed by a continuous wavelet transform. Other techniques for deriving information related to fluid responsiveness of a patient include, for example, analyzing the amplitude modulation, frequency modulation, and/or baseline changes of a PPG signal.

Abstract: The present disclosure relates to determining a patient's disease state based at least in pail on obtaining or determining certain underlying characteristics, such as vasotone, venous compliance, or ability of the vascular system to drain venous blood, of the patient's vascular system. The characteristics may be obtained by analyzing changes to a patient signal, such as the overall signal change, the rate of change, the shape of the change, changes in signal energy, or changes in the baseline and/or the amplitude of the signal, and/or the time period(s) over which the signal changes, that are caused by inducing a load on the vascular system. In some embodiments, the signal changes may be analyzed by transforming the signal using, for example, a continuous wavelet transform. The patient's health status or disease state may be determined using the one or more vascular system characteristics that influenced the signal change.

Abstract: According to embodiments, estimated values for a signal transform may be generated using estimated values for the signal. Signal parameters may then be determined based on the estimated signal transform. A first portion of a signal may be obtained. A second portion of the signal may be estimated. The second portion of the signal may correspond to a portion of the that is unknown, that is not yet available and/or that is obscured by noise and/or artifacts. A transform (e.g., a continuous wavelet transform) of both of the signal portions may be performed. One or more parameters corresponding to the signal may then be determined from transformed signal.

Abstract: According to embodiments, a wavelet transform ratio surface measure signal may be generated from two PPG signals. Values of the wavelet transform ratio surface measure signal at a given moment of time (i.e., instantaneous values) may be indicative of localized signal discrepancies within and/or between the PPG signals such as noise and signal artifacts. Spikes in the instantaneous values of the wavelet transform ratio surface measure signal may be located and used to determine a signal quality measure for the PPG signals. Characteristics of the spikes such as number, location, grouping, distribution, amplitude, and polarity may be used in the signal quality determination.

Abstract: Techniques for non-invasive blood pressure monitoring are disclosed. Data corresponding to a patient may be received from a hospital information system. The data may include, for example, drug administration data, medical procedure data, medical equipment data, or a combination thereof. Whether a blood pressure monitoring system needs to be recalibrated may be determined, based at least in part on the received data. If it is determined that the blood pressure monitoring system needs to be recalibrated, the recalibration may be performed and at least one blood pressure measurement of the patient may be computed using the recalibrated blood pressure monitoring system.

Abstract: The present disclosure relates to pulse oximetry measurements and, more particularly, relates to a combined sensor that includes a pulse oximetry (SpO2) sensor component and a continuous non-invasive blood pressure (CNIBP) sensor component. The combined sensor can be positioned such that the SpO2 sensor component is located over tissues where pulsatility is weak while the CNIBP sensor component may be located over tissues where pulsatility is strong. A second separate CNIBP sensor may be used to together with the CNIBP sensor component of the combined sensor in order to detect the differential pressure pulse transit time from the heart to two different locations on the body. A pulse signal detected by the CNIBP sensor component of the combined sensor can be used to trigger the SpO2 measurement from the SpO2 sensor component in order to improve SpO2 measurement fidelity.

Abstract: According to embodiments, techniques for detecting probe-off events are disclosed. A sensor or probe may be used to obtain a plethysmograph or photoplethysmograph (PPG) signal from a subject. A wavelet transform of the signal may be performed and a scalogram may be generated based at least in part on the wavelet transform. One or more characteristics of the scalogram may be determined. The determined characteristics may include, for example, an energy decrease, a broadscale high-energy cone, a regular, repeated high-scale pattern, a low-scale information pattern; and a pulse band. The absence or presence of these and other characteristics, along with information about the characteristics, may be analyzed to detect a probe-off event. A confidence indicator may be calculated in connection with probe-off event detections and alarms may be generated when probe-off events occur.

Abstract: Techniques for detecting a signal quality decrease are disclosed. A sensor or probe may be used to obtain a plethysmograph or photoplethysmograph (PPG) signal from a subject. A wavelet transform of the signal may be performed and a scalogram may be generated based at least in part on the wavelet transform. One or more characteristics of the scalogram may be determined. The determined characteristics may include, for example, energy values and energy structural characteristics in a pulse band, a mains hum band, and/or a noise band. Such characteristics may be analyzed to produce signal quality values and associated signal quality trends. One or more signal quality values and signal quality trends may be used to determine if a signal quality decrease has occurred or is likely to occur.

Abstract: The present disclosure relates to signal processing systems and methods, and more particularly, to systems and methods for analyzing multiparameter spaces to determine changes in a physiological state. In embodiments, a first signal and a second signal may be obtained, from which a first plurality of values of a physiological parameter may be determined. At least one of the signals also may be used to generate a scalogram derived at least in part from the signal. A second plurality of values may be determined based at least in part on a feature in the scalogram. The first and second plurality of values may then be associated, and a physiological state may be analyzed using the associated first and second values. In an embodiment, the signals may be PPG signals and the associated first and second values may include a parameter scatter plot that may permit a user to determine changes in a patient's ventilation state over time.

Abstract: According to embodiments, systems and methods for computing a physiological parameter are provided. The physiological parameter may be calculated using a continuous wavelet transform technique as well as using a non-continuous wavelet transform technique. More than one value for the physiological parameter may be calculated using various techniques. The values may be evaluated to select a desired value, or an average or weighted average of the values may be computed to generate a desired value.