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: Systems and methods for detecting and monitoring arrhythmias from a signal are provided. A signal processing system may transform a signal using a wavelet transformation and analyze changes in features of the transformed signal to detect pulse rhythm abnormalities. For example, the system may detect pulse rhythm abnormalities by analyzing energy parameters, morphology changes, and pattern changes in the scalogram of a PPG signal. Further, the system may detect pulse rhythm abnormalities by analyzing both the PPG signal and its corresponding scalogram. Physiological information, such as cardiac arrhythmia, may be derived based on the detected pulse rhythm abnormality.

Abstract: A patient monitoring system may determine portions of a PPG signal that correspond to artifacts, to a baseline shift that exceeds a threshold, or to a pulse-to-pulse variability that exceeds a threshold. The patient monitoring system may identify a contiguous portion of the PPG signal that does not include the determined portions. The contiguous portion of the PPG signal may be used to determine physiological information.

Abstract: Systems and methods for detecting and monitoring arrhythmias from a signal are provided. A signal processing system may transform a signal using a wavelet transformation and analyze changes in features of the transformed signal to detect pulse rhythm abnormalities. For example, the system may detect pulse rhythm abnormalities by analyzing energy parameters, morphology changes, and pattern changes in the scalogram of a PPG signal. Further, the system may detect pulse rhythm abnormalities by analyzing both the PPG signal and its corresponding scalogram. Physiological information, such as cardiac arrhythmia, may be derived based on the detected pulse rhythm abnormality.

Abstract: Systems and methods are provided for determining respiration information from physiological signals such as PPG signals. A physiological signal is processed to generate at least one respiration information signal and an autocorrelation sequence is generated based on the at least one respiration information signal. In some embodiments, a respiration peak is identified based on the autocorrelation sequence and a composite peak is generated based on the identified peak and at least one previous respiration peak. Respiration information is calculated based on the composite peak. In some embodiments, a determination is made whether the autocorrelation sequence includes an undesired harmonic. When the autocorrelation sequence includes an undesired harmonic, the autocorrelation sequence may not be used in the calculation of respiration information.

Abstract: Systems and methods are provided for detecting held breath events. A physiological signal, such as a photoplethysmograph (PPG) signal, is processed to extract respiration-related morphology metric signals. The morphology signals are analyzed to determine when a patient's breath is being held.

Abstract: According to embodiments, techniques for determining respiratory parameters are disclosed. More suitable probe locations for determining respiratory parameters, such as respiration rate and respiratory effort, may be identified. The most suitable probe location may be selected for probe placement. A scalogram may be generated from the detected signal at the more suitable location, resulting in an enhanced breathing band for determining respiratory parameters. Flexible probes that allow for a patient's natural movement due to respiration may also be used to enhance the breathing components of the detected signal. From the enhanced signal, more accurate and reliable respiratory parameters may be determined.

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.

Abstract: Methods and systems are provided for determining fluid responsiveness based on physiological signals. The system may detect gain changes or excessive baseline modulations. In some embodiments, based on the detected gain changes or excessive baseline modulations, the system may ignore portions of physiological signals and determine a parameter indicative of fluid responsiveness based on a plurality of amplitudes determined from other portions of the physiological signals. In some embodiments, based on the detected gain changes or excessive baseline modulations, the system may determine fluid responsiveness, or refrain from determining fluid responsiveness.

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 may include an input receiving a photoplethysmograph (PPG) signal representing light absorption by a patient's tissue, and a fluid responsiveness predictor (FRP) calculator programmed to calculate an FRP metric. The monitor also may include a memory storing a relationship between the FRP metric and a pulse pressure variation (PPV) metric. The FRP metric is calculated based on a respiratory variation of the PPG signal and based on the relationship.

Abstract: A patient monitoring system may receive a physiological signal such as a photoplethysmograph (PPG) signal. A plurality of respiration morphology signals may be determined from the PPG signal. Principal component analysis may be performed on the respiration morphology signals, resulting in one or more principal components. Respiration information such as respiration rate may be determined at least in part from a principal component that corresponds to a respiration source signal.

Abstract: Methods and systems are disclosed for analyzing a physiological respiratory signal in order to monitor respiratory depression events. In certain embodiments, respiratory depression is monitored by extracting a respiratory signal from a photoplethysmograph (“PPG”) signal, identifying a morphological characteristic of the respiratory signal, and generating a respiratory condition signal. In certain embodiments, an alarm and therapeutic intervention strategy are triggered upon determination of respiratory depression event.

Abstract: A test unit may generate a pulse signal based on a pulsatile profile and a frequency modulation component of a respiratory profile. A respiration modulated signal may be generated from the pulse signal, an amplitude modulation component, and a baseline modulation component. A patient modulated signal may be generated based on the respiration modulated signal and a patient profile. The artificial PPG signal may be generated based on the patient modulated signal and an artifact profile. The artificial PPG signal may be output to an electronic device.

Abstract: A patient monitoring system may generate a derivative signal from a physiological signal. The derivative signal may be filtered based on a pulse rate estimate associated with the physiological signal. A plurality of crossing points may be determined for the filtered derivative signal and translated to the derivative signal. A plurality of fiducial points may be determined for the derivative signal based on the plurality of crossing points. The plurality of fiducial points may be utilized to determine physiological information from the physiological signal.

Abstract: A patient monitoring system may receive a physiological signal such as a photoplethysmograph (PPG) signal. The PPG signal may include a pulsatile component that functions as a carrier signal and a frequency modulation component that represents respiration information. The patient monitoring system may more the frequency modulation component to a baseline component of the PPG signal. Respiration information may be calculated based on the frequency modulation component.

Abstract: A patient monitoring system may receive a physiological signal such as a photoplethysmograph (PPG) signal. The PPG signal may include a pulsatile component that functions as a carrier signal and an amplitude modulation component that represents respiration information. The patient monitoring system may move the amplitude modulation component to a baseline component of the PPG signal. Respiration information may be calculated based on the amplitude modulation component.

Abstract: According to embodiments, techniques for selecting a consistent part of a signal, including a photoplethysmograph (PPG) signal, are disclosed. A pulse oximetry system including a sensor or probe may be used to obtain a PPG signal from a subject. Signal peaks may be identified in the PPG signal. Characteristics of the signal peaks, including the amplitude levels of the signal peaks and/or the time-distance between the signal peaks may be used to determine if the PPG signal is consistent. In an embodiment, signal peaks are processed based on a consistency metric, and the processed signal peaks are compared to the consistency metric to determine if the PPG signal is consistent. If the PPG signal is determined to be consistent, the PPG signal may be further analyzed to determine an underlying signal parameter, including, for example, a patient respiration rate.

Abstract: A patient monitoring system may determine portions of a PPG signal that correspond to artifacts, to a baseline shift that exceeds a threshold, or to a pulse-to-pulse variability that exceeds a threshold. The patient monitoring system may identify a contiguous portion of the PPG signal that does not include the determined portions. The contiguous portion of the PPG signal may be used to determine physiological information.

Abstract: According to embodiments, a respiration signal may be processed to normalize respiratory feature values in order to improve and/or simplify the interpretation and subsequent analysis of the signal. Data indicative of a signal may be received at a sensor and may be used to generate a respiration signal. Signal peaks in the respiration signal may be identified and signal peak thresholds may be determined. The identified signal peaks may be adjusted based on the signal peak threshold values to normalize the respiration signal.

Abstract: According to embodiments, techniques for selecting a consistent part of a signal, including a photoplethysmograph (PPG) signal, are disclosed. A pulse oximetry system including a sensor or probe may be used to obtain a PPG signal from a subject. Signal peaks may be identified in the PPG signal. Characteristics of the signal peaks, including the amplitude levels of the signal peaks and/or the time-distance between the signal peaks may be used to determine if the PPG signal is consistent. In an embodiment, signal peaks are processed based on a consistency metric, and the processed signal peaks are compared to the consistency metric to determine if the PPG signal is consistent. If the PPG signal is determined to be consistent, the PPG signal may be further analyzed to determine an underlying signal parameter, including, for example, a patient respiration rate.