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: 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: 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 and methods are provided for storing event markers. The value of a monitored physiological metric may be monitored and compared to a reference value. A patient monitoring system may compute a difference between a monitored metric and a reference value, and compare the difference to a threshold value to determine whether a physiological event has occurred. Based on the determination, a patient monitoring system may store an event marker, trigger a response, update a metric value, or perform any other suitable function.

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: 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 and methods are provided for determining when to update a blood pressure measurement. The value of a physiological metric may be monitored and compared to a reference value. A patient monitoring system may compute a difference between a monitored metric and a reference value, and compare the difference to a threshold value to determine whether to update a blood pressure measurement. The threshold value may be constant or variable, and may depend on the monitored metric.

Abstract: The present disclosure relates to monitoring a characteristic physiological parameter of a patient during a suitable time period that either precedes or follows a triggering event, such as a clinician/patient interaction, that 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, tracking the physiological parameter 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 physiological parameter. The patient signal used to derive a patient's physiological parameter may be of an oscillatory nature or may include oscillatory features that may be analyzed to derive a characteristic blood pressure or a characteristic respiration rate.

Abstract: Breathing effort of a patient, as determined (for example) from a photoplethysmograph (“PPG”) signal from the patient, can be calibrated in relation to air pressure in the patient's respiratory system. This calibration can be done by subjecting the patient to varying amounts of breathing resistance; and for each such amount, concurrently measuring (1) air pressure in the respiratory system (e.g., in the oral/nasal cavity) and (2) breathing effort (from the PPG signal). Use can be made of this calibration, e.g., during a sleep study of the patient. During such a study, breathing effort, again determined from the PPG signal and occurring, for example, during an apneic event of the patient, can be used to infer air pressure in the respiratory system by using the above calibration.

Abstract: According to embodiments, systems and methods for high-pass filtering a plethysmograph or photoplethysmograph (PPG) signal are disclosed. A sensor or probe may be used to obtain a plethysmograph or PPG signal from a subject. The sensor may be placed at any suitable location on the body, e.g., the forehead, finger, or toe. The PPG signal generated by the sensor may be high-pass filtered to disambiguate certain features of the PPG signal, including one or more characteristic points. The cut-off frequency for the high-pass filter may be greater than 0.75 Hz and less than 15 Hz. The cut-off frequency for the high-pass filter may be selected to be greater than the subject's computed pulse rate. These characteristic points on the filtered PPG signal may be used to compute non-invasive blood pressure measurements continuously or on a periodic basis. For example, the time difference between two or more characteristic points in a high-pass filtered version of the generated PPG signal may be computed.

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: A medical sensor includes a first set of optical components configured to obtain a first set of signals for determining a first regional oxygen saturation measurement. The first set of optical components includes a first emitter, a first detector separated from the first emitter by a first distance along a first axis, and a second detector separated from the first emitter by a second distance along the first axis, wherein the second distance is greater than the first distance. The sensor also includes a second set of optical components configured to obtain a second set of signals for determining a second regional oxygen saturation measurement. The second set of optical components includes a second emitter and a third detector separated from the second emitter by a third distance along a second axis, different from the first axis.

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: 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: The present disclosure provides methods, devices and systems for calculating integrated breath status values comprising: defining breath cycles based on CO2 waveforms; generating transformed signals based on PPG signals; calculating respiratory effort values based on the transformed PPG signals; and calculating integrated breath status values based on the defined breath cycles and the respiratory effort values. The disclosure also provides methods, devices and systems for calculating cardiovascular status values comprising: defining breath cycles based on a CO2 waveforms; generating transformed signals based on a PPG signals; calculating pulse output values based on the transformed PPG signal; calculating pulse output per breath values based on the defined breath cycles and the calculated pulse output values; and determining integrated cardiovascular status values based on a comparison of a change in the pulse output per breath values and in the CO2 waveforms.

Abstract: An apnea analysis system may include a photoplethysmographic (PPG) sub-system, a breath detection sub-system, and an apnea analysis module. An apnea analysis system includes a photoplethysmographic (PPG) sub-system, a breath detection sub-system, and an apnea analysis module. The PPG sub-system is configured to be operatively connected to an individual and output a PPG signal from the individual. The breath detection sub-system is configured to be operatively connected to the individual and output a breath signal from the individual. The apnea analysis module is in communication with the PPG sub-system and the breath detection sub-system. The apnea analysis module analyzes the breath signal and a respiratory component of the PPG signal and, based on the analysis, identifies a presence of apnea, differentiates between obstructive apnea and central apnea, and provides an indication of the identified apnea.

Abstract: According to embodiments, systems and methods for high-pass filtering a plethysmograph or photoplethysmograph (PPG) signal are disclosed. A sensor or probe may be used to obtain a plethysmograph or PPG signal from a subject. The sensor may be placed at any suitable location on the body, e.g., the forehead, finger, or toe. The PPG signal generated by the sensor may be high-pass filtered to disambiguate certain features of the PPG signal, including one or more characteristic points. The cut-off frequency for the high-pass filter may be greater than 0.75 Hz and less than 15 Hz. The cut-off frequency for the high-pass filter may be selected to be greater than the subject's computed pulse rate. These characteristic points on the filtered PPG signal may be used to compute non-invasive blood pressure measurements continuously or on a periodic basis. For example, the time difference between two or more characteristic points in a high-pass filtered version of the generated PPG signal may be computed.

Abstract: Provided are systems and methods for processing a physiological signal in order to detect whether a patient's breathing is being controlled by a ventilator. A signal, such as a photoplethysmograph (PPG) may be processed to determine one or more various metrics indicative of the consistency of the patient's respiration.

Abstract: Systems and methods are provided for generating respiration alarms. Respiration information and oxygen saturation information is determined from a photoplethysmograph (PPG) signal. This information is analyzed in connection with activating a respiration lost alarm.

Abstract: One or more respiratory characteristics of a patient are measured by coupling patient monitor apparatus (e.g., a photoplethysmograph (“PPG”)) to the patient in order to produce a patient monitor signal that includes signal indicia indicative of effort the patient is exerting to breathe. A breathing or respiratory effort signal for the patient is extracted from the patient monitor signal. A respiratory characteristic signal is extracted (at least in part) from the effort signal. This may be done, for example, on the basis of an amplitude feature of the effort signal and a relative time of occurrence of that amplitude feature. Alternatively, the respiratory characteristic signal may be based on a relationship between two amplitude features of the effort signal, with or without regard for specifics of the times of occurrence of those amplitude features. A breath air flow meter may also be coupled to the patient, if desired, in order to produce a flow signal.