Abstract: Embodiments described herein may include systems and methods for detecting events that may be associated with sleep apnea. Some embodiments are directed to a system and/or method for automated detection of reduction in airflow events using polysomnograph signals, wherein the reduction in airflow events may relate to sleep apnea. The PSG signals may be limited to four signals, including data from an airflow channel, a blood oxygen saturation channel, a chest movement channel, and an abdomen movement channel. Using information from these channels, some embodiments may automatically identify reduction in airflow events.

Abstract: Present embodiments are directed to a system and method capable of detecting and graphically indicating physiologic patterns in patient data. For example, present embodiments may include a monitoring system that includes a monitor capable of receiving input relating to patient physiological parameters and providing indications or alarms related to oxygen saturation declines and oxygen desaturation patterns associated with sleep apnea. Present embodiments may include methods and systems for mediating between alarms and other indicators associated with oxygen desaturation and ventilatory instability.

Abstract: A patient monitoring system may receive a physiological signal having gap portions in the received data. The gap portions may be identified and a plurality of morphology metric signals may be modified based on the identified gap portions. The morphology metric signals may be modified based on the identified gaps, and a combined autocorrelation sequence may be generated based on the modified morphology metric signals. The combined autocorrelation sequence may be used to determine physiological information.

Abstract: A patient monitoring system may receive a physiological signal such as a photoplethysmograph (PPG) signal that exhibits frequency and amplitude modulation based on respiration. A phase locked loop may generate a frequency demodulated signal and an amplitude demodulated signal from the PPG signal. An autocorrelation sequence may be generated for each of the frequency demodulated signal and the amplitude demodulated signal. The autocorrelation sequences may be combined and respiration information may be determined based on the combined autocorrelation sequence.

Abstract: Arrhythmia may impact the determination of physiological information from a physiological signal. A patient monitoring system may detect the presence of arrhythmia based on changes in the physiological signal. Derived value data sets may be extracted from the physiological signal and calculations performed to generate arrhythmia features. The arrhythmia features may be used to generate an arrhythmia indicator that may indicate the presence of arrhythmia in the physiological signal.

Abstract: A patient monitoring system may generate an autocorrelation sequence for a physiological signal such as a photoplethysmograph signal. A series of peak values may be identified for the autocorrelation sequence. The peak values may be modified based on a historical distribution of a physiological parameter. A physiological parameter such as respiration rate may be determined based on the modified peak values.

Abstract: A patient monitoring system may receive a photoplethysmograph (PPG) signal including samples of a pulse waveform. The PPG signal may demonstrate morphology changes based on respiration. The system may calculate morphology metrics from the PPG signal, the first derivative of the PPG signal, the second derivative of the PPG signal, or any combination thereof. The morphology metrics may demonstrate amplitude modulation, baseline modulation, and frequency modulation of the PPG signal that is related to respiration. Morphology metric signals generated from the morphology metrics may be used to determine respiration information such as respiration rate.

Abstract: A signal representing physiological information may include information related to respiration. A patient monitoring system may utilize a wavelet transform to generate a scalogram from the signal. A threshold for the scalogram may be calculated, and scalogram values may be compared to the threshold. One of the scales meeting the threshold may be selected as representing respiration information such as respiration rate. The respiration information may be determined based on the selected scale.

Abstract: A signal representing physiological information may include information related to respiration. A patient monitoring system may generate a plurality of autocorrelation sequences from the signal and combine the autocorrelation sequences to generate a combined autocorrelation sequence. The combined autocorrelation sequence may be analyzed to identify one or more peaks that may correspond to respiration information. Respiration information such as respiration rate may be determined based on the one or more peaks.

Abstract: A patient monitoring system may receive a photoplethysmograph (PPG) signal including samples of a pulse waveform. A plurality of morphology metric signals may be generated from the PPG signal. The system may generate an autocorrelation sequence for each of the morphology metric signals. An autocorrelation metric may be generated from each of the autocorrelation sequences and may represent the regularity or periodicity of the morphology metric signal. The autocorrelation sequences may be combined to generate a combined autocorrelation sequence, with the weighting of the autocorrelation sequences based on the autocorrelation metric. The combined autocorrelation sequence may be used to determine physiological information.

Abstract: Embodiments described herein may include systems and methods for detecting events that may be associated with sleep apnea. Some embodiments are directed to a system and/or method for automated detection of reduction in airflow events using polysomnograph signals, wherein the reduction in airflow events may relate to sleep apnea. The PSG signals may be limited to four signals, including data from an airflow channel, a blood oxygen saturation channel, a chest movement channel, and an abdomen movement channel. Using information from these channels, some embodiments may automatically identify reduction in airflow events.

Abstract: Methods and systems are discussed for determining venous oxygen saturation by calculating a ratio of ratios from respiration-induced baseline modulations. A calculated venous ratio of ratios may be compared with a look-up table value to estimate venous oxygen saturation. A calculated venous ratio of ratios is compared with an arterial ratio of ratios to determine whether baseline modulations are the result of a subject's respiration or movement. Such a determination is also made by deriving a venous ratio of ratios using a transform technique, such as a continuous wavelet transform. Derived venous and arterial saturation values are used to non-invasively determine a cardiac output of the subject.

Abstract: Methods and systems are discussed for determining venous oxygen saturation by calculating a ratio of ratios from respiration-induced baseline modulations. A calculated venous ratio of ratios may be compared with a look-up table value to estimate venous oxygen saturation. A calculated venous ratio of ratios is compared with an arterial ratio of ratios to determine whether baseline modulations are the result of a subject's respiration or movement. Such a determination is also made by deriving a venous ratio of ratios using a transform technique, such as a continuous wavelet transform. Derived venous and arterial saturation values are used to non-invasively determine a cardiac output of the subject.

Abstract: A patient monitoring system may be configured to use template matching in determining physiological parameters. A physiological signal may be monitored, and a wavelet transform may be performed. The wavelet transform, or parameters derived thereof such as energy distribution or relative phase difference, may be compared with one or more templates using template matching. Templates may be based on, for example, physiological data, mathematical models, or look-up tables, and may be pre-computed and stored. Physiological parameters may be determined based on the template matching results. Scale variability, confidence metrics, or both, may be used to aid in determining the physiological parameter.

Abstract: Methods and systems are disclosed for computing one or more continuous wavelet transforms on a dedicated integrated circuit. The systems comprise an integrated circuit having a receiver, memory, and processing circuitry. The receiver receives input data corresponding to an input signal. The memory stores information corresponding to one or more wavelet functions scaled over a set of scales. The processing circuitry is configured to compute, in-parallel, various portions of a single continuous wavelet transform of the input signal based on the received input data and the stored information corresponding to a single wavelet function computed over a set of scales.

Abstract: Embodiments disclosed herein may include systems and methods for evaluating physiological parameter data. Embodiments of methods may include monitoring a patient to produce a signal comprising a sequence of numerical values for a physiological parameter over a time period, calculating an index from the signal, comparing the index to a reported index, and if the index is greater than the reported index, setting the reported index to the value of the index. Embodiments of methods may include calculating a modulation of the signal, comparing the modulation to a previous valise of the modulation to identity a trend in the modulation and if the trend corresponds to an undesirable condition, using a first function, to increase the reported index. Embodiments of methods may include providing an indication of a physiological status based on the reported index.

Abstract: A method for identifying one or more spot colors in a full color multi-bit image data, and processing the identified spot colors for output on an image printing system is provided. The method includes inputting the full color image data, wherein the full color image data includes a plurality of pixels; analyzing the inputted image to identify the pixels with a spot color from the pixels with a non-spot color, wherein each pixel with a spot color is within a predetermined threshold from a desired color value; processing the identified spot color pixels; and combining the processed spot color pixels with non-spot color pixels to form a data structure.

Abstract: Embodiments disclosed herein may include systems and methods for evaluating physiological parameter data. Embodiments of methods may include monitoring a patient to produce a signal comprising a sequence of numerical values for a physiological parameter over a time period, calculating an index from the signal, comparing the index to a reported index, and if the index is greater than the reported index, setting the reported index to the value of the index. Embodiments of methods may include calculating a modulation of the signal, comparing the modulation to a previous value of the modulation to identify a trend in the modulation and if the trend corresponds to an undesirable condition, using a first function to increase the reported index. Embodiments of methods may include providing an indication of a physiological status based on the reported index.

Abstract: Various embodiments may provide methods and systems capable of evaluating physiological parameter data. The methods and systems may include monitoring a patient to produce a signal comprising a sequence of numerical values for blood oxygen saturation over a time period. The signal may be analyzed to identify two or more desaturation patterns within the time period, and at least two numerical differences are calculated between the desaturation patterns. A saturation pattern detection index may be calculated using the numerical differences between the desaturation patterns. The saturation pattern detection index may be used to provide an indication of a physiological condition. Other embodiments may provide a medical device that may be used to evaluate physical parameter data according to the techniques described.

Abstract: Methods and systems are disclosed for tuning first and second wavelet functions to resolve at least one component of a signal. A first characteristic frequency corresponding to a first scale band of interest is determined, and a first wavelet function is tuned to the first characteristic frequency in at least a region of a first scale band of interest. A second characteristic frequency corresponding to a second scale band of interest is determined, and a second wavelet function is tuned to the second characteristic frequency in at least a region of the second scale band of interest. A signal is transformed for the first and second wavelet functions using a continuous wavelet transform to create a transform signal, and a scalogram is generated based at least in part on the transformed signal.