Abstract: A physiological measurement system is disclosed which can take a pulse oximetry signal such as a photoplethysmogram from a patient and then analyse the signal to measure physiological parameters including respiration, pulse, oxygen saturation and movement. The system comprises a pulse oximeter which includes a light emitting device and a photodetector attachable to a subject to obtain a pulse oximetry signal; analogue to digital converter means arranged to convert said pulse oximetry signal into a digital pulse oximetry signal; signal processing means suitable to receive said digital pulse oximetry signal and arranged to decompose that signal by wavelet transform means; feature extraction means arranged to derive physiological information from the decomposed signal; an analyser component arranged to collect information from the feature extraction means; and data output means arranged in communication with the analyser component.

Abstract: A physiological measurement system is disclosed which can take a pulse oximetry signal such as a photoplethysmogram from a patient and then analyse the signal to measure physiological parameters including respiration, pulse, oxygen saturation and movement. The system comprises a pulse oximeter which includes a light emitting device and a photodetector attachable to a subject to obtain a pulse oximetry signal; analogue to digital converter means arranged to convert said pulse oximetry signal into a digital pulse oximetry signal; signal processing means suitable to receive said digital pulse oximetry signal and arranged to decompose that signal by wavelet transform means; feature extraction means arranged to derive physiological information from the decomposed signal; an analyser component arranged to collect information from the feature extraction means; and data output means arranged in communication with the analyser component.

Abstract: A physiological measurement system is disclosed which can take a pulse oximetry signal such as a photoplethysmogram from a patient and then analyse the signal to measure physiological parameters including respiration, pulse, oxygen saturation and movement. The system comprises a pulse oximeter which includes a light emitting device and a photodetector attachable to a subject to obtain a pulse oximetry signal; analogue to digital converter means arranged to convert said pulse oximetry signal into a digital pulse oximetry signal; signal processing means suitable to receive said digital pulse oximetry signal and arranged to decompose that signal by wavelet transform means; feature extraction means arranged to derive physiological information from the decomposed signal; an analyser component arranged to collect information from the feature extraction means; and data output means arranged in communication with the analyser component.

Abstract: A physiological measurement system is disclosed which can take a pulse oximetry signal such as a photoplethysmogram from a patient and then analyse the signal to measure physiological parameters including respiration, pulse, oxygen saturation and movement. The system comprises a pulse oximeter which includes a light emitting device and a photodetector attachable to a subject to obtain a pulse oximetry signal; analogue to digital converter means arranged to convert said pulse oximetry signal into a digital pulse oximetry signal; signal processing means suitable to receive said digital pulse oximetry signal and arranged to decompose that signal by wavelet transform means; feature extraction means arranged to derive physiological information from the decomposed signal; an analyser component arranged to collect information from the feature extraction means; and data output means arranged in communication with the analyser component.

Abstract: A physiological measurement system is disclosed which can take a pulse oximetry signal such as a photoplethysmogram from a patient and then analyse the signal to measure physiological parameters including respiration, pulse, oxygen saturation and movement. The system comprises a pulse oximeter which includes a light emitting device and a photodetector attachable to a subject to obtain a pulse oximetry signal; analogue to digital converter means arranged to convert said pulse oximetry signal into a digital pulse oximetry signal; signal processing means suitable to receive said digital pulse oximetry signal and arranged to decompose that signal by wavelet transform means; feature extraction means arranged to derive physiological information from the decomposed signal; an analyser component arranged to collect information from the feature extraction means; and data output means arranged in communication with the analyser component.

Abstract: A physiological measurement system is disclosed which can take a pulse oximetry signal such as a photoplethysmogram from a patient and then analyse the signal to measure physiological parameters including respiration, pulse, oxygen saturation and movement. The system comprises a pulse oximeter which includes a light emitting device and a photodetector attachable to a subject to obtain a pulse oximetry signal; analogue to digital converter means arranged to convert said pulse oximetry signal into a digital pulse oximetry signal; signal processing means suitable to receive said digital pulse oximetry signal and arranged to decompose that signal by wavelet transform means; feature extraction means arranged to derive physiological information from the decomposed signal; an analyser component arranged to collect information from the feature extraction means; and data output means arranged in communication with the analyser component.

Abstract: A physiological measurement system is disclosed which can take a pulse oximetry signal such as a photoplethysmogram from a patient and then analyze the signal to measure physiological parameters including respiration, pulse, oxygen saturation and movement. The system comprises a pulse oximeter which includes a light emitting device and a photodetector attachable to a subject to obtain a pulse oximetry signal; analogue to digital converter means arranged to convert said pulse oximetry signal into a digital pulse oximetry signal; signal processing means suitable to receive said digital pulse oximetry signal and arranged to decompose that signal by wavelet transform means; feature extraction means arranged to derive physiological information from the decomposed signal; an analyzer component arranged to collect information from the feature extraction means; and data output means arranged in communication with the analyzer component.

Abstract: A physiological measurement system is disclosed which can take a pulse oximetry signal such as a photoplethysmogram from a patient and then analyse the signal to measure physiological parameters including respiration, pulse, oxygen saturation and movement. The system comprises a pulse oximeter which includes a light emitting device and a photodetector attachable to a subject to obtain a pulse oximetry signal; analogue to digital converter means arranged to convert said pulse oximetry signal into a digital pulse oximetry signal; signal processing means suitable to receive said digital pulse oximetry signal and arranged to decompose that signal by wavelet transform means; feature extraction means arranged to derive physiological information from the decomposed signal; an analyser component arranged to collect information from the feature extraction means; and data output means arranged in communication with the analyser component.

Abstract: According to embodiment, systems and methods for processing a physiological measurement and generating alarms based on the measurement are provided. Multiple features of a single physiological measurement may be concurrently monitored to generate alarms. One or more of the features may be based on a trend of the physiological measurement. One or more of the features may be based on a wavelet transform of the physiological measurement. Different features may be used in different combinations to lower the percentage of false alarms while still recognizing valid alarm events.

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: A method and system are provided for evaluating in patient monitoring whether a signal is sensed optimally by receiving a signal, transforming the signal using a wavelet transform, generating a scalogram based at least in part on the transformed signal, identifying a pulse band in the scalogram, identifying a characteristic of the pulse band, determining, based on the characteristic of the pulse band, whether the signal is sensed optimally; and triggering an event. The characteristics of the pulse band and scalogram may be used to provide an indication of monitoring conditions.

Abstract: According to embodiments, systems, devices, and methods for ridge selection in scalograms are disclosed. Ridges or ridge components are features within a scalogram which may be computed from a signal such as a physiological (e.g., photoplethysmographic) signal. Ridges may be identified from one or more scalograms of the signal. Parameters characterizing these ridges may be determined Based at least in part on these parameters, a ridge density distribution function is determined A ridge is selected from analyzing this ridge density distribution function. In some embodiments, the selected ridge is used to determine a physiological parameter such as respiration rate.

Abstract: According to embodiments, techniques for using continuous wavelet transforms and spectral transforms to identify pulse rates from a photoplethysmographic (PPG) signal are disclosed. According to embodiments, candidate pulse rates of the PPG signal may be identified from a wavelet transformed PPG signal and a spectral transformed PPG signal. A pulse rate may be determined from the candidate pulse rates by selecting one of the candidate pulse rates or by combining the candidate pulse rates. According to embodiments, a spectral transform of a PPG signal may be performed to identify a frequency region associated with a pulse rate of the PPG signal. A continuous wavelet transform of the PPG signal at a scale corresponding to the identified frequency region may be performed to determine a pulse rate from the wavelet transformed signal.

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 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: 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: According to embodiments, systems, devices, and methods for ridge selection in scalograms are disclosed. Ridges or ridge components are features within a scalogram which may be computed from a signal such as a physiological (e.g., photoplethysmographic) signal. Ridges may be identified from one or more scalograms of the signal. Parameters characterizing these ridges may be determined. Based at least in part on these parameters, a ridge density distribution function is determined. A ridge is selected from analyzing this ridge density distribution function. In some embodiments, the selected ridge is used to determine a physiological parameter such as respiration rate.

Abstract: The present disclosure is directed towards embodiments of systems and methods for discriminating (e.g., masking out) scale bands that are determined to be not of interest from a scalogram derived from a continuous wavelet transform of a signal. Techniques for determining whether a scale band is not of interest include, for example, determining whether a scale band's amplitude is being modulated by one or more other bands in the scalogram. Another technique involves determining whether a scale band is located between two other bands and has energy less than that of its neighboring bands. Another technique involves determining whether a scale band is located at about half the scale of another, more dominant (i.e., higher energy) band.

Abstract: Methods and systems are provided for deriving and analyzing shape metrics, including skewness metrics, from physiological signals and their derivatives to determine measurement quality, patient status and operating conditions of a physiological measurement device. Such determinations may be used for any number of functions, including indicating to a patient or care provider that the measurement quality is low or unacceptable, alerting a patient or care provider to a change in patient status, triggering or delaying a recalibration of a monitoring device, and adjusting the operating parameters of a monitoring system.