Abstract: An acoustic physiological monitoring system and method wherein the usability for physiological monitoring of time segments of an acoustic signal recording body sounds is determined using frequency analysis. A time segment of the acoustic signal is filtered into a target portion in a target frequency band and a non-target portion in a non-target frequency band. Energies of the target portion and the non-target portion are computed. A usability indicator for the time segment is computed using the energies. The usability of the time segment is determined using the usability indicator. A physiological parameter estimate is selectively calculated using the time segment based on the usability of the time segment. Finally, information based on the physiological parameter estimate is outputted.

Abstract: A sleep monitoring method and device classify segments of an acoustic physiological signal captured during sleep as snore and apnea segments. The method and device employ a phase-locked loop array to rapidly detect snore segments for widely variant snoring rhythms exhibited by different people or the same person over time. The phase-locked loop array integrates seamlessly with an apnea timer-thresholding mechanism that detects apnea segments.

Abstract: A sleep monitoring method and device classify segments of an acoustic physiological signal captured during sleep as snore and apnea segments. The method and device employ a phase-locked loop array to rapidly detect snore segments for widely variant snoring rhythms exhibited by different people or the same person over time. The phase-locked loop array integrates seamlessly with an apnea timer-thresholding mechanism that detects apnea segments.

Abstract: An adaptive acoustic signal filter for a respiration monitoring system includes a filter stage and a cutoff frequency adapter. The filter stage applies a cutoff frequency to an input acoustic signal waveform containing respiration and heart sound components in a filtering operation to produce a filtered acoustic signal waveform from which heart sound components have been removed. The adapter then performs cutoff frequency optimization tests on the filtered signal waveform and determines from the tests whether adjustment of the cutoff frequency is indicated. These tests assess whether the filtering operation struck a proper balance between removing heart sound components and preserving respiration sound components in the filtered signal waveform. If adjustment of the cutoff frequency is indicated, the adapter adjusts the cutoff frequency and the adjusted cutoff frequency is provided to the filter stage for application in a next filtering operation performed on the input signal waveform.

Abstract: Dual path noise detection and isolation for an acoustic respiration monitoring system detects noise in an acoustic signal recording lung sounds using two discrete noise detection techniques. A first technique detects portions of the signal that exhibit long-term, moderate amplitude noise by analyzing cumulative energy in the signal. A second technique detects portions of the signal that exhibit short-term, high amplitude noise by analyzing peak energy in the signal. Noisy portions of the signal are isolated using the combined results of the dual path detection. A respiration parameter is estimated using the signal without resort to the noisy portions and information based at least in part on the respiration parameter is outputted.

Abstract: A multistage system and method for estimating respiration parameters from an acoustic signal. At a first stage, the method and system detect and isolate portions of the signal that exhibit long-term, moderate amplitude noise by analyzing cumulative energies in the signal, and portions of the signal that exhibit short-term, high amplitude noise by analyzing peak energies in the signal. At a second stage, the method and system filter heart sound from the signal energy envelope by applying an adaptive filter that minimizes the loss of respiration sound. At a third stage, the system and method isolate respiration phases in the signal by identifying trends in the energy envelope. Once respiration phases are isolated, these phases are used to estimate respiration parameters, such as respiration rate and I/E ratio.

Abstract: An acoustic physiological monitoring system and method wherein the usability for physiological monitoring of time segments of an acoustic signal recording body sounds is determined using frequency analysis. A time segment of the acoustic signal is filtered into a target portion in a target frequency band and a non-target portion in a non-target frequency band. Energies of the target portion and the non-target portion are computed. A usability indicator for the time segment is computed using the energies. The usability of the time segment is determined using the usability indicator. A physiological parameter estimate is selectively calculated using the time segment based on the usability of the time segment. Finally, information based on the physiological parameter estimate is outputted.

Abstract: Dual path noise detection and isolation for an acoustic respiration monitoring system detects noise in an acoustic signal recording lung sounds using two discrete noise detection techniques. A first technique detects portions of the signal that exhibit long-term, moderate amplitude noise by analyzing cumulative energy in the signal. A second technique detects portions of the signal that exhibit short-term, high amplitude noise by analyzing peak energy in the signal. Noisy portions of the signal are isolated using the combined results of the dual path detection. A respiration parameter is estimated using the signal without resort to the noisy portions and information based at least in part on the respiration parameter is outputted.

Abstract: A multistage system and method for estimating respiration parameters from an acoustic signal. At a first stage, the method and system detect and isolate portions of the signal that exhibit long-term, moderate amplitude noise by analyzing cumulative energies in the signal, and portions of the signal that exhibit short-term, high amplitude noise by analyzing peak energies in the signal. At a second stage, the method and system filter heart sound from the signal energy envelope by applying an adaptive filter that minimizes the loss of respiration sound. At a third stage, the system and method isolate respiration phases in the signal by identifying trends in the energy envelope. Once respiration phases are isolated, these phases are used to estimate respiration parameters, such as respiration rate and I/E ratio.

Abstract: The present invention isolates respiration phases in an acoustic signal using trend analysis. Once respiration phases are isolated, they are used to estimate respiration parameters. An exemplary method comprises receiving an acoustic signal recording body sounds; identifying candidate peaks at maxima of the signal; identifying candidate valleys at minima of the signal; selecting significant peaks from among the candidate peaks using heights of the candidate peaks; selecting significant valleys from among the candidate valleys using heights of the candidate valleys; detecting silent phases in the signal based at least in part on rise rates from the significant valleys; isolating respiration phases in the signal based at least in part on the significant valleys and the silent phases; calculating respiration parameter estimates based at least in part on the respiration phases; and outputting the respiration parameter estimates.

Abstract: A method and system for reliably estimating inspiration-to-expiration ratio from an acoustic physiological signal. A background sound level is set to an energy level whereat a predetermined share of data points on an energy envelope is below the energy level, after which respiration phase start and end times are determined at energy crossings above the background sound level, enabling more reliable determination of respiration phases. Moreover, reliably determined respiration phase start and end times, in addition to being used to estimate inspiration-to-expiration ratio, are applied to other purposes, such as estimating respiration period, validating an independently computed respiration period and/or adjusting a sampling window of the acoustic physiological signal, reducing system complexity and conserving computational resources.

Abstract: Methods and devices for continual respiratory monitoring of a human subject using adaptive windowing provide continual estimates of the respiration period of the subject by continually buffering and evaluating samples of a respiratory signal in which the subject's breath sounds are embodied, and dynamically adjust the sampling window length based at least in part on the respiration period. Through this adaptive windowing technique, a sampling window length is maintained that is tailored to the subject's breathing habits, does not unduly inhibit real-time respiratory monitoring, and does not place unnecessary burdens on memory and processing resources of the respiratory monitoring device.