Abstract: A method and system that reliably estimates a respiration parameter from an acoustic physiological signal without introducing undue complexity or intense computation. A median filter is applied to an energy envelope of the signal to remove heart sound “sparks” from the envelope and better isolate lung sounds. The median filter is followed by a low-pass filter that removes abrupt changes in the envelope caused by the median filter's nonlinearity. Various peak cross-checks are performed on an autocorrelation result generated from the envelope to confirm the reliability of the signal before an estimate of a respiration parameter is generated from the autocorrelation result.

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: Lightweight wheeze detection methods and systems for portable respiratory health monitoring devices conserve computing resources in portable respiratory health monitoring devices by employing lightweight algorithm that calculates a partial STFT image of a respiratory signal that includes all data points necessary for wheeze detection but excludes many data points that are unnecessary for wheeze detection. The methods and systems provide substantial savings in computing resources while still ensuring every wheeze in a respiratory signal is detected.

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.

Abstract: Physiological signal quality classification methods and systems designed to improve ambulatory monitoring. Physiological signals are classified as good, noisy or weak based on signal properties. Once classified, signals are processed differently depending on their classification in order to encourage reliance on reliable physiological data, discourage reliance on unreliable physiological data and induce action to improve signal quality. For example, for a good signal, physiological data may be extracted from the signal and displayed to a person being monitored. For a noisy signal, a noisy signal notification may be displayed to the person in lieu of extracted physiological data. For a weak signal, a weak signal notification may be displayed to the person in lieu of extracted physiological data.

Abstract: A method and system classify respiratory phases in a single channel acoustic signal as inspiratory and expiratory using explicit labeling with label verification. In the method and system, a subject explicitly indicates through a user input the start of a respiratory cycle (i.e. start of inspiration). The phase indication is applied to provisionally label several consecutive phases of a single channel acoustic signal as inspiratory and expiratory. A provisional phase rule set is then generated based on characteristic differences between the inspiratory and expiratory phases. The phase indication, provisional labeling and provisional rule set generation steps are then repeated. The two generated provisional rule sets are then compared for a match to verify the accuracy of the subject's phase indications and the ability to automatically recover phase in the event of signal loss.

Abstract: A personal environmental monitoring method and system and a portable monitor for use therein permit real-time mobile monitoring of environmental conditions in the immediate vicinity to ensure compatibility with the particular environmental sensitivities of a person being monitored. The portable monitor may be a fully integrated mobile device that provides real-time mobile monitoring of immediate environmental conditions without network connectivity.

Abstract: Methods and systems for particle characterization using a light fluctuation component of an optical sensor output signal. The use of the light fluctuation component enables particle characterization (e.g. provision of information on particle size, type and confidence) without requiring measurements at multiple wavelengths or multiple angles and using relatively lightweight calculations. The methods and systems allow integration of real-time airborne particle characterization into portable monitors. The methods and systems in some embodiments also use the output signal to further characterize particles through determination of particle density information.

Abstract: A heath monitoring method and system estimate a patient's respiratory rate and heart rate using different frequency components of a shared acoustic signal. Use of a common acoustic signal to estimate the patient's respiratory rate and heart rate permit more economical and simplified heath monitoring.

Abstract: A respiratory signal detection and time domain signal processing method and system classifies respiratory phases and determines respiratory time data useful in respiratory health determinations. The method and system analyze respiratory signals collected at multiple detection points at least one of which ensures that respiratory phases can be properly classified. Moreover, the method and system employ a time domain signal processing approach that facilitates determination of respiratory time data while realizing savings in computing power relative to frequency domain processing approaches.