摘要:
Linear classification is used to determine the quality of acoustic physiological signal samples. A feature dataset is extracted from acoustic physiological signal samples of known quality (i.e., weak, noisy, good) acquired over a sampling period. A linear discriminant analysis is performed on the feature dataset to determine a direction of a linear classifier for the feature dataset. A classification error risk analysis is performed on the feature dataset to determine an offset of the linear classifier. The linear classifier is used to classify into reliability classes acoustic physiological signal samples acquired over an operating period. Information is selected for outputting using the assigned classifications, and is outputted.
摘要:
Method and device for continual physiological monitoring in which the display of physiological parameter estimates is conditioned on conformance of the estimates with expectations. Current estimates of physiological parameters are compared with expectations for the current estimates determined using prior estimates of the physiological parameters. Nonconformance with expectations can result in display of information indicating present unavailability of an estimate for the physiological parameter. The method and device are adaptable for use with various types of monitored physiological parameters and various expectation metrics.
摘要:
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.
摘要:
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.
摘要:
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.
摘要:
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.
摘要:
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.
摘要:
Lightweight automatic gain control (AGC) methods and systems reduce usage of often scarce computing resources in ambulatory monitoring systems through an AGC algorithm that relies on lightweight calculations and judicious constraints on gain reevaluations and adjustments. Statistical range sampling is used to adjust the gain of a physiological signal to keep the signal within a target amplitude range and may be coupled with dynamic range control to prevent gain adjustments from occurring too frequently. Moreover, gain reevaluations and adjustments may be temporarily suspended when the physiological signal is noisy.
摘要:
A physiological monitoring device and large noise handling method for use on such a device in which a reliable estimate of a physiological parameter is ensured by identifying and replacing large noise components of a physiological signal prior to estimation. An estimation period for a physiological parameter is segmented into time windows. Noisy time windows within the estimation period are identified. The noisy time windows are replaced with replacement time windows having a baseline amplitude. An estimate of the physiological parameter for the estimation period is calculated using the replacement time windows in lieu of the noisy time windows, and is outputted. If the share of noisy time windows exceeds a predetermined limit share, calculating and/or outputting of an estimate may be precluded. The physiological parameter may be heart rate.
摘要:
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.