Data binning method and system for estimating respiratory airflow from body sound signal
First Claim
1. A method for estimating respiratory airflow on a respiratory monitoring device, comprising the steps of:
- receiving on the respiratory monitoring device body sound signal data from a first source and respiratory airflow data from a second source;
generating on the respiratory monitoring device time-aligned data points from the body sound signal data and the respiratory airflow data;
assigning on the respiratory monitoring device each of the time-aligned data points to one of a plurality of bins each spanning a discrete body sound signal range;
calculating on the respiratory monitoring device without invoking best fit analysis respiratory airflow estimation data for each bin using the time-aligned data points assigned to that bin;
populating on the respiratory monitoring device a lookup table with an entry for each bin associating the discrete body sound signal range for that bin and the estimation data for that bin;
acquiring on the respiratory monitoring device additional body sound signal data;
retrieving on the respiratory monitoring device from the lookup table estimation data corresponding to the additional body sound signal data; and
outputting on the respiratory monitoring device respiratory airflow output data based on the estimation data.
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Abstract
Data binning methods and systems for estimating a subject'"'"'s respiratory airflow from a body sound signal detected by an acoustic sensor on the subject'"'"'s body. The methods and systems operate in a configuration mode followed by a monitoring mode. In the configuration mode, a body sound signal and respiratory airflow are detected by an on-body acoustic sensor and a spirometer, respectively, over a common time period. Time-aligned body sound signal and respiratory airflow data points are then generated and assigned to bins each spanning a discrete signal range (e.g. discrete signal entropy range or signal amplitude range). Respiratory airflow estimation data (e.g. mean airflow and standard deviation) are then calculated for each bin and an entry for each bin associating the discrete range and the estimation data is stored in a lookup table. Then, in the monitoring mode, the lookup table is accessed using subsequent body sound signal readings (e.g. taken in the field or at home) to provide respiratory airflow estimates without further need for a spirometer.
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Citations
20 Claims
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1. A method for estimating respiratory airflow on a respiratory monitoring device, comprising the steps of:
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receiving on the respiratory monitoring device body sound signal data from a first source and respiratory airflow data from a second source; generating on the respiratory monitoring device time-aligned data points from the body sound signal data and the respiratory airflow data; assigning on the respiratory monitoring device each of the time-aligned data points to one of a plurality of bins each spanning a discrete body sound signal range; calculating on the respiratory monitoring device without invoking best fit analysis respiratory airflow estimation data for each bin using the time-aligned data points assigned to that bin; populating on the respiratory monitoring device a lookup table with an entry for each bin associating the discrete body sound signal range for that bin and the estimation data for that bin; acquiring on the respiratory monitoring device additional body sound signal data; retrieving on the respiratory monitoring device from the lookup table estimation data corresponding to the additional body sound signal data; and outputting on the respiratory monitoring device respiratory airflow output data based on the estimation data. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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14. A respiratory monitoring device, comprising:
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a first input interface; a second input interface; a database; an output interface; and a processor communicatively coupled with the first and second input interfaces, the output interface and the database, wherein the device receives body sound signal data on the first input interface and respiratory airflow data on the second input interface, and under control of the processor generates time-aligned data points from the body sound signal data and the respiratory airflow data, assigns each of the time-aligned data points to one of a plurality of bins each spanning a discrete body sound signal range, calculates without invoking best fit analysis respiratory airflow estimation data for each bin using the time-aligned data points assigned to that bin, populates a lookup table in the database with an entry for each bin associating the discrete body sound signal range for that bin and the estimation data for that bin, receives additional body sound signal data via the first input interface, retrieves from the lookup table estimation data corresponding to the additional body sound signal data, and outputs on the output interface output data based on the estimation data. - View Dependent Claims (15, 16, 17, 18, 19, 20)
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Specification