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US 10,327,698 B2Granted
Food intake monitoring system using apnea detection in breathing signals
AssigneeBoard of Trustees of Michigan State University
InventorsSubir Biswas, Bo Dong
Life of this patent
Estimating the term…
Abstract
A wearable breathing sensor, such as a piezoelectric chest belt system, generates a breathing signal that is analyzed by a classifier to identify apnea patterns indicating that the subject has swallowed during breathing. These breathing signals are computer-analyzed to extract inferences regarding the subject's eating and drinking patterns and thereby provide useful data for monitoring food or beverage intake for remote health monitoring.
Claims17
A system for monitoring food or beverage intake of a living subject, comprising:
- a wearable breathing sensor adapted to be worn around the torso of the subject and being responsive of inhale-exhale movement of the subject's torso to produce a breathing signal expressed as electrical data, wherein the wearable breathing sensor includes (i) a chest-worn belt and (ii) at least one piezoelectric sensor placed between two elastic strips;
- a classifier receptive of the electrical data and operative to classify the electrical data according to a predefined set of breathing patterns that include at least one apnea pattern indicating that the subject has swallowed during a breathing cycle;
- a swallow pattern analyzer coupled to the classifier and operable to recognize food and beverage intake patterns in the electrical data, wherein the food and beverage intake patterns are associated with eating and drinking different types of food and beverage;
- a processor programmed to store the classified electrical data in an associated data storage device;
- a food intake analyzer that correlates a record of classified apnea patterns with food and beverage consumption logs entered by or on behalf of the subject;
- and
- a server configured to receive the correlation to enable remote monitoring of the living subject,
- wherein:
- the classifier is configured to classify the electrical data according to a predefined set of breathing patterns that include:
- a normal breathing pattern,
- a breathing cycle with exhale swallow pattern, and
- a breathing cycle with inhale swallow pattern,
- the classifier employs a plurality of matched filters that includes (i) a first matched filter for the normal breathing pattern, (ii) a second matched filter for the breathing cycle with exhale swallow pattern, and (iii) a third matched filter for the breathing cycle with inhale swallow pattern,
- the classifier is configured to use the plurality of matched filters to determine a plurality of similarity scores for the electrical data,
- each score of the plurality of similarity scores is associated with a pattern of the predefined set of breathing patterns, and
- the classifier is configured to classify the electrical data based on the plurality of similarity scores.
13 more elements
A method of monitoring food or beverage intake of a living subject, comprising:
- placing a breathing sensor around the subject's torso to measure the subject's inhale-exhale movement and generating a breathing signal expressed as electrical data, wherein the breathing sensor includes (i) a chest-worn belt and (ii) at least one piezoelectric sensor placed between two elastic strips;
- using electrical circuitry to automatically classify said electrical data according to a predefined set of breathing patterns that include at least one apnea pattern indicating that the subject has swallowed during a breathing cycle;
- using the classified electrical data as a measure of the subject's food or beverage intake;
- using a processor receptive of the classified electrical data to (i) store the classified electrical data in a data storage device associated with said processor and (ii) analyze the classified data to recognize food and beverage intake patterns associated with eating and drinking different types of food and beverage;
- using the processor to correlate a record of classified apnea patterns with food and beverage consumption logs entered by or on behalf of the subject;
- and
- transmitting the correlation to a server to enable remote monitoring of the living subject,
- wherein:
- the step of classifying said electrical data is performed by classifying the electrical data according to a predefined set of breathing patterns that include:
- a normal breathing pattern,
- a breathing cycle with exhale swallow pattern, and
- a breathing cycle with inhale swallow pattern,
- the electrical circuitry employs a plurality of matched filters that includes (i) a first matched filter for the normal breathing pattern, (ii) a second matched filter for the breathing cycle with exhale swallow pattern, and (iii) a third matched filter for the breathing cycle with inhale swallow pattern,
- classifying said electrical data includes:
- using the plurality of matched filters to determine a plurality of similarity scores for the electrical data, wherein each score of the plurality of similarity scores is associated with a pattern of the predefined set of breathing patterns, and
- the classifier is configured to classify the electrical data based on the plurality of similarity scores.
13 more elements
Dependencies are inferred from the claim text.