Consumer-oriented biometrics data management and analysis system
First Claim
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1. A method comprising:
- receiving, by a server device, a set of information including pluralities of data points for each of manually entered health-related data for a user, automatically collected health-related data for the user, and medical test results for the user, wherein the server device receives the automatically collected health-related data periodically via a network from a wearable health-tracking device worn by the user;
in response to receiving the set of information, integrating, by the server device, the manually entered health-related data for the user, the automatically collected health-related data for the user, and the medical test results for the user into a comprehensive health profile for the user, wherein integrating the manually entered health-related data for the user, the automatically collected health-related data for the user, and the medical test results for the user into the comprehensive health profile for the user comprises;
(i) determining a health-related correlation between diet, medication intake, and reported mood of the user, wherein the health-related correlation indicates an extent to which respective data points related to the diet, medication intake, and reported mood of the user vary together,(ii) adding an indication of the health-related correlation to the comprehensive health profile for the user,(iii) performing, by an analytics engine, goodness-of-fit tests between (a) a series of blood sugar levels from the user measured at points in time after the user has eaten, and (b) curves representing each of a normal blood sugar response after eating, a pre-diabetic blood sugar response after eating, and a diabetic blood sugar response after eating, wherein the series of blood sugar levels from the user is part of the one or more of the manually entered health-related data for the user, the automatically collected health-related data for the user, and the medical test results for the user,(iv) based on the goodness-of-fit tests, concluding, by the analytics engine, that the series of blood sugar levels from the user indicates the normal blood sugar response after eating, the pre-diabetic blood sugar response after eating, or the diabetic blood sugar response after eating,(v) adding an indication of the conclusion to the comprehensive health profile for the user,(vi) determining one or more longitudinal trends regarding one or more of the manually entered health-related data for the user, the automatically collected health-related data for the user, and the medical test results for the user, wherein the one or more longitudinal trends include a longitudinal trend of a weight of the user that indicates that the user gains weight during a particular season,(vii) adding an indication of the one or more longitudinal trends to the comprehensive health profile for the user, and(viii) determining, by the analytics engine, a seasonal diet and exercise recommendation for the user based on the longitudinal trend; and
upon a request made on behalf of the user, providing, by the server device, part of the comprehensive health profile, including a result of the goodness-of-fit tests or the seasonal diet and exercise recommendation, to the user.
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Abstract
A set of information including manually entered health-related data for a user, automatically collected health-related data for the user, and test results for the user may be received. In response to receiving the set of information, the manually entered health-related data for the user, the automatically collected health-related data for the user, and the test results for the user may be integrated into a comprehensive health profile for the user. Upon a request made on behalf of the user, at least part of the comprehensive health profile may be provided to the user.
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Citations
15 Claims
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1. A method comprising:
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receiving, by a server device, a set of information including pluralities of data points for each of manually entered health-related data for a user, automatically collected health-related data for the user, and medical test results for the user, wherein the server device receives the automatically collected health-related data periodically via a network from a wearable health-tracking device worn by the user; in response to receiving the set of information, integrating, by the server device, the manually entered health-related data for the user, the automatically collected health-related data for the user, and the medical test results for the user into a comprehensive health profile for the user, wherein integrating the manually entered health-related data for the user, the automatically collected health-related data for the user, and the medical test results for the user into the comprehensive health profile for the user comprises; (i) determining a health-related correlation between diet, medication intake, and reported mood of the user, wherein the health-related correlation indicates an extent to which respective data points related to the diet, medication intake, and reported mood of the user vary together, (ii) adding an indication of the health-related correlation to the comprehensive health profile for the user, (iii) performing, by an analytics engine, goodness-of-fit tests between (a) a series of blood sugar levels from the user measured at points in time after the user has eaten, and (b) curves representing each of a normal blood sugar response after eating, a pre-diabetic blood sugar response after eating, and a diabetic blood sugar response after eating, wherein the series of blood sugar levels from the user is part of the one or more of the manually entered health-related data for the user, the automatically collected health-related data for the user, and the medical test results for the user, (iv) based on the goodness-of-fit tests, concluding, by the analytics engine, that the series of blood sugar levels from the user indicates the normal blood sugar response after eating, the pre-diabetic blood sugar response after eating, or the diabetic blood sugar response after eating, (v) adding an indication of the conclusion to the comprehensive health profile for the user, (vi) determining one or more longitudinal trends regarding one or more of the manually entered health-related data for the user, the automatically collected health-related data for the user, and the medical test results for the user, wherein the one or more longitudinal trends include a longitudinal trend of a weight of the user that indicates that the user gains weight during a particular season, (vii) adding an indication of the one or more longitudinal trends to the comprehensive health profile for the user, and (viii) determining, by the analytics engine, a seasonal diet and exercise recommendation for the user based on the longitudinal trend; and upon a request made on behalf of the user, providing, by the server device, part of the comprehensive health profile, including a result of the goodness-of-fit tests or the seasonal diet and exercise recommendation, to the user. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. An article of manufacture including a non-transitory computer-readable medium, having stored thereon program instructions that, upon execution by a server device, cause the server device to perform operations comprising:
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receiving a set of information including pluralities of data points for each of manually entered health-related data for a user, automatically collected health-related data for the user, and medical test results for the user, wherein the server device receives the automatically collected health-related data periodically via a network from a wearable health-tracking device worn by the user; in response to receiving the set of information, integrating the manually entered health-related data for the user, the automatically collected health-related data for the user, and the medical test results for the user into a comprehensive health profile for the user, wherein integrating the manually entered health-related data for the user, the automatically collected health-related data for the user, and the medical test results for the user into the comprehensive health profile for the user comprises; (i) determining a health-related correlation between diet, medication intake, and reported mood of the user, wherein the health-related correlation indicates an extent to which respective data points related to the diet, medication intake, and reported mood of the user vary together, (ii) adding an indication of the health-related correlation to the comprehensive health profile for the user, (iii) performing, by an analytics engine, goodness-of-fit tests between (a) a series of blood sugar levels from the user measured at points in time after the user has eaten, and (b) curves representing each of a normal blood sugar response after eating, a pre-diabetic blood sugar response after eating, and a diabetic blood sugar response after eating, wherein the series of blood sugar levels from the user is part of the one or more of the manually entered health-related data for the user, the automatically collected health-related data for the user, and the medical test results for the user, (iv) based on the goodness-of-fit tests, concluding, by the analytics engine, that the series of blood sugar levels from the user indicates the normal blood sugar response after eating, the pre-diabetic blood sugar response after eating, or the diabetic blood sugar response after eating, (v) adding an indication of the conclusion to the comprehensive health profile for the user, (vi) determining one or more longitudinal trends regarding one or more of the manually entered health-related data for the user, the automatically collected health-related data for the user, and the medical test results for the user, wherein the one or more longitudinal trends include a longitudinal trend of a weight of the user that indicates that the user gains weight during a particular season, (vii) adding an indication of the one or more longitudinal trends to the comprehensive health profile for the user, and (viii) determining, by the analytics engine, a seasonal diet and exercise recommendation for the user based on the longitudinal trend; and upon a request made on behalf of the user, providing part of the comprehensive health profile, including a result of the goodness-of-fit tests or the seasonal diet and exercise recommendation, to the user. - View Dependent Claims (9, 10, 11)
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12. A server device comprising:
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at least one processor; data storage; and program instructions, stored in the data storage, that upon execution by the at least one processor cause the server device to perform operations including; receiving a set of information including pluralities of data points for each of manually entered health-related data for a user, automatically collected health-related data for the user, and medical test results for the user, wherein the server device receives the automatically collected health-related data periodically via a network from a wearable health-tracking device worn by the user; in response to receiving the set of information, integrating the manually entered health-related data for the user, the automatically collected health-related data for the user, and the medical test results for the user into a comprehensive health profile for the user, wherein integrating the manually entered health-related data for the user, the automatically collected health-related data for the user, and the medical test results for the user into the comprehensive health profile for the user comprises; (i) determining a health-related correlation between diet, medication intake, and reported mood of the user, wherein the health-related correlation indicates an extent to which respective data points related to the diet, medication intake, and reported mood of the user vary together, (ii) adding an indication of the health-related correlation to the comprehensive health profile for the user, (iii) performing, by an analytics engine, goodness-of-fit tests between (a) a series of blood sugar levels from the user measured at points in time after the user has eaten, and (b) curves representing each of a normal blood sugar response after eating, a pre-diabetic blood sugar response after eating, and a diabetic blood sugar response after eating, wherein the series of blood sugar levels from the user is part of the one or more of the manually entered health-related data for the user, the automatically collected health-related data for the user, and the medical test results for the user, (iv) based on the goodness-of-fit tests, concluding, by the analytics engine, that the series of blood sugar levels from the user indicates the normal blood sugar response after eating, the pre-diabetic blood sugar response after eating, or the diabetic blood sugar response after eating, (v) adding an indication of the conclusion to the comprehensive health profile for the user, (vi) determining one or more longitudinal trends regarding one or more of the manually entered health-related data for the user, the automatically collected health-related data for the user, and the medical test results for the user, wherein the one or more longitudinal trends include a longitudinal trend of a weight of the user that indicates that the user gains weight during a particular season, (vii) adding an indication of the one or more longitudinal trends to the comprehensive health profile for the user, and (viii) determining, by the analytics engine, a seasonal diet and exercise recommendation for the user based on the longitudinal trend; and upon a request made on behalf of the user, providing part of the comprehensive health profile, including a result of the goodness-of-fit tests or the seasonal diet and exercise recommendation, to the user. - View Dependent Claims (13, 14, 15)
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Specification