Application US20190244541

SYSTEMS AND METHODS FOR GENERATING PERSONALIZED NUTRITIONAL RECOMMENDATIONS
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US20190244541

1. A computer-implemented method for assisting with a user's nutritional needs, the method comprising: (16) (5)

obtaining, from a computing device, a plurality of physiological and food consumption inputs associated with the user;

obtaining, from a database, a food ontology comprising information on a plurality of different food items;

generating a plurality of constraints specific to the user based on (1) the plurality of physiological and food consumption inputs and (2) the food ontology, wherein the plurality of constraints comprises (i) health constraints, (ii) nutrient constraints and (iii) dietary norms;

applying the plurality of constraints to an optimization algorithm to generate a graphical visual object representative of a food space; and

determining and recommending one or more optimal diets for the user, based on selection of one or more points on the graphical visual object within the food space that satisfy the plurality of constraints.

2. The method of claim 1, wherein the computing device comprises a mobile device, a tablet, or a personal computer associated with the user. (1) (0)

4. The method of claim 1, wherein the plurality of physiological and food consumption inputs associated with the user comprises: (a) historical food consumption data, (b) eating habits, (c) culinary preferences, (d) health or physical goals, (e) a medical profile comprising physical and medical information of the user, or (f) an activity profile comprising an amount or type of physical activities that the user engages in. (2) (0)

5. The method of claim 1, wherein the food ontology comprises a hierarchical association of each food item to selected groups or categories of foods. (1) (0)

6. The method of claim 1, wherein the food ontology comprises an association of each food item to a set of meals or meal types. (0)

9. The method of claim 1, wherein the information on the plurality of different food items comprises nutritional information of each food item. (1) (0)

11. The method of claim 1, wherein the one or more optimal diets comprises a list of food items recommended to be consumed by the user over a defined time period. (1) (0)

16. The method of claim 1, wherein the optimization algorithm is configured to dynamically modify the one or more optimal diets depending on how closely the user is following the recommended diet(s). (0)

17. The method of claim 1, wherein the optimization algorithm is configured to dynamically modify the one or more optimal diets depending on how the user's feedback on the recommended diet(s), wherein the user's feedback is provided via the computing device. (0)

18. The method of claim 1, wherein the graphical visual object representative of the food space is configured to be displayed on the computing device of the user or other computing devices. (1) (0)

20. The method of claim 1, wherein the food space comprises an N+1 dimensional space for N number of food items. (0)

21. The method of claim 1, wherein the food space comprises a curved and/or elevation map representing the user's taste in different foods. (0)

22. The method of claim 1, wherein different points within the food space represent different diets or combinations of foods. (2) (0)

25. The method of claim 1, further comprising: (1) (1)

28. The method of claim 1, wherein the plurality of constraints comprise linear and/or nonlinear constraints. (0)

29. The method of claim 1, wherein said method is configured to assist a plurality of users with their nutritional needs, the method further comprising: (2) (2)

clustering the plurality of users to define a plurality of groups having different dietary preferences or needs; and

associating each user with a group that is closest to said user, to thereby generate a nutritional crowd sourcing platform.

30. The method of claim 29, wherein the nutritional crowd sourcing platform comprises trends, insights, and food recommendations that are provided to the users in the plurality of groups based on their different dietary preferences or needs. (0)

31. The method of claim 29, wherein the plurality of users are clustered into and associated with different groups using K-near neighbor (K-NN), collaborative filtering, a Bayesian network, or matrix factorization. (0)

32. The method of claim 1, wherein the optimization algorithm is configured to calculate a probability of the user's preference for a specific food item based on changes that the user makes to the one or more recommended optimal diets. (0)

33. A system for assisting a plurality of users with their nutritional needs, the system comprising: (0) (3)

a server in communication with a plurality of computing devices and a database; and

a memory storing instructions that, when executed by the server, causes the server to perform operations comprising:

obtaining, from each of the computing devices, a plurality of physiological and food consumption inputs associated with a user of the corresponding computing device; obtaining, from the database, a food ontology comprising information on a plurality of different food items;

generating, for each of the users, a plurality of constraints specific to the user based on (1) the plurality of physiological and food consumption inputs and (2) the food ontology, wherein the plurality of constraints comprises (i) health constraints, (ii) nutrient constraints and (iii) dietary norms;

applying the plurality of constraints to an optimization algorithm to generate a graphical visual object representative of a food space; and

determining and recommending one or more optimal diets for each of the users, based on selection of one or more points on the graphical visual object within the food space that satisfy the plurality of constraints.

34. A non-transitory computer-readable medium including instructions that, when executed by a server, cause the server to perform operations comprising: (0) (5)

obtaining, from each of a plurality of computing devices, a plurality of physiological and food consumption inputs associated with a user of the corresponding computing device;

obtaining, from the database, a food ontology comprising information on a plurality of different food items;

applying the plurality of constraints to an optimization algorithm to generate a graphical visual object representative of a food space; and

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Application US20190244541

SYSTEMS AND METHODS FOR GENERATING PERSONALIZED NUTRITIONAL RECOMMENDATIONS

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