Mobile computing weight, diet, nutrition, and exercise tracking system with enhanced feedback and data acquisition functionality

• US 8,690,578 B1
• Filed: 01/03/2013
• Issued: 04/08/2014
• Est. Priority Date: 01/03/2013
• Status: Expired due to Fees

• Current Assignee: SmarTEN LLC
• Original Assignee: Mark E. Nusbaum, Vincent Pera Jr
• Inventors: Nusbaum, Mark E., Rhoads, Jan E., Pera, Vincent Jr., Nusbaum, Jennifer L.
• Primary Examiner(s): Thomson, Bill
• Assistant Examiner(s): Downey, John R
• Application Number:
  US13/733,588
• Time in Patent Office: 460 Days
• Field of Search: 434/127, 128/921, 128/905, 705/2, 705/3, 707/802
• US Class Current: 434/127
• CPC Class Codes: A63B 2024/0071 Distinction between different activities, movements, or kind of sports performed
• CPC Class Codes: A63B 2220/12 Absolute positions, e.g. by using GPS
• CPC Class Codes: A63B 2220/17 Counting, e.g. counting periodical movements, revolutions or cycles, or including further data processing to determine distances or speed
• CPC Class Codes: A63B 2220/20 Distances or displacements
• CPC Class Codes: A63B 2220/807 Photo cameras
• CPC Class Codes: A63B 2225/50 Wireless data transmission, e.g. by radio transmitters or telemetry
• CPC Class Codes: A63B 2230/04 heartbeat characteristics, e.g. ECG, blood pressure modulations
• CPC Class Codes: A63B 2230/75 calorie expenditure
• CPC Class Codes: A63B 24/0062 Monitoring athletic performances, e.g. for determining the work of a user on an exercise apparatus, the completed jogging or cycling distance
• CPC Class Codes: G09B 19/00 Teaching not covered by other main groups of this subclass teaching or practice apparatus for gun-aiming or gun-laying F41G3/26
• CPC Class Codes: G09B 19/0092 Nutrition
• CPC Class Codes: G09B 5/125 the stations being mobile
• CPC Class Codes: G16H 20/30 relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• CPC Class Codes: G16H 20/60 relating to nutrition control, e.g. diets
• CPC Class Codes: G16H 40/67 for remote operation
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass

Abstract

An illustrative mobile computing device executing weight, nutrition, health, behavior and exercise application software serves as a simulated combination personal trainer and dietician/nutritionist for the user using comprehensive databases storing personalized health, nutrition and exercise information. A mobile computing device, such as a smartphone, executing such software monitors, tracks and/or adjusts caloric intake, energy expenditure taking into account nutritional information and behavioral factors. The mobile computing device receives food consumption, exercise-related, behavior and other input using speech input and the device'"'"'s GPS subsystem to ease data entry burden on users and to promote continued long-term usage. The system rewards user goal achievement in an automatic, seamless manner, through, for example, downloading music, books, or other media. In illustrative implementations, the system assists users to make healthy food and exercise choices by using a comprehensive color code system to identify good choices, bad choices and those in between.

Claims

1. A mobile weight and exercise management computing system comprising:

at least one input device for inputting a food identifying signal indicating a food in response to a user identifying a food and for inputting an exercise identifying signal indicating an exercise in response to a user identifying an exercise;

a GPS receiver;

a storage system for storing health-related information about said user including data identifying the user'"'"'s weight and a health-related goal including a weight loss or weight gain goal;

a processing subsystem operatively coupled to said at least one input device, said GPS receiver, and to said storage system, and including;

a food monitoring subsystem operable to receive said food identifying signal indicating a food, said food monitoring subsystem being operative to generate data indicative of the calories expected to be consumed by said user upon eating said food based upon said food identifying signal;

an exercise monitoring subsystem operable to receive said exercise identifying signal indicating an exercise to be performed by said user, said exercise monitoring subsystem being operable to acquire location-related data from said GPS receiver, and being operable to access said storage system to determine the calories expected to be burned by the user upon performing said exercise based in part upon said user'"'"'s weight;

said storage system including;

a first set of memory locations for storing data identifying a plurality of foods expected to be consumed by said user, wherein each of said foods is associated with a unique food identifying signal, and for storing a plurality of descriptors associated with at least one of said foods, wherein said plurality of descriptors includes the quantity of each food, and a flavoring add-on associated with at least one of said foods, said first set of memory locations further operable to store data relating to the calories expected to be consumed by said user for each food, and

a second set of memory locations for storing data identifying a plurality of exercises expected to be performed by said user and for storing a plurality of descriptors associated with at least one of said exercises, wherein said plurality of descriptors includes the duration of each exercise, said second set of memory locations further storing data related to the user'"'"'s location during at least one exercise based upon data received from said GPS receiver, said second set of memory locations further operable to store data relating to the calories expected to be burned by said user during each exercise;

said processing subsystem being configured to request the user to specify said flavoring add-on associated with at least one of said foods;

said processing subsystem further being configured to request the user to specify said plurality of exercises together with at least one descriptor associated with each of said exercises;

said processing subsystem being further configured to use said location data from said GPS receiver to generate data indicative of distance traveled during at least one exercise;

said processing subsystem being further configured to access said storage system and to determine if said health-related goal including a weight loss goal has been met by said user based upon data from said food monitoring subsystem identifying calories consumed by said user and data from said exercise monitoring subsystem identifying calories burned by said user; and

an output generation subsystem, operatively coupled to said processing subsystem, for providing feedback to the user relating to progress towards achievement of said health-related goal including said weight loss goal.

2. A mobile weight and exercise management computing system according to claim 1, wherein said input device is an audio input device for receiving a speech signal from a user indicative of a food, and wherein said storage system including memory locations storing a set of instructions for performing speech recognition and analysis.

3. A mobile weight and exercise management computing system according to claim 1, further including an image capturing device for capturing one or more of a digital image of a food or exercise-related related target image.

4. A mobile weight and exercise management computing system according to claim 1, wherein said processing subsystem is operable to use data from said GPS receiver to determine the location of said mobile weight and exercise management computing system over time, said exercise monitoring subsystem being operatively coupled to said GPS receiver to monitor an exercise by determining the user'"'"'s distance traveled over time using said GPS receiver, and to determine the calories burned by said user at least in part based upon the user'"'"'s distance traveled over time.

5. A mobile weight and exercise management computing system according to claim 1, wherein said processing subsystem is operable to store in said storage system a profile of said user including data indicative of the size of a user'"'"'s body frame, wherein said processing subsystem is configured to categorize the user'"'"'s obesity level based upon the user'"'"'s weight and body frame.

6. A mobile weight and exercise management computing system according to claim 1, wherein said processing subsystem is operable to store in said storage system a profile of said user including data indicative of a user'"'"'s wrist size, wherein said processing subsystem is configured to categorize the user'"'"'s obesity level based upon the user'"'"'s weight and wrist size.

7. A mobile weight and exercise management computing system according to claim 1, wherein said processing subsystem is operable to store in said storage system a profile of said user including data indicative of one of a user'"'"'s handicaps, ailments, or injuries.

8. A mobile weight and exercise management computing system according to claim 1, wherein said processing subsystem is operable to store in said storage system a profile of said user including data indicative of food or exercise restrictions that are applicable to the user.

9. A mobile weight and exercise management computing system according to claim 1, wherein said processing subsystem stores in said storage system, the identity of a first food and a second food input by said user, an associated health-related rating of said first food and said second food, and an add-on, quantity, and nutrients descriptor for at least one of said first food and said second food.

10. A mobile weight and exercise management computing system according to claim 1, wherein said second set of memory locations stores for at least one exercise, the number of repetitions expected to be performed.

11. A mobile weight and exercise management computing system according to claim 9, wherein said associated health-related rating for said first food and said second food includes a color code permitting the identification of said first food and said second food in categories of worst, bad, average, good, better than good, and top source, further including a display for displaying food related feedback to the user including a color code for said first food and said second food.

12. A mobile weight and exercise management computing system according to claim 1, wherein said processing subsystem stores in said storage system, the identity of a first and a second exercise input by said user and an associated health-related rating for said first exercise and said second exercise, wherein said associated health-related rating for said first exercise and said second exercise includes a color code, further including a display for displaying exercise-related feedback to the user including a color code for said first exercise and said second exercise.

13. A mobile weight and exercise management computing system according to claim 1, wherein for each food and exercise being monitored an associated health-related color code is displayed to the user.

14. A mobile weight and exercise management system according to claim 1, wherein said storage system includes memory locations for storing a user profile containing said user health-related data, wherein a first health-related color code is associated with a first food being tracked and a second health related color code is associated with a first exercise being tracked, such that said processing subsystem is operable to dynamically adjust said first color code and said second color code based upon the contents of said user profile and to display said first color code and said second color code to said user.

15. A mobile weight and exercise management computing system according to claim 1, wherein said processing subsystem further includes a behavioral subsystem for requesting input from a user relating to adherence to the user'"'"'s diet, and generating dietary recommendations in response to the user'"'"'s input.

16. A mobile weight and exercise management computing system according to claim 1, wherein said processing subsystem further includes a behavioral subsystem for requesting input from a user relating to adherence to the user'"'"'s exercise regimen, and generating exercise recommendations in response to the user'"'"'s input.

17. A mobile weight and exercise management computing system according to claim 1, wherein said processing subsystem further includes a reward generating subsystem for automatically selecting a reward to be downloaded to said mobile computing device if said weight-related goal has been met by said user.

18. A mobile weight and exercise management computing system comprising:

at least one input device including an audio input device for receiving speech input from a user identifying a food and for generating a speech food input-related signal therefrom and for receiving speech input from a user identifying an exercise and for generating a speech exercise input-related signal therefrom;

a GPS receiver;

a storage system for storing health-related information about said user including data identifying the user'"'"'s weight and a health-related goal including a weight loss or gain goal;

a processing subsystem operatively coupled to said at least one input device, said GPS receiver and said storage system and including;

a food monitoring subsystem operable to receive said speech food input-related signal and to generate a digital food identifying signal indicating said food identified by said user, said food monitoring subsystem being further operative to generate data indicative of the calories expected to be consumed by said user upon eating said food based upon said food identifying signal;

said processing subsystem being further operative to in real time associate a first color code with said food identified if said food identified is determined to be one of a small number of top foods having a superior nutrient-related rating and to associate a second color code if said food identified has a nutrient-related rating higher than other foods with a good nutrient-related rating but lower than the superior nutrient-related rating of said top foods;

an exercise monitoring subsystem for acquiring exercise data using signals received from at least one of said GPS receiver or said at least one input device, said exercise monitoring system being operable to determine the calories expected to be burned by said user upon performing said exercise based in part upon said user'"'"'s weight;

said storage system including;

a first set of memory locations for storing data identifying a plurality of foods expected to be consumed by said user, wherein each of said foods is associated with a unique food identifying signal, and for storing a plurality of descriptors associated with at least one of said foods, wherein said plurality of descriptors includes the quantity of each food, and a flavoring add-on associated with at least one of said foods, said first set of memory locations further operable to store data relating to the calories expected to be consumed by said user for each food, and

a second set of memory locations for storing data identifying a plurality of exercises expected to be performed by said user and for storing a plurality of descriptors associated with at least one of said exercises, wherein said plurality of descriptors includes the duration of each exercise, said second set of memory locations further storing data indicative of distance traveled during at least one exercise based upon data received from said GPS receiver, said second set of memory locations further operable to store data relating to the calories expected to be burned by said user during each exercise;

said processing subsystem being configured to request the user to specify said add-on associated with at least one of said foods;

said processing subsystem further being configured to request the user to specify said plurality of exercises together with at least one descriptor associated with each of said exercises;

said processing subsystem being configured to access said storage system to determine the color code to be associated with said food expected to be consumed by said user in light of said health-related information about said user and a nutrient-related rating of said food, and to determine if said health-related goal has been met by said user based upon data from said food monitoring subsystem and data from said exercise monitoring subsystem; and

an output generation subsystem, operatively coupled to said processing subsystem, for providing real time feedback to the user relating to progress towards achievement of said health-related goal, and for providing, color code rating information associated in real time with respect to food input, to the user indicative of a health-related rating associated with said food expected to be consumed by said user.

19. A mobile weight and exercise management computing system according to claim 18, wherein said storage system includes memory locations for storing a set of instructions for performing speech recognition and analysis.

20. A mobile weight and exercise management computing system according to claim 18, further including an image capturing device for capturing one or more of a digital image of a food or exercise-related related target image.

21. A mobile weight and exercise management computing system according to claim 18, wherein said processing subsystem is operable to use data from said GPS receiver to determine the location of said mobile weight and exercise management computing system over time, said exercise monitoring subsystem being operatively coupled to said GPS receiver to monitor an exercise performed by said user by determining the user'"'"'s distance traveled over time using said GPS receiver, and to determine the calories burned by said user at least in part based upon the user'"'"'s distance traveled over time.

22. A mobile weight and exercise management computing system according to claim 18, wherein said processing subsystem is operable to store in said storage system, a profile of said user including data indicative of the size of a user'"'"'s body frame, wherein said processing system is configured to categorize the user'"'"'s obesity level based upon the user'"'"'s weight and body frame.

23. A mobile weight and exercise management computing system according to claim 18, wherein said processing subsystem is operable to store in said storage system, a profile of said user including data indicative of a user'"'"'s wrist size, wherein said processing system is configured to categorize the user'"'"'s obesity level based upon the user'"'"'s weight and wrist size.

24. A mobile weight and exercise management computing system according to claim 18, wherein said processing subsystem is operable to store in said storage system, a profile of said user including data indicative of one of a user'"'"'s handicaps, ailments, or injuries.

25. A mobile weight and exercise management computing system according to claim 18, wherein said processing subsystem is operable to store in said storage system, a profile of said user including data indicative of food or exercise restrictions that are applicable to the user.

26. A mobile weight and exercise management computing system according to claim 18, wherein said processing subsystem stores in said storage system, the identity of a first food and a second food input by said user, an associated health-related color code rating assigned to said first food and said second food, and an add-on, quantity, and nutrients descriptor for at least one of said first food and said second food, wherein said color code ratings are assigned at least in part based upon health-related information about said user.

27. A mobile weight and exercise management computing system according to claim 18, wherein said processing subsystem stores in said storage system, the identity of a first and a second exercise input by said user and an associated health-related color code rating assigned to said first exercise and said second exercise, wherein said color code ratings are assigned at least in part based upon health-related information about said user, and wherein said second set of memory locations stores for at least one exercise, the number of repetitions expected to be performed.

28. A mobile weight and exercise management system according to claim 18, wherein said storage system includes memory locations for storing a user profile containing said user health-related data, wherein a first health-related color code is associated with a first food expected to be consumed by said user, and a second health related color code is associated with a first exercise expected to be performed by said user, such that said processing subsystem is operable to dynamically adjust said first color code and said second color code based upon the contents of said user profile and to display said first color code and said second color code to said user.

29. A mobile weight and exercise management computing system according to claim 18, wherein said processing subsystem further includes a behavioral subsystem for requesting input from a user relating to adherence to the user'"'"'s diet, and generating recommendations in response to the user'"'"'s input.

30. A mobile weight and exercise management computing system according to claim 18, wherein said processing subsystem further includes a behavioral subsystem for requesting input from a user relating to adherence to the user'"'"'s exercise regimen, and generating recommendations in response to the user'"'"'s input.

31. A mobile weight and exercise management computing system according to claim 18, wherein said processing subsystem further includes a reward generating subsystem for automatically selecting a reward to be downloaded to said mobile computing system if said health-related goal has been met by said user.

32. A mobile weight and exercise management computing system according to claim 18, wherein said processing subsystem is configured to identify an alternative food related to said food input by said user, that has a higher health-related rating as indicated by a different color code than the food input by said user so as to recommend a healthier alternative food to the user.

33. A mobile weight and exercise management computing system according to claim 18, wherein said storage system includes storage locations for storing sets of related foods said processing subsystem being operable to access at least one of said sets of related foods to provide alternative foods to replace a less healthy food selected by said user.

34. For use in a mobile weight and exercise management computing system having at least one input device including an audio input device, a storage system, a GPS receiver, a processing subsystem, operatively coupled to said at least one input device, said GPS receiver and said storage system, including a food monitoring subsystem and an exercise monitoring subsystem, and an output generating subsystem, operatively coupled to said processing subsystem, a method of operating said mobile weight and exercise management computing system comprising:

storing in said storage system health-related information about said user, including the user'"'"'s weight and a health-related goal including a weight loss or gain goal;

receiving at least speech input via said audio input device from said user identifying a plurality of foods including a first food;

processing said speech input to generate a first food identifying signal indicative of a first food identified by said user;

determining in real time by said processing subsystem a first color code to be associated with said first food expected to be consumed by said user if said first food identified is determined to be one of a small number of top foods having a superior nutrient-related rating;

determining in real time by said processing subsystem a second color code to be associated with said first food expected to be consumed by said user if said first food identified has a nutrient-related rating higher than other foods with a good nutrient-related rating but lower than the nutrient-related rating of said top foods;

requesting the user to specify a flavoring add-on to be consumed with at least one of said plurality of foods;

storing data identifying said plurality of foods expected to be consumed by said user based upon corresponding input food identifying signals, and a plurality of descriptors associated with at least one of said foods, wherein said plurality of descriptors includes the quantity associated with each of said foods and a flavoring add-on associated with at least one of said foods;

generating by said food monitoring subsystem data indicative of the calories expected to be consumed by said user upon eating said first food based upon said first food identifying signal and its plurality of descriptors;

acquiring exercise data for a first exercise performed by said user via at least one of said at least one input device or said GPS receiver,

storing data identifying a plurality of exercises expected to be performed by said user, storing data relating to the calories expected to be burned during each exercise, and storing a plurality of descriptors associated with each exercise, wherein said plurality of descriptors includes the duration of said exercise;

generating and storing data indicative of distance traveled during said at least one exercise using said data received from said GPS receiver;

determining by said exercise monitoring subsystem the calories expected to be burned by said user based in part upon the stored exercise data and based in part upon said user'"'"'s weight;

accessing said health-related information about said user from said storage system;

determining if said health-related goal has been met by said user based upon data from said food monitoring subsystem and data from said exercise monitoring subsystem; and

providing real-time feedback to the user relating to progress towards achievement of said health-related goal, and providing color code information associated in real time with respect to food input, to the user based upon said health-related information about the user and indicative of a health-related rating associated with said first food expected to be consumed by said user.

35. A method according to claim 34, further including capturing one or more of a digital image of a food or exercise-related related target image.

36. A method according to claim 34, wherein said step of acquiring exercise data for an exercise performed by a user includes determining, using data received from said GPS receiver, the location of said mobile computing system over time;

and further including determining the user'"'"'s distance traveled over time and determining the calories burned by said user, at least in part based upon the user'"'"'s distance traveled over time.

37. A method according to claim 34, further including storing in said storage system, a profile of said user including data indicative of the size of a user'"'"'s body frame, and categorizing by said processing subsystem the user'"'"'s obesity level based upon the user'"'"'s weight and body frame.

38. A method according to claim 34, further including storing in said storage system, a profile of said user including data indicative of a user'"'"'s wrist size, and categorizing by said processing subsystem the user'"'"'s obesity level based upon the user'"'"'s weight and wrist size.

39. A method according to claim 34, further including storing in said storage system, a profile of said user including data indicative of one of a user'"'"'s handicaps, ailments, or injuries.

40. A method according to claim 34, further including storing in said storage system, a profile of said user including data indicative of food or exercise restrictions that are applicable to the user.

41. A method according to claim 34, further including storing in said storage system, the identity of said first food and a second food input by said user, assigning a health-related color code rating to said first food and said second food, and add-on, quantity and nutrients descriptors to at least one of said first food or said second food, such that the color code ratings are assigned at least in part based upon said health-related information about said user.

42. A method according to claim 34, further including storing in said storage system, the identity of a first and a second exercise input by said user and an associated health-related color code rating for said first and second exercises, such that the first exercise and said second exercise color code ratings are assigned at least in part based upon said health-related information about said user, and storing for at least one exercise, the number of repetitions expected to be performed.

43. A method according to claim 34, further including for each identified food and exercise assigning an associated health-related color code;

and displaying assigned food and exercise color codes to the user.

44. A method according to claim 34, further including storing in said storage system, a user profile for storing user health-related data, wherein a first health-related color code is associated with a first food being tracked and a second health-related color code is associated with a first exercise being tracked, wherein said processing subsystem is operable to dynamically adjust at least one of said first or said second health related color codes based upon the contents of said user profile and to display said first and said second health-related color codes to said user.

45. A method according to claim 34, further including generating at least one question about the user'"'"'s diet, receiving input in response to said at least one question from a user relating to the user'"'"'s diet, and generating recommendations in response to the user'"'"'s input.

46. A method according to claim 34, further including generating at least one question about the user'"'"'s exercise regimen, receiving input from a user relating to the user'"'"'s exercise regimen, and generating recommendations in response to the user'"'"'s input.

47. A method according the claim 34, further including automatically downloading to said mobile computing device, a reward for said user in response to determining that said health-related goal has been met by said user.

48. A method according the claim 34, further including the step of identifying by the processing subsystem, a second food related to said first food having a health-related rating as indicated by a different color code than the first food that is indicative of a healthier food than the first food and providing to the user the identity of the second food as a recommended alternative to the first food.

49. A method according to claim 34, further including storing in said storage system a set of related foods specifying related-foods for a user to consume that differ in health rating, accessing by said processing subsystem at least one of said sets of related foods to provide alternative foods to replace a less healthy selection.

50. A mobile weight and exercise management computing system comprising:

at least one input device including an audio input device for receiving speech input from a user identifying a first food expected to be consumed by said user and for generating a speech food input-related signal and for receiving speech input from a user identifying an exercise expected to be performed by said user and for generating a speech exercise input-related signal;

a storage system including storage locations for storing health-related information about said user including data identifying the user'"'"'s weight and a health-related goal including a weight loss or gain goal, said storage system further including storage locations for storing data indicative of various foods including a plurality of nutrients contained in each of said foods including said first food;

a processing subsystem, operatively coupled to said at least one input device and said storage system, including;

a food monitoring subsystem operable to process said speech food input-related signal and to generate a digital food identifying signal indicative of said first food identified by said user, said processing subsystem being operable to access from said storage system, the plurality of nutrients contained in said first food, said food monitoring subsystem being further operative to generate data indicative of the calories expected to be consumed by said user upon eating said first food based upon said food identifying signal;

an exercise monitoring subsystem operable to process said speech exercise input-related signal for acquiring data indicative of at least one of a plurality of exercises to be performed by said user, said exercise monitoring subsystem being operable to determine the calories expected to be burned by said user upon performing any one of said plurality of exercises based in part upon said user'"'"'s weight;

said processing subsystem being further operative in real time to associate a first color code with said first food identified if said first food is determined to be one of the top food sources of at least one nutrient contained in said first food identified and to associate a second color code if said first food identified is determined to be a good source of said at least one nutrient but not as good a source as said top food sources;

said processing subsystem being further operative in real time to associate one of a plurality of color codes with each of said plurality of exercises, the assigned color codes being differentiated according to the calories expected to be burned during each of said plurality of exercises;

said storage system including;

a first set of memory locations for storing data identifying a plurality of foods expected to be consumed by said user, wherein each of said foods is associated with a food identifying signal, and for storing a plurality of descriptors associated with each of said foods, wherein said plurality of descriptors includes the quantity of each food and a flavoring add-on associated with at least one of said foods, said first set of memory locations further operable to store data related to the calories expected to be consumed by the user for each food, and

a second set of memory locations for storing data identifying a plurality of exercises expected to be performed by said user and for storing a plurality of descriptors associated with at least one of said exercises, wherein said plurality of descriptors includes the duration of said exercise, said second set of memory locations for storing data relating to the calories expected to be burned by said user during each exercise;

said processing subsystem being configured to request the user to specify said add-on associated with at least one of said foods;

said processing subsystem further being configured to request the user to specify at least one of said plurality of exercises together with at least one descriptor associated with each exercise;

said processing subsystem being configured to access said storage system and said health-related information about said user to determine if said health-related goal has been met by said user based upon data from said food monitoring subsystem and data from said exercise monitoring subsystem; and

an output generation subsystem, operatively coupled to said processing subsystem, for providing real time feedback to the user relating to progress towards achievement of said health-related goal, and for identifying to the user nutrient-related information associated with said first food, and for providing color code feedback to said user associated in real time, with respect to food and exercise input, with said first food expected to be consumed by said user and said at least one exercise expected to be performed by said user.

51. A mobile weight and exercise management computing system according to claim 50, said processing subsystem being operable to generate a health-related color code rating of at least one of said plurality of nutrients contained in said first food permitting the identification of said first food as a source of said at least one nutrient in categories of worst, bad, average, good, better than good, and top source.

52. A mobile weight and exercise management computing system according to claim 50, said processing subsystem being operative to associate a color code with said identified first food, said color code being indicative of a health-related rating for said identified first food that distinguishes between identifying said first food as being one of the worst sources of a nutrient and being a bad source of the nutrient.

53. A mobile weight and exercise management computing system according to claim 50, wherein said nutrient-related information regarding said first food includes the amount of calories and nutrients selected from the group consisting of cholesterol, sugars, sodium, carbohydrates, protein, vitamin and fat-related information, and wherein color codes are assigned for cholesterol based upon the amount of HDL and LDL cholesterol.

54. A mobile weight and exercise management computing system according to claim 50, wherein said processing subsystem is operable to access nutrient information in response to a user requesting an identification of the nutrients in a food.

55. A mobile weight and exercise management computing system according to claim 50, wherein said storage system includes storage locations for storing data relating to a user'"'"'s favorite meals.

56. A mobile weight and exercise management computing system according to claim 50, further including a GPS receiver, said processing subsystem being operable to use data from said GPS receiver to determine the location of said mobile weight and exercise management computing system over time, said exercise monitoring subsystem being operable to monitor an exercise performed by said user by determining the user'"'"'s distance traveled over time using data from said GPS receiver, and to determine the calories burned by said user at least in part based upon the user'"'"'s distance traveled over time.

57. A mobile weight and exercise management computing system according to claim 50, wherein said processing subsystem is operable to store in said storage system, a profile of said user including data indicative of the size of a user'"'"'s body frame, wherein said processing subsystem is configured to categorize the user'"'"'s obesity level based upon the user'"'"'s weight and body frame.

58. A mobile weight and exercise management computing system according to claim 50, wherein said processing subsystem is operable to store in said storage system, a profile of said user including data indicative of a user'"'"'s wrist size, wherein said processing subsystem is configured to categorize the user'"'"'s obesity level based upon the user'"'"'s weight and wrist size.

59. A mobile weight and exercise management computing system according to claim 50, wherein said processing subsystem is operable to store in said storage system, a profile of said user including data indicative of one of a user'"'"'s handicaps, ailments, or injuries.

60. A mobile weight and exercise management computing system according to claim 50, wherein said processing subsystem is operable to store in said storage system, a profile of said user including data indicative of food or exercise restrictions that are applicable to the user.

61. A mobile weight and exercise management computing system according to claim 50, wherein said processing subsystem further includes a behavioral subsystem for generating at least one question about the user'"'"'s diet, receiving input from a user relating to the user'"'"'s diet in response to said at least one question relating to a user'"'"'s diet, and generating recommendations in response to the user'"'"'s input.

62. A mobile weight and exercise management computing system according to claim 50, wherein said processing subsystem further includes a behavioral subsystem for generating at least one question about the user'"'"'s exercise regimen, receiving input from a user in response to said at least one question relating to a user'"'"'s exercise regimen, and generating recommendations in response to the user'"'"'s input.

63. A mobile weight and exercise management computing system according to claim 50, wherein said processing subsystem further includes a reward generating subsystem for automatically selecting a reward to be downloaded to said mobile computing system if said health-related goal has been met by said user.

64. A mobile weight and exercise management computing system according to claim 50, wherein said processing subsystem is configured to identify a further food related to a food input by said user having a health-related rating as indicated by a color code that differs from the color code of the food input by said user and that is indicative of a food providing healthier nutrients than the food input by said user, and providing to the user the identity of the further food as a recommended alternative to the food input by the user.