A health and fitness management system is provided that has a health and fitness application operating, e.g., on a smart phone, that can wirelessly communicate with an activity module worn on the user which has an accelerometer. The application accepts food and weight inputs (e.g., from the smart ph
A health and fitness management system is provided that has a health and fitness application operating, e.g., on a smart phone, that can wirelessly communicate with an activity module worn on the user which has an accelerometer. The application accepts food and weight inputs (e.g., from the smart phone) and user activity units (e.g., from the activity unit) and develops a user intrinsic metabolism. The application includes fitness arc and health quotient graphical indicators that guide the user on health and fitness activities.
대표청구항▼
1. A non-transitory machine readable medium storing instructions that, when executed by a computing device, cause the computing device to perform a method for instantaneously and continuously assessing real time energy balance for fitness management, comprising: (a) collecting food intake informatio
1. A non-transitory machine readable medium storing instructions that, when executed by a computing device, cause the computing device to perform a method for instantaneously and continuously assessing real time energy balance for fitness management, comprising: (a) collecting food intake information for actual or expected food intake of a user over a specified period of time and contemporaneously converting the food intake information into food intake energy units for the specified period of time, wherein the food intake energy units are based on energy content of one food compared to another without relying on user-inputted caloric values;(b) collecting by a device activity information for actual or expected activity by the user over the specified period of time and contemporaneously converting the activity information into activity energy units for the user for the specified period of time;(c) instantaneously deriving, via a computing device, a calculated currently determined constant that reflects efficiency, which is a rate at which the user extracts energy from the food units that can be referenced against predicted and actual changes in weight, wherein the constant is a surrogate for intrinsic metabolic rate;(d) instantaneously calculating by an algorithm from the calculated currently determined constant in (c) a predicted energy balance for the user, by:(i) calculating a ratio of an amount of activity units expected divided by an amount of activity observed;(ii) calculating a ratio of an amount of food units expected divided by an amount of food units observed;(iii) weighting the ratio in (a) against the ratio in (b) according to goals of the user; and(iv) modifying the weighted ratio in (iii) by a rate at which the user performs the actual or expected activity;(e) instantaneously predicting a change in weight from the predicted energy balance;(f) determining and reporting a fitness level of the user in real time comprising a fitness arc and a health quotient, based on the efficiency of energy consumption so that user can modify or continue user's fitness behavior. 2. The non-transitory machine readable medium of claim 1, wherein collecting food intake information in (a) comprises inputting type and portion of food visually. 3. The non-transitory machine readable medium of claim 1, further comprising displaying the predicted energy balance graphically. 4. The non-transitory machine readable medium of claim 1, wherein in (d) the algorithm maintains an accurate prediction of weight change in (e) by adjusting to inaccuracies in food intake information, activity information or both. 5. The non-transitory machine readable medium of claim 1, wherein the calculated currently determined constant that reflects efficiency is recalculated, new values are assigned, or both, when the algorithm cannot make predictions of energy balance and change in weight accurately. 6. The non-transitory machine readable medium of claim 1, wherein the value of the food intake energy units and activity energy units are referenced against actual indicated weight change and the calculated currently determined constant that reflects efficiency and that serves as a surrogate for intrinsic metabolic rate of the user. 7. The non-transitory machine readable medium of claim 1, wherein the predicted energy balance comprises a relationship between: a. a first power equation in which power P is the rate at which energy can be transferred or consumed and that measures a rate of energy transfer; andb. a second power equation in which power P′ is the rate at which work can be performed, and that measures movement of a fixed mass over a specified distance per unit time. 8. The non-transitory machine readable medium of claim 7, wherein the rate of energy transfer is estimated from a rate at which weight is gained or lost. 9. The non-transitory machine readable medium of claim 7, wherein the amount of food units expected is the number of food energy units that, for a specified time of day and for actual/predicted activity levels the user can consume. 10. The non-transitory machine readable medium of claim 7, wherein the first and second power equations are given a relative weight and summed to produce a percentage change in observed versus predicted food energy units consumed and activity energy unit expended. 11. The non-transitory machine readable medium of claim 7, wherein the activity energy unit expected is based upon history of amount and type of activity performed by the user. 12. The non-transitory machine readable medium of claim 1, the method further comprising adjusting food allowance for the user throughout the specified time based on what activity is expected and what activity has actually occurred. 13. The non-transitory machine readable medium of claim 1, wherein the predicted energy balance between food intake energy units, activity energy units and the calculated currently determined constant that reflects efficiency and that serves as a surrogate for intrinsic metabolic rate is periodically updated. 14. The non-transitory machine readable medium of claim 1, wherein the calculated currently determined constant that reflects efficiency and that serves as a surrogate for intrinsic metabolic rate corrects variance between predicted energy consumption and observed energy consumption. 15. The non-transitory machine readable medium of claim 1, wherein value of a food energy unit or an activity energy unit is defined by how the user inputs data. 16. The non-transitory machine readable medium of claim 1, wherein the algorithm creates an ongoing user profile of intrinsic metabolism, activity, food choice and food amount that is unique to the user. 17. The non-transitory machine readable medium of claim 1, wherein the food intake information is a graphic input. 18. The non-transitory machine readable medium of claim 17, wherein the graphic input is an iconic food item. 19. The non-transitory machine readable medium of claim 1, wherein the collecting activity information for actual activity is achieved by wireless transmission by a motion sensor. 20. The non-transitory machine readable medium of claim 19, wherein the motion sensor is an accelerometer. 21. The non-transitory machine readable medium of claim 1, wherein the computing device is selected from the group consisting of a smart cell phone, a tablet device, a PDA, and a personal computer. 22. The non-transitory machine readable medium of claim 1, wherein the food intake information for actual or expected food intake of the user over a specified period of time is a first period of time, wherein the first period of time includes at least a part or parts of a first week, and wherein a further specified period of time is a second period of time,wherein the second period of time includes at least a part or parts of a second subsequent week. 23. A system for instantaneously and continuously assessing real time energy balance for fitness management comprising: a computing device configured to:(a) collect food intake information for actual or expected food intake of a user over a specified period of time and contemporaneously converting the food intake information into food intake units for the specified period of time, wherein the food intake energy units are based on energy content of one food compared to another without relying on user-inputted caloric values;(b) collect by a device activity information for actual or expected activity by the user over the specified period of time and contemporaneously converting the activity information into activity units for the user for the first period of time;(c) instantaneously derive, via a computing device, a calculated currently determined constant that reflects efficiency, which is a rate at which the user extracts energy from the food units that can be referenced against predicted and actual changes in weight, wherein the constant is a surrogate for intrinsic metabolic rate;(d) instantaneously calculate by an algorithm from the calculated currently determined constant in (c) a predicted energy balance for the user, by:(i) calculating a ratio of an amount of activity units expected divided by an amount of activity observed;(ii) calculating a ratio of an amount of food units expected divided by an amount of food units observed;(iii) weighting the ratio in (a) against the ratio in (b) according to goals of the user; and(iv) modifying the weighted ratio in (iii) by a rate at which the user performs the actual or expected activity;(e) instantaneously predict a change in weight from the predicted energy balance;(f) determine and report a fitness level of the user in real time comprising a fitness arc and a health quotient, based on the efficiency of energy consumption so that user can modify or continue user's fitness behavior. 24. The fitness management system of claim 23, wherein collecting food intact information in (a) comprises inputting type and portion of food visually. 25. The fitness management system of claim 23, further comprising displaying the predicted energy balance graphically. 26. The fitness management system of claim 23, wherein in (d) the algorithm maintains an accurate prediction of weight change in (e) by adjusting to inaccuracies in food intake information, activity information or both. 27. The fitness management system of claim 23, wherein the calculated currently determined constant that reflects efficiency is recalculated, new values are assigned, or both, when the algorithm cannot make predictions of energy balance and change in weight accurately. 28. The fitness management system of claim 23, wherein value of the food intake energy units and activity energy units are referenced against actual indicated weight change and the calculated currently determined constant that reflects efficiency and that serves as a surrogate for intrinsic metabolic rate of the user. 29. The fitness management system of claim 23, wherein the predicted energy balance comprises a relationship between: a. a first power equation in which power P is the rate at which energy can be transferred or consumed and that measures a rate of energy transfer; andb. a second power equation in which power P′ is the rate at which work can be performed, and that measures movement of a fixed mass over a specified distance per unit time. 30. The fitness management system of claim 23, wherein the rate of energy transfer is estimated from a rate at which weight is gained or lost. 31. The fitness management system of claim 23, wherein the amount of food units expected is the number of food energy units that, for a specified time of day and for actual/predicted activity levels the user can consume. 32. The fitness management system of claim 23, wherein the first and second power equations are given a relative weight and summed to produce a percentage change in observed versus predicted food energy units consumed and activity energy unit expended. 33. The fitness management system of claim 23, wherein the activity energy unit expected is based upon history of amount and type of activity performed by the user. 34. The fitness management system of claim 23, further comprising adjusting food allowance for the user throughout the specified time based on what activity is expected and what activity has actually occurred. 35. The fitness management system of claim 23, wherein the predicted energy balance between food intake energy units, activity energy units and the calculated currently determined constant that reflects efficiency and that serves as a surrogate for intrinsic metabolic rate is periodically updated. 36. The fitness management system of claim 23, wherein the calculated currently determined constant that reflects efficiency and that serves as a surrogate for intrinsic metabolic rate corrects variance between predicted energy consumption and observed energy consumption. 37. The fitness management system of claim 23, wherein value of a food energy unit or an activity energy unit is defined by how the user inputs data. 38. The fitness management system of claim 23, wherein the algorithm creates an ongoing user profile of intrinsic metabolism, activity, food choice and food amount that is unique to the user. 39. The fitness management system of claim 23, wherein the food intake information is a graphic input. 40. The fitness management system of claim 39, wherein the graphic input is an iconic food item. 41. The fitness management system of claim 23, wherein the collecting activity information for actual activity is achieved by wireless transmission by a motion sensor. 42. The fitness management system of claim 41, wherein the motion sensor is an accelerometer. 43. The fitness management system of claim 23, wherein the computing device is selected from the group consisting of a smart cell phone, a tablet device, a PDA, and a personal computer.
연구과제 타임라인
LOADING...
LOADING...
LOADING...
LOADING...
LOADING...
이 특허에 인용된 특허 (5)
Sagel, Paul Joseph, Body weight management system.
Brown,Michael Wayne; Lawrence,Kelvin Roderick; Paolini,Michael A., Program and system for managing fitness activity across diverse exercise machines utilizing a portable computer system.
Pacione, Christopher; Menke, Steve; Andre, David; Teller, Eric; Safier, Scott; Pelletier, Raymond; Handel, Mark; Farringdon, Jonathan; Hsiung, Eric; Vishnubhatla, Suresh; Hanlon, James; Stivoric, John M.; Spruce, Neal; Shassberger, Steve, System for monitoring and managing body weight and other physiological conditions including iterative and personalized planning, intervention and reporting capability.
Hyde, Roderick A.; Ishikawa, Muriel Y.; Kare, Jordin T.; Leuthardt, Eric C.; Levien, Royce A.; Lord, Richard T.; Lord, Robert W.; Malamud, Mark A.; Tegreene, Clarence T.; Whitmer, Charles; Wood, Jr., Lowell L.; Wood, Victoria Y. H.; Myhrvold, Nathan P.; Sweeney, Elizabeth A., Quantified-self machines and circuits reflexively related to kiosk systems and associated food-and-nutrition machines and circuits.
※ AI-Helper는 부적절한 답변을 할 수 있습니다.