Personalized Vitamin Supplement

• US 20170148348A1
• Filed: 11/23/2015
• Published: 05/25/2017
• Est. Priority Date: 11/23/2015
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Hardee, Christopher James, Joroff, Steve, Schneider, Scott Edward, Nesbitt, Pamela Ann
• Granted Patent: US 10,332,418 B2
• Time in Patent Office: Days
• CPC Class Codes: A61B 2560/0242 adapted to measure environmental factors, e.g. temperature, pollution
• CPC Class Codes: A61B 5/486 Bio-feedback A61B5/375 takes precedence
• CPC Class Codes: A61B 5/4866 Evaluating metabolism A61B5/083 takes precedence
• CPC Class Codes: G01N 33/0047 Organic compounds
• CPC Class Codes: G01N 33/20 Metals
• CPC Class Codes: G09B 19/0092 Nutrition

Abstract

An embodiment of the invention provides a method of collecting data to provide a personalized nutrition recommendation to a user, including receiving input from a sensor and/or an interface of a wearable electronic device of the user. The input includes physiological factors and/or environmental factors measured by the wearable electronic device, the environmental factors including sun exposure and air quality. A processor connected to the sensor and/or interface predicts nutritional deficiencies based on the input. The processor generates a personalized supplement recommendation for the user based on the nutritional deficiencies. The personalized supplement recommendation is displayed to the user on a display connected to the processor.

Claims

1. A method, comprising:

receiving input from at least one of a sensor and an interface of a wearable electronic device of a user, the input including physiological factors and environmental factors measured by the wearable electronic device;

predicting at least one nutritional deficiency with a processor, the at least one nutritional deficiency being predicted based on the input; and

generating a personalized supplement recommendation for the user, the personalized supplement recommendation being generated with the processor based on the at least one nutritional deficiency.

2. The method according to claim 1, wherein the environmental factors include at least one of sun exposure and air quality.

3. The method according to claim 1, further comprising measuring an amount of time that the wearable electronic device is exposed to a light threshold level.

4. The method according to claim 1, further comprising at least one of:

measuring an amount of airborne toxins that the wearable electronic device is exposed to in the environment; and

measuring an amount of particulate matter that the wearable electronic device is exposed to in the environment.

5. The method according to claim 1, wherein the physiological factors include at least one of blood pressure, hydration level, sweat salt content, sweat amount, caloric consumption, calorie expenditure, planned exercise, human waste amount, human waste type, amount of sleep, sleep quality, a time that the user went to sleep, a time that the user woke up, an amount of sleep, and an amount of being awake.

6. The method according to claim 1, further comprising generating a meal recipe for the user, the meal recipe including a list of ingredients and instructions for preparing a meal, the meal recipe being generated with the processor based on the at least one nutritional deficiency.

7. The method according to 6, further comprising generating a dietary plan for the user, the dietary plan including a list of meal recipes for at least one week, the dietary plan being generated with the processor based on the at least one nutritional deficiency.

8. The method according to claim 1, further comprising generating a food additive recommendation for the user, the food additive including a list of ingredients and instructions for preparing an additive to be added to food, the food additive recommendation being generated with the processor based on the at least one nutritional deficiency.

9. The method according to claim 1, further comprising sending the personalized supplement recommendation to a 3D food printer.

10. The method according to claim 1, further comprising generating a personalized supplement recommendation for an additional user, the additional user being positioned less than a threshold distance from the wearable electronic device when the wearable electronic device received the input, the personalized supplement recommendation being generated with the processor based on the at least one nutritional deficiency.

11. A method of collecting data to provide a personalized nutrition recommendation to a user, said method comprising:

receiving input from a sensor and an interface of a wearable electronic device of the user, the input including physiological factors and environmental factors measured by the wearable electronic device, the environmental factors including sun exposure and air quality;

predicting nutritional deficiencies with a processor, the nutritional deficiencies being predicted based on the input;

generating a personalized supplement recommendation for the user, the personalized supplement recommendation being generated with the processor based on the nutritional deficiencies; and

displaying the personalized supplement recommendation to the user on a display connected to the processor.

12. The method according to claim 11, further comprising measuring an amount of time that the wearable electronic device is exposed to a light threshold level.

13. The method according to claim 11, further comprising:

measuring an amount of airborne toxins that the wearable electronic device is exposed to in a first sample period; and

measuring an amount of particulate matter that the wearable electronic device is exposed to in a second sample period.

14. The method according to claim 11, wherein the physiological factors include at least one of blood pressure, hydration level, sweat salt content, sweat volume, caloric consumption, caloric expenditure, planned exercise, human waste amount, human waste type, amount of sleep, sleep quality, time of sleep, and time of wake.

15. The method according to claim 11, further comprising generating a meal recipe for the user, the meal recipe including a list of ingredients and instructions for preparing a meal, the meal recipe being generated with the processor based on the nutritional deficiencies.

16. The method according to 15, further comprising generating a dietary plan for the user, the dietary plan including a list of meal recipes for at least one week, the dietary plan being generated with the processor based on the nutritional deficiencies.

17. The method according to claim 11, further comprising generating a food additive for the user, the food additive recommendation including a list of ingredients and instructions for preparing an additive to be added to food, the food additive recommendation being generated with the processor based on the nutritional deficiencies.

18. The method according to claim 11, further comprising sending the personalized supplement recommendation to a 3D food printer.

19. The method according to claim 11, further comprising generating a personalized supplement recommendation for an additional user, the additional user being positioned less than a threshold distance from the wearable electronic device when the wearable electronic device received the input, the personalized supplement recommendation being generated with the processor based on the nutritional deficiencies.

20. A computer program product comprising:

a computer readable storage medium having stored thereon;

first program instructions executable by a device to cause the device to receive input from at least one of a sensor and an interface of a wearable electronic device of a user, the input including physiological factors and environmental factors measured by the wearable electronic device;

second program instructions executable by the device to cause the device to predict at least one nutritional deficiency based on the input; and

third program instructions executable by the device to cause the device to generate a personalized supplement recommendation for the user based on the at least one nutritional deficiency.