IP Library Granted Patent US 10,078,733
Granted Patent B2
US 10,078,733 · App. 15/636,852 · Granted Sep 18, 2018

System and methods for nutrition monitoring

Inventors: Hassan Ghasemzadeh (Moscow, ID); Niloofar Hezarjaribi (Pullman, WA)
Assignee: WASHINGTON STATE UNIVERSITY
G06F19/3475A23L33/30A61B5/48G16H20/60G10L13/08
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 10,078,733
App. No.
15/636,852
Granted
Sep 18, 2018
Kind
B2
Abstract

An apparatus comprising a natural language processor, a mapper, a string comparator, a nutrient calculator, and a diet planning module, the diet planning module configured to generate a diet action control, the diet action control comprising instructions to operate the client device to perform a diet change recommendation on the client device, and apply the diet action control to the client device.

Claims (47)

1. An apparatus comprising:

a natural language processor to receive text from a client device and transform the text into a generated entity;

a mapper to transform the generated entity into mapped data lists;

a string comparator to transform the mapped data lists into a verified diet-specific control utilizing a nutrition control memory structure;

a nutrient calculator to determine nutrition content from the verified diet-specific control;

a diet planning module to generate a diet action control, the diet action control comprising instructions to operate the client device to perform a diet change recommendation on the client device and apply the diet action control to the client device; and

a prompting module to:

receive a prompt activation signal from the natural language processor;

generate a prompt comprising instructions to operate the client device to display on a machine display of the client device an indication of a prompt item, the prompt item comprising an intent signal or a required entity;

receive an unstructured input, the unstructured input enabling the natural language processor to transform the text into the generated entity; and

send the prompt to the client device.

2. The apparatus of claim 1 , further comprising a speech recognition module to:

receive an audio from the client device;

generate the text from the audio; and

send the text to the natural language processor.

3. The apparatus of claim 1 , wherein the natural language processor comprises:

an intent matching component to:

compare the text to the intent signal in an intent signal control memory structure; and

generate the prompt activation signal in response to the text not matching the intent signal; and

an entity matching component to:

compare the text to entity signals in an entity signal control memory structure;

transform the text into the generated entity by associating the text with the entity signals;

receive a list of required entities; and

generate the prompt activation signal in response to the generated entity not comprising one or more of required entities of the list of required entities.

4. The apparatus of claim 1 , further comprising a training component to:

generate the intent signal and entity signals; and

send the intent signal to an intent signal control memory structure and the entity signals to an entity signal control memory structure.

5. The apparatus of claim 4 , wherein the training component generates the intent signal and the entity signals from the text.

6. The apparatus of claim 1 , wherein the mapper further comprises:

a simple mapping component to:

associate food name entities in the generated entity with other entities in the generated entity; and

a value mapping component to:

compare the other entities associated with each of the food name entities to a standard entity in one or more list dictionaries; and

alter the other entities into the standard entity in response to the other entities being one of one or more synonymous entities to the standard entity.

7. The apparatus of claim 1 , the string comparator further to:

determine whether food name entities in the mapped data lists match the nutrition control memory structure; and

in response to one or more of the food name entities not matching the nutrition control memory structure, utilizing an approximate matching component to determine the verified diet-specific control.

8. The apparatus of claim 7 , the approximate matching component further to:

determine a similarity probability of the one or more of the food name entities to the verified diet-specific control in the nutrition control memory structure;

receive a pre-determined threshold value;

determine an edit distance of the verified diet-specific control to the one or more of the food name entities for the verified diet-specific control greater than the pre-determined threshold value; and

select the verified diet-specific control with the edit distance that is a lowest value.

9. The apparatus of claim 1 , wherein the diet action control affects the client device to display a text message on the machine display associated with the diet change recommendation.

10. The apparatus of claim 1 , wherein the diet action control affects the client device to emit an audible alert associated with the diet change recommendation.

11. The apparatus of claim 1 , wherein the diet action control affects the client device to display an action control on the machine display, the action control to:

receive an input; and

in response to the input, effect a purchase of a product associated with the diet change recommendation.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 29, 2017
From: GHASEMZADEH, HASSAN; HEZARJARIBI, NILOOFAR
To: WASHINGTON STATE UNIVERSITY
Reel/Frame 042867/0009 →
Continuity (2)
Provisional Application 62357205 · Jun 30, 2016
Related Publication 20180004913A1 · Jan 4, 2018