DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Remarks
In response to communications sent July 1, 2022 claim(s) 1-20 are pending in this application; of these claims 1 and 14 are in independent form.
Priority
Claims 1-8 are being given the filing date of the provisional patent application filed May 1, 2017.
Claims 9, 10, and 14-20 are being given the filing date of July 1, 2022 because of the matter in the continuation-in-part application that was not in the original application. For example, there is no mention of food color recognition in the application filed April 30, 2018 nor in the provisional patent application filed May 1, 2017, nor is there mention of a smart refrigerator/pantry.
Drawings
The drawing(s) filed on July 1, 2022 and September 8, 2022 are accepted by the Examiner.
Specification
The abstract of the disclosure is objected to because the first sentence is unclear. The sentence recites what the invention “relates to” and also what is “provided” in a way that seems to be grammatically incorrect. A corrected abstract of the disclosure is required and must be presented on a separate sheet, apart from any other text. See MPEP § 608.01(b).
Information Disclosure Statement
The Information Disclosure Statement(s) is/are acknowledged and the references contained therein have been considered by the Examiner. This includes the Information Disclosure Statements(s) filed on: January 13, 2023 and August 30, 2023.
Claim Objections
Claim 11 is objected to because of the following informalities: The claim is truncated and omits a period. Appropriate correction is required.
Claim 15 is objected to because of the following informalities: The claim omits a period. Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
The term “smart” in claims 6 and 15 is a relative term which renders the claim indefinite. The term “smart” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. A simple controller might be considered “smart” relative to a device without a controller, but not if compared to an AI-driven computerized device. Hence, it is unclear what degree of “smart” defines the metes and bounds of the claim.
The term “in conflict with” in claims 1 and 14 is a relative term which renders the claim indefinite. The term “in conflict with” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. The palate preferences, dietary constraints, and optimized meal plans include quantitative preferences and constraints. Because these are quantitative standards, it is unclear what degree of conflict between the constraints would fall within the metes and bounds of the claim. See MPEP § 2173.05(b) I. Claims 2-13 and 15-20 are rejected because they depend from claims 1 and 14 respectively.
The following is a quotation of 35 U.S.C. 112(d):
(d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
The following is a quotation of pre-AIA 35 U.S.C. 112, fourth paragraph:
Subject to the following paragraph [i.e., the fifth paragraph of pre-AIA 35 U.S.C. 112], a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
Claim 11 is rejected under 35 U.S.C. 112(d) or pre-AIA 35 U.S.C. 112, 4th paragraph, as being of improper dependent form for failing to further limit the subject matter of the claim upon which it depends, or for failing to include all the limitations of the claim upon which it depends. The claim appears to be truncated and does not actually describe the calculation of the nutritional compliance score. Applicant may cancel the claim(s), amend the claim(s) to place the claim(s) in proper dependent form, rewrite the claim(s) in independent form, or present a sufficient showing that the dependent claim(s) complies with the statutory requirements.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a mental process without significantly more. The claim(s) recite(s) various mental processes executed on a general purpose computer. This judicial exception is not integrated into a practical application because the additional elements are necessary extra-solution activity including receiving data over a network and outputting. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the courts have recognized that receiving data over a network is well-understood, routine, and conventional. Claims 2, 5, 6, 9, and 15 introduce more receipt of data as extra-solution activity; claims 3, 4, 7-13, 16-18, and 20 refine the mental processes. Claim 19 adds a method of organizing human activities, which is also a judicial exception and therefore does not add significantly more to the claim beyond what is considered the judicial exception.
1. A computerized method for providing dietary recommendations to a user (applying an abstract idea on a general purpose computer), the method comprising:
receiving palate preferences, physiological data and dietary constraints for a user (receiving data over a network is an additional element beyond the abstract idea; however, it is necessary pre-solution activity to carry out the abstract idea; see MPEP § 2106.05(d) II.i.);
generating a nutritionally optimized meal plan based upon macronutrient and micronutrient requirements (mental process, possible with paper and pencil, but here with the aid of a computer);
cross referencing the optimized meal plan against the palate preferences and dietary constraints to identify dietary elements within the optimized meal plan that are in conflict with the palate preferences and dietary constraints (mental process, possible with paper and pencil, but here with the aid of a computer);
responsive to the macronutrient and micronutrient requirements, substituting the identified dietary elements with substitutions to generate a final meal plan (mental process, possible with paper and pencil, but here with the aid of a computer);
identifying a computing platform employed by the user (mental process);
formatting an output for the final meal plan based upon the computing platform (mental process);
presenting the output to the user (necessary post-solution activity to carry out the abstract idea);
receiving feedback from the user regarding compliance with the final meal plan (receiving data over a network is an additional element beyond the abstract idea; however, it is necessary pre-solution activity to carry out the abstract idea; see MPEP § 2106.05(d) II.i.); and
generating at least two scores based upon the feedback, wherein a first score is a nutritional compliance score, and a second score is a consumption characterization score (mental process, possible with paper and pencil, but here with the aid of a computer).
2. The method of claim 1, further comprising providing curated resources to the user (receiving data over a network is an additional element beyond the abstract idea; however, it is necessary pre-solution activity to carry out the abstract idea; see MPEP § 2106.05(d) II.i.).
3. The method of claim 2, wherein the curated resources are responsive to the user's physiological data (mental process, responsive to necessary pre-solution inputs).
4. The method of claim 1, wherein the optimized meal plan is responsive to the user's physiological data (mental process, responsive to necessary pre-solution inputs).
5. The method of claim 1, further comprising collecting independently verified information regarding the user (mental process of collecting information, see MPEP § 2016.04(a)(2) III A, citing to Electric Power Group v. Alstom, S.A., 830 F.3d 1350, 1353-54, 119 USPQ2d 1739, 1741-42 (Fed. Cir. 2016).
6. The method of claim 5, wherein the independently verified information includes information from at least one of a medical professional, a wearable device, a smart scale, or a smart exercise equipment (mental process of collecting information, see MPEP § 2016.04(a)(2) III A, citing to Electric Power Group v. Alstom, S.A., 830 F.3d 1350, 1353-54, 119 USPQ2d 1739, 1741-42 (Fed. Cir. 2016).
7. The method of claim 1, further comprising providing at least one value added service to the user (mental process of generating a shopping list as a value-added service).
8. The method of claim 7, wherein the at least one value added service includes at least one of the automated generation of a shopping list, a grocery delivery service, a meal preparation service, and a coaching service (mental process of generating a shopping list).
9. The method of claim 1, further comprising:
receiving a digital image of a meal (necessary pre-solution activity);
digitally parsing the image for color segments (decoding colors does not require the use of a computer and could be performed by a human using a photo and pen and paper for the segmenting; the computer is for applying the mental process using general purpose computing);
generating a nutritional score for the meal responsive to diversity of the color segments present, and wherein particular color segments are weighted differently (mental process).
10. The method of claim 9, wherein high contrast colors in the red, orange, green and yellow spectrum are weighted more than lower contrast colors (decoding colors does not require the use of a computer and could be performed by a human using a photo and pen and paper for the segmenting; the computer is for applying the mental process using general purpose computing).
11. The method of claim 1, wherein the nutritional compliance score is calculated as (mental process; note that the claim, as submitted, has been truncated):
12. The method of claim 1, wherein the consumption characterization score is calculated as a point for each of consuming greater than approximately 25 grams of fiber in a 24 hour period, and consuming no greater than 2 servings of processed meats per 7 day period (mental process).
13. The method of claim 1, wherein the at least two scores includes an activity level score (mental process).
14. A computerized method for generating a shopping list for a user (applying an abstract idea on a general purpose computer), the method comprising:
receiving palate preferences, physiological data and dietary constraints for a user (receiving data over a network is an additional element beyond the abstract idea; however, it is necessary pre-solution activity to carry out the abstract idea; see MPEP § 2106.05(d) II.i.);
generating a nutritionally optimized meal plan based upon macronutrient and micronutrient requirements (mental process, possible with paper and pencil, but here with the aid of a computer);
cross referencing the optimized meal plan against the palate preferences and dietary constraints to identify dietary elements within the optimized meal plan that are in conflict with the palate preferences and dietary constraints (mental process, possible with paper and pencil, but here with the aid of a computer);
responsive to the macronutrient and micronutrient requirements, substituting the identified dietary elements with substitutions to generate a final meal plan (mental process, possible with paper and pencil, but here with the aid of a computer);
identifying all ingredients for the final meal plan (mental process);
aggregating the identified ingredients with ingredients from a plurality of other planned meals to generate a final ingredient list (mental process);
cross referencing the final ingredients list with a cupboard list to remove ingredients from the final ingredients list that are present in the cupboard list to generate a refined ingredients list (mental process);
receiving input from a user to remove ingredients from the refined ingredients list to generate the shopping list (receiving data over a network is an additional element beyond the abstract idea; however, it is necessary extra-solution activity to carry out the abstract idea; see MPEP § 2106.05(d) II.i.); and
outputting the shopping list to an electronic grocery application for a retailer or an aggregation grocery delivery service (necessary post-solution activity for the abstract idea).
15. The method of claim 14, further comprising receiving feedback from a smart fridge to populate the cupboard list (receiving data over a network is an additional element beyond the abstract idea; however, it is necessary pre-solution activity to carry out the abstract idea; see MPEP § 2106.05(d) II.i.)
16. The method of claim 14, wherein the removal of ingredients from the refined ingredients list populates the cupboard list (mental process executed on a general purpose computer).
17. The method of claim 14, further comprising querying the user regarding items in the cupboard list after a set time period (mental process executed on a general purpose computer).
18. The method of claim 14, further comprising querying the user regarding items in the cupboard list after a usage quantity over a plurality of meal plans (mental process executed on a general purpose computer).
19. The method of claim 14, wherein the outputted shopping list is automatically delivered to the residence of the user on a configurable cadence (method of organizing human activities for a commercial interaction).
20. The method of claim 14, further comprising selecting at least one retailer for the shopping list by minimizing total cost of the shopping list (mental process for a commercial interaction).
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-8 and 11-13 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by US 2019/0259489 A1 (“Petris”).
As to claim 1, Petris teaches a computerized (Petris Para [0056] a networked computer system with multiple components capable of being scaled) method for providing dietary recommendations to a user (Petris Para [0007]: for meeting nutritional needs), the method comprising:
receiving palate preferences (Petris Para [0089] receiving the user’s food preferences and foods not appreciated), physiological data (Petris Para [00015]: weight) and dietary constraints for a user (Petris Para [0006]: allergies);
generating a nutritionally optimized meal plan (Petris Para [0089]: generating an individualized user diet pattern to enhance health) based upon macronutrient and micronutrient requirements (Petris Para [0100]: the diet patterns in the database are generated using the pre-established guidelines that resulted in a “Mediterranean Diet”);
cross referencing the optimized meal plan against the palate preferences and dietary constraints (Petris Para [0089]: generating an individualized user diet pattern to enhance health) to identify dietary elements within the optimized meal plan that are in conflict with the palate preferences and dietary constraints (Petris Para [0089]: basing a diet on foods not appreciated);
responsive to the macronutrient and micronutrient requirements, substituting the identified dietary elements with substitutions to generate a final meal plan (Petris Para [0129]: at meal time, the user is presented the opportunity to adjust the food intake aspect of the food regiment in response to a clear indication of the compliance of a food that is about to be consumed; see also Petris Para [0006]: adopting healthy habits using the compliance framework);
identifying a computing platform employed by the user (Petris Para [0056]: identifying user device 131);
formatting an output for the final meal plan based upon the computing platform (Petris Para [0058]: formatting an output using a mobile app on the user device);
presenting the output to the user (Petris Para [0056]: the device may be a smartphone, which the Examiner interprets to present output);
receiving feedback from the user regarding compliance with the final meal plan (Peris Para [0026]: the compliance score is composed of a core score about the rules of the diet pattern and an advantage score based on the nutrition information of the individual foods, each of which takes into account the guidelines of the diet pattern and the amount of compliance by the user); and
generating at least two scores based upon the feedback, wherein a first score is a nutritional compliance score, and a second score is a consumption characterization score (Peris Para [0026]: the compliance score is composed of a core score about the rules of the diet pattern and an advantage score based on the nutrition information of the individual foods, each of which takes into account the guidelines of the diet pattern and the amount of compliance by the user).
As to claim 2, Petris teaches the method of claim 1, further comprising providing curated resources to the user (Petris Para [0100]: diet patterns provided via a database are generated using the pre-established guidelines that resulted in a “Mediterranean Diet”).
As to claim 3, Petris teaches the method of claim 2, wherein the curated resources are responsive to the user's physiological data (Petris [0160]: the system optimizes the adoption of healthy habits for the user and preventing cardiovascular disease in as described in Para [0006]).
As to claim 4, Petris teaches the method of claim 1, wherein the optimized meal plan is responsive to the user's physiological data (Petris Para [0089]: the finalized user diet pattern is based on the user’s food profile and energy requirements).
As to claim 5, Petris teaches the method of claim 1, further comprising collecting independently verified information regarding the user (Petris Para [0089]: a user’s device provides information about the degree of physical activity).
As to claim 6, Petris teaches the method of claim 5, wherein the independently verified information includes information from at least one of a medical professional, a wearable device (Petris Para [0089]: a user’s device provides information about the degree of physical activity), a smart scale, or a smart exercise equipment (these elements are recited in the alternative and do not all need to be mapped).
As to claim 7, Petris teaches the method of claim 1, further comprising providing at least one value added service to the user (Petris Para [0065] and Table 1: the Examiner interprets the Mediterranean diet pattern as a “menu choice” that has value-added).
As to claim 8, Petris teaches the method of claim 7, wherein the at least one value added service includes at least one of the automated generation of a shopping list (Petris Para [0065] and Table 1: the Examiner interprets the Mediterranean diet pattern as a “menu choice” that has value-added as a guide for shopping), a grocery delivery service (Petris Para [0161]: a family as the group participants; which the Examiner interprets a family as sometimes being a transportation provider), a meal preparation service (Petris Para [0065] and Table 1: the Examiner interprets the Mediterranean diet pattern as a “menu choice” that has value-added as providing information for meal preparation), and a coaching service (Petris Para [0161]: a team as the group participants; the Examiner interprets a team as sometimes providing coaching).
As to claim 11, Petris teaches the method of claim 1, wherein the nutritional compliance score is calculated (Petris Para [0065]-[0066]: a Mediterranean diet in Table 1 on page 5: a Mediterranean diet described in Table 1) as (this claim appears to have been erroneously truncated):
As to claim 12, Petris teaches the method of claim I, wherein the consumption characterization score is calculated as a point for each of consuming greater than approximately 25 grams of fiber in a 24 hour period (Petris Para [0065]-[0066]: a Mediterranean diet in Table 1 on page 5: a Mediterranean diet described in Table 1: various quantities in the range from 33 grams to 56 grams of Dietary fiber), and consuming no greater than 2 servings of processed meats per 7 day period (Petris Para [0065]-[0066]: a Mediterranean diet in Table 1 on page 5: a Mediterranean diet described in Table 1, zero to three servings of 50-g cold cuts, which has not been quantified, The Examiner argues that a maximum of 150-grams of cold cuts specified in the reference corresponds to being less than 3 servings; slice ham is “processing” because it has been subject to processing in that it has been “chopped up”).
As to claim 13, Petris teaches the method of claim 1, wherein the at least two scores includes an activity level score (Petris Para [0089]: a user’s device provides information about the degree of physical activity; the Examiner interprets the “degree of exercise” as commonly measured in calories).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 9 and 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over US 2019/0259489 A1 (“Petris”) in view of US 11138901 B1 (“Angel”).
As to claim 9, Petris teaches the method of claim 1, but does not teach further comprising:
receiving a digital image of a meal;
digitally parsing the image for color segments;
generating a nutritional score for the meal responsive to diversity of the color segments present, and wherein particular color segments are weighted differently.
Nevertheless, Angel teaches:
receiving a digital image of a meal (Angel Col 35 Line 58 to Col 36 Line 22: receiving a digital image of a meal, such as a banana);
digitally parsing the image for color segments (Angel Col 35 Line 58 to Col 36 Line 22: determining color and shape of the banana);
generating a nutritional score for the meal responsive to diversity of the color segments present, and wherein particular color segments are weighted differently (Angel Col 28 lines 30-49: in one embodiment, a nutrition information is derived from the ripeness of the banana, which is derived from the yellow color regions; different nutritional values are determined for green or brown bananas vs. yellow bananas).
Petris and Angel are in the same field of nutritional informatics. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Petris to include the teachings of Angel because the image recognition can be used to retrieve basic nutrition information for nutrient tracking (See Angel, Abstract). There would be reasonable expectation of success because the color information is a relatively simple recognition task.
As to claim 10, Petris in view of Angel teaches the method of claim 9, wherein high contrast colors in the red, orange, green and yellow spectrum are weighted more than lower contrast colors (Angel Col 28 lines 30-49: yellow and green is weighted as more nutritious than brown, which is rotten).
Claim(s) 14-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over US 2019/0259489 A1 (“Petris”) in view of US 20180053440 A1 (“Staveley”).
As to claim 14, Petris teaches a computerized method (Petris Para [0056] a networked computer system with multiple components capable of being scaled) for generating a shopping list for a user (Petris Para [0065] and Table 1: the Examiner interprets the Mediterranean diet pattern as a “menu choice” that has value-added as a guide for shopping), the method comprising:
receiving palate preferences (Petris Para [0089] receiving the user’s food preferences and foods not appreciated), physiological data (Petris Para [00015]: weight) and dietary constraints for a user (Petris Para [0006]: allergies);
generating a nutritionally optimized meal plan (Petris Para [0089]: generating an individualized user diet pattern to enhance health) based upon macronutrient and micronutrient requirements (Petris Para [0100]: the diet patterns in the database are generated using the pre-established guidelines that resulted in a “Mediterranean Diet”);
cross referencing the optimized meal plan against the palate preferences and dietary constraints (Petris Para [0089]: generating an individualized user diet pattern to enhance health) to identify dietary elements within the optimized meal plan that are in conflict with the palate preferences and dietary constraints (Petris Para [0089]: basing a diet on foods not appreciated);
responsive to the macronutrient and micronutrient requirements, substituting the identified dietary elements with substitutions to generate a final meal plan (Petris Para [0129]: at meal time, the user is presented the opportunity to adjust the food intake aspect of the food regiment in response to a clear indication of the compliance of a food that is about to be consumed; see also Petris Para [0006]: adopting healthy habits using the compliance framework).
However, Petris does not teach:
identifying all ingredients for the final meal plan;
aggregating the identified ingredients with ingredients from a plurality of other planned meals to generate a final ingredient list;
cross referencing the final ingredients list with a cupboard list to remove ingredients from the final ingredients list that are present in the cupboard list to generate a refined ingredients list;
receiving input from a user to remove ingredients from the refined ingredients list to generate the shopping list; and
outputting the shopping list to an electronic grocery application for a retailer or an aggregation grocery delivery service.
Nevertheless, Staveley teaches:
identifying all ingredients for the final meal plan (Petris Para [0083]: identifying a recipe for a nutritional objective);
aggregating the identified ingredients with ingredients from a plurality of other planned meals to generate a final ingredient list (Petris Para [0083]: identifying a plurality of recipes for a nutritional objective);
cross referencing the final ingredients list with a cupboard list to remove ingredients from the final ingredients list that are present in the cupboard list to generate a refined ingredients list (Petris Para [0083]: to populate a smart grocery order to complete a recipe, perform a comparison to what is in a pantry);
receiving input from a user to remove ingredients from the refined ingredients list to generate the shopping list (Petris Para [0083]: populate a smart grocery order to complete a recipe, based on the comparison to what is in the pantry); and
outputting the shopping list to an electronic grocery application for a retailer or an aggregation grocery delivery service (Petris Para [0083]: smart grocery list).
Petris and Staveley are in the same field of nutritional informatics. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Petris to include the teachings of Staveley because meeting nutritional objectives with a smart refrigerator helps to reward prescribed diets (See Staveley, abstract). There would be a reasonable expectation of success because the diet rules of Petris can predictably prescribe the desired shopping list using simple predictable algorithmic rules in a way that is computerized. The combination of references amounts to combining these rule-based systems, one specifying the diet and one that is a smart refrigerator/pantry.
As to claim 15, Petris in view of Staveley teaches the method of claim 14, further comprising receiving feedback from a smart fridge to populate the cupboard list (Petris Para [0083]: populate a smart grocery order to complete a recipe, based on the comparison to what is in the pantry)
As to claim 16, Petris in view of Staveley teaches the method of claim 14, wherein the removal of ingredients from the refined ingredients list populates the cupboard list (Petris Para [0083]: to populate a smart grocery order to complete a recipe, perform a comparison to what is in a pantry).
As to claim 17, Petris in view of Staveley teaches the method of claim 14, further comprising querying the user regarding items in the cupboard list after a set time period (Petris Para [0083]:push notifications regarding grocery items for completing a recipe).
As to claim 18, Petris in view of Staveley teaches the method of claim 14, further comprising querying the user regarding items in the cupboard list after a usage quantity over a plurality of meal plans (Petris Para [0083]-[0084]: the tracking module, which does the push notifications, also permits edit the nutritional profile basis of the ingredient lists).
As to claim 19, Petris in view of Staveley teaches the method of claim 14, wherein the outputted shopping list is automatically delivered to the residence of the user on a configurable cadence (Petris Para [0072]: delivery to the home; Para [0074]: a user interface configures the date).
As to claim 20, Petris in view of Staveley teaches the method of claim 14, further comprising selecting at least one retailer for the shopping list by minimizing total cost of the shopping list (Petris Para [0070] using a particular payment system that involves rewards to save money).
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1-8 and 11-13 are rejected on the ground of nonstatutory double patenting as being unpatentable over claim 1 of U.S. Patent No. 12,119,124 in view of US 2019/0259489 A1 (“Petris”). The claims of the instant application are broader than the claims of U.S. Patent 12,119,124, with slight differences that are taught by US 2019/0259489 A1 (“Petris”) as noted in the comparison chart below:
Instant Application 17/856,782
U.S. Patent 12,119,124 in view of US 2019/0259489 A1 (“Petris”)
1. A computerized method for providing dietary recommendations to a user, the method comprising: receiving palate preferences, physiological data and dietary constraints for a user;
generating a nutritionally optimized meal plan based upon macronutrient and micronutrient requirements; cross referencing the optimized meal plan against the palate preferences and dietary constraints to identify dietary elements within the optimized meal plan that are in conflict with the palate preferences and dietary constraints; responsive to the macronutrient and micronutrient requirements, substituting the identified dietary elements with substitutions to generate a final meal plan; identifying a computing platform employed by the user;
formatting an output for the final meal plan based upon the computing platform;
presenting the output to the user; receiving feedback from the user regarding compliance with the final meal plan; and generating at least two scores based upon the feedback, wherein a first score is a nutritional compliance score, and a second score is a consumption characterization score.
U.S. Patent 12,119,124 claims: 1. A computerized method designed to customize a healthy dietary pattern metabolomic regiment specifically to prevent and/or reverse at least one diet-related disease is provided, wherein the diet-related disease includes at least one of hypertension, diabetes mellitus, dyslipidemias, cardiovascular disease, stroke, kidney disease, liver disease and some cancers, and wherein customization of the healthy dietary metabolomic regiment is achieved by a computerized system and is unique to the beneficiary, the method comprising: receiving characteristics of the beneficiary associated with a metabolic beneficiary; receiving pabulum preferences associated with the metabolic beneficiary including baseline behavior data; identifying specific foods for exclusion from a superset of foods based on the pabulum preferences; generating an automated taste prediction utilizing the pabulum preferences derived from the baseline behavior data; generating a unique palate signature for the beneficiary based on the automated taste prediction; generating an individualized healthy dietary metabolomic regiment to enhance metabolomics of the beneficiary, wherein the individualized healthy dietary metabolomic regiment excludes the identified foods, is extracted from a comprehensive nutrition database, the individualized healthy dietary metabolomic regiment enhances metabolomics of the beneficiary based on the beneficiary characteristics and the unique palate signature; wherein the comprehensive nutrition database provides the beneficiary with the healthy dietary metabolomic regiment: maximizing healthy foods which include minimally processed and plant-based foods with sufficient dietary fiber from fruits, vegetables and whole grains; and minimizing unhealthy foods which include, sweetened beverages, highly processed food and salt; optimizing health outcomes of the beneficiary by providing the individualized healthy metabolomic regiment to the beneficiary for prevention of dietary-related diseases, and wherein the individualized healthy metabolomic regiment includes: 4.5 or more cups of fruits and vegetables per day; 3 or more servings of whole grains per day; at least 2 servings of fish per week; less than 1,500 mg of sodium per day; less than 36 ounces of sweet beverages per week; less than 2 servings per week of processed meats; and greater than 25 grams of dietary fiber; computing a rating of compliance to the individualized healthy metabolomic regiment by the beneficiary, wherein the computation of the rating of compliance includes tracking a journal maintained by the beneficiary, and wherein the journal includes a compilation of food consumed by the beneficiary wherein the rating of compliance includes a score based on a degree of adherence to the individualized healthy metabolomic regiment, wherein the score includes at least one point for each of at least the following: consumption of greater than 4.5 cups of fruit and vegetables per day; consumption of greater than 3 servings of whole grains per day; consumption of less than 1500 mg of salt per day; consumption of less than 5 oz of sweetened beverages per day; consumption of greater than 2 servings of fish per week; and wherein the score includes bonus points, for each of the following: consumption of greater than 25 grams of fiber per day; and consumption of less than 2 servings of processed meats per week; periodically adjusting the individualized healthy metabolomic regiment responsive to the score being above a predefined threshold that is to achieve an ideal dietary health, and is responsive to the pabulum preferences of the individual, wherein the computerized system creates, in an automated fashion the dietary metabolomic regiment, customized to the beneficiary's pabulum preferences and maintaining the score above the threshold for the purpose of preventing and/or reversing at least one diet-related disease; providing the rating of compliance to the beneficiary and to a stakeholder; and enabling the stakeholder to give positive reinforcing compliance feedback to the beneficiary and wherein the stakeholder iteratively makes the periodic adjustments to the individualized healthy metabolomic regiment to increase the rating of compliance, thereby enhancing the metabolomics of the beneficiary in a personalized manner to prevent and/or reverse the at least one diet-related disease, and wherein the computerized system is scalable for a general population.
However, the ‘124 patent does not teach:
identifying a computing platform employed by the user;
formatting an output for the final meal plan based upon the computing platform;
presenting the output to the user; receiving feedback from the user regarding compliance with the final meal plan
Nevertheless, this is taught by Petris as noted in the prior art rejection above (Petris Para [0056]: identifying user device 131; Petris Para [0058]: formatting an output using a mobile app on the user device);
The ’124 patent and Petris are in the same field of nutritional informatics. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the ‘124 patent claims to include the teachings of Petris because the output customization leads to a better user interface, with the customization predictable in a rule-based, algorithmic computing environment.
2. The method of claim 1, further comprising providing curated resources to the user.
Claim 1 in view of Petris. (Petris Para [0100]: diet patterns provided via a database are generated using the pre-established guidelines that resulted in a “Mediterranean Diet”)
3. The method of claim 2, wherein the curated resources are responsive to the user's physiological data.
Claim 1 in view of Petris. (Petris [0160]: the system optimizes the adoption of healthy habits for the user and preventing cardiovascular disease in as described in Para [0006])
4. The method of claim 1, wherein the optimized meal plan is responsive to the user's physiological data.
Claim 1 in view of Petris. (Petris Para [0089]: the finalized user diet pattern is based on the user’s food profile and energy requirements).
5. The method of claim 1, further comprising collecting independently verified information regarding the user.
Claim 1 in view of Petris. (Petris Para [0089]: a user’s device provides information about the degree of physical activity)
6. The method of claim 5, wherein the independently verified information includes information from at least one of a medical professional, a wearable device, a smart scale, or a smart exercise equipment.
Claim 1 in view of Petris. (Petris Para [0089]: a user’s device provides information about the degree of physical activity)
7. The method of claim 1, further comprising providing at least one value added service to the user.
Claim 1 in view of Petris. (Petris Para [0065] and Table 1: the Examiner interprets the Mediterranean diet pattern as a “menu choice” that has value-added)
8. The method of claim 7, wherein the at least one value added service includes at least one of the automated generation of a shopping list, a grocery delivery service, a meal preparation service, and a coaching service.
Claim 1 in view of Petris. (Petris Para [0065] and Table 1: the Examiner interprets the Mediterranean diet pattern as a “menu choice” that has value-added as a guide for shopping; Petris Para [0161]: a family as the group participants; which the Examiner interprets a family as sometimes being a transportation provider; Petris Para [0065] and Table 1: the Examiner interprets the Mediterranean diet pattern as a “menu choice” that has value-added as providing information for meal preparation; Petris Para [0161]: a team as the group participants; the Examiner interprets a team as sometimes providing coaching)
11. The method of claim 1, wherein the nutritional compliance score is calculated as:
Claim 1 in view of Petris. (Petris Para [0065]-[0066]: a Mediterranean diet in Table 1 on page 5: a Mediterranean diet described in Table 1) as (this claim appears to have been erroneously truncated)
12. The method of claim 1, wherein the consumption characterization score is calculated as a point for each of consuming greater than approximately 25 grams of fiber in a 24 hour period, and consuming no greater than 2 servings of processed meats per 7 day period.
Claim 1 in view of Petris. (Petris Para [0065]-[0066]: a Mediterranean diet in Table 1 on page 5: a Mediterranean diet described in Table 1: various quantities in the range from 33 grams to 56 grams of Dietary fiber; Petris Para [0065]-[0066]: a Mediterranean diet in Table 1 on page 5: a Mediterranean diet described in Table 1, zero to three servings of 50-g cold cuts, which has not been quantified, The Examiner argues that a maximum of 150-grams of cold cuts specified in the reference corresponds to being less than 3 servings; slice ham is “processing” because it has been subject to processing in that it has been “chopped up”)
13. The method of claim 1, wherein the at least two scores includes an activity level score.
Claim 1 in view of Petris. (Petris Para [0089]: a user’s device provides information about the degree of physical activity; the Examiner interprets the “degree of exercise” as commonly measured in calories)
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 20210192596 A1: shopping list for recipes
Vasiloglou, Maria F., et al. "Assessing mediterranean diet adherence with the smartphone: The medipiatto project." Nutrients 12.12 (2020): 3763.
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/JESSE P FRUMKIN/Primary Examiner, Art Unit 1685 March 6, 2026