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 .
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 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis 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.
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed in parent Application No. GB2112347.6, filed on 8/30/2021.
Claim Objections
Regarding Claims 8, 12-13, and 18: Claim 8, 12-13, and 18 are objected to as being dependent upon a rejected base claim, but would be free of prior art if rewritten in independent form including all of the limitations of the base claim and any intervening claims. Notably, however, the claims remain rejected under 35 U.S.C. 101. These rejections must also be overcome.
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 16-19 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because the claims are directed to a software per se.
Claims 16-19 do not fall within at least one of the four categories of patent eligible subject matter because claims 16-19 are directed to a system, but does not recite any hardware. The claims recite a foot profiling module and a foot growth pattern module, a recommendation module, and a prediction module. The modules are not defined with any particularity in the specification, and Fig. 1 shows the various modules as blocks within a footwear recommendation system, and by broadest reasonable interpretation, can be any software or program within the system. As such, claims 16-19 recite a system of software, as opposed to a system of computer hardware.
Claims 16-19 are rejected because the claims are directed to the software, which is not one of the four statutory classes of invention. Applicant is advised to amend the claims to recite computer hardware to execute the various modules to overcome the rejection.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claims are directed to a judicial exception without significantly more.
Step 1:
Claims 1-15 are directed to a method, which is a process. Claims 16-19 are directed to a system, but is a system of software as discussed above, but will be analyzed in steps 2A and 2B for the sake of compact prosecution. Claim 20 is directed to non-transitory computer-readable medium, which is an article of manufacture. Therefore, claims 1-15 and 20 are directed to one of the four statutory categories of invention.
Step 2A (Prong 1):
Taking claim 1 as representative claim 1 sets forth the following limitation reciting the abstract idea of predicting foot growth based on measurements to recommend the footwear sizes and when to take another measurement:
receiving a plurality of images of a foot of a user during a current scan of the user foot;
analyzing the plurality of images to generate a 3D foot profile of the user;
determining the foot size of the user based on the 3D foot profile of the user;
determine a foot growth pattern of the user, using a user profile from the current and one or more previous scans of the user and one or more other users;
recommending one or more footwear sizes for the user based on at least one of: the foot size and the predicted foot growth pattern, one or more footwear brands, and one or more footwear models;
predicting a time of next scan of the user based on the recommended footwear size and the predicted foot growth pattern of the user and one or more other users.
The recited limitations above set forth the process for predicting foot growth based on measurements to recommend the footwear sizes and when to take another measurement. These limitations amount to certain methods of organizing human activity, including commercial or legal transactions (e.g. agreements in the form of contracts, advertising, marketing or sales activities or behaviors, etc.). The claims are directed to predicting a size of the user’s feet to recommend products, which is an advertising and marketing activity. Such concepts have been identified by the courts as abstract ideas (see: MPEP 2106.04(a)(2)).
Step 2A (Prong 2):
Examiner acknowledges that representative claim 1 recites additional elements, such as:
wherein the scan is performed through a mobile computing device;
using machine learning techniques;
Taken individually and as a whole, representative claim 1 does not integrate the recited judicial exception into a practical application of the exception. The additional elements do no more than generally link the use of a judicial exception to a particular technological environment or field of use.
Furthermore, this is also because the claim fails to (i) reflect an improvement in the functioning of a computer, or an improvement to other technology or technical field, (ii) implement a judicial exception with a particular machine, (iii) effect a transformation or reduction of a particular article to a different state or thing, or (iv) apply the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment.
While the claims recite a scan performed through a mobile computing device and machine learning techniques, these elements are recited with a very high level of generality, and are merely used to gather data. The scanning is not discussed with any detail within the specification. The closest disclosure in the specification occurs in paragraph [0093], which merely discloses the scanner captures a plurality of images and in [0023], which merely discloses capturing a plurality of images with the camera of a user computing device. The computing device is also disclosed with a high level of generality as being any generic device, such as a personal computer, a mobile phone, a portable computing device, and the like (specification: [0046]). As such, it is evident that any scanning technology and computing device is a generic device or technique that is merely applied to the abstract idea to gather foot data. The machine learning is also disclosed generally, merely disclosing the machine learning as possibly being k-means or DBSCAN, without any further detail except to provide an output for the abstract idea (specification: [0055]). It is evident that the machine learning is any generic machine learning that is applied to the abstract idea. The generating of a 3D foot profile is not considered an additional element because it is recited in passing as merely providing the dimensions of the foot. There are not details that require the use of computer-generated graphics or any other computer functionality. Even if these elements were recited in the claims, the specification does not disclose any detail to how the 3D foot profile is generated, and it would be interpreted as being another generic technique that merely provides a general link to a computing environment.
In view of the above, under Step 2A (Prong 2), representative claim 1 does not integrate the recited exception into a practical application (see: MPEP 2106.04(d)).
Step 2B:
Returning to representative claim 1, taken individually or as a whole, the additional elements of claim 1 do not provide an inventive concept (i.e. whether the additional elements amount to significantly more than the exception itself). As noted above, the additional elements recited in claim 1 are recited in a generic manner with a high level of generality and only serve to implement the abstract idea on a generic computing device. The claims result only in an improved abstract idea itself and do not reflect improvements to the functioning of a computer or another technology or technical field. As discussed above with respect to the integration of the abstract idea into a practical application, the additional elements used to perform the claimed process ultimately amount to no more than the mere instructions to apply the exception using a generic computer and/or no more than a general link to a technological environment.
Even when considered as an ordered combination, the additional elements of claim 1 do not add anything further than when they are considered individually.
In view of the above, claim 1 does not provide an inventive concept under step 2B, and is ineligible for patenting.
Regarding Claim 16 (system): Claim 16 recites at least substantially similar concepts and elements as recited in claim 1 such that similar analysis of the claims would be readily apparent to one of ordinary skill in the art. As such, claim 16 is rejected under at least similar rationale as provided above regarding claim 1.
Regarding Claim 20 (non-transitory computer readable medium): Claim 20 recites at least substantially similar concepts and elements as recited in claim 1 such that similar analysis of the claims would be readily apparent to one of ordinary skill in the art. As such, claim 20 is rejected under at least similar rationale as provided above regarding claim 1.
Dependent claims 2-15 and 17-19 recite further complexity to the judicial exception (abstract idea) of claim 1, such as by further defining the algorithm of predicting foot growth based on measurements to recommend the footwear sizes and when to take another measurement. Thus, each of claims 2-15 and 17-19 are held to recite a judicial exception under Step 2A (Prong 1) for at least similar reasons as discussed above.
Under prong 2 of step 2A, the additional elements of dependent claims 2-15 and 17-19 also do not integrate the abstract idea into a practical application, considered both individually or as a whole. More specifically, dependent claims 2-15 and 17-19 rely on at least similar elements as recited in claim 1. Further additional elements are also acknowledged (e.g., clustering-based machine learning techniques (claim 7)); however, the additional elements of claims 2-15 and 17-19 are recited only at a high level of generality (i.e. as generic computing hardware) such that they amount to nothing more than the mere instructions to implement or apply the abstract idea on generic computing hardware (or, merely uses a computer as a tool to perform an abstract idea). Further, the additional elements do no more than generally link the use of a judicial exception to a particular technological environment or field of use (such as the Internet or computing networks).
Secondly, this is also because the claims fails to (i) reflect an improvement in the functioning of a computer, or an improvement to other technology or technical field, (ii) implement the judicial exception with, or use the judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim, (iii) effect a transformation or reduction of a particular article to a different state or thing, or (iv) applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment.
Taken individually and as a whole, dependent claims 2-15 and 17-19 do not integrate the recited judicial exception into a practical application of the exception under step 2A (prong 2).
Lastly, under step 2B, claims 2-15 and 17-19 also fail to result in “significantly more” than the abstract idea under step 2B. The dependent claims recite additional functions that describe the abstract idea and use the computing device to implement the abstract idea, while failing to provide an improvement to the functioning of a computer, another technology, or technical field. The dependent claims fail to confer eligibility under step 2B because the claims merely apply the exception on generic computing hardware and generally link the exception to a technological environment.
Even when viewed as an ordered combination (as a whole), the additional elements of the dependent claims do not add anything further than when they are considered individually.
Taken individually or as an ordered combination, the dependent claims simply convey the abstract idea itself applied on a generic computer and are held to be ineligible under Steps 2B for at least similar rationale as discussed above regarding claim 1. Thus, dependent claims 2-15 and 17-19 do not add “significantly more” to the abstract idea.
Claim Rejections - 35 USC § 102
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 person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(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.
Claims 1-6, 9-11, 15-17, and 19-20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Marks (US 20160081435 A1).
Regarding Claim 1: Marks discloses a method comprising:
receiving a plurality of images of a foot of a user during a current scan of the user foot, wherein the scan is performed through a mobile computing device; Marks discloses receiving scan data of the foot and/or feet, which includes images, the scanning device which may be integral to the computing device (Marks: [0079]; [0020]; see also: [0022]; [0018]).
analyzing the plurality of images to generate a 3D foot profile of the user; Marks discloses generating a 3D representation of the foot and/or feet based on the scan data (Marks: [0080]; see also: [0011]; [0026]).
determining the foot size of the user based on the 3D foot profile of the user; Marks discloses determining the fit of the foot with various footwear, including the width, height, and shape of the foot (Marks: [0083]; [0027-0028]; see also: [0012]).
determine a foot growth pattern of the user, using machine learning techniques based on the 3D foot profile and user profile from the current and one or more previous scans of the user and one or more other users; Marks discloses estimating the growth of the foot and the fit at a future point in time based on 3D representations of the user’s feet over time, average growth information of users deemed to be similar to the user, and the fit and activity preferences of the user (Marks: [0071-0072]; see also: [0011]; [0035]).
recommending one or more footwear sizes for the user based on at least one of: the foot size and the predicted foot growth pattern, one or more footwear brands, and one or more footwear models; Marks discloses recommending footwear to the user based on the 3D representation of the user’s feet, historical data of the user’s feet, and level of fit with the manufacturer of the footwear (Marks: [0083]; see also: [0012]; [0027-0028]).
predicting a time of next scan of the user based on the recommended footwear size and the predicted foot growth pattern of the user and one or more other users. Marks teaches a history of scan and 3D representation data of the user’s feet over time estimating future growth of the user’s feet, including information of the general population (Marks: [0035-0036]; see also: [0053]; [0072]).
Regarding Claim 2: Marks discloses the limitations of claim 1 above.
Marks further discloses recommending a plurality of footwear to the user by searching in a pre-defined footwear inventory based on the recommended footwear size, the 3D foot profile and the user profile of the user and one or more other users, wherein the plurality of footwear is arranged for viewing by the user in a decreasing order of probability of being a good fit to the foot, and wherein the searching in the pre0defined footwear inventory includes matching a category of the 3D foot profile to one or more footwear brands and models. Marks discloses searching footwear based on differences of characteristics of the 3D representation with information of footwear items associated with various manufacturers, designers, or retailers, and ranking the footwear by the calculated level of fit (Marks; [0027-0029]; see also: [0072]; [0083]).
Regarding Claim 3: Marks discloses the limitations of claim 2 above.
Marks further discloses recommending the plurality of footwear based on the first through fifth inputs, the first input including the foot size of the user, the second input including dimensions of the manufacturer’s footwear, the third input including properties of the manufacturer’s shoes including type, colour, material, brand, id of manufacturer, and inventory data, the fourth input including user profile of the user, including phenotype and preferences including purchase data from activity and feedback of past purchases, and the fifth input including user profile of the one or more other users, including phenotype and preferences including the purchase data from activity and feedback of past purchases. Marks discloses input of scan information to determine the user foot size and 3D representation, a footwear data store to retrieve data of the footwear, including sizes, shapes, and manufacturers, and profile information of the user and a population of users that include preferences for fit and activities (Marks: 0027-0029]; see also: [0031-0033]; [0053]; [0051-0052]).
Regarding Claim 4: Marks discloses the limitations of claim 3 above.
Marks further discloses wherein the recommending comprises a first step of employing a feet-shoe dimension matching algorithm based on the first and second inputs to generate a first lift of shoe recommendations for the user. Marks discloses comparing the dimensions of the user’s feet and the footwear data to determine the level of fit for various footwear items of different manufacturers (Marks: [0027-0028]).
Regarding Claim 5: Marks discloses the limitations of claim 4 above.
Marks further discloses comparing 3D profile of a shoe with the 3D foot profile to generate the first list of shoe recommendations for the user. Marks discloses comparing the dimensions of the user foot with the footwear item data using the 3D using the 3D representation of the user’s foot and 3D representation of the footwear item (Marks: [0027]; see also: [0083]).
Regarding Claim 6: Marks discloses the limitations of claim 4 above.
Marks further discloses wherein the recommending comprises a second step of employing a profile-shoe matching algorithm based on the third and fourth inputs to reduce down the first lift of the shoe recommendations for the user. Marks discloses comparing the characteristics of the foot and footwear based on the user preferences to rank the footwear for recommendation (Marks: [0029]; see also: [0083]).
Regarding Claim 9: Marks discloses the limitations of claim 2 above.
Marks further discloses predicting the footwear inventory based on the recommended plurality of footwear. Marks discloses using the data to assist in distributing footwear items to different geographical regions or types of footwear items to be manufactured (Marks: [0015]).
Regarding Claim 10: Marks discloses the limitations of claim 1 above.
Marks further discloses wherein the 3D foot profile includes at least one of: a length, a width, an ankle width, a foot height, and a hallux angle of the foot of the user. Marks discloses the 3D representation including the length and width of the foot, and size and shape of the ankle (Marks: [0028]; [0026]).
Regarding Claim 11: Marks discloses the limitations of claim 1 above.
Marks further discloses wherein the user profile includes at least one of: the age, the height, the ethnicity, preferences, and the gender. Marks discloses the profile including an ethnicity, height, age, gender, and preferences of the suer (Marks: [0043-0047]; [0032]).
Regarding Claim 15: Marks discloses the limitations of claim 1 above.
Marks further discloses a method comprising:
performing longitudinal analysis of foot growth between current and next scans to predict foot growth and development of the user; Marks discloses estimating future growth based on historical changes in 3D representations of the user’s foot and general population growth (Marks: [0035-0036]; see also: [0072]).
detect an anomaly in the foot growth by analyzing the foot growth in respect of a 3D foot profile and a footwear size applicable for the age and gender of the user. Marks discloses differences in previous growth of the user and the general population, such as less than an inch growth when the general population grows 1.5 inches, and identifying foot conditions for the user, such as a swollen toe that has remained swollen (Marks: [0034-0035]).
Regarding Claims 16 and 20: Claims 16 and 20 recite substantially similar limitations as claim 1. Therefore, claims 16 and 20 are rejected under the same rationale as claim 1 above.
Regarding Claim 17: Claim 16 recites substantially similar limitations as claim 2. Therefore, claim 17 is rejected under the same rationale as claim 2 above.
Regarding Claim 19: Claim 19 recites substantially similar limitations as claim 15. Therefore, claim 19 is rejected under the same rationale as claim 15 above.
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.
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable by Marks (US 20160081435 A1) in view of Zhou (US 20190065598 A1).
Regarding Claim 7: Marks discloses the limitations of claim 6 above.
Marks does not explicitly teach wherein the recommending comprises a third step of querying a user profile model previously trained with the fifth input using clustering-based machine learning techniques to create a structure of user profiles with observations aggregating features of the user phenotype, preferences, feet dimensions and shoes purchasing status, to obtain a list of user profiles ranked by similarity. Notably, however, Marks does disclose collecting data of users’ feet, including scan data, 3D representations, and preferences, grouping the users by common characteristics (Marks: [0053]).
To that accord, Zhou does teach wherein the recommending comprises a third step of querying a user profile model previously trained with the fifth input using clustering-based machine learning techniques to create a structure of user profiles with observations aggregating features of the user phenotype, preferences, feet dimensions and shoes purchasing status, to obtain a list of user profiles ranked by similarity. Zhou teaches retrieving and scoring profiles of members to identify the most similar profiles using machine learning techniques of logistic regression (Zhou: [0057]; [0041]).
It would have been obvious, to one of ordinary skill in the art, before the effective filing date of the invention, to modify the invention of Marks disclosing a footwear recommendation system that generates a 3D representation of the user’s foot and using information of similar users with the creating a structure of user profiles to obtain a list of similar profiles as taught by Zhou. One of ordinary skill in the art would have been motivated to do so in order to identify similar profiles to the target profile (Zhou: [0014]).
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable by Marks (US 20160081435 A1) in view of Parker (US 20200302506 A1).
Regarding Claim 14: Marks discloses the limitations of claim 1 above.
Marks does not explicitly teach providing a user interface so as to enable the user to provide their feedback; and processing the feedback to revise the recommended footwear. Notably, however, Marks does disclose an interface for users to receive footwear recommendations (Marks: [0050]).
To that accord, Parker does teach providing a user interface so as to enable the user to provide their feedback; and processing the feedback to revise the recommended footwear. Parker teaches the user providing feedback to recommendations and the feedback being utilized to refine the recommendations of the user (Parker: [0020]).
It would have been obvious, to one of ordinary skill in the art, before the effective filing date of the invention, to modify the invention of Marks disclosing a footwear recommendation system that generates a 3D representation of the user’s foot and using information of similar users with the user providing feedback to revise the recommendation as taught by Parker. One of ordinary skill in the art would have been motivated to do so in order to more accurately predict user interests based on customer actions (Parker: [0001]).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. PTO-892 Reference U discloses measuring the accuracy of 3D scanning of feet to determine foot.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to TIMOTHY J KANG whose telephone number is (571)272-8069. The examiner can normally be reached Monday - Friday: 7:30 - 5:00.
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/TIMOTHY J KANG/Examiner, Art Unit 3688