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 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.
Notice of Amendment
In response to the amendment(s) filed on 3/12/26, amended claim(s) 1-4 and 6-10, and canceled claim(s) 5 is/are acknowledged. The following new and/or reiterated ground(s) of rejection is/are set forth:
Claim Objections
Claim 1 is objected to because of the following informalities: “of foot” (line 6) appears that it should be “of a foot.”
Claim 9 is objected to because of the following informalities: “of foot” (line 5) appears that it should be “of a foot.”
Claim 10 is objected to because of the following informalities: “of foot” (line 5) appears that it should be “of a foot.”
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claim(s) 1-4 and 6-10 is/are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
For claim 1, the claim language “estimate a progression state of hallux valgus of the foot of the pedestrian wearing the footwear by inputting the gait feature amount having been extracted to a trained neural network and receiving an output from the trained neural network, the trained neural network having been trained using training data in which progression states of hallux valgus are used as labels and gait feature amounts extracted from gait waveform data of pedestrians having the progression states of hallux valgus are used as input data” does not appear to be described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for pre-AIA the inventor(s), at the time the application was filed, had possession of the claimed invention. A claim may lack written description when the specification does not disclose the computer and the algorithm (i.e., the necessary steps and/or flowcharts) that perform the claimed function in sufficient detail such that one of ordinary skill in the art can reasonably conclude that the inventor invented the claimed subject matter. See MPEP 2161.01(I). Here, the claim recites the function of estimating a progression state of hallux valgus of the foot of the pedestrian wearing the footwear by inputting the gait feature amount having been extracted to a trained neural network and receiving an output from the trained neural network, the trained neural network having been trained using training data in which progression states of hallux valgus are used as labels and gait feature amounts extracted from gait waveform data of pedestrians having the progression states of hallux valgus are used as input data, but the specification never discloses the necessary steps and/or flowcharts of how this occurs. The term “a trained neural network” is treated as a black box and the specification does not describe the specifics of how to achieve the above-recited function(s) with this algorithm. For example, how many and what types of layers are there? How is the data propagated? What logics are programmed to help the machine learning algorithm make a decision? Is the training supervised or unsupervised? What are the weightings? Are other training concepts sed such as regression? What assumptions are being made regarding the perception of the model? It is not enough that a skilled artisan could devise a way to accomplish the function because this is not relevant to the issue of whether the inventor has shown possession of the claimed invention. See MPEP 2161.01(I). Therefore, adequate disclosure is needed.
For claim 6, the claim language “estimate an angle formed by a center line of a first metatarsal bone and a center line of a first proximal phalanx by using the trained neural network that receives the gait feature amount having been extracted as input and outputs the angle formed by the center line of the first metatarsal bone and the center line of the first proximal phalanx, the trained neural network having been trained using training data in which the angle formed by the center line of the first metatarsal bone and the center line of the first proximal phalanx is used as a label and the gait feature amount is used as input data” does not appear to be described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for pre-AIA the inventor(s), at the time the application was filed, had possession of the claimed invention. A claim may lack written description when the specification does not disclose the computer and the algorithm (i.e., the necessary steps and/or flowcharts) that perform the claimed function in sufficient detail such that one of ordinary skill in the art can reasonably conclude that the inventor invented the claimed subject matter. See MPEP 2161.01(I). Here, the claim recites the function of estimating an angle formed by a center line of a first metatarsal bone and a center line of a first proximal phalanx by using a trained neural network that receives the gait feature amount having been extracted as input and outputs the angle formed by the center line of the first metatarsal bone and the center line of the first proximal phalanx, the trained neural network having been trained using training data in which the angle formed by the center line of the first metatarsal bone and the center line of the first proximal phalanx is used as a label and the gait feature amount is used as inputs, but the specification never discloses the necessary steps and/or flowcharts of how this occurs. The term “a trained neural network” is treated as a black box and the specification does not describe the specifics of how to achieve the above-recited function(s) with this algorithm. For example, how many and what types of layers are there? How is the data propagated? What logics are programmed to help the machine learning algorithm make a decision? Is the training supervised or unsupervised? What are the weightings? Are other training concepts sed such as regression? What assumptions are being made regarding the perception of the model? It is not enough that a skilled artisan could devise a way to accomplish the function because this is not relevant to the issue of whether the inventor has shown possession of the claimed invention. See MPEP 2161.01(I). Therefore, adequate disclosure is needed.
For claim 9, the claim language “estimating a progression state of hallux valgus of the foot of the pedestrian wearing the footwear by inputting the gait feature amount having been extracted to a trained neural network and receiving an output from the trained neural network, the trained neural network having been trained using training data in which progression states of hallux valgus are used as labels and gait feature amounts extracted from gait waveform data of pedestrians having the progression states of hallux valgus are used as input data” does not appear to be described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for pre-AIA the inventor(s), at the time the application was filed, had possession of the claimed invention. A claim may lack written description when the specification does not disclose the computer and the algorithm (i.e., the necessary steps and/or flowcharts) that perform the claimed function in sufficient detail such that one of ordinary skill in the art can reasonably conclude that the inventor invented the claimed subject matter. See MPEP 2161.01(I). Here, the claim recites the function of estimating a progression state of hallux valgus of the foot of the pedestrian wearing the footwear by inputting the gait feature amount having been extracted to a trained neural network and receiving an output from the trained neural network, the trained neural network having been trained using training data in which progression states of hallux valgus are used as labels and gait feature amounts extracted from gait waveform data of pedestrians having the progression states of hallux valgus are used as input data, but the specification never discloses the necessary steps and/or flowcharts of how this occurs. The term “a trained neural network” is treated as a black box and the specification does not describe the specifics of how to achieve the above-recited function(s) with this algorithm. For example, how many and what types of layers are there? How is the data propagated? What logics are programmed to help the machine learning algorithm make a decision? Is the training supervised or unsupervised? What are the weightings? Are other training concepts sed such as regression? What assumptions are being made regarding the perception of the model? It is not enough that a skilled artisan could devise a way to accomplish the function because this is not relevant to the issue of whether the inventor has shown possession of the claimed invention. See MPEP 2161.01(I). Therefore, adequate disclosure is needed.
For claim 10, the claim language “estimating a progression state of hallux valgus of the foot of the pedestrian wearing the footwear by inputting the gait feature amount having been extracted to a trained neural network and receiving an output from the trained neural network, the trained neural network having been trained using training data in which progression states of hallux valgus are used as labels and gait feature amounts extracted from gait waveform data of pedestrians having the progression states of hallux valgus are used as input data” does not appear to be described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for pre-AIA the inventor(s), at the time the application was filed, had possession of the claimed invention. A claim may lack written description when the specification does not disclose the computer and the algorithm (i.e., the necessary steps and/or flowcharts) that perform the claimed function in sufficient detail such that one of ordinary skill in the art can reasonably conclude that the inventor invented the claimed subject matter. See MPEP 2161.01(I). Here, the claim recites the function of estimating a progression state of hallux valgus of the foot of the pedestrian wearing the footwear by inputting the gait feature amount having been extracted to a trained neural network and receiving an output from the trained neural network, the trained neural network having been trained using training data in which progression states of hallux valgus are used as labels and gait feature amounts extracted from gait waveform data of pedestrians having the progression states of hallux valgus are used as input data, but the specification never discloses the necessary steps and/or flowcharts of how this occurs. The term “a trained neural network” is treated as a black box and the specification does not describe the specifics of how to achieve the above-recited function(s) with this algorithm. For example, how many and what types of layers are there? How is the data propagated? What logics are programmed to help the machine learning algorithm make a decision? Is the training supervised or unsupervised? What are the weightings? Are other training concepts sed such as regression? What assumptions are being made regarding the perception of the model? It is not enough that a skilled artisan could devise a way to accomplish the function because this is not relevant to the issue of whether the inventor has shown possession of the claimed invention. See MPEP 2161.01(I). Therefore, adequate disclosure is needed.
Dependent claim(s) 2-4 and 6-10 fail to cure the deficiencies of independent claim 1, thus claim(s) 1-4 and 6-10 is/are rejected under 35 U.S.C. 112(a).
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.
Claim(s) 1-4 and 6-10 is/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.
For claim 1, the claim terms “foot” (line 6) and “a foot” (line 31) are ambiguous. It is unclear whether the different feet or the same foot is being referred to. The claim is examined under the latter interpretation.
For claim 7, the claim language “optimized for healthcare use” is ambiguous. It is unclear what is meant by “optimized” for healthcare use. That is, a skilled artisan would not understand an objective mete and bounds for the scope of an “optimized” use for healthcare. What characteristics or features of the “content related to the gait” quality it was “optimized for healthcare use” versus not being “optimized for healthcare use”? The claim is examined as meaning “transmit the content related to the gait of the pedestrian for health use to the mobile terminal used by the pedestrian.”
For claim 9, the claim terms “foot” (line 5) and “a foot” (line 30) are ambiguous. It is unclear whether the different feet or the same foot is being referred to. The claim is examined under the latter interpretation.
For claim 10, the claim terms “foot” (line 5) and “a foot” (line 30) are ambiguous. It is unclear whether the different feet or the same foot is being referred to. The claim is examined under the latter interpretation.
Dependent claim(s) 2-4 and 6-10 fail to cure the ambiguity of independent claim 1, thus claim(s) 1-4 and 6-10 is/are rejected under 35 U.S.C. 112(b).
Allowable Subject Matter
Claim(s) 1-4 and 6-10 would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 112(a) and 35 U.S.C. 112(b) set forth in this Office action and to include all of the limitations of the base claim and any intervening claims.
Response to Arguments
Applicant’s arguments filed 3/12/26 have been fully considered.
With respect to the claim objections, Applicant’s amendments and arguments are persuasive and thus the previous objections are withdrawn. However, new objections have been necessitated by Applicant’s amendments.
With respect to the 112 rejections, some of the rejections have been withdrawn in view of Applicant’s amendments and arguments. The remaining 112 rejections are necessary in view of Applicant’s amendments. The support identified in the response does not seem to answer the issues raised in the Office action. Specifically, there still appears to be a lack of description of architecture for the claimed “neural network” and the “optimized for healthcare” is still ambiguous as to what that exactly means.
With respect to the 101 rejections, Applicant’s amendments and arguments are persuasive and thus the rejections are withdrawn. Specifically, the amendments relate a particular sensor configuration to a particular data processing workflow that is similar to the fact pattern in Thales v. Visionx. It is these specific amendments that were made in the response that cause the rejections to be withdrawn.
With respect to the 102/103 rejections, Applicant’s amendments and arguments are persuasive and thus the rejections are withdrawn.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DANIEL LEE CERIONI whose telephone number is (313) 446-4818. The examiner can normally be reached M - F 8:00 AM - 5:00 PM PT.
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/DANIEL L CERIONI/Primary Examiner, Art Unit 3791