CTNF 18/730,822 CTNF 93159 Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. Claim Objections 07-05-05 Applicant is advised that should claims 10-12 be found allowable, claims 18-20 will be objected to under 37 CFR 1.75 as being a substantial duplicate thereof. When two claims in an application are duplicates or else are so close in content that they both cover the same thing, despite a slight difference in wording, it is proper after allowing one claim to object to the other as being a substantial duplicate of the allowed claim. See MPEP § 608.01(m). Claim Rejections - 35 USC § 112 07-30-02 AIA 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. 07-34-01 Claim 1, 3, 5-8, 10-16 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. Claim 1 (5-8, 10-12 by dependency) recites “A method of predicting foot contact data” but no prediction is being made. Examiner notes that the claim merely recites training a neural network. It is unclear how foot contact data can be predicted without use of the neural network. Claim 3 (13-16 by dependency) recites “applying a trained deep neural network”. It is unclear if Applicant is referring to any neural network or the neural network trained in claim 1. Further, if the former, it is unclear how any neural network (for example on trained on real estate data or stock prices) can be used to motion data and force estimates. Claim 8, 16 recites “a frame”. A frame of what? Is Applicant referring to some image or video data? It is unclear what this means. Claim 8, 16 recites “surrounding frames”. The scope of the claim is unclear. What surrounding frames is the Applicant referring to? Claim 9, 17 recites “across frames. There is insufficient antecedent basis for this limitation. Further it is unclear what “frames” is referring to. Claim Rejections - 35 USC § 101 07-04-01 AIA 07-04 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 an abstract idea without significantly more. The claim(s) recite(s) determining skeletal reactive force estimates, applying a contacts function to the skeletal reactive force estimates to generate body contact estimates . The abstract idea is part of the Mathematical Concepts group(s) identified in the Ninth Edition, Revision 10.2019 (revised June 2020) of the Manual of Patent Examination Procedure (MPEP). This judicial exception is not integrated into a practical application because they amount to simply implementing the abstract idea on a computer; data-gathering steps do not add a meaningful limitation to the method as they are insignificant extra-solution activity; there is no improvement to a computer or other technology; does not apply the abstract idea to effect a particular treatment or prophylaxis for a disease or medical condition; does not apply the abstract idea with, or by use of, a particular machine. The additional elements are identified as follows: a memory and processor . The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements, when considered both individually and as a whole, do not amount to significantly more than the abstract idea. The additional computer and data-gathering elements, which are recited at a high level of generality, provide conventional computer and data-gathering functions that do not add meaningful limitations to practicing the abstract idea. Those in the relevant field of art would recognize the above-identified additional elements as being well-understood, routine, and conventional means for data-gathering and computing, as demonstrated by non-patent literature of record in the application . Thus, the claimed additional elements “are so well-known that they do not need to be described in detail in a patent application to satisfy 35 U.S.C. § 112(a).” Berkheimer Memorandum, III. A. 3. When considered in combination, the additional elements (generic computer functions and conventional equipment/steps) do not amount to significantly more than the abstract idea. The Federal Circuit has held that combining additional elements for data-gathering with abstract ideas does not make a claim patent-eligible. Looking at the claim limitations as a whole adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation. Regarding the dependent claims, the dependent claims are directed to either 1) steps that are also abstract or 2) additional data gathering that is well-understood, routine and previously known to the industry. Although the dependent claims are further limiting, they do not recite significantly more than the abstract idea. A narrow abstract idea is still an abstract idea and an abstract idea with additional well-known data-gathering equipment/functions is not significantly more than the abstract idea. Claim Rejections - 35 USC § 102 07-06 AIA 15-10-15 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. 07-07-aia AIA 07-07 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 – 07-08-aia AIA (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. 07-15-aia AIA Claim(s) 3-4, 12-15, 20 is/are rejected under 35 U.S.C. 102 (a)(1) as being anticipated by Scott et al. (From Image to Stability: Learning Dynamics from Human Pose; ECCV 2020 – sited by Applicant), hereinafter Scott . Regarding Claim 3, Scott teaches: A method, comprising: applying a trained deep neural network to human motion data to generate skeletal reactive force estimates (page 1-2); and, applying a contacts function to the skeletal reactive force estimates to generate body contact estimates (figure 1, 5; page 1-2; section 4). Regarding Claim 4 , Scott teaches: An apparatus comprising a memory and a processor (implied; page 1 and 2), configured to perform: applying a trained deep neural network to human motion data to generate skeletal reactive force estimates (page 1-2); and, applying a contacts function to the skeletal reactive force estimates to generate body contact estimates (figure 1, 5; page 1-2; section 4). Regarding Claim 12 and 20 , Scott teaches: The apparatus of claim 4, wherein a contacts function is used to validate ground truth contacts with contact estimates (page 12, paragraph 1; figure 7). Regarding Claim 13 , Scott teaches: The method of claim 3, wherein the skeletal reactive forces are vertical ground forces (Examiner notes that this is an inherent property of skeletal reactive forces – vertical ground forces). Regarding Claim 14 , Scott teaches: The method of claim 3, wherein the human motion data comprises foot pressure data (page 1-2). Regarding Claim 15 , Scott teaches: The method of claim 3, wherein the human motion data is positioned at multiple points in a global Euclidean space (figure 1, pages 1-4) . Claim Rejections - 35 USC § 103 07-06 AIA 15-10-15 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. 07-20-aia AIA 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. 07-23-aia AIA The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows: 1. Determining the scope and contents of the prior art. 2. Ascertaining the differences between the prior art and the claims at issue. 3. Resolving the level of ordinary skill in the pertinent art. 4. Considering objective evidence present in the application indicating obviousness or nonobviousness. 07-21-aia AIA Claim (s) 1-2, 5-7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Scott . Regarding Claim 1 , Scott teaches: A method of predicting foot contact data (page 2 paragraph 2), comprising: training a deep neural network by determining foot pressure estimates from a database (page 1; figure 1) comprising motion information and foot pressure (page 6; paragraph 2). Scott does not explicitly mention skeletal reactive force. However, Scott does mention the relationship between force and pressure (page 3; direct measurement of foot pressure using force plates). Further, when viewed in light of the Specification (which states that pressure data itself is used to generate ground reactive force; paragraph 0022-0023). It would have been obvious to one of ordinary skill in the art, before the effective filing date to have modified the method to include the use of skeletal reactive force as the substitute of force for pressure would have yielded predictable training and estimating results to one of ordinary skill. It is well known in the art force and pressure are proportionally related to each other. Regarding Claim 2 , Scott teaches: An apparatus for predicting foot contact data (page 1), comprising: Memory (implied; page 1 and 2); and, a processor (implied; page 1 and 2), configured to perform: training a deep neural network by determining foot pressure estimates from a database (page 1; figure 1) comprising motion information and foot pressure (page 6; paragraph 2). Scott does not explicitly mention skeletal reactive force. However, Scott does mention the relationship between force and pressure (page 3; direct measurement of foot pressure using force plates). Further, when viewed in light of the Specification (which states that pressure data itself is used to generate ground reactive force; paragraph 0022-0023). It would have been obvious to one of ordinary skill in the art, before the effective filing date to have modified the method to include the use of skeletal reactive force as the substitute of force for pressure would have yielded predictable training and estimating results to one of ordinary skill. It is well known in the art force and pressure are proportionally related to each other. Regarding Claim 5 , Scott teaches: The method of claim 1, wherein the skeletal reactive forces are vertical ground forces (Examiner notes that this is an inherent property of skeletal reactive forces – vertical ground forces). Regarding Claim 6 , Scott teaches: The method of claim 1, wherein the human motion data comprises foot pressure data (page 1-2). Regarding Claim 7 , Scott teaches: The method of claim 1, wherein the human motion data is positioned at multiple points in a global Euclidean space (figure 1, pages 1-4) . 07-21-aia AIA Claim (s) 10, 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Scott in view of Benton et al. (Learning Invariances in Neural Networks; 34th Conference on Neural Information Processing Systems NeurIPS 2020), hereinafter Benton . Regarding Claim 10 , Scott teaches: The apparatus of claim 4, but does not explicitly mention wherein said training comprises applying random vertical ground reactive force-invariant transformations on input sequences. Benton teaches that it is known in the art that applying random invariant transformations on input sequences is a way to improve generalization properties of the neural network (abstract). It would have been obvious to one of ordinary skill in the art, before the effective filing date to have modified the apparatus to include wherein said training comprises applying random vertical ground reactive force-invariant transformations on input sequences to build a more robust neural network . 07-21-aia AIA Claim (s) 11, 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Scott in view of Goodwin IV et al. (US 20190251398 A1), hereinafter Goodwin . Regarding Claim 11 , Scott teaches: The apparatus of claim 4, wherein said training but does not explicitly mention further comprises minimizing mean squared logarithmic error. Goodwin teaches the use of minimizing mean squared logarithmic error as standard practice when training a neural network (abstract; paragraph 0116). It would have been obvious to one of ordinary skill in the art, before the effective filing date to have modified the apparatus to include minimizing mean squared logarithmic error to make the trained neural network more robust . Conclusion 07-96 AIA The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Mourot et al UnderPressure: Deep Learning for Foot Contact Detection, Ground Reaction Force Estimation and Footskate Cleanup ACMSIGGRAPH/Eurographics Symposium on Computer Animation 2022 (Year: 2022) Warmerdam et al. The walking surface influences vertical ground reaction force and centre of pressure data obtained with pressure-sensing Front. Digit. Health 6:1476335. (Year: 2024) Yu et al. Principal Component Analysis of the Running Ground Reaction Forces With Different Speeds Front. Bioeng. Biotechnol., 24 March 2021 (Year: 2021) Jiang et al. Estimating Vertical Ground Reaction Force during Walking Using a Single Inertial Sensor; Sensors 2020, 20, 4345; doi:10.3390/s20154345 (Year: 2020) Any inquiry concerning this communication or earlier communications from the examiner should be directed to JAY B SHAH whose telephone number is (571)272-0686. The examiner can normally be reached M-F 8-5. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jennifer Robertson can be reached at 571-272-5001. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. JAY SHAH Primary Examiner Art Unit 3791 /JAY B SHAH/Primary Examiner, Art Unit 3791 Application/Control Number: 18/730,822 Page 2 Art Unit: 3791 Application/Control Number: 18/730,822 Page 3 Art Unit: 3791 Application/Control Number: 18/730,822 Page 4 Art Unit: 3791 Application/Control Number: 18/730,822 Page 5 Art Unit: 3791 Application/Control Number: 18/730,822 Page 6 Art Unit: 3791 Application/Control Number: 18/730,822 Page 7 Art Unit: 3791 Application/Control Number: 18/730,822 Page 8 Art Unit: 3791 Application/Control Number: 18/730,822 Page 9 Art Unit: 3791 Application/Control Number: 18/730,822 Page 10 Art Unit: 3791 Application/Control Number: 18/730,822 Page 11 Art Unit: 3791
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