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 .
Abstract
The abstract of the disclosure is objected to because on the sixth line (as presented in corresponding publication WO 2023/028523 A1), --on-- or --upon-- should be inserted after “part”. A corrected abstract of the disclosure is required and must be presented on a separate sheet, apart from any other text (MPEP § 608.01(b)).
Specification
The disclosure is objected to because of the following informalities: In paragraph 0002, second line, “point” should be --joint--. In paragraph 0003, second to last line, “point” should be --joint--. In paragraph 0022, last line, there are two right braces “}” but only one left brace “{“. In paragraph 0027, sixth line, “then” should read --than--. In paragraph 0032, fourteenth line, “is_unbalance′” should be replaced by --′is_unbalance′--, as it is on the nineteenth line of said paragraph. In paragraph 0039, third to last line, “an” should be --and--. In paragraph 0044, third to last line, “where” should be replaced by --were--. In paragraph 0055, sixth line, “provide.” lacks proper grammatical syntax. Appropriate correction is required.
Claim Objections
Claims 2, 4, and 16 are objected to because of the following informalities: In claim 2, line 2, “transform” should apparently be --transformation--. In claim 4, line 1, “point” should read --joint--. In claim 16, line 1, “point” should be --joint--. Appropriate correction is required.
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.
Claims 1-9 and 11-16 are rejected under 35 U.S.C. 102(a)(1) as being clearly anticipated by Wu et al., CN 107397649 A, which discloses a method and a system comprising generating muscle model parameters (muscle lengths, moment arms, etc.) by a musculoskeletal kinematic transformation implemented by a first artificial neural network in the form of a support vector machine (Figure 3; machine translation: page 3, third and fourth full paragraphs; page 4, steps 1-3; note: attached copy of machine translation text and paragraphs are shifted downwardly a few lines relative to examiner’s printed copy), the muscle model parameters based in part upon EMG sensor inputs from various arm muscles [Figure 2; page 4, fourth paragraph (lines 4-9); page 5, second paragraph]; generating, from the muscle model, physics engine parameters (e.g., joint angles) based partly on the muscle model parameters (page 3, third through fifth and seventh full paragraphs; page 4, steps 1-3; page 5, second paragraph); and generating a physics engine transformation implemented by a second artificial neural network involving a radial basis function neural network based partly on the physics engine parameters (abstract; page 3, first and fifth through sixth full paragraphs; bottom of page 4, steps 4-5; page 5, second paragraph), the physics engine transformation representing segment dynamics and interactions with the environment via output torques (Figure 1; page 3, second full paragraph and last four paragraphs; bottom of page 6 through page 7).
Regarding claims 2, 5, and 13, the physics engine transformation controls a sensorimotor mechanism with torque controllers 3 and 4 (abstract; Figure 1; page 2; page 4, lines 4-9; page 7). Regarding claims 3-4 and 15-16, the “upper limb musculoskeletal model” includes joints with degree(s) of freedom and muscles with positions and lengths so as to define moment arms (page 4, step 1; page 5, middle lines). Regarding claims 6 and 14, the physics engine parameters comprise neural activity [abstract (“electromyogram signal fatigue characteristics”); page 3, second and seventh full paragraphs; page 4, step 5; page 5, second paragraph; page 7, middle portions]. Regarding claims 7 and 12, the sensor inputs comprise surface EMG signals (Figure 2; page 4, step 2; page 5, line 9). Regarding claims 8-9, training datasets for the first ANN (support vector machine, which is a type of supervised learning algorithm) are generated using an approximation of musculoskeletal relationships, with “different levels of muscle fatigue degree” involved in predicting joint flexion and extension intent and rehabilitation training (page 3, second full paragraph) and the musculoskeletal model incorporating test data of a particular subject (page 4, eight paragraph; page 5, second paragraph). Regarding claim 11, at line 1, “for prosthetic control” is functional in nature (MPEP § 2114) and is deemed to merely state the purpose or intended use of the invention (MPEP § 2111.02); the Wu et al. system is capable of working with upper limb assist devices and arm prostheses.
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 10 is rejected under 35 U.S.C. 103 as being unpatentable over Wu et al., CN 107397649 A. The artificial neural networks having a latency of less than 20 milliseconds would have been obvious in order to quickly respond in “real-time” (abstract, sixth line) to changes in user intent and to accommodate a large number of EMG inputs from the various arm muscles and data from other components, with the ordinary practitioner having been left to select appropriate ANN modules or processors, many of which were quite fast at the effective filing date of the instant invention.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to David H. Willse, whose telephone number is 571-272-4762. The examiner can normally be reached on Monday through Thursday. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor Melanie Tyson can be reached at telephone number 571-272-9062. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/DAVID H WILLSE/ Primary Examiner, Art Unit 3774
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