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 .
Claim Objections
Claim 9 is objected to because of the following informalities:
Slight rewording is suggested for claim 10’s preamble. Examiner suggests amending “A non-transitory recording medium recording a learning program for cause a computer to execute …” to “A non-transitory recording medium recording a learning program causing a computer to execute…” to clearly disclose details of the preamble.
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 1-9 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.
In claims 1, 8, and 9, it is unclear what “generate an estimation model by learning relationships information on the lower limbs and index value of physical condition for each of the plurality of users through a machine learning” is intended to mean and how much the claim limitation intends to cover, as “learning device” and “learning system” are disclosed in the Applicant’s Specification but not “machine learning” and what “performing a machine learning” entails.
Claim 2 recites the limitation "geometric mode" in line 25 of page 1. There is insufficient antecedent basis for this limitation in the claim.
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 1-9 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Each of Claims 1-9 has been analyzed to determine whether it is directed to any judicial exceptions.
Step 2A, Prong 1
Each of Claims 1-9 recites at least one step or instruction for mathematical calculations, which is grouped as a mathematical concept under the 2019 PEG. The claimed limitation involves a generic computer carrying out mathematical calculations without demonstrating the computer into a practical application. Accordingly, each of Claims 1-9 recites an abstract idea.
Specifically, Claim 1 recites:
A memory;
A processor;
acquire time-series data of sensor data for a plurality of users, wherein the time-series data of the sensor data is related to motion of a foot (Insignificant Extra-Solution Activity, see MPEP 2106.05(g));
perform a measurement of lower limbs by using the time-series data of the sensor data for each of the plurality of users, based on a geometric model on which a constraint condition related to motion of the lower limbs is imposed (mathematical calculations, which is grouped as a mathematical concept under the 2019 PEG); and
generate an estimation model by learning relationships information on the lower limbs and index value of physical condition for each of the plurality of users through a machine learning, wherein the information on the lower limbs is a result of the measurement of the lower limbs, and the estimation model estimates the index value of the physical condition from information on the lower limbs (mathematical calculations, which is grouped as a mathematical concept under the 2019 PEG).
Claims 8 and 9 provide parallel limitations.
Examiner notes that claim limitations include sensor data being used to perform the measurement. However, it is further noted that claims 1-9 are related to data processing without claiming any sensing elements.
Accordingly, as indicated above, each of the above-identified claims recites an abstract idea.
Further, dependent Claims 2-7 merely include limitations that either further define the abstract idea (and thus don’t make the abstract idea any less abstract) or amount to no more than generally linking the use of the abstract idea to a particular technological environment or field of use because they’re merely incidental or token additions to the claims that do not alter or affect how the process steps are performed.
Step 2A, Prong 2
The above-identified abstract idea in each of independent Claims 1 (and its respective dependent Claims 2-7), 8, and 9 is not integrated into a practical application under 2019 PEG because the additional elements (identified above in independent Claim 1), either alone or in combination, generally link the use of the above-identified abstract idea to a particular technological environment or field of use. Examiner notes that claims 8 and 9 fail to positively claim additional elements. More specifically, the additional elements of: A memory and a processor are generically recited computer elements in independent Claim 1 (and its respective dependent claims) which do not improve the functioning of a computer, or any other technology or technical field. Nor do these above-identified additional elements serve to apply the above-identified abstract idea with, or by use of, a particular machine, effect a transformation or apply or use the above-identified abstract idea in some other meaningful way beyond generally linking the use thereof to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception. Furthermore, the above-identified additional elements do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer. For at least these reasons, the abstract idea identified above in independent Claims 1, 8, and 9 (and their respective dependent claims) is not integrated into a practical application under 2019 PEG.
Moreover, the above-identified abstract idea is not integrated into a practical application under 2019 PEG because the claimed method and system merely implements the above-identified abstract idea (e.g., mathematical concepts) using rules (e.g., instructions) executed by a computer (e.g., processor as claimed). In other words, these claims are merely directed to an abstract idea with additional generic computer elements which do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer. Additionally, Applicant’s specification does not include any discussion of how the claimed invention provides a technical improvement realized by these claims over the prior art or any explanation of a technical problem having an unconventional technical solution that is expressed in these claims. That is, like Affinity Labs of Tex. v. DirecTV, LLC, the specification fails to provide sufficient details regarding the manner in which the claimed invention accomplishes any technical improvement or solution. Thus, for these additional reasons, the abstract idea identified above in independent Claims 1, 8, and 9 (and their respective dependent claims) is not integrated into a practical application under the 2019 PEG.
Accordingly, independent Claims 1, 8, and 9 (and their respective dependent claims) are each directed to an abstract idea under 2019 PEG.
Step 2B
None of Claims 1-9 include additional elements that are sufficient to amount to significantly more than the abstract idea for at least the following reasons.
These claims require the additional elements of: A memory and a processor, as recited in independent claim 1.
Per Applicant’s specification, the term “processor” is described as being responsible for developing the program stored in the auxiliary storage device or the like, in the main storage device, executing the program developed in the main storage device, and executing control and processing according to the present example embodiment [see in ¶ 0153] and the term “memory” can be “a dynamic random access memory (DRAM)” and “a nonvolatile memory such as a magnetoresistive random access memory (MRAM) may be configured/added as the main storage device” [see in ¶ 0154].
Accordingly, in light of Applicant’s specification, the claimed terms “processor” and “memory” are reasonably construed as a generic computing device. Like SAP America vs Investpic, LLC (Federal Circuit 2018), it is clear, from the claims themselves and the specification, that these limitations require no improved computer resources, just already available computers, with their already available basic functions, to use as tools in executing the claimed process.
Furthermore, Applicant’s specification does not describe any special programming or algorithms required for the processor. This lack of disclosure is acceptable under 35 U.S.C. §112(a) since this hardware performs non-specialized functions known by those of ordinary skill in the computer arts. By omitting any specialized programming or algorithms, Applicant's specification essentially admits that this hardware is conventional and performs well understood, routine and conventional activities in the computer industry or arts. In other words, Applicant’s specification demonstrates the well-understood, routine, conventional nature of the above-identified additional elements because it describes these additional elements in a manner that indicates that the additional elements are sufficiently well-known that the specification does not need to describe the particulars of such additional elements to satisfy 35 U.S.C. § 112(a) (see Berkheimer memo from April 19, 2018, (III)(A)(1) on page 3). Adding hardware that performs “‘well understood, routine, conventional activit[ies]’ previously known to the industry” will not make claims patent-eligible (TLI Communications).
The recitation of the above-identified additional limitations in Claims 1-9 amounts to mere instructions to implement the abstract idea on a computer. Simply using a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); and TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Moreover, implementing an abstract idea on a generic computer, does not add significantly more, similar to how the recitation of the computer in the claim in Alice amounted to mere instructions to apply the abstract idea of intermediated settlement on a generic computer.
A claim that purports to improve computer capabilities or to improve an existing technology may provide significantly more. McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314-15, 120 USPQ2d 1091, 1101-02 (Fed. Cir. 2016); and Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335-36, 118 USPQ2d 1684, 1688-89 (Fed. Cir. 2016). However, a technical explanation as to how to implement the invention should be present in the specification for any assertion that the invention improves upon conventional functioning of a computer, or upon conventional technology or technological processes. That is, the disclosure must provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. Here, Applicant’s specification does not include any discussion of how the claimed invention provides a technical improvement realized by these claims over the prior art or any explanation of a technical problem having an unconventional technical solution that is expressed in these claims. Instead, as in Affinity Labs of Tex. v. DirecTV, LLC 838 F.3d 1253, 1263-64, 120 USPQ2d 1201, 1207-08 (Fed. Cir. 2016), the specification fails to provide sufficient details regarding the manner in which the claimed invention accomplishes any technical improvement or solution.
For at least the above reasons, the device, method, and non-transitory recording medium of claims 1-9 are directed to applying an abstract idea (e.g., mathematical concept) on a general purpose computer without (i) improving the performance of the computer itself (as in McRO, Bascom and Enfish), or (ii) providing a technical solution to a problem in a technical field (as in DDR). In other words, none of Claims 1-9 provide meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that these claims amount to significantly more than the abstract idea itself.
Taking the additional elements individually and in combination, the additional elements do not provide significantly more. Specifically, when viewed individually, the above-identified additional elements in independent Claim 1 (and its dependent claims) do not add significantly more because they are simply an attempt to limit the abstract idea to a particular technological environment. That is, neither the general computer elements nor any other additional element adds meaningful limitations to the abstract idea because these additional elements represent insignificant extra-solution activity. When viewed as a combination, these above-identified additional elements simply instruct the practitioner to implement the claimed functions with well-understood, routine and conventional activity specified at a high level of generality in a particular technological environment. As such, there is no inventive concept sufficient to transform the claimed subject matter into a patent-eligible application. As such, the above-identified additional elements, when viewed as whole, do not provide meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that the claims amount to significantly more than the abstract idea itself. Thus, Claims 1-9 merely apply an abstract idea to a computer and do not (i) improve the performance of the computer itself (as in Bascom and Enfish), or (ii) provide a technical solution to a problem in a technical field (as in DDR).
Therefore, none of the Claims 1-9 amounts to significantly more than the abstract idea itself.
Accordingly, Claims 1-9 are not patent eligible and rejected under 35 U.S.C. 101 as being directed to abstract ideas implemented on a generic computer in view of the Supreme Court Decision in Alice Corporation Pty. Ltd. v. CLS Bank International, et al. and 2019 PEG.
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.
Claims 1, 2, and 5-9 are rejected under 35 U.S.C. 103 as being unpatentable over over Hagimoto et al. (JP 2008173365 A – Cited by Applicant), hereinafter Hagimoto, in view of Washizawa et al. (JP 2015195913 A – Cited by Applicant), hereinafter Washizawa, further in view of Jagannathan et al. (US 10842415 B1), hereinafter Jagannathan.
Regarding claim 1, and substantially similar limitations in claims 8 and 9, Hagimoto discloses a learning system comprising:
a memory storing instructions [memory resources 17, see in ¶ 0033]; and
a processor connected to the memory and configured to execute the instructions to [CPU 16, see in ¶ 0033; The output of the A/D converter15 is passed to the CPU 16 where predetermined calculations are performed. The CPU 16 has memory resources 17 such as ROM and RAM, see in ¶ 0033]:
acquire time-series data of sensor data for a plurality of users, wherein the time-series data of the sensor data is related to motion of a foot [see in ¶ 0009 and ¶ 0017];
perform a measurement of lower limbs by using the time-series data of the sensor data for each of the plurality of users [walking data and gait analysis, see in ¶ 0040 – ¶ 0041].
Hagimoto fails to disclose that the measurement of lower limbs is based on a geometric model on which a constraint condition related to motion of the lower limbs is imposed. Hagimoto also fails to disclose the step of generating an estimation model by learning relationships information on the lower limbs and index value of physical condition for each of the plurality of users through a machine learning, wherein the information on the lower limbs is a result of the measurement of the lower limbs, and the estimation model estimates the index value of the physical condition from information on the lower limbs.
However, Washizawa discloses However, Washizawa discloses a measurement based on a geometric model [a model angle based on a model that smoothly connects adjacent bones in the spine and the range of motion set, see in ¶ 0042] on which a constraint condition related to motion of the lower limbs is imposed [constraint conditions to determine model angle, see in ¶ 0040].
Hagimoto and Washizawa are both analogous to the claimed invention because
they are in the same field of walking analysis. Therefore, it would have been obvious to
someone of ordinary skill in the art before the filing date of the claimed invention to have
modified Hagimoto to incorporate the teachings of Washizawa and include constraint
conditions based off a geometric model in performing measurement of the lower limbs,
in order to obtain measurements of lower limb movement while taking limitations
relating to limb positions, joint angles, and range of motion into consideration.
Hagimoto, as modified, still fails to disclose the step of generating an estimation model by learning relationships information on the lower limbs and index value of physical condition for each of the plurality of users through a machine learning, wherein the information on the lower limbs is a result of the measurement of the lower limbs, and the estimation model estimates the index value of the physical condition from information on the lower limbs. However, Jagannathan discloses generating an estimation model by learning relationships information on the lower limbs and index value of physical condition for each of the plurality of users through a machine learning, wherein the information on the lower limbs is a result of the measurement of the lower limbs, and the estimation model estimates the index value of the physical condition from information on the lower limbs [see in Fig. 8; see in Col. 7, lines 8-15; see in Col. 22, lines 27-49].
Hagimoto and Jagannathan are both analogous to the claimed invention because they are in the same field of walking analysis. Therefore, it would have been obvious to someone of ordinary skill in the art before the filing date of the claimed invention to have modified Hagimoto to incorporate the teachings of Jagannathan and include that an estimation model is generated by learning relationships information on the lower limbs and index value of physical condition for each of the plurality of users using machine learning in order to effectively analyze complex movement data that involves multiple degrees of freedom. Regarding claim 2, Hagimoto, as modified, discloses the learning system according to claim 1, wherein the processor is further configured to execute the instructions to: detect a gait event from the time-series data of sensor data [see in ¶ 0009 and ¶ 0017]; and perform the measurement of the lower limbs by using the time- series data of the sensor data for a prescribed period with a timing of the gait event as a start point, based on the geometric mode [walking data and gait analysis, see in ¶ 0040 and ¶ 0041].
Regarding claim 5, Hagimoto, as modified, discloses the learning system according to claim 1, wherein the estimation model estimates the recommendation information for making decision related to health based on the index value of the physical condition [doctors and physical therapists who make health decisions (related to treatment) have access to analysis results, see in ¶ 0042; see also in ¶ 0067].
Regarding claim 6, Hagimoto, as modified, discloses the learning system according to claim 1, wherein the information on the lower limbs includes at least one of foot information, knee information, and pelvis information, the foot information is information on motion of a foot, the knee information is information on motion of a knee, and the pelvis information is information on motion of pelvis [aims to realize a gait analysis system that can measure the foot movement of a walker in three dimensions and measure and analyze the spatial movement of the swing leg without imposing any load on the walker, see in ¶ 0008].
Regarding claim 7, Hagimoto, as modified, discloses the learning system according to claim 1.
Hagimoto fails to disclose that the index of the physical condition is at least one of degree of balance, flexibility of the lower limbs, muscle tightness, gait stability and harmonic ratio.
However, Jagannathan discloses monitoring gait, stability, or balance as a health parameter of an individual [see in Col. 7, lines 35-38].
Hagimoto and Jagannathan are both analogous to the claimed invention because they are in the same field of walking analysis. Therefore, it would have been obvious to someone of ordinary skill in the art before the filing date of the claimed invention to have modified Hagimoto to incorporate the teachings of Jagannathan and include that gait, stability, or balance is monitored as a health parameter, as offsets in gait, stability, or balance can be a sign of a movement related health condition that would require treatment.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HY KHANH DOAN whose telephone number is (703)756-5434. The examiner can normally be reached Monday - Friday 8:00 a.m. - 5 p.m..
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/ERIC F WINAKUR/Primary Examiner, Art Unit 3791
/HY KHANH DOAN/ Examiner, Art Unit 3791