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 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 1, 9, and 16 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.
Claim 1 recites the limitation “an optimal state.” The optimal state recited is a relative term which does not clearly establish metes and bounds. For the purposes of this action, an optimal state is interpreted as the proper operation of an IoT device.
Concerning claims 9 and 16, see the rejection of claim 1.
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.
Claims 7 and 14 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.
Regarding computer implemented functional limitations, MPEP §2161.01 (I) states:
“Similarly, original claims may lack written description when the claims define the invention in functional language specifying a desired result but the specification does not sufficiently describe how the function is performed or the result is achieved. For software, this can occur when the algorithm or steps/procedure for performing the computer function are not explained at all or are not explained in sufficient detail (simply restating the function recited in the claim is not necessarily sufficient). In other words, the algorithm or steps/procedure taken to perform the function must be described with sufficient detail so that one of ordinary skill in the art would understand how the inventor intended the function to be performed.”
Claim 7 of the present application requires the following computer implemented functional steps:
“training, using the historical user action data, a machine learning model to identify a plurality of actions that a plurality of users require assistance performing”
“generating, by the machine learning model and based on the training, a guidance corpus for assisting users when performing the plurality of actions”
Regarding limitation a that describes the functional result of training off of historical user data using a machine learning model, Applicant’s specifications states in par. [0043], “A machine learning model undergoes training with a specific algorithm, receiving inputs to make predictions, also known as predicted outputs or outputs. The model includes a representation or artifact comprising parameter values (theta values) used by the algorithm to generate predictions. Training involves determining these theta values, and their structure depends on the algorithm employed.” This is a recitation of a functional result without setting forth any particular steps or algorithms that achieve the result. Applicant states a machine learning model is trained to generate predictions, but does not disclose any steps, configurations, details, etc. that actually obtains the claimed result.
Other portions of the specification that discuss the functional results of the machine learning model can be found in par. [0035, 0063].
Regarding limitation b that describes generating a guidance corpus using a machine learning model, Applicant’s specification states in par. [0063]: “The guidance corpus may be generated by machine learning. For example, this may include collecting historical user action data from a plurality of IoT devices; training, using the historical user action data, a machine learning model to identify a plurality of actions that a plurality of users require assistance performing; and generating, by the machine learning model and based on the training, a guidance corpus for assisting users when performing the plurality of actions.” Much like the limitation a, limitation b is only described in term of functional results without any steps, configurations, details, etc. that actually obtains the claimed result. Other portions of the specification that discuss generating a guidance corpus using a machine learning model can be found in par. [0033, 0039, 0066].
In each instance above, limitations a and b are only claimed and described in terms of functional results and lack any details regarding the steps, processes, algorithms, etc. that accomplish the claimed and disclosed results.
Furthermore, when determining the requisite level of detail necessary to show Applicant had possession of the claimed invention, the level of complexity and predictability of the technology must be taken into account (§2161.01 (I)):
“The level of detail required to satisfy the written description requirement varies depending on the nature and scope of the claims and on the complexity and predictability of the relevant technology. Ariad, 598 F.3d at 1351, 94 USPQ2d at 1172; Capon v. Eshhar, 418 F.3d 1349, 1357-58, 76 USPQ2d 1078, 1083-84 (Fed. Cir. 2005).”
In this regard, Applicant claims the training and use of a machine learning model; and the claims and specification fail to disclose any details of any particular or exemplary machine learning models, feature extractors or classifiers that can be used. Therefore, the broadest, reasonable interpretation of “machine learning model” in the claims would encompass any-and-all possible machine learning models, presently known and unknown. Likewise for the feature extractors and classifiers. Machine learning is a highly complex field on the cutting-edge of technology that is also highly unpredictable. Depending on a model chosen, the data set used to train said model and ultimately the inputs fed to said model during use (for example), the results for even one chosen machine learning algorithm would unpredictably vary from one input data set to another. Compound that with the task of comparing said training, input and results from one model to a disparate model, even more unpredictability is injected into the problem of selecting and identifying an accurate model. Therefore, due to the complexity and unpredictability in the relevant field of machine learning models, the level of detail necessary to provide written description support for the claimed invention is relatively high, wherein the process as claimed encompasses: training the machine learning model with data using an undisclosed algorithm and using an undisclosed machine learning model that generates a guidance corpus uses an undisclosed feature extraction process to update the machine learning model in an undisclosed way.
Additionally, MPEP §2161.01 states a flow chart can be a tool to provide written description support:
““When examining computer-implemented functional claims, examiners should determine whether the specification discloses the computer and the algorithm (e.g., 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 possessed the claimed subject matter at the time of filing. An algorithm is defined, for example, as "a finite sequence of steps for solving a logical or mathematical problem or performing a task." Microsoft Computer Dictionary (5th ed., 2002). Applicant may "express that algorithm in any understandable terms including as a mathematical formula, in prose, or as a flow chart, or in any other manner that provides sufficient structure." Finisar Corp. v. DirecTV Grp., Inc., 523 F.3d 1323, 1340, 86 USPQ2d 1609, 1623 (Fed. Cir. 2008) (internal citation omitted).”
However, the provided flowchart in Fig. 6 has the same deficiencies highlighted in the previously cited and discussed paragraphs. The flow chart only provides generic labels on displayed boxes with little to no detail regarding how the extraction and classification processes are accomplished and little to no details on the steps, processes, algorithms the machine learning model uses to produce the claimed results. Fig. 6 in essence is a very broad depiction of black-box algorithms.
Lastly, the Reviewer notes that given enough time and resources, it could be argued that one skilled in the art could potentially figure out a combination of classifiers, feature extractors and machine learning models to produce outputs that would meet the claimed functional results. However, as noted in §2161.01:
“It is not enough that one skilled in the art could write a program to achieve the claimed function because the specification must explain how the inventor intends to achieve the claimed function to satisfy the written description requirement. See, e.g., Vasudevan Software, Inc. v. MicroStrategy, Inc., 782 F.3d 671, 681-683, 114 USPQ2d 1349, 1356, 1357 (Fed. Cir. 2015)”
This is not a question of enablement but instead is a question of whether Applicant as provided sufficient detail to “reasonably conveys to those skilled in the art that the inventor had possession of the claimed subject matter as of the filing date” (MPEP §2161.01). Given the totality of the record as discussed above, it is asserted that the invention as claimed lack adequate written description support.
Concerning claim 14, see the rejection of claim 7.
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.
Regarding claim 1, analyzed as representative claim:
[Step 1] Claim(s) 1-20 are drawn to statutory categories of invention of machine and/or method.
[Step 2A — Prong 1] Regarding claim 1, the claim recites a series of steps which can practically be performed by one or more humans through mathematical concepts, and/or mental process (i.e. (See MPEP 2106.04(a)(2) (III). See underlined portions below.
Claim 1 recites: A computer-implemented method comprising:
receiving a set of actions that a user requires assistance performing;
identifying one or more Internet of Things (IoT) devices associated with the user;
analyzing real-time data from the one or more IoT devices to determine a contextual surrounding of the user;
determining, in response to the analyzing, that a first contextual surrounding matches a first action of the set of actions that the user requires assistance performing;
determining, based on analyzing a current state of the user from the real-time data, if the user is in an optimal state to receive guidance when performing the first action;
generating, in response to the user being in the optimal state, guidance for assisting the user to perform the first action; and
providing the guidance to the user via the one or more IoT devices.
As indicated above, the “receiving”, “identifying”, “analyzing”, “determining”, and “generating” limitations encompass, under broadest reasonable interpretation, limitations that can practically be mathematical concepts, and/or mental process. For example, a teacher or tutor could merely gather information from a student through questions and answers, perform any mathematic analysis, and use the information to provide the guidance and/or feedback described. In other words, the underlined portions could have been done by a teacher using mental processes and mathematical concepts using pen and paper to provide the guidance described. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind and/or the utilization of mathematical calculations, then it falls within the “mental processes” and “mathematical concepts” grouping(s) of abstract ideas. Accordingly, the claim encompasses an abstract idea.
[Step 2A – Prong 2] The claim fails to recite additional limitations to integrate the abstract idea into a practical application. The claim, under broadest reasonable interpretation, does not integrate the abstract idea into a practical application (See MPEP 2106.05(g)). If generic computing, add this: Moreover, IoT devices/Augmented Reality (AR) devices is/are a generic computing component (e.g., software/application), recited at a high level of generality, such that it amounts to no more than instructions to apply the abstract idea using a generic computer and/or to implement the abstract idea in a computer environment, i.e., field of use. The claim does not recite (i) an improvement to the functionality of a computer or other technology or technical field (See MPEP 2106.05(a)), (ii) a “particular machine” to apply or use the abstract idea (See MPEP 2106.05(b)), (iii) a particular transformation of an article to a different thing or state (See MPEP 2106.05(c)), or (iv) any other meaningful limitation (See MPEP 2106.05(e)). The additional claim limitations are NOT indicative of integration into a practical application as they add insignificant extra-solution activity to the judicial exception (See MPEP 2106.05(g)).
Accordingly, the claim is directed to the abstract idea
[Step 2B] As discussed above with respect to integration of the abstract idea into a practical application, the additional limitations amount to no more than mere instructions to apply the abstract idea using a generic computer/implement the abstract idea in a computer environment and insignificant extra-solution activity. An AR device is disclosed as being conventional in US Publication 2013/0120365 to Lee et al. Taken alone, the additional elements do not amount to significantly more than the above-identified abstract idea. Looking at the limitations as an ordered combination 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 and/or implements the use of a particular machine. Their collective functions merely provide conventional computer implementation. Therefore, claim 1 is not patent eligible.
Independent claims 9 and 16 are rejected for similar reasoning. The additional limitations of “a processor; and a computer-readable storage medium communicatively coupled to the processor and storing program instructions” and ” a computer program product comprising a computer-readable storage medium” recite generic computing component (e.g., software/application), recited at a high level of generality, such that it amounts to no more than instructions to apply the abstract idea using a generic computer and/or to implement the abstract idea in a computer environment, i.e., field of use. Claims 9 and 16 fail to include additional limitations to integrate the abstract idea into a practical application or provide significantly more (i.e., an inventive concept). Accordingly, claims 9 and 16 are also not patent eligible.
Claims 2-8, 10-15, and 17-20 are dependent on claims 1, 9, and 16 respectively, and therefore recite the same abstract idea noted above. While the dependent claims have a narrower scope than the independent claims, the claims fail to recite additional limitations that would integrate the abstract idea into a practical application or provide significantly more. Particularly, the additional limitations further define the insignificant extra-solution of evaluation of the mental processes and mathematical concepts and additional iterations on the existing abstract concepts. Furthermore, these additional limitations encompass the use of generic computing component (e.g., software/application), recited at a high level of generality, such that it amounts to no more than instructions to apply the abstract idea using a generic computer and/or to implement the abstract idea in a computer environment, i.e., field of use. The dependent claims do not recite (i) an improvement to the functionality of a computer or other technology or technical field (See MPEP 2106.05(a)), (ii) a “particular machine” to apply or use the abstract idea (See MPEP 2106.05(b)), (iii) a particular transformation of an article to a different thing or state (See MPEP 2106.05(c)), or (iv) any other meaningful limitation (See MPEP 2106.05(e)).
Accordingly, the dependent claims are directed 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)(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.
Claim(s) 1-3, 5-11, 13-18, and 20 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by US Publication 2021/0327304 A1 to Buras et al. (hereinafter Buras).
Concerning claim 1,
Buras discloses a computer-implemented method comprising: receiving a set of actions that a user requires assistance performing (0101-0102);
identifying one or more Internet of Things (IoT) devices associated with the user (0102-0104, where the IOT device is considered to be and AR device);
analyzing real-time data from the one or more IoT devices to determine a contextual surrounding of the user (0104);
determining, in response to the analyzing, that a first contextual surrounding matches a first action of the set of actions that the user requires assistance performing (0106-0107, wherein the position of peripheral devices relevant to guidance is considered to be context relating to the surroundings and the identification of peripheral devices relevant to guidance is considered to be matching as broadly claimed);
determining, based on analyzing a current state of the user from the real-time data, if the user is in an optimal state to receive guidance when performing the first action (0099-0101, see the 112b rejection above);
generating, in response to the user being in the optimal state, guidance for assisting the user to perform the first action (0099-0101, see the 112b rejection above); and
providing the guidance to the user via the one or more IoT devices (0102-0103, Figure 1).
Concerning claim 2,
Buras discloses the one or more IoT devices is at least one of an augmented reality device, a virtual reality device, or a wearable smart device (0102-0104, Figure 1).
Concerning claim 3,
Buras discloses the guidance is provided to the user as a visual simulation via a display on the one or more IoT devices (0104).
Concerning claim 5,
Buras discloses the guidance is provided to the user as audio content via a speaker of the one or more IoT devices (0282, 0370, wherein an audio module requires a speaker).
Concerning claim 6,
Buras discloses the set of actions that a user requires assistance performing is chosen from a group of actions consisting of:
a speed measurement of one or more objects within the contextual surrounding of the user;
a speed measurement of the user with respect to one or more objects within the contextual surround of the user;
a distance measurement between two or more objects within the contextual surrounding of the user;
a geographic measurement of an area within the contextual surrounding of the user;
an assessment of volumetric space for receiving one or more objects within the contextual surrounding of the user; and
a mapping of one or more object within the contextual surrounding of the user (0107-0108, wherein the tracking of one or more portions of the medical equipment system described in Buras is considered to be a distance measurement between two or more objects within the contextual surrounding of the user).
Concerning claim 7,
Buras discloses collecting historical user action data from a plurality of IoT devices (0114, 0121-0124);
training, using the historical user action data, a machine learning model to identify a plurality of actions that a plurality of users require assistance performing (0114, 0121-0124); and
generating, by the machine learning model and based on the training, a guidance corpus for assisting users when performing the plurality of actions (0169-0171, The guidance corpus, as broadly claimed, is interpreted to include the iteration of the weights for the machine learning model).
Concerning claim 8,
Buras discloses monitoring the real-time data to determine if the user has successfully completed the first action according to the guidance (0150); and
in response to identifying that the user has successfully completed the first action according to the guidance, updating the guidance corpus with the generated guidance (0169-0171, The guidance corpus, as broadly claimed, is interpreted to include the iteration of the weights for the machine learning model).
Concerning claims 9-11, 13-18, and 20, see the rejection of claims 1-3 and 5-8.
Claim Rejections - 35 USC § 103
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.
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.
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.
Claim(s) 4, 12, and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over US Publication 2021/0327304 A1 to Buras et al. in view of US Publication 2019/0130788 A1 to Seaton (hereinafter Seaton).
Concerning claim 4,
Buras does not disclose the one or more IoT devices is at least one of a virtual reality device or an augmented reality device, and wherein providing the guidance to the user comprises displaying a gamified version of the guidance to the user.
Seaton teaches the one or more IoT devices is at least one of a virtual reality device or an augmented reality device, and wherein providing the guidance to the user comprises displaying a gamified version of the guidance to the user (0030-0031, 0052).
It would have been obvious for one with ordinary skill in the art before the effective filing date of the claimed invention to incorporate the gamification from the AR training device from Seaton with the AR medical guidance apparatus from Buras as both devices disclose AR based training and education. The gamification described in Seaton would improve the reward system for the AR medical guidance apparatus of Buras, increasing retention and focus.
Concerning claims 12 and 19, see the rejection of claim 4.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ISHAYU SINGH whose telephone number is (571)272-3179. The examiner can normally be reached Flex.
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/I.S./Examiner, Art Unit 3715
/DMITRY SUHOL/Supervisory Patent Examiner, Art Unit 3715