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 .
Information Disclosure Statement
The information disclosure statement (IDS) is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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.
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claims 1-18 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 1-18 has been analyzed to determine whether it is directed to any judicial exceptions.
Step 2A, Prong 1
Each of Claims 1-18 recites at least one step or instruction for the predication of brain age score, which is grouped as a mental process under the 2019 PEG. Accordingly, each of Claims 1-18 recites an abstract idea.
Specifically, Claims 1-18 recite receiving EEG data for a user account via a remote cloud, specifying recording conditions (eyes open or closed), and applying pre and prost data manipulations such as augmentation and channel rolling to expand a convolution receptive field and model map generation. The data is then processed with a DCNN that performs regression to output a brain age score (observation, judgment or evaluation, which is grouped as a mental process under the 2019 PEG);
Accordingly, as indicated above, each of the above-identified claims recites an abstract idea.
Step 2A, Prong
The above-identified abstract idea in each of Claims 1-18 is not integrated into a practical application under 2019 PEG because the additional elements, either alone or in combination, generally link the use of the above-identified abstract idea to a particular technological environment or field of use. More specifically, the additional elements of: a server, a PC and electrodes are generically recited computer elements in Claims 1-18 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 Claims 1-18 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., mental process and certain method of organizing human activity) using rules (e.g., computer instructions) executed by a computer (PC 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 Claims 1-18 is not integrated into a practical application under the 2019 PEG.
Accordingly, Claims 1-18 are each directed to an abstract idea under 2019 PEG.
Step 2B
None of Claims 1-18 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 PC and server, which the specification frames as generic, conventional computer components.
The above-identified additional elements are generically claimed computer components which enable the above-identified abstract idea(s) to be conducted by performing the basic functions of automating mental tasks. The courts have recognized such computer functions as well understood, routine, and conventional functions when claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity. See, Versata Dev. Group, Inc. v. SAP Am., Inc. , 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); and OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93.
Accordingly, in light of Applicant’s specification, the claimed additional elements 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 PC or server. 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 1-18 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 of Claims 1-18 is directed to applying an abstract idea as identified above on a general purpose computer without (i) improving the performance of the computer itself, or (ii) providing a technical solution to a problem in a technical field. None of Claims 1-18 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 Claims 1-18 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. When viewed as whole, the above-identified additional elements 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 1-18 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 1-18amounts to significantly more than the abstract idea itself. Accordingly, Claims 1-18are not patent eligible and rejected under 35 U.S.C. 101.
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 1-18 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.
Regarding Claims 1 and 11, the limitation “associated with a corresponding person computer (PC) device” renders the claim indefinite because of the ambiguous nature of “associated with”. It is unclear what an association is (ownership vs. access. vs. credential link). For purposes of examination the indefinite limitation has been deemed to claim where the user account is accessible on the PC.
Regarding Claims 1 and 11, the limitation “integrating a data augmentation process to the dataset” renders the claim indefinite because of the preposition “to”. The limitation is unclear because it is unclear what operation is being performed (apply vs. append vs. incorporate). For purposes of examination the indefinite limitation has been deemed to claim that the dataset itself is augmented.
Regarding Claim 1 and 11, the limitation “the automatically defined characteristics” renders the claim indefinite because the limitation lacks proper antecedent basis. It is unclear which aspects of the claim are automatically defined and how this automation predicts a brain age score. For purposes of examination the indefinite limitation has been deemed to claim that steps (A)-(E) are the automated steps used to predict brain age.
Regarding Claims 3 and 13, the limitation “enable to increase accuracy of the brain age score prediction” renders the claim define because such limitation is results oriented, and has no objective baseline or measurement context, and is grammatically ambiguous. For purposes of examination the indefinite limitation has been deemed to claim that the steps of Claim 2 provide score prediction.
Regarding Claims 4 and 14, the limitation “the feature extraction” renders the claim indefinite because the limitation lacks proper antecedent basis. For purposes of examination the indefinite limitation has been deemed to claim “a feature extraction”.
Regarding claims 6 and 16, the limitation “to the DCNN model” renders the claim indefinite because of the preposition “to”. The limitation is unclear because it is unclear what operation is being performed (apply vs. append vs. incorporate). For purposes of examination the indefinite limitation has been deemed to claim the channel rolling and model attribution is somehow modifying the DCNN model.
Regarding Claims 7 and 17, the limitation “the respective field”, “the first convolution layer” and “the network” renders the claim indefinite because the limitation lacks proper antecedent basis. For purposes of examination the indefinite limitation has been deemed to claim “a respective field”, “a first convolution layer” and where “the network” means the DCNN model.
Regarding Claims 8 and 16, the limitation “enable to identifying and highlight EEG segments” renders the claim define because such limitation is results oriented, and has no objective baseline or measurement context, and is grammatically ambiguous. For purposes of examination the indefinite limitation has been deemed to claim that the model attribution being performed identifies and highlights the respect EEG segments.
Regarding Claims 9 and 11, the limitation “a cloud-based service is provided to implement … through the DCNN model” renders the claim indefinite because the relationship between the cloud-based service, the providing and implementing, and what is meant by “through” the DCNN is unclear. The pipeline of information, or what is bring done to the information is unclear. For purposes of examination the indefinite limitation has been deemed to claim where the cloud-based service states that augmentation process by way of the DCNN model.
Regarding Claims 10 and 18, the limitation “enable generation of activation maps” renders the claim define because such limitation is results oriented, and has no objective baseline or measurement context, and is grammatically ambiguous. For purposes of examination the indefinite limitation has been deemed to claim that at least one aspect of the invention allows for generation of maps (such as EEG data, which could be used to map the maps).
Regarding Claims 10 and 18, the limitation “activation maps” is used twice, and it is unclear if each of the claimed maps are the same map. For purposes of examination the indefinite limitation has been deemed to claim that the second instance of “activation maps” should read “the activation maps”.
Regarding Claims 10 and 19, the limitation “wherein activation maps may be used as an alternative to more widespread methods that estimate feature importance for deep learning models” is indefinite because “may be” makes it unclear if the claim language following the statement has patentable weight (or is optional and not necessary) and “widespread” and “importance” are terms of degrees that are not defined by the claims and comparative, non-limiting language. For purposes of examination the indefinite limitation has been deemed to claim where the activation maps are capable of being used for other purposes.
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.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1-5 and 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over “Predicting Age From Brain EEG Signals – A Machine Learning Approach” to Al Zoubi et al. (hereinafter, Al Zoubi) in view of US 20150351655 A1 to Coleman and “Data augmentation for learning predictive models on EEG: a systematic comparison” to Rommel, and further in view of “EEGNet: a compact convolutional neural network for EEG-based brain–computer interfaces” to Lawhern et al. (hereinafter, Lawhern).
Regarding Claims 1-4, Al Zoubi discloses a patient-specific brain age score prediction method comprising inter alia:
(B) providing at least one dataset of EEG measurements corresponding to a human subject (Al Zoubi uses human EEG datasets to predict age, see Abstract “…we can predict the chronological age and obtain BrainAGE estimates using a rigorous ML framework with a novel and extensive EEG features extraction.”);
(E) processing the dataset of EEG measurements wherein processing comprises a regression process (The task is framed as regression to chronological age (continuous target), see Machine Learning Methods at Page 4 for discussion of “regression algorithms” with evaluation by MAE/R2, see RESULTS at Page 7);
(F) predicting a brain age score of the human subject based on the automatically defined characteristics of the data set of EEG measurements of the human subject (The BrainAGE-style metrics are directly predicted from EEG, see Abstract “…we can predict the chronological age and obtain BrainAGE estimates using a rigorous ML framework with a novel and extensive EEG features extraction.”),
taking EEG measurements using resting state eyes closed condition for the human subject (see Introduction, Page 2, “The beta relative power was positively correlated with age for older subjects for resting with eye closed condition.”); and taking EEG measurements using resting state eyes open conditions for the human subject (see EEG Recording, Page 3 “The participants were instructed to relax and keep their eyes open and fixate on a cross.”, “Their results showed accuracy of R2 = 0.60 for eyes open and R2 = 0.48 for eyes closed.”),
wherein using of both resting state eyes open (see EEG Recording, Page 3 “The participants were instructed to relax and keep their eyes open and fixate on a cross.”) and eyes closed (see EEG Recording, Page 3 “The participants were instructed to relax and keep their eyes open and fixate on a cross.”, “Their results showed accuracy of R2 = 0.60 for eyes open and R2 = 0.48 for eyes closed.”) conditions for EEG measurements enable to increase accuracy of the brain age score prediction for the human subject,
wherein a number of electrodes used for EEG measurements ranges between 8 and 24 (see EEG Recording, “EEG signals were recorded simultaneously with fMRI using a 32-channel MR-compatible EEG system…” ), and
enabling generation of activation maps for EEG signals (Al Zoubi discloses that the generation of EEG signal maps is enabled, because EEG signals are recorded, and the claim does not set forth any metes and bounds to what necessarily provides the enabling), wherein activation maps may be used as an alternative to more widespread methods that estimate feature importance for deep learning models (The enabled maps of Al Zoubi are capable of being used as an alternative, because they are capable of being created and used as an alternative to more widespread claimed methods).
Therefore, Al Zoubi discloses where EEG measurements, processing by the use of regression framing and prediction of an age/BrainAGE output.
Al Zoubi discloses the claimed invention except for expressly disclosing (A) providing at least one user account managed by at least one remote server, wherein the user account is associated with a corresponding personal computing (PC) device, (C) integrating a data augmentation process to the dataset to provide an augmented dataset, wherein the augmented dataset is an increased size dataset of the EEG measurements, and (D) inputting the augmented dataset to a deep convolutional neural network (DCNN) model.
However, Coleman teaches the limitations in (A) including a cloud-based user profile and accounts and a server-side machine learning processing of neurologic and EEG data, returned through the user’s profile (see paragraphs [0131] and [0132]) and a corresponding PC device (paragraph [0064]), and Rommel teaches the limitations in (C) including the systematic evaluation of 13 EEG augmentations (see Abstract).
One having an ordinary skill in the art at the time the invention was filed would have found it obvious to modify brain age score prediction method and dataset of Al Zoubi to include the user account, remote server and PC of Coleman and the augmentation of Rommel as Coleman teaches at paragraph [0127] that managing data on a cloud database would have allowed for processing and analysis and further teaches at paragraph [0128] that providing the data to a PC would have enhanced the user’s experience and Rommel teaches in the Abstract that augmentation improves accuracy.
The combination of Al Zoubi, Coleman and Rommel teach the limitation in (D), including the augmented dataset as set forth and cited above and Al Zoubi further teaches classic machine learning. However, the combination of Al Zoubi, Coleman and Rommel do not expressly disclose (D) inputting the augmented dataset to a deep convolutional neural network (DCNN) model that integrates the feature extraction and regression processes into a single automated architecture. Lawhern teaches a deep convolution network design for EEG, using single temporal and depthwise and spatial convolutions across channels, and provides formatting, training and model visualization examples (see Abstract). One having an ordinary skill in the art at the time the invention was filed would have found it obvious to modify the classic machine learning the augmented dataset of Al Zoubi, Coleman and Rommel with the DCNN model of Lawhern, as Lawhern teaches in the Abstract that DCNN achieves high performance.
Allowable Subject Matter
Claims 6-9 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. The prior art of record (Al Zoubi, Coleman, Rommel, Lawhern) fail to disclose, teach or fairly suggestion, in combination, the channel rolling process and model attribution algorithm as set forth in Claim 6. The cited references either disclose EEG age prediction without these steps and disclose attribution without the claimed pre-model channel rolling and post-model attribution algorithm.
Claim 11 would be allowable if rewritten or amended to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, set forth in this Office action. The prior art of record (Al Zoubi, Coleman, Rommel, Lawhern) fail to disclose, teach or fairly suggestion, in combination, the channel rolling process and model attribution algorithm as set forth in Claim 11. The cited references either disclose EEG age prediction without these steps and disclose attribution without the claimed pre-model channel rolling and post-model attribution algorithm.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SEAN PATRICK DOUGHERTY whose telephone number is (571)270-5044. The examiner can normally be reached 8am-5pm (Pacific Time).
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/SEAN P DOUGHERTY/ Primary Examiner, Art Unit 3791