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 .
Response to Amendment
The amendment filed 27 July 2026 has been entered. Claim(s) 1-2, 5-9, 12-16, and 18-22 are pending in the application. Applicant’s amendments to the claims have overcome each and every rejection under 35 U.S.C. 102/103 previously set forth in the Office Action mailed 28 April 2026.
Claim Objections
Claim 21 is objected to because of the following informalities:
Claim 21, line 1 “model represented” should be “model represents”.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
Claims 1-2, 5-9, 12-16, and 18-22 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. While the instant specification describes “providing personalized therapy to caregivers of patients with dementia” (Paragraph 0050) and provides a general statement that localization of functional brain activity may enable novel treatments and assistive technologies (Paragraph 0074) and there is additional disclosure that a processor of the system may inform targeted interventions via the display of aligned mean waveforms (Paragraph 0015, 0019, 0021), there is no disclosure of “direct a localized treatment of the neurodegenerative disease according to the source in the brain” as claimed in claims 1, 8, and 15. At best, the disclosure provides for a display to present aligned mean waveforms which may serve to inform targeted therapy inventions to a caregiver, but where these interventions are not specified to be localized treatments and are not necessarily selected according to the identified source.
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 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.
Claims 1, 8, and 15 recite “obtain recordings of electrical activity arising from a brain of an animal”. It is unclear if “an animal” in this instance is the same as “an individual animal” of the previous line or if it is some other animal whose recordings are obtained to be extrapolated to other animals. The limitation is interpreted as referring to the individual animal as previously referenced in the claim.
Claims 1, 8, and 15 are unclear as to whether the “generate mean waveforms of signals from at least one condition” refers to signals from the brain of the individual animal or signals from the brains of the population of animals, whether multiple mean waveforms are created from each of the “signals” for a given “at least one condition” or if multiple mean waveforms are created and each mean waveform represents only one condition, whether the “at least one condition” refers to a condition of the waveforms (such as signals exceeding a certain peak amplitude or frequency of oscillation) or a condition such as the neurodegenerative disease (such as the presence of Alzheimer’s disease). The limitation is currently interpreted as referring to a mean waveform of brain signals from the brains of a group of animals of the population of animals, generated for each condition of at least one condition, where the condition relates to a neurodegenerative disease (e.g., the generation of a mean waveform for a group of animals each identified as having a neurodegenerative disease of interest) and which are then used to indicate a brain state of the individual animal.
Claims 2, 5-7, 9, 12-14, 16, and 18-22 are additionally rejected under 35 U.S.C. 112(b) as indefinite due to their dependence on claims 1, 8, or 15, which have been rejected as indefinite.
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.
Utilizing the two step process adopted by the Supreme Court (Alice Corp vs CLS Bank Int'l, US
Supreme Court, 110 USPQ2d 1976 (2014) and the recent 101 guideline Federal Register Vol. 84, No., Jan
2019)), determination of the subject matter eligibility under the 35 U.S.C. 101 is as follows: Specifically, the Step 1 requires claim belongs to one of the four statutory categories (process, machine, manufacture, or composition of matter). If Step 1 is satisfied, then in the first part of Step 2A (Prong One), identification of any judicial recognized exceptions in the claim is made. If any limitation in the claim is identified as judicial recognized exception, then in the second part of Step 2A (Prong Two), determination is made whether the identified judicial exception is being integrated into practical application. If the identified judicial exception is not integrated into a practical application, then in Step 2B, the claim is further evaluated to see if the additional elements, individually and in combination provide "inventive concept" that would amount to significantly more than the judicial exception. If the element and combination of elements do not amount to significantly more than the judicial recognized exception itself, then the claim is ineligible under the 35 U.S.C. 101.
Claims 1-2, 5-9, 12-16, and 18-22 are rejected under 35 U.S.C. 101.
Claim 1 is rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception, in this case an abstract idea, without significantly more. The claim recite(s) “to train a machine learning model using normative data of waveform features of historical beta wave events observed from a population of animals that include empirical or probability distributions or likelihoods of the historical beta wave events, wherein the machine learning model is trained employing one or more time- domain feature learning and extraction methods to perform prediction of clinical indication and functional brain states in which the machine learning model is configured to digitize cortical surfaces of respective brains of the population of animals via a boundary element model”, “detect beta wave events from the recordings by extracting extrema and time-domain features in unnormalized representations of the recordings, wherein the extrema and the time-domain features comprise characteristics selected from the group consisting of: a peak time, a trough time, a peak amplitude, a trough amplitude, an oscillation period, a peak width, a trough width, an inter-peak timing, and an inter-trough timing; process the beta wave events to generate a first representation of short-time segments representing a plurality of amplitude fluctuations indicating the extrema and a second representation for identifying temporal positions of the extrema in the first representation; compare statistical distributions of a plurality of feature characteristics of the beta wave events based upon the extracted extrema and the time-domain features and the first representation and the second representation; generate mean waveforms of signals from at least one condition aligned by the temporal positions assigned to one or more of peaks, troughs, and extrema of the mean waveforms to indicate a brain state of the animal from which the recordings were obtained; determine empirical distributions of the plurality of feature characteristics; simulate, via resampling, effects of alterations of the empirical distributions of at least one of the feature characteristics of the plurality of feature characteristics on the mean waveforms; localize using the empirical distributions and the simulated effects of the alterations of the empirical distributions, a source in the brain for the beta wave events associated with the neurodegenerative disease". This judicial exception is not integrated into a practical application and the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Claim 1 satisfies Step 1, namely the claim is directed to one of the four statutory classes, machine. Following Step 2A Prong one, any judicial exceptions are identified in the claims. In claim 1, the limitations “to train a machine learning model using normative data of waveform features of historical beta wave events observed from a population of animals that include empirical or probability distributions or likelihoods of the historical beta wave events, wherein the machine learning model is trained employing one or more time- domain feature learning and extraction methods to perform prediction of clinical indication and functional brain states in which the machine learning model is configured to digitize cortical surfaces of respective brains of the population of animals via a boundary element model”, “detect beta wave events from the recordings by extracting extrema and time-domain features in unnormalized representations of the recordings, wherein the extrema and the time-domain features comprise characteristics selected from the group consisting of: a peak time, a trough time, a peak amplitude, a trough amplitude, an oscillation period, a peak width, a trough width, an inter-peak timing, and an inter-trough timing; process the beta wave events to generate a first representation of short-time segments representing a plurality of amplitude fluctuations indicating the extrema and a second representation for identifying temporal positions of the extrema in the first representation; compare statistical distributions of a plurality of feature characteristics of the beta wave events based upon the extracted extrema and the time-domain features and the first representation and the second representation; generate mean waveforms of signals from at least one condition aligned by the temporal positions assigned to one or more of peaks, troughs, and extrema of the mean waveforms to indicate a brain state of the animal from which the recordings were obtained; determine empirical distributions of the plurality of feature characteristics; simulate, via resampling, effects of alterations of the empirical distributions of at least one of the feature characteristics of the plurality of feature characteristics on the mean waveforms; localize using the empirical distributions and the simulated effects of the alterations of the empirical distributions, a source in the brain for the beta wave events associated with the neurodegenerative disease" are abstract ideas as they are directed to a mental process or mathematical concept, as the comparison of statistical distributions can be performed mentally as a matter of judgment while training a machine learning model, generating mean waveforms, determining empirical distributions, simulating effects of altering distributions, and localizing a source of events based on the distributions which in their broadest reasonable interpretations may be performed as a series of mathematical calculations which may be performed in the human mind with the aid of pen and paper. With the identification of an abstract idea, the next phase is to proceed Step 2A, Prong Two, wherewith additional elements and taken as a whole, evaluation occurs of whether the identified abstract idea is integrated into a practical application.
In Step 2A, Prong Two, the claim does not recite any additional elements or evidence that amounts to significantly more than the judicial exception. Besides the abstract idea, the claim recites the additional elements “a first computing device comprising: a non-transitory machine-readable storage medium storing instructions; and a processor coupled to the non-transitory machine-readable storage medium and configured to execute the instructions”, “wherein for an individual animal the machine learning model, once trained, is applied to: obtain recordings of electrical activity arising from a brain of an animal for treatment of a neurodegenerative disease in the animal, the neurodegenerative disease selected from the group consisting of: Alzheimer's disease (AD); Dementia; and Parkinson's disease (PD)” and “direct a localized treatment of the neurodegenerative disease according to the source in the brain”. However, these components may be seen as the use of well-understood, routine, or conventional elements to perform a non-mental process in order to gather data for the mental process step and output a result of the mental process step, much like the example given in MPEP 2106.04(d)(2)(c), such that these limitations are extra-solution activity and thus do not integrate the judicial exception into a practical application. The measurement and calculation steps leads to the final limitation of “direct[ing]” such that the end result of use of the system may be any generic output, as “direct[ing]” has not been defined to have any particular meaning and may encompass any output ranging from a yes/no output reflecting whether an animal needs treatment to a particular treatment recommendation, each of which merely provides output for some outside user rather than prompting a direct action by the system itself. As this determination is not defined as requiring any further action, such as a form of prophylaxis or treatment or an improvement to a computer or other technology, the claim limitations constitute mere generation of data, in this case the measurement of data relating to extrema and temporal positions of extrema of beta wave events, such that the claim does not integrate the judicial exception into any practical application. Regarding “a processor” and the training of the machine learning model and processing of the data to be used in comparing and determining steps, the limitations amount to nothing more than an instruction to apply the abstract idea using a generic computer, which does not render an abstract idea eligible. The steps performed by the a processor are, as claimed, capable of being performed in the human mind similar to the examples given in MPEP 2106.04(a)(2)(III)(A)-(C), wherein it is described that “a claim to ‘collecting information, analyzing it, and displaying certain results of the collection and analysis’ where the data analysis steps are recited at a high level of generality such that they could practically be performed in the human mind” recites a mental process and that claims which merely use a computer as a tool to perform a mental process are not eligible when “there is nothing in the claims themselves that foreclose them from being performed by a human, mentally or with pen and paper” such as “mental processes of parsing and comparing data” when the steps are recited at a high level of generality and a computer is used merely as a tool to perform the processes. Under the broadest reasonable interpretation, the claim elements are recited with a high level of generality (as written, each claimed step of the process may be performed by a person in an undefined manner including observing the sensor readings for extrema and corresponding temporal information and then performing mathematical transformations and/or comparisons) that there are no meaningful limitations to the abstract idea. Consequently, with the identified abstract idea not being integrated into a practical application, the next step is Step 2B, evaluating whether the additional elements provide "inventive concept" that would amount to significantly more than the abstract idea.
In Step 2B, claim 1 does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The limitation of “a first computing device comprising: a non-transitory machine-readable storage medium storing instructions; and a processor coupled to the non-transitory machine-readable storage medium and configured to execute the instructions”, “wherein for an individual animal the machine learning model, once trained, is applied to: obtain recordings of electrical activity arising from a brain of an animal for treatment of a neurodegenerative disease in the animal, the neurodegenerative disease selected from the group consisting of: Alzheimer's disease (AD); Dementia; and Parkinson's disease (PD)” and “direct a localized treatment of the neurodegenerative disease according to the source in the brain”. constitutes extra-solution activity to the judicial exception, which does not amount to an inventive concept when the activity is well-understood, routine, or conventional, and are thus not indicative of integration into a practical application. The claim limitation constitutes adding a generic processor and memory, which Lee (US 20240382162 A1) describes as both well-understood, routine, or conventional in its description of a generic processor and memory (Paragraph 0072-- a dedicated processor (for example, an embedded processor) configured to perform the corresponding operation or a generic-purpose processor (for example, a CPU or an application processor) which is capable of performing the operations by executing one or more software programs stored in a memory device). As discussed above with respect to integration of the abstract idea into a practical application, the present elements amount to no more than mere indications to apply the exception.
In Summary, Claim 1 recites abstract idea without being integrated into a practical application, and does not provide additional elements that would amount to significantly more. As such, taken as a whole, the claim and is ineligible under the 35 U.S.C. 101.
Claims 8 and 15 are rejected for similar reasons.
Claims 2 and 5-7 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception, in this case an abstract idea, without significantly more. As each of these claims depends from claim 1, which was rejected under 35 U.S.C. 101 in paragraph 12 of this action, these claims must be evaluated on whether they sufficiently add to the practical application of claim 1, or comprise significantly more than the limitations of claim 1.
Besides the abstract idea of claim 1: claim 2 constitutes the addition of further elements which does not amount to an inventive concept when the activity is well-understood, routine, or conventional, and are thus not indicative of integration into a practical application. The claim limitation constitutes adding a generic processor, memory, and sensors, which Lee (US 20240382162 A1) describes as both well-understood, routine, or conventional in its description of a generic processor and memory and an electroencephalogram (Paragraph 0072-- a dedicated processor (for example, an embedded processor) configured to perform the corresponding operation or a generic-purpose processor (for example, a CPU or an application processor) which is capable of performing the operations by executing one or more software programs stored in a memory device; Paragraphs 0079-0082); claims 5-7 recite additional limitations which may be seen as abstract ideas which can be performed as mental processes using basic mathematical concepts, such as determining various extrema and time-domain features or template matching mentally or with the aid of pen and paper, and additional elements of extra-solution activity, such as the storing of data which is a generic computer function; claims 21-22 recite additional elements of extra-solution activity, in this case details of models which are seen as generic computer functions for the gathering of data to be used in the mental process steps.
The claim element of claim 1 of a system is recited with a high level of generality (as written, the actions of the processor may be carried out by a person alone or with a generic computer in any undefined manner). This limitation provides no practical application, nor does it provide meaningful limitations to the abstract idea.
Claims 9, 12-14, 16, and 18-20 are additionally rejected under 35 U.S.C. 101 for similar reasons.
Response to Arguments
Applicant's arguments filed 27 July 2026 with respect to the rejection of the claims under 35 U.S.C. 112(b) have been fully considered but they are not persuasive. While the clarity of the claims has been improved via the applicant’s amendments, it remains unclear which signals are being used to generate mean waveforms and what is being referred to as at least one condition as explained above in this action. It is recommended that the claims clarify, as necessary, when signals relate to the population of animals (or a subset of the population of animals) versus the individual animal and additionally clarify whether a condition is the same as “a neurodegenerative disease”.
Applicant's arguments filed 27 July 2026 with respect to the rejection of the claims under 35 U.S.C. 101 have been fully considered but they are not persuasive.
In particular, the applicant argues that the claims provide for improved training of machine learning models and provides for improvement for the specific treatment of prophylaxis of diseases.
However, the current claim language does not provide for a specific treatment of prophylaxis of disease as “a localized treatment” provides no particular treatment or prophylaxis and in fact appears to serve merely as an output that may at best suggest a treatment to a user.
Furthermore, the claim language of independent claims 1, 8, and 15 appears similar to Example 47, claim 2 of the July 2024 Subject Matter Eligibility Examples, which is described as ineligible as the analogous steps of training an artificial neural network based on a selected training algorithm including backpropagation and gradient descent algorithms and detecting anomalies using the trained ANN recited generic computer functions, and the later analysis of the detected anomalies are directed toward judicial exceptions. Specifically, the claimed discretizing, detecting, and analyzing steps of Example 47 claim 2 encompass mental choices or evaluations, and the claimed discretizing and training using a backpropagation algorithm and gradient descent algorithm encompasses performing mathematical calculations, where utilizing a trained machine learning model in later detection and analysis steps provides nothing more than instructions to implement an abstract idea on a generic computer. While the claims recite an output step in “directing a localized treatment”, the step merely requires a generic output and does not impose any limits on this output or require any particular use of the output.
The claims remain rejected under 35 U.S.C. 101.
Applicant’s arguments, see page 14-15 of applicant's response, filed 27 July 2026, with respect to the rejection of the claims under 35 U.S.C. 102/103 have been fully considered and are persuasive. The rejection of claims has been withdrawn.
The claims are not currently rejected under 35 U.S.C. 102/103. The prior art of the record fails to teach and/or fairly suggest, in combination with all other recited limitations, “simulate, via resampling, effects of alterations of the empirical distributions of at least one of the feature characteristics of the plurality of feature characteristics on the mean waveforms”.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ANNA ROBERTS whose telephone number is (571)272-7912. The examiner can normally be reached M-F 8:30-4:30 EST.
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/ANNA ROBERTS/ Examiner, Art Unit 3791
