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
No information disclosure statements (IDS) has been submitted by Applicant
Claim Objections
Claims 7 and 15 are objected to because of the following informalities:
Claims 7 and 15 recite the limitations
“one coupled” in line 2. Examiner notes this should be “one of the two electrode contacts coupled”
“another coupled” in line 3. Examiner notes this should be “another of the two electrode contacts coupled”
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 7, 8, 15 and 16 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.
Claims 7 and 15 recite the limitation “an individual” in line 3. Does this refer to the individual mentioned previously in claims 1 and 9, respectively?
Claims 8 and 16 recite the limitation “an individual” in line 3. Does this refer to the individual mentioned previously in claims 1 and 9, respectively?
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) as a whole, considering all claim elements both individually and in combination, do not amount to significantly more than an abstract idea. A streamlined analysis of claim 1 follows.
Regarding claim 1, the claim recites a method comprising: method comprising: acquiring, by a computing device, electroencephalography (EEG)-based features from brain activity electrical recordings of an individual. Thus, the claim is directed to a process, which is one of the statutory categories of invention
The claim is then analyzed to determine whether it is directed to any judicial exception. The following limitations set forth a judicial exception:
“acquiring, by a computing device, electroencephalography (EEG)-based features from brain activity electrical recordings of an individual; inputting, by the computing device, the EEG-based features into a deep neural network-based classifier; classifying, by the computing device using the deep neural network-based classifier,”
These limitations describe a mental process as the skilled artisan is capable of performing the judicial exception mentally, or using pen and paper. Furthermore, nothing from the claims or applicant’s accompanying specification shows that the skilled artisan would not be able to perform the judicial exception mentally, or using pen and paper.
Next, the claim as a whole is analyzed to determine whether any element, or combination of elements, integrates the identified judicial exception into a practical application.
For this part of the 101 analysis, the following additional limitations are considered:
“based on a value of the real-valued principal dimension, generating, by the computing device, a prediction of a seizure onset pro-ictal event”
These additional limitations do not integrate the judicial exception into a practical application. Rather, the additional limitations are each recited at a high level of generality such that it amounts to insignificant pre-solution and post-solution activity, e.g., mere receiving data and/or outputting.
Furthermore, the additional limitations do not add significantly more to the judicial exception as the recited limitations amount to well-known and conventional data gathering techniques in the art.
Additionally, regarding claim 9, the claim recites a system comprising: method comprising: acquiring, by a computing device, electroencephalography (EEG)-based features from brain activity electrical recordings of an individual. Thus, the claim is directed to a machine, which is one of the statutory categories of invention
The claim is then analyzed to determine whether it is directed to any judicial exception. The following limitations set forth a judicial exception:
“acquiring, by a computing device, electroencephalography (EEG)-based features from brain activity electrical recordings of an individual; inputting, by the computing device, the EEG-based features into a deep neural network-based classifier; classifying, by the computing device using the deep neural network-based classifier,”
These limitations describe a mental process as the skilled artisan is capable of performing the judicial exception mentally, or using pen and paper. Furthermore, nothing from the claims or applicant’s accompanying specification shows that the skilled artisan would not be able to perform the judicial exception mentally, or using pen and paper.
Next, the claim as a whole is analyzed to determine whether any element, or combination of elements, integrates the identified judicial exception into a practical application.
For this part of the 101 analysis, the following additional limitations are considered:
“at least one processor; and memory configured to communicate with the at least one processor; and based on a value of the real-valued principal dimension, generating, by the computing device, a prediction of a seizure onset pro-ictal event”
These additional limitations do not integrate the judicial exception into a practical application. Rather, the additional limitations are each recited at a high level of generality such that it amounts to insignificant pre-solution and post-solution activity, e.g., mere receiving data and/or outputting.
Furthermore, the additional limitations do not add significantly more to the judicial exception as the recited limitations amount to well-known and conventional data gathering techniques in the art.
Independent claim 17 is also not patent eligible for substantially similar reasons.
Dependent claims 2-8, 10-16 and 18-20 also fail to add something more to the abstract independent claims as they merely further limit the abstract idea.
Therefore, claims 1-20 are not patent eligible under 35 USC 101.
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 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.
Claims 1, 2, 9, 10, 17 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Arcot (U.S. Patent Application Document 2022/0314002) and in further view of Firouzi (U.S. Patent Application Document 2024/0225611)
Regarding claim 1, Arcot teaches a method comprising: acquiring, by a computing device, electroencephalography (EEG)-based features from brain activity electrical recordings of an individual [par. 93]; inputting, by the computing device, the EEG-based features into a neural network-based classifier [par. 102]; classifying, by the computing device using the neural network-based classifier, the EEG-based features to a real-valued principal dimension [par. 6, 103, 118]; and based on a value of the real-valued principal dimension, generating, by the computing device, a detection of an episode [par. 118, 119, 199]
However, Arcot does not teach a deep neural network-based classifier and a prediction of a seizure onset pro-ictal event
Firouzi teaches a deep neural network-based classifier [par. 353]
Therefore, it would have been prima facie obvious to a person having ordinary skill in the art when the invention was filed to modify the method as taught by Arcot, to incorporate a deep neural network-based classifier, as deep neural networks can be used as a predictive means, as evidence by Firouzi [par. 353]
Firouzi teaches a prediction of a seizure onset pro-ictal event [par. 478]
Therefore, it would have been prima facie obvious to a person having ordinary skill in the art when the invention was filed to modify the method as taught by Arcot, to incorporate a prediction of a seizure onset pro-ictal event, as seizures can result in physical injuries, including occasionally broken bones, as evidence by Firouzi [par. 478]
Regarding claims 2, 10 and 18, Arcot further teaches comprising alerting the individual of the onset episode [par. 199]
However, Arcot does not teach prediction of the seizure onset pro-ictal event
Firouzi teaches a prediction of a seizure onset pro-ictal event [par. 478]
Therefore, it would have been prima facie obvious to a person having ordinary skill in the art when the invention was filed to modify the method as taught by Arcot, to incorporate a prediction of a seizure onset pro-ictal event, as seizures can result in physical injuries, including occasionally broken bones, as evidence by Firouzi [par. 478]
Regarding claims 9 and 17, Arcot teaches a system and a non-transitory computer readable medium comprising machine readable instructions comprising: at least one processor [fig. 7, element 702; par. 136]; and memory [fig. 7, element 704; par. 136] configured to communicate with the at least one processor [par. 136], wherein the memory stores instructions that, in response to execution by the at least one processor, cause the at least one processor to perform operations comprising: acquiring, by a computing device, electroencephalography (EEG)-based features from brain activity electrical recordings of an individual [par. 93]; inputting, by the computing device, the EEG-based features into a neural network-based classifier [par. 102]; classifying, by the computing device using the neural network-based classifier, the EEG-based features to a real-valued principal dimension [par. 6, 103, 118]; and based on a value of the real-valued principal dimension, generating, by the computing device, a detection of an episode [par. 118, 119, 199].
However, Arcot does not teach a deep neural network-based classifier and a prediction of a seizure onset pro-ictal event
Firouzi teaches a deep neural network-based classifier [par. 353]
Therefore, it would have been prima facie obvious to a person having ordinary skill in the art when the invention was filed to modify the method as taught by Arcot, to incorporate a deep neural network-based classifier, as deep neural networks can be used as a predictive means, as evidence by Firouzi [par. 353]
Firouzi teaches a prediction of a seizure onset pro-ictal event [par. 478]
Therefore, it would have been prima facie obvious to a person having ordinary skill in the art when the invention was filed to modify the method as taught by Arcot, to incorporate a prediction of a seizure onset pro-ictal event, as seizures can result in physical injuries, including occasionally broken bones, as evidence by Firouzi [par. 478]
Claims 3, 11 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Arcot and Firouzi and in further view of Weffers-Albu (U.S. Patent Application Document 2018/0085000)
Regarding claims 3, 11 and 19, Arcot and Firouzi teach a method comprising: acquiring, by a computing device, electroencephalography (EEG)-based features from brain activity electrical recordings of an individual
However, Arcot and Firouzi do not teach the seizure onset pro-ictal event is predicted to occur at least 30 minutes before the individual experiences a seizure
Weffers-Albu teaches the seizure onset pro-ictal event is predicted to occur at least 30 minutes before the individual experiences a seizure [par. 87]
Therefore, it would have been prima facie obvious to a person having ordinary skill in the art when the invention was filed to modify the method as taught by Arcot and Firouzi, to incorporate the seizure onset pro-ictal event is predicted to occur at least 30 minutes before the individual experiences a seizure, for determining epilepsy triggers, as evidence by Weffers-Albu [par. 93]
Claims 4, 12 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Arcot and Firouzi and in further view of Tyler (U.S. Patent Application Document 2012/0289869)
Regarding claims 4, 12 and 20, Arcot and Firouzi teach a method comprising: acquiring, by a computing device, electroencephalography (EEG)-based features from brain activity electrical recordings of an individual
Arcot further teaches the brain activity electrical recordings comprise continuous EEG electrical recordings [par. 71]
However, Arcot and Firouzi do not teach thalamocortical EEG electrical recordings
Tyler teaches thalamocortical EEG electrical recordings [par. 93]
Therefore, it would have been prima facie obvious to a person having ordinary skill in the art when the invention was filed to modify the method as taught by Arcot and Firouzi, to incorporate thalamocortical EEG electrical recordings, as thalamocortical oscillations are known to occur during wakefulness or alertness, as evidence by Tyler [par. 93]
Claims 5, 6, 13 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Arcot and Firouzi and in further view of Opie (U.S. Patent Application Document 2023/0302282)
Regarding claims 5 and 13, Arcot and Firouzi teach a method comprising: acquiring, by a computing device, electroencephalography (EEG)-based features from brain activity electrical recordings of an individual
However, Arcot and Firouzi do not teach the EEG-based features are classified based on an EEG-based signature
Opie teaches the EEG-based features are classified based on an EEG-based signature [par. 93]
Therefore, it would have been prima facie obvious to a person having ordinary skill in the art when the invention was filed to modify the method as taught by Arcot and Firouzi, to incorporate the EEG-based features are classified based on an EEG-based signature, as specific signatures indicate seizures, as evidence by Opie [par. 93]
Regarding claims 6 and 14, Opie further teaches the EEG-based signature comprises a power-based signature of the seizure onset pro-ictal event [par. 93].
Therefore, it would have been prima facie obvious to a person having ordinary skill in the art when the invention was filed to modify the method as taught by Arcot and Firouzi, to incorporate the EEG-based signature comprises a power-based signature of the seizure onset pro-ictal event, as specific signatures indicate seizures and to provide “responsive neurostimulation” when the intracorporeal target is stimulated in response to a detected electrophysiological signal associated or correlated with the onset of epileptic seizures, as evidence by Opie [par. 93, 95]
Claims 7, 8, 15 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Arcot and Firouzi and in further view of Burton (U.S. Patent Application Document 2021/0169417)
Regarding claims 7 and 15, Arcot and Firouzi teach a method comprising: acquiring, by a computing device, electroencephalography (EEG)-based features from brain activity electrical recordings of an individual
However, Arcot and Firouzi do not teach acquiring the brain activity electrical recordings from two electrode contacts with one coupled to a seizure onset zone of the brain of an individual and another coupled to a thalamus structure of the brain of the individual
Burton teaches acquiring the brain activity electrical recordings from two electrode contacts with one coupled to a seizure onset zone of the brain of an individual and another coupled to a thalamus structure of the brain of the individual [par. 617-635 Examiner notes these paragraphs mention all EEG electrode placements]
Therefore, it would have been prima facie obvious to a person having ordinary skill in the art when the invention was filed to modify the method as taught by Arcot and Firouzi, to incorporate acquiring the brain activity electrical recordings from two electrode contacts with one coupled to a seizure onset zone of the brain of an individual and another coupled to a thalamus structure of the brain of the individual, as the thalamus is the region related to consciousness, as evidence by Burton [par. 411]
Regarding claims 8 and 16, Burton further teaches the EEG-based features comprise power and/or phase-amplitude coupling features between a seizure onset zone and thalamus of a brain of an individual [par. 400]
Therefore, it would have been prima facie obvious to a person having ordinary skill in the art when the invention was filed to modify the method as taught by Arcot and Firouzi, to incorporate the EEG-based features comprise power and/or phase-amplitude coupling features between a seizure onset zone and thalamus of a brain of an individual, in order to most effectively “pin-point” or localise the anatomical sources of interest, as evidence by Burton [par. 400]
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to GRACE L ROZANSKI whose telephone number is (571)272-7067. The examiner can normally be reached M-F 8:30am-5pm, alt F 8:30am-5pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Alexander Valvis can be reached on (571)272-4233. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/GRACE L ROZANSKI/Examiner, Art Unit 3791
/AURELIE H TU/Primary Examiner, Art Unit 3791