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(s) (IDS) submitted on 8/16/24; 1/13/26 has/have been acknowledged and is/are being considered by the Examiner.
Specification
The disclosure is objected to because of the following informalities: the first paragraph of the specification should be updated to indicate the present status of the priority application.
Appropriate correction is required.
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.
Claim(s) 1-14 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1- Claim 8
Claim 8 and dependent claims 9-14 are drawn to a method and thus meet the requirements for step 1.
Step 2a (prong 1) - Claim 8
Claims 8 recites the step of “classifying the extract feature vector”, under the broadest reasonable interpretation, this step covers a concept capable of being performed in the human mind, and thus falls within the mental processes grouping of abstract ideas. Other than reciting the method is “computer-implemented” in the preamble, nothing in the claim precludes the step from practically being performed in the mind.
Accordingly, claim 8 recites an abstract idea.
Step 2a (prong 2) – Claim 8
The judicial exception is not integrated into a practical application. Claim 8 recites the additional elements of:
An extraction operation of extracting a feature vector of an electrocardiogram is insignificant extra-solution activity (i.e., data gathering),
A classification operation of classifying the extracted feature vector is insignificant extra-solution activity (i.e., data gathering).
These steps do not integrate the abstract idea into a practical application because they are insignificant extra solution activity.
Step 2b- Claim 8
The additional elements when considered individually and in combination are not enough to qualify as significantly more than the abstract idea. As discussed above with respect to the integration of the abstract idea into a practical application, providing a classification operation is recited at a high level of generality (i.e., as generic devices, a “computer-implemented” method, performing generic computer functions like sending, receiving, and visually displaying data). Further, extracting a feature vector of an electrocardiogram is considered data gathering. It is noted that the extraction operation and classification operation are recited at a high level of generality.
The additional elements that were considered insignificant extra solution activity have been re-analyzed and do not amount to anything more than what is well-understood, routine and conventional when considered individually and in combination with evidence provided. Specifically:
Extracting a feature vector of an electrocardiogram is well understood, routine, and conventional (i.e., receiving data MPEP 2106.05(d)(II)).
Ensemble model using a support vector machine and naïve Bayes is well-understood routine and conventional (i.e., gathering data/statistics MPEP 2106.05(d)(II)).
Claim 8 is thus consider to be directed to an abstract idea without significantly more.
Claims 9-14 depend from claim 8. Claims 9-14 are directed toward to the extra solution activity of processing data. Thus, the dependent claims do not change the overall analysis that claims 9-14 are also directed to an abstract idea.
Claims 1-7
Independent claim 1 is directed to a system containing limitations similar to that for claim 8 and further includes a processor with memory. Analyzing the processor and memory of claim 1 under step 2a, prong 1, the processor and memory are recited at a high level of generality and merely use the computer elements (the processor and memory) as a tool. When analyzed under step 2a, prong 2, the processor and memory perform generic computer functions like storing and processing data. Further, when the analysis is extended to step 2b, the processor and memory are considered to use the computer elements as tools, MPEP 2106.05(d)(II). Thus, claim 1 is also considered to be patent ineligible subject matter. Dependent claims 2-7 are similar to dependent claims 9-14 and are rejected on the same grounds.
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)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-4, 7-11 and 14 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Varadan et al. (U.S. Pub. 2023/0181121 hereinafter “Varadan”).
Regarding claims 1 and 8, Varadan discloses an apparatus and method using an ensemble model, the mental stress classification apparatus comprising: a processor (e.g. ¶¶ 27, 43; device); and a storage medium on which one or more programs configured to be executable by the processor are recorded (e.g. ¶139; memory), wherein the processor is configured to extract a feature vector of an electrocardiogram (ECG) signal (e.g. 1410), and classify the extracted feature vector using the ensemble model (e.g. 110), wherein the ensemble model is a mixture model of a support vector machine and a naive Bayes (e.g. ¶¶ 51, 123, 143).
Regarding claims 2 and 9, meeting the limitations of claims 1 and 8 above, Varadan further discloses wherein the feature vector includes at least one of an R-S peak, an R-R interval, and a Q-T interval of the ECG signal, and the processor classifies each feature vector (e.g. ¶27 ).
Regarding claims 3 and 10, meeting the limitations of claims 1 and 8 above, Varadan further discloses wherein the support vector machine is a pre-trained model that classifies the feature vector into one of multi-classes using a decision boundary (e.g. ¶¶57, 83, 111), and the naive Bayes is a pre-trained model that classifies a stress index for the feature vector based on a preset contour plot in the class classified by the decision boundary (e.g. ¶¶53, 83, 91).
Regarding claims 4 and 11, meeting the limitations of claims 1 and 8 above, Varadan further discloses wherein the contour plot is obtained using a probability density function of a normal distribution for feature vectors belonging to each of the multi-classes, based on an ECG signal stored in a database (e.g. ¶123).
Regarding claims 7 and 14, meeting the limitations of claims 1 and 8 above, Varadan further discloses wherein the processor is further configured to remove noise by low-pass filtering the ECG signal, wherein the low-pass filter is a Butterworth low-pass filter (e.g. ¶111).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to REX R HOLMES whose telephone number is (571)272-8827. The examiner can normally be reached Monday-Thursday 7:00AM-5:30PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jennifer McDonald can be reached at (571) 270-3061. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/REX R HOLMES/ Primary Examiner, Art Unit 3796
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