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 following is in response to the amendment filed on March 27, 2026.
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 therefore, subject to the conditions and requirements of this title.
Claims 1-13 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
With respect to claim 1:
Step 2A Prong 1:
Selecting, by performing feature template matching between the no-load feature data and the plurality of feature templates, at least one of (i) the plurality of feature templates to be used to estimate the subjective pain sensation level of the estimation target object or (ii) the plurality of models to be used to estimate the subjective pain sensation level of the estimation target object, based on the no-load feature data; and (abstract idea – mental process, selecting a templated based on data matching could be performed in the mind)
Estimating the subjective pain sensation level of the estimation target object, based on (i) the feature data and the selected at least one of the plurality of feature templates or (ii) the feature data and the selected at least one of the plurality of models. (abstract idea – mental process, estimating a pain sensation level based on feature data could be performed in the mind)
Step 2A Prong 2:
This judicial exceptions are not integrated into a practical application because the additional elements are as follows:
A processor;
A memory storing instructions that, when executed by the processor, cause the processor to perform operations comprising:
Receiving feature data of a brain wave signal acquired from the estimation target object;
Storing, in the memory, (i) a plurality of feature templates respectively extracted from a plurality of brain wave signals acquired from a plurality of modeling target objects including a first modeling target object and a second modeling target object, and (ii) a plurality of models generated by machine learning by using, as learning data, the plurality of feature templates respectively corresponding to the plurality of modeling target objects. (Adding insignificant extra-solution activity to the judicial exception - see MPEP 2106.05(g)).
Wherein each of the plurality of feature templates associates pieces of feature data of a plurality of samples sampled from the brain wave signal with a value indicating the subjective pain sensation level, the plurality of feature templates including a first feature template extracted from a first brain wave signal acquired from the first modeling target object and a second feature template extracted from a second brain wave signal acquired from the second modeling target object, (Adding insignificant extra-solution activity to the judicial exception - see MPEP 2106.05(g), further defining the feature templates is insignificant extra solution activity).
Wherein each of the plurality of models is configured to output a value indicating the subjective pain sensation level in response to an input of feature data, and the plurality of models includes a first model generated by using the first feature template and a second model generated by using the second feature template; (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f) – Examiner’s note: high level recitation of training a machine learning model with previously determined data);
Step 2B:
A processor;
A memory storing instructions that, when executed by the processor, cause the processor to perform operations comprising:
Receiving feature data of a brain wave signal acquired from the estimation target object;
Storing, in the memory, (i) a plurality of feature templates respectively extracted from a plurality of brain wave signals acquired from a plurality of modeling target objects including a first modeling target object and a second modeling target object, and (ii) a plurality of models generated by machine learning by using, as learning data, the plurality of feature templates respectively corresponding to the plurality of modeling target objects. (MPEP 2106.05(d)(II) indicate that merely “storing and retrieving information in memory” is a well‐understood, routine, conventional function when it is claimed in a merely generic manner (as it is in the present claim). Thereby, a conclusion that the claimed storing step is well-understood, routine, conventional activity is supported under Berkheimer).
Wherein each of the plurality of feature templates associates pieces of feature data of a plurality of samples sampled from the brain wave signal with a value indicating the subjective pain sensation level, the plurality of feature templates including a first feature template extracted from a first brain wave signal acquired from the first modeling target object and a second feature template extracted from a second brain wave signal acquired from the second modeling target object, (Adding insignificant extra-solution activity to the judicial exception - see MPEP 2106.05(g), further defining the feature templates is insignificant extra solution activity).
Wherein each of the plurality of models is configured to output a value indicating the subjective pain sensation level in response to an input of feature data, and the plurality of models includes a first model generated by using the first feature template and a second model generated by using the second feature template; (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f) – Examiner’s note: high level recitation of training a machine learning model with previously determined data);
The additional elements as disclosed above alone or in combination do not integrate the judicial exception into practical application as they are mere insignificant extra solution activity in combination of generic computer functions being implemented with generic computer elements in a high level of generality to perform the disclosed abstract idea above. Therefore the claim is ineligible.
With respect to claim 2:
Step 2A Prong One:
Estimating the subjective pain sensation level of the estimation target object, based on the plurality of correlation coefficient sets. (abstract idea – mental process, estimating a subjective pain sensation level based on data could be done in the mind)
Step 2A Prong Two:
Obtaining a plurality of correlation coefficient sets by correlating each of the plurality of feature templates with the piece of feature data; (this amounts to insignificant extra solution activity, mere data gathering, as per MPEP 2106.05(g))
Step 2B:
Obtaining a plurality of correlation coefficient sets by correlating each of the plurality of feature templates with the piece of feature data; (this amounts to insignificant extra solution activity, mere data gathering, as per MPEP 2106.05(g); furthermore, this amounts to well-understood, routine and conventional activity as per MPEP 21.06.05(d))
With respect to claim 3:
Wherein the estimating of the subjective pain sensation level based on the plurality of correlation coefficient sets comprises: identifying, for each of the plurality of correlation coefficient sets, a value indicating a subjective pain sensation level that is associated with a sample corresponding to a highest correlation coefficient; taking an ensemble average of the values indicating the subjective pain sensation levels of the plurality of correlation coefficient sets; and determining a score indicating the subjective pain sensation level based on the ensemble average; identifying, taking an average, and determining a score are evaluations that can be performed by a human in the mind or with pen and paper, and are thus a mental process
With respect to claim 4:
wherein the estimating of the subjective pain sensation level based on the plurality of correlation coefficient sets comprises: identifying, for each of the plurality of correlation coefficient sets, values indicating subjective pain sensation level that are associated with samples corresponding to a top plurality of correlation coefficients; obtaining an ensemble average correlation coefficient by, for each of the correlation coefficient sets, taking an ensemble average of the values indicating the top plurality of the subjective pain sensation levels; taking an ensemble average of the ensemble average correlation coefficients of the plurality of correlation coefficient sets; and determining a score indicating the subjective pain sensation level based on the ensemble average”; identifying, taking an average, and determining a score are evaluations that can be performed by a human in the mind or with pen and paper, and are thus a mental process
With respect to claim 5:
Wherein the operations further comprise: obtaining a plurality of outputs by inputting the feature data to each of the plurality of models, the plurality of outputs including a first output outputted from the first model and a second output outputted from the second model; and estimating the subjective pain sensation level of the estimation target object, based on the plurality of outputs; evaluating data to produce an output based on the evaluation, and then performing an estimation is a mental process under Step 2A Prong 1; using a broadly recited machine learning “model” at a high level of generality to do so, amounts to nothing more than an instruction to apply the abstract idea using a generic computer as per MPEP 2106.05(f) under Steps 2A Prong 2 and 2B.
With respect to claim 6:
Wherein the estimating of the subjective pain sensation level based on the plurality of outputs comprises: taking an ensemble average of the plurality of outputs; and determining a score indicating the subjective pain sensation level based on the ensemble average”; taking an average and determining a score are evaluations that can be performed by a human in the mind or with pen and paper, and are thus a mental process
With respect to claim 7:
Wherein the storing, in the memory further comprises storing a plurality of standardization parameters extracted from the plurality of brain wave signals, the plurality of standardization parameters including a plurality of first standardization parameters extracted from the first brain wave signal acquired from the first modeling target object and a plurality of second standardization parameters extracted from the second brain wave signal acquired from the second modeling target object”; this amounts to insignificant extra solution activity, mere data gathering and “selecting a particular data source or type of data to be manipulated”, as per MPEP 2106.05(g); furthermore, this is well-understood, routine, and conventional activity (“i. Receiving or transmitting data over a network”, “iii. Electronic recordkeeping”, “iv. Storing and retrieving information in memory”) as per MEP 2106.05(d)
The operation further comprise generating a plurality of pieces of standardized feature data by standardizing the feature data by the plurality of standardization parameters, the plurality of pieces of standardized feature data including a plurality of pieces of first standardized feature data obtained by standardizing the feature data by the plurality of first standardization parameters, and a plurality of pieces of second standardized feature data obtained by standardizing the feature data by the plurality of second standardization parameters; manipulating data in order to standardize it is an evaluation that can be carried out by a human in the mind or with pen and paper, and is thus a mental process
and the obtaining of the plurality of outputs by inputting the feature data to each of the plurality of models comprises obtaining a plurality of outputs of the plurality of models by inputting the plurality of pieces of standardized feature data to the plurality of models, the plurality of outputs of the plurality of models including a plurality of first outputs obtained by inputting the plurality of pieces of first standardized feature data to the first model and a plurality of second outputs obtained by inputting the plurality of pieces of second standardized feature data to the second model; evaluating data to produce an output based on the evaluation, and then performing an estimation is a mental process under Step 2A Prong 1; using a broadly recited machine learning “model” at a high level of generality to do so, amounts to nothing more than an instruction to apply the abstract idea using a generic computer as per MPEP 2106.05(f) under Steps 2A Prong 2 and 2B.
With respect to claim 8:
wherein the estimating of the subjective pain sensation level based on the plurality of outputs comprises: obtaining a plurality of ensemble average outputs by taking an ensemble average of the plurality of outputs of each of the plurality of models, the plurality of ensemble average outputs including a first ensemble average output obtained by taking an ensemble average of the plurality of first outputs and a second ensemble average output obtained by taking an ensemble average of the plurality of second outputs; taking an ensemble average of the plurality of ensemble average outputs; and determining a score indicating the subjective pain sensation level based on the ensemble average; taking an average and determining a score are evaluations that can be performed by a human in the mind or with pen and paper, and are thus a mental process
With respect to claim 9:
The value indicating the subjective pain sensation level is an average value of COVAS template labels respectively corresponding to the plurality of samples sampled from the brain wave signal, wherein the COVAS template label corresponds to a value such that an additional average of COVAS of the plurality of modeling target objects when the modeling target objects are given the same heat stimulus and the additional average is fitted to the scale of 0 -100. (Adding insignificant extra-solution activity to the judicial exception - see MPEP 2106.05(g), further defining the value indicating subjective pain is insignificant extra solution activity).
With respect to claim 10:
Wherein the plurality of modeling target objects are n modeling target objects, the plurality of feature templates are n feature templates, the plurality of models are n models, and n is an integer equal to or larger than two; this merely quantifies elements of the analysis of the preceding claims, and thus the claim is still directed to an abstract idea
With respect to claim 11:
Wherein the brain wave signal acquired from the estimation target object is a brain wave signal at a time when a stimulus is given to the estimation target object, the plurality of brain wave signal are a plurality of brain wave signal at a time when a stimulus is given to the plurality of modeling target objects, the first brain wave signal is a first brain wave signal at the time when the stimulus is given to the first modeling target object, and the second brain wave signal is a second brain wave signal at the time when the stimulus is given to the second modeling target object,”; this amounts to insignificant extra solution activity, mere data gathering, as per MPEP 2106.05(g) under Step 2A Prong 2; furthermore, this is well-understood, routine, and conventional activity (“i. Receiving or transmitting data over a network”) as per MEP 2106.05(d) under Step 2B; this may also be considered merely indicating a field of use or technological environment in which to apply a judicial exception under 2106.05(h) under both Steps 2A Prong 2 and 2B
Wherein the operations includes estimating the subjective pain sensation level by the estimation target object; performing an estimation is an evaluation that can be performed by a human in the mind or with pen and paper, and is thus a mental process
Claims 12 and 13 are rejected according to the rejection of claim 1 above.
Allowable Subject Matter
Claim 1- 13 have been found allowable over prior art.
Response to Amendment
Claim Rejections - 35 USC § 112
The instant amendments overcome the 112 rejections.
Claim Rejections - 35 USC § 101
Applicant argues “The claimed invention is directed to a practical application, namely evaluation a “subjective pain level” which is generally difficult to assess objectively.”. Examiner respectfully disagree, evaluating a subjective pain level is an abstract idea and the claims have not integrated into a practical application.
Applicant also argues “The body of the claims recites, for example: “selecting, by performing feature template matching between the no-load feature data and the plurality of feature templates” Examiner respectfully disagrees, selecting by matching data is an abstract idea, a human could mentally select by matching data.
Applicant also argues “By expressly requiring, “matching with the feature templates” the claims make clear that a particular feature template or model is selected. This, in turn, clarifies that estimation is carried out using a template or model expected to provide higher estimation accuracy for the target object. This feature contributes to obtaining a more objective evaluation value.” Examiner respectfully disagrees. It appears from the argument that applicant is stating that matching with the feature templates is an improvement to the technology, however that improvement is not explicitly recited in the claim as part of a limitation not designated as an exception.
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 MARIELA D REYES whose telephone number is (571)270-1006. The examiner can normally be reached Monday-Friday, 7:30 am -5:00 pm.
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/Mariela Reyes/Supervisory Patent Examiner, Art Unit 2142
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