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 .
Claim Objections
Claim 1 is objected to because of the following informalities: Claim 1 recites “using an EEG monitoring system…” but should recite --using an electroencephalography (EEG) monitoring system…--. Appropriate correction is required.
Claims 5-15 are objected to under 37 CFR 1.75(c) as being in improper form because a multiple dependent claim is not permitted to depend from another multiple dependent claim (see table below elaborating upon improper dependencies). See MPEP § 608.01(n). Accordingly, the Claims 5-15 has not been further treated on the merits.
Objected-to Claim
Problematic Language
Source of Problematic Multiple Dependency
Claim 5
“The method of any preceding claim…”
Claim 4, “The method of claim 1 or claim 2 or claim 3…”
Claim 6
“The method of claim 5…”
Claim 4; Claim 5
Claim 7
“The method of claim 5 or claim 6…”
Claim 4; Claim 5; Claim 6
Claim 8
“The method of any preceding claim…”
Claim 4; Claim 5; Claim 6; Claim 7
Claim 9
“The method of claim 8…”
Claim 4; Claim 5; Claim 6; Claim 7; Claim 8
Claim 10
“The method of any preceding claim…”
Claim 4; Claim 5; Claim 6; Claim 7; Claim 8; Claim 9
Claim 11
“The method of any preceding claim…”
Claim 4; Claim 5; Claim 6; Claim 7; Claim 8; Claim 9; Claim 10
Claim 12
“The method of any preceding claim…”
Claim 4; Claim 5; Claim 6; Claim 7; Claim 8; Claim 9; Claim 10; Claim 11
Claim 13
“A system…, the system comprising: a processor operable to carry out the method of any one of claims 1 to 12…”
Claim 4; Claim 5; Claim 6; Claim 7; Claim 8; Claim 9; Claim 10; Claim 11; Claim 12
Claim 14
“The system of claim 13…”
Claim 4; Claim 5; Claim 6; Claim 7; Claim 8; Claim 9; Claim 10; Claim 11; Claim 12; Claim 13
Claim 15
“A computer programme product operable, when run on a processor of a system according to claim 13 or claim 14, to cause the processor to carry out the method of any one of claims 1 to 12”
Claim 4; Claim 5; Claim 6; Claim 7; Claim 8; Claim 9; Claim 10; Claim 11; Claim 12; Claim 13; Claim 14
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.
Claim 1, and Claims 2-4 by dependency, 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 Independent Claim 1, Claim 1 recites “scaling an EEG template to fit event EEG data at a specified latency following the event to derive an EEG scaling factor.” It is grammatically unclear in what sense the term “at a specified latency following the event” modifies the remainder of the recitation. For example, “at a specified latency following the event” could modify (a) “scaling an EEG template” itself (i.e., the EEG template is scaled “at a specified latency following the event”), (b) “to fit event EEG data” (i.e., event data is scaled “at a specified latency following the event”), (c) “scaling an EEG template to fit event EEG data” (i.e., the manner in which an EEG template is scaled relative to event EEG data is such that the scaling is done “at a specified latency following the event”), or (d) something else. The scope of Claim 1 is thus unclear.
For purposes of this Office Action, the term “scaling an EEG template to fit event EEG data at a specified latency following the event to derive an EEG scaling factor” is being interpreted to mean that the EEG template is scaled “at a specified latency following the event.”
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 1-4 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., an abstract idea) without significantly more.
Eligibility Step 1 – The Four Categories of Statutory Subject Matter
Claims 1-4 each fall within one of the four categories of statutory subject matter.
Eligibility Step 2A, Prong One
Claims 1-4 recite abstract ideas:
Regarding Independent Claim 1:
“scaling an EEG template to fit event EEG data at a specified latency following the event to derive an EEG scaling factor” recites a mathematical concept, and more particularly a mathematical calculation when afforded its broadest reasonable interpretation. See MPEP 2106.04(a)(2)(I). “A mathematical calculation is a mathematical operation (such as multiplication) or an act of calculating using mathematical methods to determine a variable or number, e.g., performing an arithmetic operation such as exponentiation.” MPEP 2106.04(a)(2)(I)(C). Determining a rate of change is a mathematical operation, and thus recites a mathematical calculation when afforded its broadest reasonable interpretation in light of the Specification
“determining a heart rate change due to the event using the heart rate data” recites a mathematical concept, and more particularly a mathematical calculation when afforded its broadest reasonable interpretation. See MPEP 2106.04(a)(2)(I). “A mathematical calculation is a mathematical operation (such as multiplication) or an act of calculating using mathematical methods to determine a variable or number, e.g., performing an arithmetic operation such as exponentiation.” MPEP 2106.04(a)(2)(I)(C). Determining heart rate change is a mathematical operation, and thus recites a mathematical calculation when afforded its broadest reasonable interpretation in light of the Specification.
“and combining the EEG scaling factor and the heart rate change to generate a score indicative of a response of the subject to the event” recites a mathematical concept, and more particularly a mathematical calculation when afforded its broadest reasonable interpretation. See MPEP 2106.04(a)(2)(I). “A mathematical calculation is a mathematical operation (such as multiplication) or an act of calculating using mathematical methods to determine a variable or number, e.g., performing an arithmetic operation such as exponentiation.” MPEP 2106.04(a)(2)(I)(C). Such combining to generate a score is a mathematical operation, and thus recites a mathematical calculation when afforded its broadest reasonable interpretation in light of the Specification.
Regarding Claim 2:
“selecting the EEG template from a set of age-dependent templates to obtain an age- appropriate EEG template, said selection being based on an age of the subject” recites a mental process when afforded its broadest reasonable interpretation. The claimed selecting could practically be performed in the human mind. See MPEP 2106.04(a)(2)(III). For example, a human could observe data reflective of a subjects age, observe a set of age-dependent templates, and exercise judgment to select an “age appropriate” template based on those observations.
Regarding Claim 3:
“wherein the selection is made using a weighted probability function” recites a mathematical concept, and more particularly a mathematical calculation when afforded its broadest reasonable interpretation. See MPEP 2106.04(a)(2)(I). “A mathematical calculation is a mathematical operation (such as multiplication) or an act of calculating using mathematical methods to determine a variable or number, e.g., performing an arithmetic operation such as exponentiation.” MPEP 2106.04(a)(2)(I)(C). Using a weighted probability function is a mathematical operation, and thus recites a mathematical calculation when afforded its broadest reasonable interpretation in light of the Specification.
Regarding Claim 4:
“deriving a goodness-of-fit between the EEG template and the event EEG data;” recites a mathematical concept, and more particularly a mathematical calculation when afforded its broadest reasonable interpretation. See MPEP 2106.04(a)(2)(I). “A mathematical calculation is a mathematical operation (such as multiplication) or an act of calculating using mathematical methods to determine a variable or number, e.g., performing an arithmetic operation such as exponentiation.” MPEP 2106.04(a)(2)(I)(C). Deriving a goodness-of-fit is a mathematical operation, and thus recites a mathematical calculation when afforded its broadest reasonable interpretation in light of the Specification.
“and weighting the EEG scaling factor using the goodness-of-fit to produce a weighted EEG scaling factor” recites a mathematical concept, and more particularly a mathematical calculation when afforded its broadest reasonable interpretation. See MPEP 2106.04(a)(2)(I). “A mathematical calculation is a mathematical operation (such as multiplication) or an act of calculating using mathematical methods to determine a variable or number, e.g., performing an arithmetic operation such as exponentiation.” MPEP 2106.04(a)(2)(I)(C). Weighting a scaling factor using a goodness-of-fit is a mathematical operation, and thus recites a mathematical calculation when afforded its broadest reasonable interpretation in light of the Specification.
Eligibility Step 2A, Prong Two
Claims 1-4 do not recite additional elements that integrate the judicial exception into a practical application:
Regarding Independent Claim 1:
“acquiring, using an EEG monitoring system, EEG data from a subject” is insignificant extra-solution activity insufficient to integrate the judicial exception into a practical application because it amounts to mere data gathering.
“acquiring, using a heart rate monitoring system, heart rate data from the subject” is insignificant extra-solution activity insufficient to integrate the judicial exception into a practical application because it amounts to mere data gathering.
Regarding Claims 2-4, Claims 2-4 do not recite any additional elements.
Eligibility Step 2B
Claims 1-4 do not amount to significantly more than the abstract ideas recited therein:
Regarding Independent Claim 1:
“acquiring, using an EEG monitoring system, EEG data from a subject” does not contribute an inventive concept. Such acquiring EEG signals is well-understood, routine and conventional in the art. See, e.g., US 2013/0096440 A1 at Para. [0007] (“Recording of EEG signals is generally known in the medical arts.”).
“acquiring, using a heart rate monitoring system, heart rate data from the subject” does not contribute an inventive concept. Such acquiring heart rate data is well-understood, routine and conventional in the art. See, e.g., US 2016/0113591 A1 at Para. [0045] (“Likewise, heart rate sensors are known in the art and known sensors include an electrocardiogram (ECG) sensor and a photoplethysmograph (PPG) sensor.”).
Regarding Claims 2-4, Claims 2-4 do not recite any additional elements.
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.
Claim 1 is rejected under 35 U.S.C. 103 as being unpatentable over Hartley Caroline Et Al.: “Nociceptive brain activity as a measure of analgesic efficacy in infants,” Science Translational Medicine, Vol. 9, No. 388, 3 May 2017 (2017-05-03), pages 1-241 (“Hartley”) in view of US 2018/0000409 A1 to Jensen et al.2 (“Jensen”).
Regarding Independent Claim 1, Hartley teaches:
A method comprising: (Abstract, “Here, we present an EEG-based measure of infant nociceptive brain activity that is evoked following acute noxious stimulation and is sensitive to analgesic modulation.”);
acquiring, using an EEG monitoring system, EEG data from a subject, (Pg. 10, Second Paragraph, “EEG activity was recorded in 14 term infants during a period of background activity and in response to a train of approximately 10 auditory, visual, tactile and experimental noxious stimuli (which were applied in a randomized order);” Pg. 9, Second and Third Paragraphs clarify further that an “EEG monitoring system” is used);
said data being recorded over a first time period, said first time period including an event; (Pg. 10, Second Paragraph, “EEG activity was recorded in 14 term infants during a period of background activity and in response to a train of approximately 10 auditory, visual, tactile and experimental noxious stimuli (which were applied in a randomized order);”
acquiring, using a heart rate monitoring system, heart rate data from the subject, (Pg. 10, Fourth Paragraph, “Physiological arousal: To investigate whether the stimuli were equally physiologically arousing, evoked changes in heart rate were examined. R-R intervals were identified from the ECG trace in the 5 seconds before and after each individual stimulus (42), and the change in heart rate between the two periods calculated.”);
said heart rate data being recorded over a second time period, said second time period also including the event; (Pg. 10, Fourth Paragraph, “Physiological arousal: To investigate whether the stimuli were equally physiologically arousing, evoked changes in heart rate were examined. R-R intervals were identified from the ECG trace in the 5 seconds before and after each individual stimulus (42), and the change in heart rate between the two periods calculated.”);
scaling an EEG template to fit event EEG data at a specified latency following the event (Pg. 2, Fourth Paragraph through Pg. 2, First Paragraph, “The topography and time-course of the response was established by considering activity across all electrodes in the 1000 ms post-stimulation period. Noxious-evoked activity was maximal at Cz, and, at this electrode site, significantly different from the activity evoked by the nonnoxious stimuli in the time-window 446 - 611 ms post-stimulation (p=0.003, clustercorrected non-parametric test (11); Figure 1A,B). To obtain a representative waveform of the noxious-evoked brain activity, Principal Component Analysis (PCA) was applied in this time window (400 – 700 ms post-stimulation) at Cz. A principal component was identified that was significantly greater in response to the noxious stimuli compared with the non-noxious stimuli and background activity (p<0.01, Figure 1C). This principal component is comparable to that identified in previous research investigating noxious-evoked brain activity in infants (6, 12–16) and was defined as the template of nociceptive brain activity. The template is scaled so that a magnitude of 1 represents the average response evoked by a stimulus of equivalent intensity to a heel lance performed in a term infant. Activity evoked following experimental noxious stimuli (up to a maximum force of 128 mN) and in younger infants is expected to be smaller in magnitude (13, 14).”);
As explained above, the term “scaling an EEG template to fit event EEG data at a specified latency following the event to derive an EEG scaling factor” is being interpreted to mean that the EEG template is scaled “at a specified latency following the event.”
to derive an EEG scaling factor; (Pg. 11, Fifth Paragraph through Pg. 12, First Paragraph)
Pg. 11, Fifth Paragraph through Pg. 12, First Paragraph describe the manner by which “[t]he magnitude of the evoked nociceptive template activity was calculated by projecting the template onto the EEG data using singular value decomposition,” resulting in “the magnitude of the noxious-evoked brain activity.” This magnitude is determined via the equation at the top of Pg. 12, and is defined as a value “U1.” Value “U1” is such a scaling factor as claimed.
determining a heart rate change due to the event using the heart rate data; (Pg. 10, Fourth Paragraph, “Physiological arousal: To investigate whether the stimuli were equally physiologically arousing, evoked changes in heart rate were examined. R-R intervals were identified from the ECG trace in the 5 seconds before and after each individual stimulus (42), and the change in heart rate between the two periods calculated.”).
Hartley does not disclose:
and combining the EEG scaling factor and the heart rate change to generate a score indicative of a response of the subject to the event.
Jensen describes “Means and methods for measuring pain and adapted for calculating the level of nociception during general anesthesia or sedation from data including electroencephalogram (EEG), facial electromyogram (EMG), heart rate variability (HRV) by electrocardiogram (ECG) and plethysmography by impedance cardiography (ICG)” (Abstract).
Jensen teaches:
and combining the EEG scaling factor and the heart rate change to generate a score indicative of a response of the subject to the event. (Claim 11, “…(i) combining the extracted EEG, EMG, ECG, and ICG data into a final index of nociception represented by a scale from 0 to 99, where a value of 99 represents a high probability of response to light noxious stimuli and a value of close or equal to 0 corresponds to a total block of afferent noxious stimuli…”).
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Hartley with the teachings of Jensen (i.e., to modify the method of Hartley such that change in heart rate is combined with Hartley’s EEG scaling factor to generate a score indicative of the subject’s response) in order to facilitate estimation of pain and nociception (Jensen at Para. [0019]).
Claim 2 is rejected under 35 U.S.C. 103 as being unpatentable over Hartley Caroline Et Al.: “Nociceptive brain activity as a measure of analgesic efficacy in infants,” Science Translational Medicine, Vol. 9, No. 388, 3 May 2017 (2017-05-03), pages 1-24 (“Hartley”) in view of US 2018/0000409 A1 to Jensen et al. (“Jensen”) as applied to Claim 1 above, and further in view of US 2015/0081226 A1 to Baki (“Baki”).
Regarding Claim 2, the combination of Hartley and Jensen renders obvious the entirety of Claim 1 as explained above.
The combination of Hartley and Jensen does not disclose:
the method further including: selecting the EEG template from a set of age-dependent templates to obtain an age- appropriate EEG template, said selection being based on an age of the subject.
Baki describes “Systems and techniques for managing EEG analysis…” (Abstract). Baki is analogous art.
Baki teaches:
the method further including: selecting the EEG template from a set of age-dependent templates to obtain an age- appropriate EEG template, said selection being based on an age of the subject (Para. [0024], “ IN an example, the patient differentiator is an age of the patient 110. FIGS. 5 and 6 illustrate two examples of interpretation interfaces 255 that can be based on templates with a patient differentiator of age. Thus, for an adult patient, the interpretation interface 500 can be presented to the EEG interpreter 135 and for a premature infant (or other pediatric), interpretation interface 600 can be presented.”).
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of combined Hartley and Jensen with the teachings of Baki (i.e., to modify the method of combined Hartley and Jensen such that the EEG template is selected from a set of age dependent templates based on the age of the subject in the manner of Baki) in order to increase efficiency when interpreting the subject’s EEG (Baki at Para. [0024]).
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Hartley Caroline Et Al.: “Nociceptive brain activity as a measure of analgesic efficacy in infants,” Science Translational Medicine, Vol. 9, No. 388, 3 May 2017 (2017-05-03), pages 1-24 (“Hartley”) in view of US 2018/0000409 A1 to Jensen et al. (“Jensen”) and US 2015/0081226 A1 to Baki (“Baki”) as applied to Claim 2 above, and further in view of US 2017/0249434 A1 to Brunner et al. (“Brunner”).
Regarding Claim 3, the combination of Hartley, Jensen and Baki renders obvious the entirety of Claim 2 as explained above.
The combination of Hartley, Jensen and Baki does not disclose:
wherein the selection is made using a weighted probability function.
Brunner describes “…systems and methods for analyzing human data related to health and disease…” (Para. [0002]), including EEG and heart rate data (Para. [0035]). Brunner is reasonably pertinent to the problem faced by the inventor, and is thus analogous art.
Brunner teaches:
wherein the selection is made using a weighted probability function. (Para. [0207], “A simple majority vote now determines that the novel sample belongs to Class 2 , as R ( 2 ) A , B , C - 0 . 28 > R ( j ) a , B , C for j = 1 , 3 , 4 , and 5 . Note that removing the influence of the correlation between algorithm A and B for the first three classes actually changed the prediction in this example . For N algorithms , an NxN table of correlation coefficients for each class can be build and used as basis for the weighting . The scores from Table III can be normalized and interpreted as probabilities...”).
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of combined Hartley, Jensen and Baki with the teachings of Brunner (i.e., to use such a weighted probability function as described by Brunner to select a template) because such a modification entails only simple substitution of one known element for another to obtain predictable results.
The prior art contains a method (i.e., the method of combined Hartley, Jensen and Baki) which differed from the claimed device by the substitution of some components (i.e., template selection based on age) with other components (i.e., template selection based on age made using a weighted probability function).
The substituted components and their functions were known in the art. For example, Brunner teaches such a weighted probability function at Para. [0207].
One of ordinary skill in the art could have substituted one known element for another, and the results of the substitution would have been predictable
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Hartley Caroline Et Al.: “Nociceptive brain activity as a measure of analgesic efficacy in infants,” Science Translational Medicine, Vol. 9, No. 388, 3 May 2017 (2017-05-03), pages 1-24 (“Hartley”) in view of US 2018/0000409 A1 to Jensen et al. (“Jensen”) and US 2015/0081226 A1 to Baki (“Baki”) and US 2017/0249434 A1 to Brunner et al. (“Brunner”) as respectively applied to Claims 1, 2 and 3 above, and further in view of FABRIZI L ET AL: "A method for removing artefacts from continuous EEG recordings during functional electrical impedance tomographyfor the detection of epileptic seizures;", PHYSIOLOGICAL MEASUREMENT, INSTITUTE OF PHYSICS PUBLISHING, BRISTOL, GB, vol. 31, no. 8, 21 July 2010 (2010-07-21)3 (“Fabrizi”), pages S57-S72, XP020196147 and WO 2021/035067 A1 to Mesgarani et al. (“Mesgarani”).
Regarding Claim 4, Claim 4 depends on Claims 1-3 in the alternative. Hartley, Jensen, Baki and Brunner render obvious Claims 1-3, respectively, as explained above.
None of Hartley, Jensen, Baki and Brunner, either alone or in combination, disclose:
the method further comprising: deriving a goodness-of-fit between the EEG template and the event EEG data; and weighting the EEG scaling factor using the goodness-of-fit to produce a weighted EEG scaling factor
Fabrizi describes “A method for removing artefacts from continuous EEG recordings…” (Title). Fabrizi is analogous art.
Fabrizi teaches estimating the quality of the match when using templates and scaling based thereupon, but does not disclose a “goodness-of-fit” as the methodology for so-doing.
Fabrizi thus teaches:
the method further comprising: deriving a [measure of match quality] between the EEG template and the event EEG data; and weighting the EEG scaling factor using the goodness-of-fit to produce a weighted EEG scaling factor (Pg. 562, "the template could be scaled in amplitude to give the best match to that period of EEG.”).
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Hartley, Jensen, Baki and Brunner as combined in any of the respective manners explained above with respect to claims 1-3 with the teachings of Fabrizi (i.e., to estimate the quality of the match when using templates and scaling based thereupon) in order to “give the best match to that period of EEG.” (Fabrizi at Pg. 562).
Mesgarani describes “Measuring language proficiency from electroencephelography data.” Mesgarni is reasonably pertinent to the problem faced by the inventor, and is thus analogous art.
Mesgarani teaches:
deriving a goodness-of-fit (Pg. 22, Ln. 11-12, “ One solution to use the EEG prediction correlation values to quantify the goodness of fit…”).
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the method off Hartley, Jensen, Baki, Brunner and Fabrizi as combined in any of the respective manners explained above with respect to claims 1-3 with the teachings of Mesgarani (i.e., to use a goodness-of-fit estimating the quality of the match when using templates) because such a modification entails only a simple substitution of one known element for another to obtain predictable results.
The prior art contains a method (i.e., the method of Fabrizi) which differed from the claimed device by the substitution of some components (i.e., estimating the quality of the match when using templates via a different algorithm) with other components (i.e., a goodness-of-fit).
The substituted components and their functions were known in the art. For example, Mesgarani teaches such a goodness-of-fit at Pg. 22, Ln. 11-12.
One of ordinary skill in the art could have substituted one known element for another, and the results of the substitution would have been predictable.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHRISTOPHER J MUTCHLER whose telephone number is (571)272-8012. The examiner can normally be reached M-F 7:00 am - 4:00 pm.
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/C.J.M./Examiner, Art Unit 3796
/ALLEN PORTER/Primary Examiner, Art Unit 3796
1 Hartley Caroline Et Al.: “Nociceptive brain activity as a measure of analgesic efficacy in infants,” Science Translational Medicine, Vol. 9, No. 388, 3 May 2017 (2017-05-03), pages 1-24 was disclosed by Applicant in the IDS dated 5/10/2024.
2 US 2018/0000409 A1 was disclosed by Applicant in the IDS dated 5/10/2024.
3 FABRIZI L ET AL: "A method for removing artefacts from continuous EEG recordings during functional electrical impedance tomography for the detection of epileptic seizures", PHYSIOLOGICAL MEASUREMENT, INSTITUTE OF PHYSICS PUBLISHING, BRISTOL, GB, vol. 31, no. 8, 21 July 2010 (2010-07-21) was disclosed by Applicant in the IDS dated 5/10/2024.