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 .
Response to Amendment
Applicant filed amended claims on Aug-24 2026 and addressed all previous 35 U.S.C. 112(b) rejections and all objections to the specification, drawings, abstract, and claims set forth in the Non-Final Office Action mailed June-05 2026. These previous objection and rejections are withdrawn. Applicant’s amendment to claims 1, 4, & 7 successfully overcome the rejection under 35 U.S.C. 102 as set forth in the Non-Final Office Action mailed June-05 2026. However, the altered scope of the claim necessitated a new grounds of rejection as set forth below. Rejections under U.S.C. 101 & 103 are addressed below.
Response to Arguments
Applicant's arguments see section III Pg 6-8 , filed Aug-24 2026, with respect to the rejection(s) of claim(s) 1, 4, & 7 under U.S.C. 101 have been fully considered but they are not persuasive.
Step 2A Prong 1
Applicant argues that the claims do not recite the claims do not recite a mental process or mathematical calculation under Step 2A Prong 1 because the claims recite:
Physical placement of a plurality of electrodes on the scalp in six specific brain regions (frontal, temporal, occipital, parietal, prefrontal, and central gyrus);
Specific digital signal processing steps: frequency spectrum analysis to derive a first measurement value from EEG, frequency spectrum analysis to derive a second measurement value from HRV, and quantitative gait analysis (including stride length and gait speed) to derive a third measurement value;
Integration of these three specific measurement values into a logistic model constructed from actual patient data for geriatric cognitive impairment diagnosis.
Sept 2A Prong 1 of the Eligibility analysis “ does the claim recite an abstract idea, law of nature, or natural phenomenon? … if the claim recites a judicial exception (i.e., an abstract idea enumerated in MPEP § 2106.04(a), a law of nature, or a natural phenomenon), the claim requires further analysis in Prong Two. If the claim does not recite a judicial exception (a law of nature, natural phenomenon, or abstract idea), then the claim cannot be directed to a judicial exception (Step 2A: NO), and thus the claim is eligible at Pathway B without further analysis.” -MPEP2106.04(II)(A)1
Regardless of whether the above listed claim elements do or do not recite a judicial exception, claims 1, 4, & 7 do recite the mental processes of collecting multiple bio-signals, measuring brain waves, and determining whether there is geriatric cognitive impairment disease (see MPEP 2106.04(a)(2)(I)C). Claims 1, 4, & 7 also recite the mathematical calculations of calculating a measurement value, and calculating a probability value (see MPEP 2106.04(a)(2)(III).
For example, aside from the recitation of “performed by a computer”, the claim encompasses a medical professional gathering biological data, using that data to perform a calculation, and making a diagnosis based on the result of that calculation.
“Claims can recite a mental process even if they are claimed as being performed on a computer. The Supreme Court recognized this in Benson, determining that a mathematical algorithm for converting binary coded decimal to pure binary within a computer’s shift register was an abstract idea. The Court concluded that the algorithm could be performed purely mentally even though the claimed procedures "can be carried out in existing computers long in use, no new machinery being necessary." … In evaluating whether a claim that requires a computer recites a mental process, examiners should carefully consider the broadest reasonable interpretation of the claim in light of the specification. For instance, examiners should review the specification to determine if the claimed invention is described as a concept that is performed in the human mind and applicant is merely claiming that concept performed 1) on a generic computer, or 2) in a computer environment, or 3) is merely using a computer as a tool to perform the concept. In these situations, the claim is considered to recite a mental process.” - MPEP 2106.04(a)(2)(III)(C)
Since the claim does recite a judicial exception, it must further be considered under Sept 2A Prong 2. Additionally, the examiner notes that a frequency spectrum analysis is a mathematical calculation that can be performed by hand, such as with a Discrete Fourier Transform, and is therefore also an abstract idea. The examiner notes that integration of values into a diagnostic model may also be considered a mental activity and that the physical placement of a plurality of electrodes on the scalp is not a claimed element of the method of claims 1 & 7 nor is it a step of the program carried about by the diagnosis device of claim 4.
Therefore, other than using a computer as a tool to do so, the claim encompasses the abstract idea of a medical professional applying observations and measurements to a diagnostic model such as the Glascow Coma Score.
Step 2A Prong 2
Applicant argues that the claims do not recite the claims integrate the recited abstract ideas into a practical application under Step 2A Prong 2 because the claims recite: a particular machine: a diagnostic device comprising a data transmission/reception module, memory, and a processor specifically programmed to perform the recited multi-modal bio-signal acquisition and feature extraction from the central nervous system (EEG from six brain regions), autonomic nervous system (HRV frequency analysis), and motor system (3D gait analysis with stride length and speed). The examiner notes that only claim 4 recites a diagnosis device. Claims 1 & 7 recite a method, but do not recite any particular hardware necessary for carrying out the steps of the method other than the plurality of electrodes and plurality of motion detection sensors that carry out the insignificant extra solution activity of data gathering (i.e. “performing clinical tests on individuals to obtain input for an equation, In re Grams, 888 F.2d 835, 839-40; 12 USPQ2d 1824, 1827-28 (Fed. Cir. 1989)”; -MPEP 2106.05(g)) and the non-transitory computer-readable recording medium on which a computer program is recorded, which amounts to nothing more than a generic computer component performing the generic computer function of storing data.
MPEP 2106.05(b) lists three relevant factors when determining if a machine recited in a claim provides significantly more. I. The particularity or generality of the elements of the machine or apparatus, i.e., the degree to which the machine in the claim can be specifically identified, II. Whether the machine or apparatus implements the steps of the method (i.e. Integral use of a machine to achieve performance of a method may integrate the recited judicial exception into a practical application or provide significantly more, in contrast to where the machine is merely an object on which the method operates, which does not integrate the exception into a practical application or provide significantly more), and III. Whether its involvement is extra-solution activity or a field-of-use, i.e., the extent to which (or how) the machine or apparatus imposes meaningful limits on the claim.
In [0031]-[0035] of the specification of instant application describing the computer components of the diagnosis device, there is nothing to suggest that the claimed data transmission/reception module, memory, a processor are anything more than generic off-the-shelf computer components. The applicant specifically states in [0031] that “the processor 130 may include all kinds of devices capable of processing data.” Therefore, the computer elements of the diagnosis device are highly general, rather than particular.
As described in MPEP § 2106.05(f), additional elements that invoke computers or other machinery merely as a tool to perform an existing process will generally not amount to significantly more than a judicial exception. See, e.g., Versata Development Group v. SAP America, 793 F.3d 1306, 1335, 115 USPQ2d 1681, 1702 (Fed. Cir. 2015) (explaining that in order for a machine to add significantly more, it must "play a significant part in permitting the claimed method to be performed, rather than function solely as an obvious mechanism for permitting a solution to be achieved more quickly"). The diagnosis device of claim is nothing more than a tool to perform an existing process as recited in claim 1. This is evidenced by both high level of generality with which the computer elements are recited and the absence of any reference to the specific diagnosis device of claim 4 in the recitation of claim 1 and as noted above, the plurality of electrodes and plurality of motion detection sensors do no more than merely carry out the insignificant extra solution activity of data gathering.
Therefore, given the high level of generality and that claimed diagnosis device as claimed appears to be no more than a mere computer used as tool for performing an existing method, the argument that it constitutes a particular machine is not found to be persuasive.
Applicant argues that their invention constitutes a technical improvement in the field of medical diagnostics by enabling accurate, non-invasive, early diagnosis by simultaneously evaluating three major nervous systems using specific, quantifiable bio-signal features.
When considering improvements to a technical field, it is important to keep in mind that an improvement in the abstract idea itself (e.g. a recited fundamental economic concept) is not an improvement in technology. For example, in Trading Technologies Int’l v. IBG, 921 F.3d 1084, 1093-94, 2019 USPQ2d 138290 (Fed. Cir. 2019), the court determined that the claimed user interface simply provided a trader with more information to facilitate market trades, which improved the business process of market trading but did not improve computers or technology.” Examples that the courts have indicated may not be sufficient to show an improvement to technology, the most relevant of which is “ii. Using well-known standard laboratory techniques to detect enzyme levels in a bodily sample such as blood or plasma, Cleveland Clinic Foundation v. True Health Diagnostics, LLC, 859 F.3d 1352, 1355, 1362, 123 USPQ2d 1081, 1082-83, 1088 (Fed. Cir. 2017)” (see MPEP 2106.05(a)II ). In this case the applicant argues that the improvement is in the abstract idea of diagnosis itself. Additionally, courts have found that limitations that merely confine the use of the abstract idea to a particular technological environment (e.g. cellular telephones, or in this case medical diagnostics) fail to add an inventive concept to the claims. 838 F.3d at 1259, 120 USPQ2d at 1204 (see MPEP 2106.05(h) ). In this case the limitations attempt to limit the recited abstract ideas (collecting, calculation, applying, etc.) to the field of medical diagnostics does add significantly more.
Therefore, as neither an improvement to the abstract idea itself nor a mere field-of-use limitation constitute integration into a practical application, this argument is not found to be persuasive.
Step 2B
Applicant argues that the additional elements, considered individually and as an ordered combination, amount to significantly more than any alleged abstract idea. Applicant argues that the specific ordered combination is not of (1) EEG measurement from six defined brain regions with frequency spectrum analysis, (2) HRV frequency spectrum analysis, (3) quantitative gait analysis including stride length and gait speed, and (4) integration into a logistic model for geriatric cognitive impairment diagnosis well-understood, routine, or conventional in the art.
Other than the six defined brain regions, each of the 4 limitations above, both individually and taken as an ordered combination constitute nothing more than the recited abstract ideas. Taking EEG measurements from the six defined brain regions of the claims is well-understood, routine, and conventional as evidenced by Jasper (Report of the Committee on Methods of Clinical Examination in Electroencephalography. Jasper, H. (1958) Electroencephalography and Clinical Neurophysiology, 10, 370-375). As noted in the Step2A Prong 2 analysis, “An inventive concept "cannot be furnished by the unpatentable law of nature (or natural phenomenon or abstract idea) itself." Genetic Techs. Ltd. v. Merial LLC, 818 F.3d 1369, 1376, 118 USPQ2d 1541, 1546 (Fed. Cir. 2016).” -MPEP 2106.05.
Therefore, the additional claims elements beyond the recited abstract ideas are nothing more than well-understood, routine, and conventional activity, and do not constitute something more for the purpose of step 2B consideration. This argument is not found to be persuasive.
The applicant argues that unlike Brunner, which uses general bio-signals or single modalities, the claimed particular multi-system feature extraction and integration for this specific diagnostic purpose and that this provides the "something more" required by Alice.
However, as noted Step2A Prong 2 analysis merely indicating a field of use or technological environment in which to apply a judicial exception is not sufficient to provide something more than judicial exception. This is comparable to the example vi “Limiting the abstract idea of collecting information, analyzing it, and displaying certain results of the collection and analysis to data related to the electric power grid, because limiting application of the abstract idea to power-grid monitoring is simply an attempt to limit the use of the abstract idea to a particular technological environment, Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016);” found in MPEP 2106.05(h).
Therefore, since use of the judicial exception for a specific diagnostic purpose is no more than a field-of-use limitation, it does not constitute something more for the purpose of step 2B consideration. This argument is not found to be persuasive.
Applicant’s arguments, see section IV Pg 8-9, filed Aug-24 2026, with respect to the rejection(s) of claim(s) 1, 4, & 7 under U.S.C. 102(a)(1) have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Brunner in view of Mohamed Elmahdy et al. (US 2020/0187829, hereinafter Mohamed Elmahdy), in further view of Jasper, further evidenced by Plarre et al. (“Continuous inference of psychological stress from sensory measurements collected in the natural environment”, Proceedings of the 10th ACM/IEEE International Conference on Information Processing in Sensor Networks, 2011, IPSN'11, pp97-108, hereinafter Plarre). This new grounds of rejection is necessitated by applicants amendments to claims 1, 4, & 7.
Applicant’s arguments with respect to the U.S.C. 103 rejection of claims 2, 3, 5, & 6 have been fully considered but are moot due to the applicant cancelling those claims. However, the below arguments are addressed as they are applicable to the new grounds of rejection.
Applicant argues that the combination of Brunner in view of Mohamed Elmahdy and further evidenced by Plarre fails to disclose or suggest the claimed invention. Applicant argues that while Mohamed Elmahdy teaches smart EEG headsets with electrodes for scalp contact and some gait characteristics (speed and stride length), it fails to teach or suggest:
The specific six brain regions now required by claim 1;
The full ordered combination of frequency spectrum analysis for EEG (first measurement value) + frequency spectrum analysis for HRV (second measurement value) + quantitative gait analysis including stride length and gait speed (third measurement value);
Integration of these three specific measurement values into a logistic model constructed specifically for geriatric cognitive impairment diagnosis "by using variables including the first measurement value, the second measurement value, and the third measurement value."
The examiner concedes that Mohamed Elmahdy does not teach specific six brain regions now required by claim 1. These six brain regions were not a part of the originally rejected claim, and this argument is unpersuasive due to new grounds of rejection.
Mohamed Elmahdy was not used to teach the combination of EEG, HRV, and gait analysis in the 103 rejection set forth in the Non-Final Office Action mailed June-05 2026. This claim element is taught by Brunner. Likewise, Brunner, not Mohamed Elmahdy, was cited as teaching the integration of three specific measurement values into a logistic model constructed specifically for geriatric cognitive impairment diagnosis in the 103 rejection set forth in the Non-Final Office Action mailed June-05 2026. These arguments are not found to be persuasive.
In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986).
Applicant further argues that Plarre only evidences that certain sensor systems use skin electrodes for HRV-related measurements. Indeed, Plarre adds nothing regarding the specific EEG regions, the particular feature calculations, or the integrated model now claimed.
In the 103 rejection set forth in the Non-Final Office Action mailed June-05 2026, Plarre is cited to evidence that the AutoSense wireless sensor system of Brunner would necessarily include heart rate variability measured through the plurality of electrodes. Plarre does not discuss the measurement of EEGs. However, in the 103 rejection set forth in the Non-Final Office Action mailed June-05 2026, the measurement of EEG signals through a plurality of electrodes in contact with the scalp is taught by Mohamed Elmahdy, not through Plarre. This argument is not found to be persuasive.
Applicant argues that there is no motivation to combine to arrive at the claimed invention. Applicant argues that Brunner is a general health monitoring platform. Mohamed Elmahdy focuses on gait-cognition links and EEG headsets. Nothing in the cited references would have led a skilled artisan to the specific ordered combination of six-region EEG + detailed multi-domain feature extraction from EEG, HRV, and gait + integration into a logistic model for geriatric cognitive impairment diagnosis.
In response to applicant’s argument that there is no teaching, suggestion, or motivation to combine the references, the examiner recognizes that obviousness may be established by combining or modifying the teachings of the prior art to produce the claimed invention where there is some teaching, suggestion, or motivation to do so found either in the references themselves or in the knowledge generally available to one of ordinary skill in the art. See In re Fine, 837 F.2d 1071, 5 USPQ2d 1596 (Fed. Cir. 1988), In re Jones, 958 F.2d 347, 21 USPQ2d 1941 (Fed. Cir. 1992), and KSR International Co. v. Teleflex, Inc., 550 U.S. 398, 82 USPQ2d 1385 (2007). In this case, it would have been obvious one of ordinary skill in the art at the time of filing of the instant application to combine the specific gait characteristic detected through EEG electrodes taught by Mohamed Elmahdy with the multiparameter logistic model capable of detecting neurodegenerative diseases taught by Brunner in order to detect early signs of cognitive aberrations using the strong link between cognition and changes in gait patterns (Mohamed Elmahdy [0013]). This argument is not found to be persuasive.
Applicant argues that the specification provides strong objective evidence of non-obviousness (i.e. unexpected results). Applicant argues that when the specific claimed combination was tested on actual patient data (100 elderly subjects aged 65 or older), it achieved an ROC AUC of 0.955 (excellent discriminatory power) and diagnostic accuracy of 92%. See e.g., paragraphs [0059]-[0061] and FIGS. 5-6. This high performance from the specific multi-bio-signal approach recited in the claims constitutes unexpected results that support a conclusion of non-obviousness.
MPEP 716.02(c)(II) states that “ "Expected beneficial results are evidence of obviousness of a claimed invention, just as unexpected results are evidence of unobviousness thereof." In re Gershon, 372 F.2d 535, 538, 152 USPQ 602, 604 (CCPA 1967). Mohamed Elmahdy teaches a predictive link between changes in cognition and changes in gait patterns.” Integrating a known strongly predictive factor into a diagnostic model would merely have the expected beneficial result of improving discriminatory power.
MPEP 716.02(d) states that “ "objective evidence of nonobviousness must be commensurate in scope with the claims which the evidence is offered to support." In other words, the showing of unexpected results must be reviewed to see if the results occur over the entire claimed range. In re Clemens, 622 F.2d 1029, 1036, 206 USPQ 289, 296 (CCPA 1980).” The invention as claimed includes measurement in six regions corresponding to the frontal lobe, temporal lobe, occipital lobe, parietal lobe, prefrontal lobe, and central gyrus of the subject. In [0039] the specification discusses how these measurements might be used including consideration of a delta-alpha ratio, a theta-alpha ratio, and a theta-beta ratio. It then goes on to describe measurements made solely from the occipital lobe. The scope of the invention claims measurement from all 6 brain regions, but the evidence presented appears to only disclose measurements made from the occipital lobe. Therefore, the evidence of non-obviousness is not commensurate with the scope of the claimed invention.
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 1-7 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1:
Claim 1 recites a method and is therefore a process.
Claim 4 and claim 7 recite a device and a non-transitory computer-readable recording medium, respectively, both of which are products.
Therefore, the claims fall within the statutory categories.
Step 2A, Prong 1:
Claims 1, 4, and 7 recite the following limitations:
collecting multiple bio-signals including brain waves, heart rate variability, and gait measurement values of a subject;
measuring brain waves through a plurality of electrodes
calculating a first/second/third measurement value by analyzing a frequency spectrum/gait measurement values
calculating a probability value of a geriatric cognitive impairment disease by using a cognitive impairment diagnosis model, based on the multiple bio-signals; and
determining whether there is a geriatric cognitive impairment disease, based on a calculated probability value,
applying brain waves, heart rate variability, and gait measurement values of a patient with a geriatric cognitive impairment disease to a logistic function
applying … values of a patient… to a logistic function for calculating the probability value
The limitations, as drafted, describe a process that, under its broadest reasonable interpretation, includes performance of the limitation in the mind or a mathematical calculation except for the recitation of “a computer”, “a data transmission/reception module, a memory, and a processor” and “a non-transitory computer-readable recording medium”, which are recited at a high level of generality and is nothing more than parts of generic computer. That is, other than reciting that parts of a generic computer is performing these tasks, nothing in the claim precludes the steps from practically being performed in the human mind or being considered as mathematical calculations. MPEP 2106.04(a)(2)(III) states that the courts consider a mental process (thinking) that "can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea and MPEP 2106.04(a)(2)(I)(C) states that a claim that recites a mathematical calculation, when the claim is given its broadest reasonable interpretation in light of the specification, will be considered as falling within the "mathematical concepts" grouping. For example, aside from the recitation of “performed by a computer”, the claim encompasses a medical professional gathering biological data, using that data to perform associated calculations, and making a diagnosis based on the results of those calculations.
Step 2A, Prong 2:
The claims recites additional element: “a computer”, to perform the abstract steps identified in Step 2A, Prong 1 section above, and “a non-transitory computer-readable recording medium”. This limitation read on a computer implemented method and is recited at a high level of generality, i.e., as a generic processor performing a generic computer function of processing data, and a generic computer memory component performing a generic computer function of storing data. This generic computer limitation is no more than mere instructions to apply the exception using generic computer components. Accordingly, this additional limitation does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claims also recite “a plurality of electrodes” and a “plurality of motion detectors”. The “a plurality of electrodes”, and “a plurality of motion detection sensors” are not part of the claimed diagnostic device, and do not perform any of the claimed steps of the method, but rather the source of the bio-signals use used by the device (see 10 and 100 in Fig. 1), and therefore constitute nothing more than mere pre-solution activity of data gathering. .
Step 2B:
As discussed with respect to Step 2A Prong Two, the additional elements in the claim amount to no more than mere instructions to apply the exception using a generic computer component. The same analysis applies here in 2B, i.e., mere instructions to apply an exception on a generic computer cannot integrate a judicial except into a practical application at Step 2A or provide an inventive concept in Step 2B.
Under 2019 PEG, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be re-evaluated in Step 2B to determined if it is more than what is well-understood, routine, conventional activity in the field. The specification in [0031]-[0035] does not provide any indication that the computer processor and non-transient computer readable recording medium are anything other than a generic, off-the-shelf computer components. Court decisions cited in MPEP 2106.05(d)(II) indicate that computer‐implemented processes not to be significantly more than an abstract idea (and thus ineligible) where the claim as a whole amounts to nothing more than generic computer functions merely used to implement an abstract idea, such as an idea that could be done by a human analog (i.e., by hand or by merely thinking). Accordingly, a conclusion that the generic computer functions merely being used to implement an abstract idea is well-understood, routine, conventional activity is supported under Berkheimer Option 2.
The use of a plurality of electrodes to collect both EEG and ECG data is well-understood, routine, conventional activity in the art as evidenced by Reilly & Lee (Electrograms (ECG, EEG, EMG, EOG) (2010) Technology and Healthcare 18, Pg 443-458) in section 3.1 Basis of the ECG and section 4.1 Electrode montages.
The use of a plurality of accelerometers (i.e. motion detection sensors) for collecting gait measurement data is well-understood, routine, conventional activity in the art as evidenced by Chiang (US 2012/002406) ([0003]-[0004]).
Using a logistic function to calculate a probability value from measured biomarkers and other data collected from a patient is well-understood, routine, conventional activity in the art as evidenced by Cohen et al. (US 2019/0131016, see [0080]).
For these reasons, there is no inventive concept in the claims and thus they are ineligible.
Claim Rejections - 35 USC § 103
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1, 41 & 7 are rejected under 35 U.S.C. 103 as being unpatentable over Brunner in view of Mohamed Elmahdy et al. (US 2020/0187829, hereinafter Mohamed Elmahdy), in further view of Jasper (Report of the Committee on Methods of Clinical Examination in Electroencephalography. Jasper, H. (1958) Electroencephalography and Clinical Neurophysiology, 10, 370-375), further evidenced by Plarre et al. (“Continuous inference of psychological stress from sensory measurements collected in the natural environment”, Proceedings of the 10th ACM/IEEE International Conference on Information Processing in Sensor Networks, 2011, IPSN'11, pp97-108, hereinafter Plarre).
Regarding claim 1, Brunner teaches a multi-bio-signal-based geriatric cognitive impairment diagnosis method (Fig. 1 and “a universal platform that can preferably accept data from any smart gadget, for … improving diagnosis… applicable to a broad range of diseases including… neurodegenerative diseases” in [0009] and “ individuals with a mental disorder such as… Alzheimer's Disease… with a sensor or set of sensors that capture health-relevant data” in [0041]) which is performed by a computer (“The methods provided for monitoring a present or prospective condition of a first subject may comprise: at a computer system comprising one or more processors and a memory” in [0020-0021]), the multi-bio-signal-based geriatric cognitive impairment diagnosis method comprising: collecting multiple bio-signals including brain waves (“Data may be any input generated by the subject… examples of data comprise, but are not restricted to… EEG (electroencephalogram)” in [0162]), heart rate variability (“a change in the values a feature takes (e.g., heart rate=90 bpm) may be correlated to changes in the values of another feature of the same functional domain (e.g., heart rate variability)” in [0176]), and gait measurement values of a subject (“the system can be used to monitor signals originating from wearable devices specifically designed for the system such as special shoes to measure subtle changes in gait or motor movement” in [0218]), wherein collecting the multiple bio-signals comprises: calculating a first measurement value by analyzing a frequency spectrum (Table V line 7, and “EEG signals or gait time series data may be analyzed using Fourier Analysis in [0170]. Examiner notes that Table V lists quantification of frequency as a type of processed data used by the platform) based on brain waves (Table IV, line 1 and Experimental data may be any data collected that measures or estimates the subjects' Physiological (e.g., EEG)… etc. (see Table IV) and Discrete data” in [0168]), calculating a second measurement value by analyzing a frequency spectrum based on heart rate variability (Tables IV & V, and “the platform may allow a research to determine distinct clusters of participants… These distinct cluster may identify those participants with certain parameters (e.g., physiological and/or biological and/or environmental), for example, low heart rate variability (HRV)” in [0045]) measured through the plurality of electrodes (“Data can be obtained using… sensors that are independent of wearable devices but provide complementary electronic data (such as, but not restricted to, AutoSense [Ref. 9]” in [0158]); analyzing gait measurement values measured through a plurality of motion detection sensors during a gait cycle of the subject(“special shoes to measure subtle changes in gait or motor movement… comprise two or four sensors, one on each shoe or limb that will provide signals indicating the relative position and movement of the feet or limbs” in [0218]),
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calculating a probability value (“a “trajectory diagnostic profile” refers to a profile of a subject… For example, a brain tumor trajectory diagnostic profile relates to the probability that a subject may develop or has a brain tumor” in [0146]) of a geriatric cognitive impairment disease by using a cognitive impairment diagnosis model, based on the multiple bio-signals (This data may form a comprehensive profile or health avatar and may be captured by the present invention allowing for a subject's placement on a trajectory diagnostic profile in [0039]); and determining whether there is a geriatric cognitive impairment disease, based on a calculated probability value (“the present invention, the system can be used to diagnose new diseases by comparing individual health trajectory against the varied disease group trajectories” in [0213] and “Using trained classifiers an early assessment can be made of his data and the feedback may consist of his classification as a healthy person or a probability that the person has a certain disease” in [0239]) wherein the cognitive impairment diagnosis model is a model constructed by applying brain waves, heart rate variability, and gait measurement values of a patient with a geriatric cognitive impairment disease to a logistic function (“multiple analytical algorithms such as, … penalized logistic regression, … can be used to analyze the data” in [0018]), for calculating the probability value of the geriatric cognitive impairment disease by using variables including the first measurement value, the second measurement value, and the third measurement value (“the present invention, the system can be used to diagnose new diseases by comparing individual health trajectory against the varied disease group trajectories” in [0213] and “Using trained classifiers an early assessment can be made of his data and the feedback may consist of his classification as a healthy person or a probability that the person has a certain disease” in [0239]).
AutoSense wireless sensor system of Brunner would necessarily include heart rate variability measured through the plurality of electrodes as evidenced by Plarre, which teaches that AutoSense wearable sensor system using a plurality of electrodes in contact with a skin of the subject to measure electrical output of the heart (“an electrocardiograph (ECG) attached to the body with two electrodes to measure electrical output of the heart)” on p100, section 3.2 Measures and Fig. 2).
Regarding claim 4, Brunner teaches A multi-bio-signal-based geriatric cognitive impairment (applicable to a broad range of diseases including… neurodegenerative diseases” in [0009] and “ individuals with a mental disorder such as… Alzheimer's Disease… with a sensor or set of sensors that capture health-relevant data” in [0041]) diagnosis device (“The methods provided for monitoring a present or prospective condition of a first subject may comprise: at a computer system comprising one or more processors and a memory in [0020-0021]) comprising: a data transmission/reception module (20 in Fig 1 and “As used herein, “Streaming Algorithm” is a trained algorithm used to process data at the sensor, smartphone, or local computer level. Streaming data is a sequence of digitally encoded coherent signals used to transmit or receive information” in [0139]); a memory storing a geriatric cognitive impairment diagnosis program; and a processor configured to execute the geriatric cognitive impairment diagnosis program stored in the memory (“one or more processors and a memory” and “obtaining a dataset comprising a first form of physiological or environmental data associated with the first subject… executing a query to obtain an optimized query answer, wherein said query comprises… a deviation or conformance to a normative group health condition by the first subject” in [0021-0026]), wherein the geriatric cognitive impairment diagnosis program collects multiple bio-signals including brain waves (“Data may be any input generated by the subject… examples of data comprise, but are not restricted to… EEG (electroencephalogram)” in [0162]), heart rate variability (“a change in the values a feature takes (e.g., heart rate=90 bpm) may be correlated to changes in the values of another feature of the same functional domain (e.g., heart rate variability)” in [0176]), and gait measurement values of a subject (“the system can be used to monitor signals originating from wearable devices specifically designed for the system such as special shoes to measure subtle changes in gait or motor movement” in [0218]); wherein collecting the multiple bio-signals comprises: calculating a first measurement value by analyzing a frequency spectrum (Table V line 7, and “EEG signals or gait time series data may be analyzed using Fourier Analysis in [0170]. Examiner notes that Table V lists quantification of frequency as a type of processed data used by the platform) based on brain waves (Table IV, line 1 and Experimental data may be any data collected that measures or estimates the subjects' Physiological (e.g., EEG)… etc. (see Table IV) and Discrete data” in [0168]), calculating a second measurement value by analyzing a frequency spectrum based on heart rate variability (Tables IV & V, and “the platform may allow a research to determine distinct clusters of participants… These distinct cluster may identify those participants with certain parameters (e.g., physiological and/or biological and/or environmental), for example, low heart rate variability (HRV)” in [0045]) measured through the plurality of electrodes (“Data can be obtained using… sensors that are independent of wearable devices but provide complementary electronic data (such as, but not restricted to, AutoSense [Ref. 9]” in [0158]); analyzing gait measurement values measured through a plurality of motion detection sensors during a gait cycle of the subject(“special shoes to measure subtle changes in gait or motor movement… comprise two or four sensors, one on each shoe or limb that will provide signals indicating the relative position and movement of the feet or limbs” in [0218]),
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calculates a probability value of a geriatric cognitive impairment disease by using a cognitive impairment diagnosis model, based on the multiple bio-signals (This data may form a comprehensive profile or health avatar and may be captured by the present invention allowing for a subject's placement on a trajectory diagnostic profile in [0039]), and determines whether there is a geriatric cognitive impairment disease, based on a calculated probability value (“a “trajectory diagnostic profile” refers to a profile of a subject… For example, a brain tumor trajectory diagnostic profile relates to the probability that a subject may develop or has a brain tumor” in [0146]), and the cognitive impairment diagnosis model is a model constructed by applying brain waves, heart rate variability, and gait measurement values of a patient with a geriatric cognitive impairment disease to a logistic function (“multiple analytical algorithms such as, … penalized logistic regression, … can be used to analyze the data” in [0018]).
AutoSense wireless sensor system of Brunner would necessarily include heart rate variability measured through the plurality of electrodes as evidenced by Plarre, which teaches that AutoSense wearable sensor system using a plurality of electrodes in contact with a skin of the subject to measure electrical output of the heart (“an electrocardiograph (ECG) attached to the body with two electrodes to measure electrical output of the heart)” on p100, section 3.2 Measures and Fig. 2).
Regarding claims 1 and 4, Brunner as evidenced by Plarre does not teach wherein collecting the multiple bio-signals comprises: measuring brain waves through a plurality of electrodes in contact with a scalp of the subject in six regions corresponding to a frontal lobe, a temporal lobe, an occipital lobe, a parietal lobe, a prefrontal lobe, and a central gyrus, measured through the plurality of electrodes and gait measurement values including a stride length and a gait speed
However, attention is drawn to the Mohamed Elmahdy reference. Mohamed Elmahdy teaches a method, a computer-readable storage device, and an apparatus for predicting a fall including collecting gait information associated with a user from a first wearable device worn by the user, collecting electroencephalography information associated with the user from a second wearable device worn by the user, calculating a likelihood that the user will fall within a threshold period of time from a current time, wherein the calculating is based on a combination of the gait information and the electroencephalography information ([0003]). Data would be collected by wearable devices 150A-1500 and 152A-152C where each of the wearable devices 150A-1500 may comprise one or a pair of smart shoe insoles or inserts, while each of the wearable device 152A-152C may comprise a smart EEG headset. The term “smart” implies the ability to measure, record, process, and communicate information ([0019]). Each of the smart EEG headsets 152A-152C may comprise a headband, hat, or other head-mounted device that includes a plurality of built-in EEG sensors or electrodes ([0021]) (measuring brain waves through a plurality of electrodes in contact with a scalp). Various characteristics of motion, such as speed and stride length, may be determined from gait information in various ways from data gathered by sensors 150A-1500 ([0029]) (gait measurement values including a stride length and a gait speed).
Mohamed Elmahdy discloses that “there is a strong link between cognition and changes in gait patterns (for instance, changes in gait can be used to detect early signs of cognitive aberrations). As an example, Alzheimer's disease primarily affects the hippocampus region of the brain (which is a key area of the brain for the formation of new memories) and may also manifest in changes in gait (e.g., cautious gait in the early stages and frontal gait disorders in the later stages)” in [0013] and that their application server may “determine characteristics of motion such as a stride length, a speed, an acceleration, an elevation, and so forth” ([0023]) and may also determine characteristics of neurological activity from the EEG information ([0028]) which can be collected from a plurality of electrodes in a head-mounted device ([0021]). They disclose that the baseline neural oscillations for Alzheimer's disease would be expected to be different from the baseline neural oscillations from a non-cognitive motor disorder such as multiple sclerosis ([0044]).
It would have been obvious one of ordinary skill in the art at the time of filing of the instant application to apply the specific metrics of speed and stride length, as taught by Mohamed Elmahdy, to the gait analysis as taught by Brunner, in order to detect early signs of cognitive aberrations using the strong link between cognition and changes in gait patterns. Further, it would have been obvious to one of ordinary skill in the art at the time of filing of the instant application to use the smart EEG headsets of Mohamed Elmahdy in the method and device of Brunner to collect the brain wave data for analysis and determination of characteristics of neurological activity.
Regarding claims 1 and 4, Brunner in view of Mohamed Elmahdy further evidenced by Plarre does not teach a plurality of electrodes in contact with a scalp of the subject in six regions corresponding to a frontal lobe, a temporal lobe, an occipital lobe, a parietal lobe, a prefrontal lobe, and a central gyrus.
However, attention is drawn to the Jasper reference. Jasper discloses a standardized placement of electrodes on the head for EEG examinations to facilitate comparison of records taken in different laboratories and to make it possible to have more satisfactory communication of results in the literature (Pg 371 ¶11). This standard applies the following principles: 1. Positions of electrodes should be determined by measurement from standard landmarks on the skull. Measurements should be proportional to skull size and shape, insofar as possible. 2. Adequate coverage of all parts of the head should be provided with standard designated positions even though all would not be used in a given examination. 3. Designations of positions should be in terms of brain areas (Frontal, Parietal, etc.) rather than only in numbers so that communication would become more meaningful to the non-specialist. 4. Anatomical studies should be carried out to determine the cortical areas most likely to be found beneath each of the standard electrode positions in the average subject. The electrodes in this system are named in reference to 5 points corresponding to brain regions. These 5 points are Frontal pole (Fp), Frontal (F), Central (C), Parietal (P), and Occipital (O). Fig. 1-5 depict the placements of the electrodes in this standard. As seen in annotated Fig. 5, Fp1 & Fp2 sit proximal to the pre-frontal lobe; FZ, F3, F4, F7, & F8 span the frontal lobe; PZ, P3, & P4 span the parietal lobe; and O1 & O2 sit proximal to the occipital lobe. As seen in annotated Fig. 4, T3, T4, T5, & T6 sit proximal to the temporal lobe. As seen in annotated Fig. 6, Cx, C3, & C4 sit proximal to the Fissure Rolandi, the anatomical feature that separates the anterior and posterior halves of the central gyrus.
It would have been obvious to one of ordinary skill in the art at the time of filing of the instant application to use the standardized system of electrode placements taught by Jasper to the place the electrodes for measuring brain waves in a multi-bio-signal-based geriatric cognitive impairment diagnosis method taught by Brunner in view of Mohamed Elmahdy further evidenced by Plarre for the purpose of providing adequate coverage of all parts of the head based on the cortical areas most likely to be found beneath each of the standard electrode positions in the average subject.
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Regarding claim 7, Brunner in view of Mohamed Elmahdy, in further view of Jasper, further evidenced by Plarre teaches a multi-bio-signal-based geriatric cognitive impairment diagnosis method according to claim 1
Brunner further teaches a non-transitory computer-readable recording medium on which a computer program for performing a multi-bio-signal-based geriatric cognitive impairment diagnosis method (“The present invention can be implemented as a computer program product that comprises a computer program mechanism embedded in a nontransitory computer readable storage medium” in [0279]).
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.
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/W.P.A./Examiner, Art Unit 3792
/AMANDA L STEINBERG/Examiner, Art Unit 3792
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