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 .
Drawings
Figures 1-105 should be designated by a legend such as --Prior Art-- because only that which is old is illustrated. See MPEP § 608.02(g). Corrected drawings in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. The replacement sheet(s) should be labeled “Replacement Sheet” in the page header (as per 37 CFR 1.84(c)) so as not to obstruct any portion of the drawing figures. If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
It is noted that Figures 1-105 of the instant application are exact copies of the same Figures 1-105 found in application 15/175905 by inventor Charles Duffy, who has been cited in the current disclosure and from which the majority of the specification also appears to be taken.
Specification
The disclosure is objected to because of the following informalities:
the specification states “The present disclosure is related to the subject matter disclosed in the following co-pending application filed on Sep. 16, 2009 and each naming Charles Joseph Duffy as the inventor: Ser. No. 12/560,583 and entitled METHOD AND SYSTEM FOR QUANTITATIVE ASSESSMENT OF FUNCTIONAL IMPAIRMENT” (0171 filed spec).
However, this statement is false as the application data of the instant invention does not support this. Furthermore, the listed prior applicant is by a completely different inventor and has nothing to do with the instant case, inventorship-wise. It is suggested that this statement be deleted.
Appropriate correction is required.
Claim Objections
Claims 1 and 7 are objected to because of the following informalities:
“accessing the onset” of a cognitive impairment should be “assessing the onset.”
Appropriate correction is required.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
No elements are interpreted under 112(f).
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-12 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.
In regard to Claims 1 and 7, the recitation of step 1d in Claim 1 and step iv of Claim 7 are indefinite because it is unclear how the previously recited first, second and third tests are presented, such as sequentially or simultaneously, to determine the cognitive assessment.
Additionally, per MPEP 2173.03: a claim, although clear on its face, may also be indefinite when a conflict or inconsistency between the claimed subject matter and the specification disclosure renders the scope of the claim uncertain as inconsistency with the specification disclosure or prior art teachings may make an otherwise definite claim take on an unreasonable degree of uncertainty. In re Moore, 439 F.2d 1232, 1235-36, 169 USPQ 236, 239 (CCPA 1971); In re Cohn, 438 F.2d 989, 169 USPQ 95 (CCPA 1971); In re Hammack, 427 F.2d 1378, 166 USPQ 204 (CCPA 1970).
In regard to Claims 1 and 7, the claims recite certain steps and details that do not appear supported in scope by the disclosure as filed. For example, the disclosure does not expressly lay out a first test, a second test, and third test as distinctly claimed.
Additionally, the steps of “aggregating” as recited in the first test and “creating a shape discrimination score” as recited in the third test do not appear reflected in the disclosure with the specified steps as claimed. For example, it is unclear how the reversal latency, said acceleration lag, said deceleration lag, and said speed profile are specifically determined. Thus, the resulting adaptive motor response profile and shape discrimination score of the above tests are indefinite because it is unclear what is referred to by these outputs or values as supported by the disclosure.
Claims 2-6 and 8-12 are rejected by virtue of dependence on Claims 1 and 7.
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.
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.
Claim(s) 1 and 7 are rejected under 35 U.S.C. 103 as being unpatentable over Duffy (US Pub No. 20170150907), referred to as Duffy ‘2017, in view of Duffy (US Pat No. 8777630), referred to as Duffy ‘630.
In regard to Claim 1, Duffy ‘2017 disclose a method for accessing the onset or progression of a cognitive impairment within a subject, the method comprising:
a) performing a first test to measure an adaptive motor response of the subject (see Claim 43), wherein the first test comprises the following steps executed on a computer processor 200, best seen in Figure 3-4 (0223-0235):
i) presenting an indicium on a GUI (see Claim 43); ii) for at least a first gain, and at least a first noise, moving said indicium, wherein said moving of said indicium comprises:
a) varying acceleration, b) varying deceleration, c) varying reversal, and d) varying speed of movement (see Claim 43);
iii) receiving input, via an input mechanism 402, best seen in Figure 3 (0261-0269), responsive to said movement of said indicium,
determining at least: a) a reversal latency, b) an acceleration lag, c) a deceleration lag, and d) a speed profile (see Claim 43); and
iv) aggregating said reversal latency, said acceleration lag, said deceleration lag, and said speed profile to determine a patient adaptive motor response profile, i.e. patient profile (see Claim 43);
b) performing a second test – see Claim 44 – to measure a visual salience of the subject, wherein the second test comprises the following steps executed on the computer processor;
i) presenting a visual stimulus having a pre-set brightness, contrast, background luminance, and spatial frequency composition, wherein the visual stimulus necessarily has said pre-set features (see Claim 44);
ii) determining a threshold value for each of the brightness, the contrast, the background luminance, and the spatial frequency composition by varying each of the brightness, the contrast, the background luminance, and the spatial frequency composition in a chosen order, individually, or in combination (see Claim 44); and
iii) determining a visual saliency profile by aggregating the brightness threshold value, the contrast threshold value, the background luminance threshold value, and the spatial frequency composition threshold value (see Claim 44).
However, Duffy ‘2017 do not expressly disclose performing a third test to measure a shape discrimination value of the subject with the steps claimed. It is noted that Duffy ‘2017 recite that in addition to performing the adaptive motor test, “performing at least one diagnostic test for said patient profile, said diagnostic test selected from the group consisting of: a visual saliency test, a perception test” (see claim 43). In other words, Duffy ‘2017 suggest performing a third test. Duffy ‘2017 also disclose a shape discrimination test – “visual form discrimination test, during which patches of regular shapes may be distorted to distinguish target area shapes from their background” (0369), including shape perception 20008 (0465).
Duffy ‘2017 also teach evaluating each of the patient adaptive motor response profile of the first test and the visual saliency profile of the second test to determine a cognitive assessment where the subject exhibits either a normal cognitive state or cognitive impairment – “responsive to said at least one diagnostic test; determining results for said diagnostic test and outputting a performance profile” (see Claim 43 bottom). Also, Duffy ‘2017 disclose “a functional impairment characteristic profile 2052 and one or more suggested diagnoses of specific types of processing impairment and likely or commonly associated underlying pathophysiologies that include conditions, diseases, disorders, intoxications, and other mechanisms of brain functional impairment” (0471), “the present disclosure may include diagnosis specific testing. In these embodiments, performance in behavioral tasks, along… may be indicative of the specific disorder” (0504).
Duffy ‘630 teach that it is well-known in the art to provide an analogous cognitive impairment assessment device such that there is a test to measure a shape discrimination value of the subject, wherein the third test comprises the following steps executed on the computer processor: i) presenting at least two stimuli simultaneously such that one of said at least two stimuli comprises a target stimulus and the other one(s) of said at least two stimuli comprises at least one non-target stimulus (see Claim 1, presenting step);
ii) monitoring the speed and accuracy of the subject's indication of a position of said target stimulus as said target stimulus moves along a specific pattern of a visual form, and a signal-to-noise ratio and a stimulus sequence duration of the target stimulus changes – “creating a subject score deriving from the subject's accuracy, speed, and precision in responding to said changes in said signal-to-noise ratios and stimulus sequence durations of said at least two stimuli” (see Claim 1);
iii) analyzing the subject's positional error with respect to said position of said target stimulus and observed subject response motion dynamics errors associated with the subject's ability to respond to a movement of said target stimulus (see Claim 1 bottom of Column 52-Column 53 top);
iv) adjusting the signal-to-noise ratio relating to said target stimulus and non-target stimulus wherein the signal-to-noise ratio is increased until the subject has correctly identified the target stimuli – “the signal-to-noise ratio is increased until the subject has correctly identified the target stimuli” (see Claim 1); and
v) creating a shape discrimination score deriving from the subject's accuracy, speed, and precision in responding to said changes in said signal-to-noise ratios and stimulus sequence durations of said at least two stimuli (see Claim 1, Column 53 top).
Duffy ‘630 teach said third test above to effectively assess the onset or progression of the subject’s cognitive impairment (Col.4: 1-12).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of filing to modify Duffy ‘2017 to include a third to measure a shape discrimination value of the subject already taught by Duffy ‘2017 to include the steps above executed on the computer processor as taught by Duffy ‘630 to effectively improve the cognitive impairment device of Duffy ‘2017 by providing an additional diagnosis test for superior assessment of the patient.
In combination, Duffy ‘2017 with Duffy ‘630 would thus provide evaluating each of the patient adaptive motor response profile of the first test, the visual saliency profile of the second test, and the shape discrimination score of the third test to determine a cognitive assessment where the subject exhibits either a normal cognitive state or cognitive impairment for superior diagnosis.
In regard to Claim 7, Duffy ‘2017 disclose an apparatus for accessing the onset or progression of a cognitive impairment within a subject, the apparatus comprising:
a) computing device 200 including a memory 206 and a processor 204, best seen in Figure 3-4 (0223-0235);
b) an input device 402, best seen in Figure 3 (0261-0269); and
c) a user interface, i.e. cursor 1050 or touch screen display panel 422, on a computer screen 198, best seen in Figure 3 and 8 (0219-0222, 0267), wherein the apparatus is configured to:
i) perform a first test to measure an adaptive motor response of the subject (see Claim 43), wherein the first test comprises the following steps executed on the processor:
a) presenting an indicium on the user interface (see Claim 43); b) for at least a first gain, and at least a first noise, moving said indicium, wherein said moving of said indicium comprises:
i) varying acceleration, ii) varying deceleration, iii) varying reversal, and iv) varying speed of movement (see Claim 43);
c) receiving input, via the input device, responsive to said movement of said indicium,
determining at least: i) a reversal latency, ii) an acceleration lag, iii) a deceleration lag, and iv) a speed profile (see Claim 43); and
d) aggregating said reversal latency, said acceleration lag, said deceleration lag, and said speed profile to determine a patient adaptive motor response profile, i.e. patient profile (see Claim 43);
ii) perform a second test – see Claim 44 – to measure a visual salience of the subject, wherein the second test comprises the following steps executed on the processor;
a) presenting a visual stimulus on the user interface having a pre-set brightness, contrast, background luminance, and spatial frequency composition (see Claim 44);
b) determining a threshold value for each of the brightness, the contrast, the background luminance, and the spatial frequency composition by varying each of the brightness, the contrast, the background luminance, and the spatial frequency composition in a chosen order, individually, or in combination (see Claim 44); and
c) determining a visual saliency profile by aggregating the brightness threshold value, the contrast threshold value, the background luminance threshold value, and the spatial frequency composition threshold value (see Claim 44).
However, Duffy ‘2017 do not expressly disclose performing a third test to measure a shape discrimination value of the subject with the steps claimed. It is noted that Duffy ‘2017 recite that in addition to performing the adaptive motor test, “performing at least one diagnostic test for said patient profile, said diagnostic test selected from the group consisting of: a visual saliency test, a perception test” (see claim 43). In other words, Duffy ‘2017 suggest performing a third test. Duffy ‘2017 also disclose a shape discrimination test – “visual form discrimination test, during which patches of regular shapes may be distorted to distinguish target area shapes from their background” (0369), including shape perception 20008 (0465).
Duffy ‘2017 also teach evaluating each of the patient adaptive motor response profile of the first test and the visual saliency profile of the second test to determine a cognitive assessment where the subject exhibits either a normal cognitive state or cognitive impairment – “responsive to said at least one diagnostic test; determining results for said diagnostic test and outputting a performance profile” (see Claim 43 bottom). Also, Duffy ‘2017 disclose “a functional impairment characteristic profile 2052 and one or more suggested diagnoses of specific types of processing impairment and likely or commonly associated underlying pathophysiologies that include conditions, diseases, disorders, intoxications, and other mechanisms of brain functional impairment” (0471), “the present disclosure may include diagnosis specific testing. In these embodiments, performance in behavioral tasks, along… may be indicative of the specific disorder” (0504).
Duffy ‘630 teach that it is well-known in the art to provide an analogous cognitive impairment assessment device such that there is a test to measure a shape discrimination value of the subject, wherein the third test comprises the following steps executed on the processor:
a) presenting at least two stimuli simultaneously such that one of said at least two stimuli comprises a target stimulus and the other one(s) of said at least two stimuli comprises at least one non-target stimulus (see Claim 1, presenting step);
b) monitoring the speed and accuracy of the subject's indication of a position of said target stimulus as said target stimulus moves along a specific pattern of a visual form, and a signal-to-noise ratio and a stimulus sequence duration of the target stimulus changes – “creating a subject score deriving from the subject's accuracy, speed, and precision in responding to said changes in said signal-to-noise ratios and stimulus sequence durations of said at least two stimuli” (see Claim 1);
c) analyzing the subject's positional error with respect to said position of said target stimulus and observed subject response motion dynamics errors associated with the subject's ability to respond to a movement of said target stimulus (see Claim 1 bottom of Column 52-Column 53 top);
d) adjusting the signal-to-noise ratio relating to said target stimulus and non-target stimulus wherein the signal-to-noise ratio is increased until the subject has correctly identified the target stimuli – “the signal-to-noise ratio is increased until the subject has correctly identified the target stimuli” (see Claim 1); and
e) creating a shape discrimination score deriving from the subject's accuracy, speed, and precision in responding to said changes in said signal-to-noise ratios and stimulus sequence durations of said at least two stimuli (see Claim 1, Column 53 top).
Duffy ‘630 teach said third test above to effectively assess the onset or progression of the subject’s cognitive impairment (Col.4: 1-12).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of filing to modify Duffy ‘2017 to include a third to measure a shape discrimination value of the subject already taught by Duffy ‘2017 to include the steps above executed on the computer processor as taught by Duffy ‘630 to effectively improve the cognitive impairment device of Duffy ‘2017 by providing an additional diagnosis test for superior assessment of the patient.
In combination, Duffy ‘2017 with Duffy ‘630 would thus provide evaluating each of the patient adaptive motor response profile of the first test, the visual saliency profile of the second test, and the shape discrimination score of the third test to determine a cognitive assessment where the subject exhibits either a normal cognitive state or cognitive impairment for superior diagnosis.
Claim(s) 2-6 and 8-12 are rejected under 35 U.S.C. 103 as being unpatentable over Duffy (US Pub No. 20170150907), referred to as Duffy ‘2017, in view of Duffy (US Pat No. 8777630), referred to as Duffy ‘630, further in view of Vaughan et al (US Pub No. 20190043618).
In regard to Claims 2 and 8, Duffy ‘2017 in combination with Duffy ‘630 disclose the invention above but do not expressly disclose using a machine learning model to evaluate each of the patient adaptive motor response profile of the first test, the visual saliency profile of the second test, and the shape discrimination score of the third test to determine an amyloid assessment wherein the subject exhibits either a negative amyloid determination or an amyloid positivity.
Duffy ‘2017 already disclose the use of machine learning models generally – “a need exists for the incorporation of artificial intelligence, that is the machine implementation of subject performance and characteristic data in the real-time parametric control of automated assessments of functional competence and impairment” (0058, 0351).
Vaughan et al teach that it is well-known in the art to provide an analogous cognitive impairment assessment device that advantageously uses a machine learning model (0113) to determine an assessment of the subject exhibiting either a negative or positive result for cognitive conditions such as Alzheimer’s disease (0003, 0204, claim 13).
Vaughan et al teach “As illustrated in FIG. 26, data inputs can be fed into a diagnostic module which can comprise data analysis (2615) using for example a classifier, algorithm (e.g. machine learning algorithm)… to make a diagnosis of whether the subject is likely to have a tested disorder (e.g. Autism Spectrum Disorder) (2620) or is unlikely to have the tested disorder (2625)… The methods and apparatus disclosed herein are not limited to disorders, and may be applied to other cognitive functions, such as behavioral, neurological, mental health, or developmental conditions” (0248). “Data can comprise information collected through diagnostic tests, diagnostic questions, or questionnaires (2605)” (0247, 0220).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of filing to modify Duffy ‘2017 as modified by Duffy ‘630 such that a machine learning model is used to evaluate each of the patient adaptive motor response profile of the first test, the visual saliency profile of the second test, and the shape discrimination score of the third test to determine an amyloid assessment wherein the subject exhibits either a negative amyloid determination or an amyloid positivity as suggested by Vaughan et al to effective assess and diagnose the subject using the advantages of artificial intelligence, as already taught by Duffy ‘2017.
3, 9. Vaughan et al teach the machine learning model employs linear modeling including one or more of linear regression, random forest (RF) regression, support vector (SVM) regression, and gradient boosted machine (GBM) regression – “ One or more machine learning algorithms may be used to construct the assessment model, such as support vector machines… For example, machine learning algorithms or other statistical algorithms may be used, such as alternating decision trees (ADTree), Decision Stumps, functional trees (FT), logistic model trees (LMT), logistic regression, Random Forests, linear classifiers, or any machine learning algorithm or statistical algorithm known in the art” (0113). It is noted that linear regression is very-well known in the art.
4-5, 10-11. Vaughan et al teach the machine learning model employs classification modeling including one or more of random forest (RF) classification, logistic regression, support vector (SVM) classification, and gradient boosted machine (GBM) classification – “FIG. 3 is a schematic diagram illustrating a portion of an exemplary assessment model 160 based on a Random Forest classifier” (0115, 0049).
6, 12. Duffy ‘2017 as modified with Vaughan et al disclose the cognitive assessment exhibits the normal cognitive state and the amyloid assessment exhibits amyloid positivity as taught by Vaughan et al to teach either positive or negative amyloid determination, the amyloid positivity is an indication of preclinical Alzheimer's Disease (0033, 0187, 0294 of Duffy ‘2017).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Huong NGUYEN whose telephone number is (571)272-8340. The examiner can normally be reached 10 am - 6 pm.
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H.Q. NGUYEN
Examiner
Art Unit 3791
/JENNIFER ROBERTSON/Supervisory Patent Examiner, Art Unit 3791
