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 .
Claims Pending
Claims 1-19 are currently under examination.
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.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are:
Claim 1: The claim limitation “a reproducibility evaluator configured to determine a reproducibility evaluation value on a basis of an analysis result regarding reproducibility of a predetermined body motion of a subject” has been interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because it uses a generic placeholder “evaluator” coupled with functional language “configured to determine a reproducibility evaluation value on a basis of an analysis result regarding reproducibility of a predetermined body motion of a subject” without reciting sufficient structure to achieve the function. Furthermore, the generic placeholder is not preceded by a structural modifier that has a known structural meaning before the phrase “evaluator”,
Claim 1: The claim limitation “a mental evaluator configured to determine a mental evaluation value on a basis of an analysis result regarding a mental state of the subject” has been interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because it uses a generic placeholder “evaluator” coupled with functional language “configured to determine a mental evaluation value on a basis of an analysis result regarding a mental state of the subject” without reciting sufficient structure to achieve the function. Furthermore, the generic placeholder is not preceded by a structural modifier that has a known structural meaning before the phrase “evaluator”,
Claim 1: The claim limitation “an evaluation value storage configured to store the reproducibility evaluation value and the mental evaluation value in association with each other” has been interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because it uses a generic placeholder “storage” coupled with functional language “configured to store the reproducibility evaluation value and the mental evaluation value in association with each other” without reciting sufficient structure to achieve the function. Furthermore, the generic placeholder is not preceded by a structural modifier that has a known structural meaning before the phrase “storage”,
Claim 1: The claim limitation “a result outputter configured to output information indicating relevance between the mental evaluation value and quality of the reproducibility evaluation value” has been interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because it uses a generic placeholder “outputter” coupled with functional language “to output information indicating relevance between the mental evaluation value and quality of the reproducibility evaluation value . without reciting sufficient structure to achieve the function. Furthermore, the generic placeholder is not preceded by a structural modifier that has a known structural meaning before the phrase “outputter”,
Claim 2: The claim limitation “a motion information acquirer configured to acquire information indicating a motion state of the subject repeatedly performing the predetermined body motion” has been interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because it uses a generic placeholder “acquirer” coupled with functional language “configured to acquire information indicating a motion state of the subject repeatedly performing the predetermined body motion” without reciting sufficient structure to achieve the function. Furthermore, the generic placeholder is not preceded by a structural modifier that has a known structural meaning before the phrase “acquirer”,
Claim 2: The claim limitation “a mental information acquirer configured to acquire information indicating the mental state of the subject” has been interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because it uses a generic placeholder “acquirer” coupled with functional language “configured to acquire information indicating the mental state of the subject” without reciting sufficient structure to achieve the function. Furthermore, the generic placeholder is not preceded by a structural modifier that has a known structural meaning before the phrase “acquirer”,
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
A review of the specification shows that the following appears to be the corresponding structure described in the specification for the 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph limitation:
“…The reproducibility evaluator 94 extracts a motion feature value of at least one of the position, the trajectory, and the moving speed of the feature point based on the temporal change of the feature point estimated in the moving image. The reproducibility evaluator 94 quantifies the reproducibility of the motion of the subject 10 on the basis of the matching degree of the motion feature value over time.” and a generic algorithm on a generic computational structure capable of the indicated function, or equivalents thereof, as described on Par. 36 and 14 of the disclosure filed on 08/30/2023, which lacks sufficient detail within the applicant’s specification as to the structure of the algorithm and will be interpreted as a generic algorithm capable of the indicated function,
“The mental evaluator 96 determines a mental evaluation value on the basis of an analysis result regarding the mental state of the subject 10. The mental evaluator 96 according to the present embodiment executes analysis for quantifying the mental state by…” “…The mental evaluator 96 may quantify the mental state by a predetermined parameter related to the tendency of the mental state according to the degree of disturbance stimulus.” and a generic algorithm on a generic computational structure capable of the indicated function and, or equivalents thereof, as described on Par. 42 and Par. 14 of the disclosure filed on 08/30/2023, which lacks sufficient detail within the applicant’s specification as to the structure of the algorithm and will be interpreted as a generic algorithm capable of the indicated function,
a generic computational structure capable of the indicated storage function, or equivalents thereof, as described on Par. 14 of the disclosure filed on 08/30/2023,
“The result outputter 51 displays information indicating the motion state acquired by the motion information acquirer 30 and information indicating the mental state acquired by the mental information acquirer 40 on the screen and transmits the information to the mental/physical state evaluation server 50 via the communicator 52” and a generic algorithm on a generic computational structure capable of the indicated function, or equivalents thereof, as described on Par. 29 and Par. 14 of the disclosure filed on 08/30/2023,
a generic computational structure capable of the indicated acquiring function, or equivalents thereof, as described on Par. 14 of the disclosure filed on 08/30/2023,
a generic computational structure capable of the indicated acquiring function, or equivalents thereof, as described on Par. 14 of the disclosure filed on 08/30/2023.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-19 rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claim 1 recites “a reproducibility evaluator configured to determine a reproducibility evaluation value on a basis of an analysis result regarding reproducibility of a predetermined body motion of a subject”, which lacks sufficient detail within the applicant’s specification in regards to the manner in which the reproducibility evaluation value is determined. The applicant’s specification does state “…The reproducibility evaluator 94 extracts a motion feature value of at least one of the position, the trajectory, and the moving speed of the feature point based on the temporal change of the feature point estimated in the moving image. The reproducibility evaluator 94 quantifies the reproducibility of the motion of the subject 10 on the basis of the matching degree of the motion feature value over time.” (Par. 36 of applicant’s spec.) “The reproducibility evaluator 94 can determine the reproducibility evaluation value by the matching degree between motions of a plurality of times for each type of the feature value…” (Par. 40 of applicant’s spec.), and a generic algorithm on a generic computational structure (Par. 14 of applicant’s specification). However, this merely further describes the functionality of the reproducibility evaluator rather than the structure of the algorithm itself. As such, the claim is rejected.
Claim 1 recites “a mental evaluator configured to determine a mental evaluation value on a basis of an analysis result regarding a mental state of the subject”, which lacks sufficient detail within the applicant’s specification in regards to the manner in which the mental evaluation value is determined. The applicant’s specification does state “The mental evaluator 96 determines a mental evaluation value on the basis of an analysis result regarding the mental state of the subject 10. The mental evaluator 96 according to the present embodiment executes analysis for quantifying the mental state by…” “…The mental evaluator 96 may quantify the mental state by a predetermined parameter related to the tendency of the mental state according to the degree of disturbance stimulus.” (Par. 42 of applicant’s specification) and a generic algorithm on a generic computational structure (Par. 14 of applicant’s specification). However, this merely further describes the functionality of the mental evaluator rather than the structure of the algorithm itself. As such, the claim is rejected.
Claims 10-18 recite the limitation “a prediction model generated on a basis of the reproducibility evaluation value and the mental evaluation value”, which lacks sufficient detail within the applicant’s specification in regards to the manner in which the prediction model is generated. The applicant’s specification does state “The model processor 97 performs machine learning by using the reproducibility evaluation value and the mental evaluation value as teacher data to generate a prediction model, and stores the generated prediction model in the evaluation value storage 98 as a personal characteristic of the subject 10. The model processor 97 may generate a prediction model as a regression model in which one of the reproducibility evaluation value and the mental evaluation value is set as an explanatory variable…” (Par. 44 of applicant’s spec.). However, simply reciting a regression model and two example input types does not amount to sufficient detail within the applicant’s specification. For example, the applicant has not provided sufficient detail regarding the exact weights or biases that are used for the model. As such, the claim is rejected.
Claim 19 recites “determining a reproducibility evaluation value on a basis of an analysis result regarding reproducibility of a predetermined body motion of a subject”, which lacks sufficient detail within the applicant’s specification in regards to the manner in which the reproducibility evaluation value is determined. The applicant’s specification does state “…The reproducibility evaluator 94 extracts a motion feature value of at least one of the position, the trajectory, and the moving speed of the feature point based on the temporal change of the feature point estimated in the moving image. The reproducibility evaluator 94 quantifies the reproducibility of the motion of the subject 10 on the basis of the matching degree of the motion feature value over time.” (Par. 36 of applicant’s spec.) “The reproducibility evaluator 94 can determine the reproducibility evaluation value by the matching degree between motions of a plurality of times for each type of the feature value…” (Par. 40 of applicant’s spec.). However, this merely further describes the functionality of the reproducibility evaluator rather than the structure of the algorithm itself. As such, the claim is rejected.
Claim 19 recites “determining a mental evaluation value on a basis of an analysis result regarding a mental state of the subject”, which lacks sufficient detail within the applicant’s specification in regards to the manner in which the mental evaluation value is determined. The applicant’s specification does state “The mental evaluator 96 determines a mental evaluation value on the basis of an analysis result regarding the mental state of the subject 10. The mental evaluator 96 according to the present embodiment executes analysis for quantifying the mental state by…” “…The mental evaluator 96 may quantify the mental state by a predetermined parameter related to the tendency of the mental state according to the degree of disturbance stimulus.” (Par. 42 of applicant’s specification). However, this merely further describes the functionality of the mental evaluator rather than the structure of the algorithm itself. As such, the claim is rejected.
Claims 2-18 are dependent on claim 1, and as such are also rejected.
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 1-19 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.
Claim 1 limitation “a reproducibility evaluator configured to determine a reproducibility evaluation value on a basis of an analysis result regarding reproducibility of a predetermined body motion of a subject” invokes 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function. The applicant’s specification does state “…The reproducibility evaluator 94 extracts a motion feature value of at least one of the position, the trajectory, and the moving speed of the feature point based on the temporal change of the feature point estimated in the moving image. The reproducibility evaluator 94 quantifies the reproducibility of the motion of the subject 10 on the basis of the matching degree of the motion feature value over time.” (Par. 36 of applicant’s spec.) “The reproducibility evaluator 94 can determine the reproducibility evaluation value by the matching degree between motions of a plurality of times for each type of the feature value…” (Par. 40 of applicant’s spec.), and a generic algorithm on a generic computational structure (Par. 14 of applicant’s specification). However, this merely further describes the functionality of the reproducibility evaluator rather than the structure of the algorithm. As such, the applicant has failed to effectively define the metes and bounds of the claim as it is unclear as to the actual structure of the “reproducibility evaluator” itself. For examination purposes, this will be interpreted as any algorithm capable of the indicated function. Therefore, the claim is indefinite and is rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph.
Claim 1 limitation “a mental evaluator configured to determine a mental evaluation value on a basis of an analysis result regarding a mental state of the subject” invokes 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function. The applicant’s specification does state “The mental evaluator 96 determines a mental evaluation value on the basis of an analysis result regarding the mental state of the subject 10. The mental evaluator 96 according to the present embodiment executes analysis for quantifying the mental state by…” “…The mental evaluator 96 may quantify the mental state by a predetermined parameter related to the tendency of the mental state according to the degree of disturbance stimulus.” (Par. 42 of applicant’s specification) and a generic algorithm on a generic computational structure (Par. 14 of applicant’s specification). However, this merely further describes the functionality of the mental evaluator rather than the structure of the algorithm. As such, the applicant has failed to effectively define the metes and bounds of the claim as it is unclear as to the actual structure of the “mental evaluator” itself. For examination purposes, this will be interpreted as any algorithm capable of the indicated function. Therefore, the claim is indefinite and is rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph.
Applicant may:
(a) Amend the claim so that the claim limitation will no longer be interpreted as a limitation under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph;
(b) Amend the written description of the specification such that it expressly recites what structure, material, or acts perform the entire claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(c) Amend the written description of the specification such that it clearly links the structure, material, or acts disclosed therein to the function recited in the claim, without introducing any new matter (35 U.S.C. 132(a)).
If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure, material, or acts and clearly links them to the function so that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed function, applicant should clarify the record by either:
(a) Amending the written description of the specification such that it expressly recites the corresponding structure, material, or acts for performing the claimed function and clearly links or associates the structure, material, or acts to the claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(b) Stating on the record what the corresponding structure, material, or acts, which are implicitly or inherently set forth in the written description of the specification, perform the claimed function. For more information, see 37 CFR 1.75(d) and MPEP §§ 608.01(o) and 2181.
Claim 2 recites the limitation “wherein the reproducibility evaluator performs analysis for quantifying the reproducibility by using a predetermined parameter related to the reproducibility of the predetermined body motion on a basis of the information indicating the motion state, and determines the reproducibility evaluation value on a basis of an analysis result thereof”, which fails to effectively define the metes and bounds of the claim as it is unclear as to the manner in which the reproducibility evaluation value is determined. How is the predetermined parameter used? What are the specific inputs and outputs? In what way are any inputs and outputs used to determine the corresponding value? As such, the claim is indefinite as the applicant has failed to effectively define the metes and bounds of the claim. For examination purposes, this will be interpreted as the determination of any type of reproducibility value based on body motion.
Claim 2 recites the limitation “wherein the mental evaluator performs analysis for quantifying the mental state by using a predetermined parameter related to a tendency of the mental state on a basis of the information indicating the mental state, and determines the mental evaluation value on a basis of an analysis result thereof”, which fails to effectively define the metes and bounds of the claim as it is unclear as to the manner in which the mental evaluation value is determined. How is the predetermined parameter used? What are the specific inputs and outputs? In what way are the inputs and outputs used to determine the corresponding mental evaluation value? As such, the claim is indefinite as the applicant has failed to effectively define the metes and bounds of the claim. For examination purposes, this will be interpreted as performing any type of calculation to quantify mental state using a parameter related to mental state and determining a mental evaluation value based on any type of mental state information.
The term “tendency” in claim 2 is a relative term which renders the claim indefinite. The term “tendency” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. It is unclear as to what “tendency” of the mental state is related to the predetermined parameter. As such, the claim is indefinite as the applicant has failed to effectively define the metes and bounds of the claim. For examination purposes, this will be interpreted as any amount.
The term “degree” in claim 3 is a relative term which renders the claim indefinite. The term “degree” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. It is unclear as to what “degree” of matching of the motion feature quantifies the reproducibility. As such, the claim is indefinite as the applicant has failed to effectively define the metes and bounds of the claim. For examination purposes, this will be interpreted as any amount of matching.
The term “tendency” in claims 4-5 is a relative term which renders the claim indefinite. The term “tendency” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. It is unclear as to what “tendency” of the mental state is related to the predetermined parameter. It is unclear as to what “tendency” of fluctuation of predetermined biological information and answer “tendency” quantify the mental state. As such, the claim is indefinite as the applicant has failed to effectively define the metes and bounds of the claim. For examination purposes, this will be interpreted as any amount.
The term “degree” in claims 6-9 is a relative term which renders the claim indefinite. The term “degree” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. It is unclear as to what “degree” of disturbance is sufficient to affect the mental state of the subject. As such, the claim is indefinite as the applicant has failed to effectively define the metes and bounds of the claim. For examination purposes, this will be interpreted as any amount of the corresponding disturbance.
The term “good” in claims 10-18 is a relative term which renders the claim indefinite. The term “good” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. It is unclear as to what reproducibility evaluation value would be considered “good”. As such, the claim is indefinite as the applicant has failed to effectively define the metes and bounds of the claim. For examination purposes, this will be interpreted as any amount.
Claims 10-18 recite the limitation “a prediction model generated on a basis of the reproducibility evaluation value and the mental evaluation value”, which lacks sufficient detail within the applicant’s specification in regards to the manner in which the prediction model is generated. The applicant’s specification does state “The model processor 97 performs machine learning by using the reproducibility evaluation value and the mental evaluation value as teacher data to generate a prediction model, and stores the generated prediction model in the evaluation value storage 98 as a personal characteristic of the subject 10. The model processor 97 may generate a prediction model as a regression model in which one of the reproducibility evaluation value and the mental evaluation value is set as an explanatory variable…” (Par. 44 of applicant’s spec.). However, simply reciting a regression model and two example input types does not amount to sufficient detail within the applicant’s specification. For example, the applicant has not provided sufficient detail regarding the exact weights or biases that are used for the model. As such, the claim is indefinite as the applicant has failed to effectively define the metes and bounds of the claim. For examination purposes, this will be interpreted as the generation of any type of algorithmic structure.
Claim 19 recites “determining a reproducibility evaluation value on a basis of an analysis result regarding reproducibility of a predetermined body motion of a subject”, which fails to effectively define the metes and bounds of the claim as it is unclear as to the manner in which the reproducibility evaluation value is determined. The applicant’s specification does state “…The reproducibility evaluator 94 extracts a motion feature value of at least one of the position, the trajectory, and the moving speed of the feature point based on the temporal change of the feature point estimated in the moving image. The reproducibility evaluator 94 quantifies the reproducibility of the motion of the subject 10 on the basis of the matching degree of the motion feature value over time.” (Par. 36 of applicant’s spec.) “The reproducibility evaluator 94 can determine the reproducibility evaluation value by the matching degree between motions of a plurality of times for each type of the feature value…” (Par. 40 of applicant’s spec.). However, this merely further describes the functionality of the reproducibility evaluator rather than the structure of the algorithm itself. What are the specific inputs and outputs? In what way are any inputs and outputs used to determine the corresponding value? What is the analysis result and how is it calculated? As such, the claim is indefinite as the applicant has failed to effectively define the metes and bounds of the claim. For examination purposes, this will be interpreted as determining any type of reproducibility value based on body motion.
Claim 19 recites “determining a mental evaluation value on a basis of an analysis result regarding a mental state of the subject”, which fails to effectively define the metes and bounds of the claim as it is unclear as to the manner in which the mental evaluation value is determined. The applicant’s specification does state “The mental evaluator 96 determines a mental evaluation value on the basis of an analysis result regarding the mental state of the subject 10. The mental evaluator 96 according to the present embodiment executes analysis for quantifying the mental state by…” “…The mental evaluator 96 may quantify the mental state by a predetermined parameter related to the tendency of the mental state according to the degree of disturbance stimulus.” (Par. 42 of applicant’s specification). However, this merely further describes the functionality of the mental evaluator rather than the structure of the algorithm itself. What are the specific inputs and outputs? In what way are any inputs and outputs used to determine the corresponding value? What is the analysis result and how is it calculated? As such, the claim is indefinite as the applicant has failed to effectively define the metes and bounds of the claim. For examination purposes, this will be interpreted as determining a mental evaluation value based on any type of mental state information.
Claims 2-18 are dependent on claim 1, and as such are also rejected.
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 1-19 are rejected under 35 U.S.C. 101 because the claimed invention is directed towards a judicial exception without significantly more. These claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception or that are sufficient to amount to significantly more than the judicial exception.
Step 1 of the subject matter eligibility test.
Claims 1 and 19 are directed towards a system and method, respectively, which describes one of the four statutory categories of patentable subject matter.
Step 2A of the subject matter eligibility test.
Prong 1: Claim 1 recites the abstract idea of a mental process as follows: “determine a reproducibility evaluation value on a basis of an analysis result regarding reproducibility of a predetermined body motion of a subject”, “determine a mental evaluation value on a basis of an analysis result regarding a mental state of the subject”, “store the reproducibility evaluation value and the mental evaluation value in association with each other”, and “output information indicating relevance between the mental evaluation value and quality of the reproducibility evaluation value”
Prong 1: Claim 19 recites the abstract idea of a mental process as follows: “determining a reproducibility evaluation value on a basis of an analysis result regarding reproducibility of a predetermined body motion of a subject”, “determining a mental evaluation value on a basis of an analysis result regarding a mental state of the subject”, “storing the reproducibility evaluation value and the mental evaluation value in association with each other”, and “outputting information indicating relevance between the mental evaluation value and quality of the reproducibility evaluation value”
The determining a reproducibility evaluation value on a basis of an analysis result regarding reproducibility of a predetermined body motion of a subject, determining a mental evaluation value on a basis of an analysis result regarding a mental state of the subject, storing the reproducibility evaluation value and the mental evaluation value in association with each other, and outputting information indicating relevance between the mental evaluation value and quality of the reproducibility evaluation value can be practically performed by the human mind, with the aid of a pen and paper, but for performance on a generic processor, in a computer environment, or merely using the computer as a tool to perform the steps.
A person of ordinary skill in the art could reasonably determine a reproducibility evaluation value based on being handed a piece of paper with an analysis result regarding reproducibility of a predetermined body motion with a generic computer or with a pen and paper.
A person of ordinary skill in the art could reasonably determine a mental evaluation value based on being handed a piece of paper with an analysis result regarding a mental state of a subject with a generic computer or with a pen and paper.
A person of ordinary skill in the art could reasonably store a reproducibility evaluation value and mental evaluation value together based on being handed a piece of paper with both values using a generic computer.
A person of ordinary skill in the art could reasonably output information indicating a relevance between a reproducibility evaluation value and mental evaluation value with a generic computer based on being handed a piece of paper with both values.
There is currently nothing to suggest an undue level of complexity in the determining, storing, or outputting steps. Therefore, a person would be able to practically be able to perform the determining steps mentally or with the aid of pen and paper.
Prong Two: Claims 1 and 19 do not recite additional elements that integrate the mental process into a practical application. Therefore, the claims are “directed to” the mental process. The additional elements merely:
Recite the words “apply it” or an equivalent with the judicial exception, or include instructions to implement the abstract idea on a computer, or merely use the computer as a tool to perform the abstract idea (e.g., a generic computational device (Claim 1) and a display (Claim 1)).
For claims 1 and 19. The additional elements merely serve to gather data to be used by the abstract idea. The computational device and screen are merely used as a pre-solution step of necessary data gathering to be used by the abstract idea. There is no practical application because the abstract idea is not applied, relied on, or used in a meaningful way. The processing that is performed remains in the abstract realm, i.e. the gathered data is not used for a treatment or meaningful purpose. Additionally, there is no overall improvement to existing technology present. The mental process merely functions on generic computer elements that do not change the functionality of the device itself. Therefore, the additional elements, alone or in combination, do not integrate the abstract idea into a practical application.
Step 2B of the subject matter eligibility test for Claims 1 and 19.
Per the Berkheimer requirement, the additional elements are well-understood, routine, and conventional. For example,
A computational device and display as disclosed by Fairbrothers (US Pub. No. 20150066524) hereinafter Fairbrothers “each computer may be well known to those skilled in the art and may include a display, a central processor, a system memory, and a system bus that couples various system components including the system memory to the central processor unit. The system bus may be any of several types of bus structures including a memory bus or memory controller, a peripheral bus, and a local bus using any of a variety of bus architectures. The structure of system memory may be well known to those skilled in the art and may include a basic input/output system ("BIOS") stored in a read only memory ("ROM") and one or more program modules such as operating systems, application programs and program data stored in random access memory ("RAM")” (Par. 22) and Eriksson (US Pub. No. 20160021425) hereinafter Eriksson, “the system 10 of FIG. 1 typically takes the form of a computer, e.g., a personal computer, comprising a processor, memory, a display, and one or more data input/output devices (e.g., a keyboard and mouse and/or touch screen), as well as a network interface card, all not shown, but well-known in the art.” (Par. 17)
are all well-understood, routine, and conventional.
Claims 2-18 do not include additional elements, alone or in combination that are sufficient to amount to significantly more than the judicial exception (i.e., an inventive concept) as all of the elements are directed to the further describing of the abstract idea, pre-solution activities, and computer implementation.
The dependent claims merely further define the abstract idea and are, therefore, directed to an abstract idea for similar reasons: they merely further describe the abstract idea:
acquire information indicating a motion state of the subject repeatedly performing the predetermined body motion (Claim 2) (Examiner's Note: A person of ordinary skill in the art could reasonably acquire information indicating a motion state with a generic computer or by being handed a piece of paper with the motion information),
acquire information indicating the mental state of the subject (Claim 2) (Examiner's Note: A person of ordinary skill in the art could reasonably acquire information indicating a mental state with a generic computer or by being handed a piece of paper with the mental state information),
perform analysis for quantifying the reproducibility by using a predetermined parameter related to the reproducibility of the predetermined body motion on a basis of the information indicating the motion state (Claim 2)(Examiner's Note: A person of ordinary skill in the art could reasonably perform analysis for quantifying reproducibility based on being handed a piece of paper with a predetermined parameter related to the reproducibility of a motion with a generic computer),
determine the reproducibility evaluation value on a basis of an analysis (Claim 2),
perform analysis for quantifying the mental state by using a predetermined parameter related to a tendency of the mental state on a basis of the information indicating the mental state (Claim 2)(Examiner's Note: A person of ordinary skill in the art could reasonably perform analysis for quantifying mental state based on being handed a piece of paper with a predetermined parameter related to the mental state with a generic computer),
determine the mental evaluation value on a basis of an analysis result (Claim 2),
extract a predetermined motion feature value as the predetermined parameter related to the reproducibility on the basis of the information indicating the motion state (Claim 3) (Examiner's Note: A person of ordinary skill in the art could reasonably extract a motion feature value as a predetermined parameter based on being handed a piece of paper with motion information with a generic computer),
quantify the reproducibility in accordance with a degree of matching of the motion feature value over time (Claim 3) (Examiner's Note: A person of ordinary skill in the art could reasonably quantify reproducibility based on being handed a piece of paper with motion information with a generic computer),
quantify the mental state by using, as the predetermined parameter related to the tendency of the mental state, at least one of a fluctuation tendency of predetermined biological information of the subject, an answer tendency of the subject to a question regarding mental information, and a result of a cognitive task for measuring concentration or attention of the subject (Claim 4 and 5) (Examiner's Note: A person of ordinary skill in the art could reasonably quantify mental state based on being handed a piece of paper with mental state information with a generic computer),
acquires information indicating a degree of disturbance stimulus that is possible to affect the mental state of the subject (Claims 6, 7, 8, and 9),
quantify the mental state by using the predetermined parameter related to the tendency of the mental state corresponding to the degree of disturbance stimulus (Claims 6, 7, 8, and 9),
stores a prediction model generated on a basis of the reproducibility evaluation value and the mental evaluation value (Claims 10-18) (Examiner's Note: A person of ordinary skill in the art could reasonably store a model with a generic computer),
outputs a result of predicting the mental evaluation value corresponding to the reproducibility evaluation value indicating a state in which the reproducibility is good (Claims 10-18).
Further describe the pre-solution activity (or structure used for such activity):
A generic computational device (Claims 2-18),
A display (Claims 10-18).
Per the Berkheimer requirement, the additional elements are well-understood, routine, and conventional. For example,
A generic computational device and display as disclosed by Fairbrothers and Eriksson above
are all well-understood, routine, and conventional.
Taken alone or in combination, the additional elements do not integrate the judicial exception into a practical application at least because the abstract idea is not applied, relied on, or used in a meaningful way. The additional elements do not add anything significantly more than the abstract idea. The collective functions of the additional elements merely provide computer/electronic implementation and processing, data gathering, and no additional elements beyond those of the abstract idea. There is no indication that the combination of elements improves the functioning of a mobile device, output device, improves technology other than the technical field of the claimed invention, etc. Therefore, the claims are rejected as being directed to non-statutory subject matter.
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 claims are generally directed towards an evaluation system comprising a reproducibility evaluator that determines a reproducibility evaluation value based on a motion of a subject, a mental evaluator that determines a mental evaluation value based on a mental state of a subject, storage that stores the two values, and an output that outputs information regarding the two values.
Claim(s) 1-19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kelner (US Pub. No. 20150342533) hereinafter Kelner, and further in view of Su (US Pub. No. 20230210402) hereinafter Su.
Regarding claim 1, Kelner discloses A mental/physical state evaluation system (Fig. 3,5A) comprising:
a reproducibility evaluator configured to determine a motion evaluation value on a basis of an analysis result regarding body motion of a subject (Par. 34, “The heart rate estimation module 70 may then be configured to calculate a heart rate derivative 84 and a representative motion value 86.” (representative motion value)) (Fig. 5A) (Par. 34, (heart rate estimation module – 70));
a mental evaluator configured to determine a mental evaluation value on a basis of an analysis result regarding a mental state of the subject (Par. 34, “calculate a heart rate derivative 84 with respect to time…” “…the operation depicted in FIG. 3 may be repeated so as to calculate the heart rate derivative 84 and the representative motion value 86 for a plurality of intervals over a period of time.” (heart rate derivative 84)) (Par. 34, (heart rate estimation module – 70)) (Fig. 5A (heart rate derivative calculation));
the motion evaluation value and the mental evaluation value in association with each other (Par. 36, “After classifying the heart rate derivative 84 into one of the plurality of quantized derivative states 89, the statistical filter 88 may then be configured to construct a data pair…” (data pair that is used for further analysis)) (Fig. 3 (data pair - 96)); and
a result outputter configured to output information indicating relevance between the mental evaluation value and quality of the motion evaluation value (Fig. 5A (Step 512-514 (display of calories burned, which indicates relevance between the heart rate and motion)).
Kelner fails to explicitly disclose a reproducibility evaluation value on a basis of an analysis result regarding reproducibility of a predetermined body motion of a subject, the reproducibility evaluation value.
However, Su teaches a reproducibility evaluation value on a basis of an analysis result regarding reproducibility of a predetermined body motion of a subject, the reproducibility evaluation value (Par. 112, “The step may be performed by processing module 220 and/or processing device 110. In some embodiments, monitoring of the movement of the user based on at least one segment of the movement signal may include matching the at least one segment of the movement signal with at least one segment of a preset movement signal to determine the movement type of the user. The at least one segment of the preset movement signal may be standard movement signals corresponding to different movements that are preset in a database. In some embodiments, a movement type of the user during motion may be determined by determining a matching degree of the at least one segment of the movement signal and the at least one segment of the preset movement signal…” (matching degree based on analysis results)).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the device of Kelner with that of Su to include a reproducibility evaluation value on a basis of an analysis result regarding reproducibility of a predetermined body motion of a subject, the reproducibility evaluation value through the combination of references as it would have yielded the predictable result of providing additional analysis metrics regarding motion performance (Su (Par. 112-113)).
Modified Kelner fails to explicitly disclose a reproducibility evaluator and mental evaluator (Examiner's Note: Kelner fails to explicitly disclose the evaluator structures as separate computational devices).
However, Kelner does teach in an example using multiple processors to execute instructions (Par. 58, “Logic machine 616 may include one or more processors configured to execute software instructions. Additionally or alternatively, the logic machine may include one or more hardware or firmware logic machines configured to execute hardware or firmware instructions. Processors of the logic machine may be single-core or multi-core, and the instructions executed thereon may be configured for sequential, parallel, and/or distributed processing. Individual components of a logic machine optionally may be distributed among two or more separate devices, which may be remotely located and/or configured for coordinated processing…”).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the device of Kelner and Su with an example of Kelner to include a reproducibility evaluator and mental evaluator through the combination of embodiments as the use of multiple processors is a known variation (Kelner (Par. 58)), and it would have yielded the same or similar results.
Modified Kelner highly suggests but fails to explicitly disclose an evaluation value storage configured to store the reproducibility evaluation value and the mental evaluation value in association with each other. (Examiner's Note: Kelner fails to explicitly disclose a “store” within a storage step)
However, Kelner does disclose the motion evaluation value and the mental evaluation value in association with each other (Par. 36, “After classifying the heart rate derivative 84 into one of the plurality of quantized derivative states 89, the statistical filter 88 may then be configured to construct a data pair…” (data pair that is constructed and used for further analysis)) (Fig. 3 (data pair - 96)).
Kelner does teach storage of data (Par. 55, “In addition, the processor may be configured to log the first biometric factor, the estimated second biometric, or both to a memory associated with the computing system, and may be further configured to upload the first biometric factor, the estimated second biometric factor, or both, to a cloud-based storage system associated with the computing system.”).
Su further teaches an evaluation storage configured to store (Par. 82, “In some embodiments, the motion monitoring system 100 may further include a database. The database may store the information (e.g., a threshold condition of an initially set, etc.) and/or the instruction (e.g., a feedback instruction)…”) (Par. 86, “In some embodiments, processed data may be stored in a memory or a hard disk.”).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the device of Kelner and Su with that of Su to include an evaluation value storage configured to store the reproducibility evaluation value and the mental evaluation value in association with each other through the combination of references as it would have yielded the predictable result of explicitly storing the data for future analysis.
Regarding claim 19, Kelner discloses a mental/physical state evaluation method (Fig. 3, 5A) comprising:
determining a motion evaluation value on a basis of an analysis result regarding body motion of a subject (Par. 34, “The heart rate estimation module 70 may then be configured to calculate a heart rate derivative 84 and a representative motion value 86.” (representative motion value)) (Fig. 5A) (Par. 34, (heart rate estimation module – 70));
determining a mental evaluation value on a basis of an analysis result regarding a mental state of the subject (Par. 34, “calculate a heart rate derivative 84 with respect to time…” “…the operation depicted in FIG. 3 may be repeated so as to calculate the heart rate derivative 84 and the representative motion value 86 for a plurality of intervals over a period of time.” (heart rate derivative 84)) (Par. 34, (heart rate estimation module – 70)) (Fig. 5A (heart rate derivative calculation));
the motion evaluation value and the mental evaluation value in association with each other (Par. 36, “After classifying the heart rate derivative 84 into one of the plurality of quantized derivative states 89, the statistical filter 88 may then be configured to construct a data pair…” (data pair that is used for further analysis)) (Fig. 3 (data pair - 96)); and
outputting information indicating relevance between the mental evaluation value and quality of the motion evaluation value (Fig. 5A (Step 512-514 (display calories burned, which indicates relevance between the heart rate and motion)).
Kelner fails to explicitly disclose a reproducibility evaluation value on a basis of an analysis result regarding reproducibility of a predetermined body motion of a subject, a reproducibility evaluation value.
However, Su teaches a reproducibility evaluation value on a basis of an analysis result regarding reproducibility of a predetermined body motion of a subject, a reproducibility evaluation value (Par. 112, “The step may be performed by processing module 220 and/or processing device 110. In some embodiments, monitoring of the movement of the user based on at least one segment of the movement signal may include matching the at least one segment of the movement signal with at least one segment of a preset movement signal to determine the movement type of the user. The at least one segment of the preset movement signal may be standard movement signals corresponding to different movements that are preset in a database. In some embodiments, a movement type of the user during motion may be determined by determining a matching degree of the at least one segment of the movement signal and the at least one segment of the preset movement signal…” (matching degree based on analysis results)).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the method of Kelner with that of Su to include a reproducibility evaluation value on a basis of an analysis result regarding reproducibility of a predetermined body motion of a subject, a reproducibility evaluation value through the combination of references as it would have yielded the predictable result of providing additional analysis metrics regarding motion performance (Su (Par. 112-113)).
Modified Kelner fails to explicitly disclose storing the reproducibility evaluation value and the mental evaluation value in association with each other.
However, Kelner does disclose the motion evaluation value and the mental evaluation value in association with each other (Par. 36, “After classifying the heart rate derivative 84 into one of the plurality of quantized derivative states 89, the statistical filter 88 may then be configured to construct a data pair…” (data pair that is used for further analysis)) (Fig. 3 (data pair - 96)).
Kelner does teach storage of data (Par. 55, “In addition, the processor may be configured to log the first biometric factor, the estimated second biometric, or both to a memory associated with the computing system, and may be further configured to upload the first biometric factor, the estimated second biometric factor, or both, to a cloud-based storage system associated with the computing system.”).
Su further teaches storing data (Par. 82, “In some embodiments, the motion monitoring system 100 may further include a database. The database may store the information (e.g., a threshold condition of an initially set, etc.) and/or the instruction (e.g., a feedback instruction)…”) (Par. 86, “In some embodiments, processed data may be stored in a memory or a hard disk.”).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the device of Kelner and Su with that of Su to include storing the reproducibility evaluation value and the mental evaluation value in association with each other through the combination of references as it would have yielded the predictable result of explicitly storing the data for future analysis.
Regarding claim 2, modified Kelner further discloses a motion information acquirer configured to acquire information indicating a motion state of the subject repeatedly performing the predetermined body motion (Kelner (Par. 26, “The heart rate estimation module 70 may be configured to receive the heart rate of the user 66 and motion of the user 68 and, based on this data, compute a correspondence 74 between the heart rate of the user 66 and the motion of the user 68. In addition, the wearable electronic device may be further configured to send the heart rate of the user 66 to memory 78. The wearable electronic device 10 may then be further configured to send the heart rate of the user 66 to a display 80 so as to be viewable by a user.”)(Par. 34, “Turning next to FIG. 3, an illustration of a statistical filter 88 applied by the heart rate estimation module 70 of FIGS. 2A and 2B to compute a correspondence 74 between the heart rate of the user 66 and motion of the user 68 is depicted. The heart rate estimation module 70 may be further configured to calculate a heart rate derivative 84 with respect to time and a representative motion value 86 for each of a plurality of intervals during the initial calibration phase…” “…may be repeated so as to calculate the heart rate derivative 84 and the representative motion value 86 for a plurality of intervals over a period of time.”)); and
a mental information acquirer configured to acquire information indicating the mental state of the subject (Kelner (Par. 26, “The heart rate estimation module 70 may be configured to receive the heart rate of the user 66 and motion of the user 68 and, based on this data, compute a correspondence 74 between the heart rate of the user 66 and the motion of the user 68. In addition, the wearable electronic device may be further configured to send…”)(Par. 34, “Turning next to FIG. 3, an illustration of a statistical filter 88 applied by the heart rate estimation module 70 of FIGS. 2A and 2B to compute a correspondence 74 between the heart rate of the user 66 and motion of the user 68 is depicted. The heart rate estimation module 70 may be further configured to calculate a heart rate derivative 84 with respect to time and a representative motion value 86 for each of a plurality of intervals during the initial calibration phase…” “…may be repeated so as to calculate the heart rate derivative 84 and the representative motion value 86 for a plurality of intervals over a period of time.”)), and
wherein the mental evaluator performs analysis for quantifying the mental state by using a predetermined parameter related to a tendency of the mental state on a basis of the information indicating the mental state (Kelner (Par. 34, “calculate a heart rate derivative 84 with respect to time…” “…the operation depicted in FIG. 3 may be repeated so as to calculate the heart rate derivative 84 and the representative motion value 86 for a plurality of intervals over a period of time.” (heart rate derivative 84)) (Par. 34, (heart rate estimation module – 70)) (Fig. 5A (heart rate derivative calculation))), and determines the mental evaluation value on a basis of an analysis result thereof (Kelner(Par. 34, “calculate a heart rate derivative 84 with respect to time…” “…the operation depicted in FIG. 3 may be repeated so as to calculate the heart rate derivative 84 and the representative motion value 86 for a plurality of intervals over a period of time.” (heart rate derivative 84)) (Par. 34, (heart rate estimation module – 70)) (Fig. 5A (heart rate derivative calculation))).
Modified Kelner fails to explicitly disclose wherein the reproducibility evaluator performs analysis for quantifying the reproducibility by using a predetermined parameter related to the reproducibility of the predetermined body motion on a basis of the information indicating the motion state, and determines the reproducibility evaluation value on a basis of an analysis result thereof.
However, Su further teaches wherein the reproducibility evaluator performs analysis for quantifying the reproducibility by using a predetermined parameter related to the reproducibility of the predetermined body motion on a basis of the information indicating the motion state (Su (Par. 112, “The step may be performed by processing module 220 and/or processing device 110. In some embodiments, monitoring of the movement of the user based on at least one segment of the movement signal may include matching the at least one segment of the movement signal with at least one segment of a preset movement signal to determine the movement type of the user. The at least one segment of the preset movement signal may be standard movement signals corresponding to different movements that are preset in a database. In some embodiments, a movement type of the user during motion may be determined by determining a matching degree of the at least one segment of the movement signal and the at least one segment of the preset movement signal…”), and determines the reproducibility evaluation value on a basis of an analysis result thereof (Su (Par. 112, “The step may be performed by processing module 220 and/or processing device 110. In some embodiments, monitoring of the movement of the user based on at least one segment of the movement signal may include matching the at least one segment of the movement signal with at least one segment of a preset movement signal to determine the movement type of the user. The at least one segment of the preset movement signal may be standard movement signals corresponding to different movements that are preset in a database. In some embodiments, a movement type of the user during motion may be determined by determining a matching degree of the at least one segment of the movement signal and the at least one segment of the preset movement signal…” (matching degree based on analysis results))).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the device of Kelner and Su with that of Su to include wherein the reproducibility evaluator performs analysis for quantifying the reproducibility by using a predetermined parameter related to the reproducibility of the predetermined body motion on a basis of the information indicating the motion state for the reasoning as indicated in claim 1 above.
Modified Kelner fails to explicitly disclose a reproducibility evaluator and mental evaluator (Examiner's Note: Kelner fails to explicitly disclose the evaluator structures as separate computational devices).
However, Kelner does teach in an example using multiple processors to execute instructions (Par. 58, “Logic machine 616 may include one or more processors configured to execute software instructions. Additionally or alternatively, the logic machine may include one or more hardware or firmware logic machines configured to execute hardware or firmware instructions. Processors of the logic machine may be single-core or multi-core, and the instructions executed thereon may be configured for sequential, parallel, and/or distributed processing. Individual components of a logic machine optionally may be distributed among two or more separate devices, which may be remotely located and/or configured for coordinated processing…”).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the device of Kelner and Su with an example of Kelner to include a reproducibility evaluator and mental evaluator through the combination of embodiments as the use of multiple processors is a known variation (Kelner (Par. 58)), and it would have yielded the same or similar results.
Regarding claim 3, modified Kelner fails toe explicitly disclose he limitations of the claim. However, Su further teaches wherein the reproducibility evaluator extracts a predetermined motion feature value as the predetermined parameter related to the reproducibility on the basis of the information indicating the motion state (Su (Par. 110 (extraction of signal segments))(Par. 112, “The step may be performed by processing module 220 and/or processing device 110. In some embodiments, monitoring of the movement of the user based on at least one segment of the movement signal may include matching the at least one segment of the movement signal with at least one segment of a preset movement signal to determine the movement type of the user…” (matching degree based on movement signals))), and quantifies the reproducibility in accordance with a degree of matching of the motion feature value over time (Su (Par. 112, “The step may be performed by processing module 220 and/or processing device 110. In some embodiments, monitoring of the movement of the user based on at least one segment of the movement signal may include matching the at least one segment of the movement signal with at least one segment of a preset movement signal to determine the movement type of the user. The at least one segment of the preset movement signal may be standard movement signals corresponding to different movements that are preset in a database. In some embodiments, a movement type of the user during motion may be determined by determining a matching degree of the at least one segment of the movement signal and the at least one segment of the preset movement signal…” (matching degree based on movement signals))).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the device of Kelner and Su with that of Su to include wherein the reproducibility evaluator extracts a predetermined motion feature value as the predetermined parameter related to the reproducibility on the basis of the information indicating the motion state, and quantifies the reproducibility in accordance with a degree of matching of the motion feature value over time for the reasoning as indicated in claim 1 above.
Regarding claims 4-5, Modified Kelner further discloses wherein the mental evaluator quantifies the mental state by using, as the predetermined parameter related to the tendency of the mental state, at least one of a fluctuation tendency of predetermined biological information of the subject (Kelner (Par. 34, “calculate a heart rate derivative 84 with respect to time…” “…the operation depicted in FIG. 3 may be repeated so as to calculate the heart rate derivative 84 and the representative motion value 86 for a plurality of intervals over a period of time.” (heart rate derivative 84)) (Par. 34, (heart rate estimation module – 70)) (Fig. 5A (heart rate derivative calculation))), an answer tendency of the subject to a question regarding mental information, and a result of am cognitive task for measuring concentration or attention of the subject.
Regarding claims 6, 7, 8, and 9, modified Kelner further discloses wherein the mental information acquirer further acquires information indicating a degree of disturbance stimulus that is possible to affect the mental state of the subject (Kelner (Par. 34, “calculate a heart rate derivative 84 with respect to time…” “…the operation depicted in FIG. 3 may be repeated so as to calculate the heart rate derivative 84 and the representative motion value 86 for a plurality of intervals over a period of time.” (heart rate derivative 84)) (Par. 34, (heart rate estimation module – 70)) (Fig. 5A (heart rate derivative calculation))), and
wherein the mental evaluator quantifies the mental state by using the predetermined parameter related to the tendency of the mental state corresponding to the degree of disturbance stimulus (Kelner (Par. 34, “calculate a heart rate derivative 84 with respect to time…” “…the operation depicted in FIG. 3 may be repeated so as to calculate the heart rate derivative 84 and the representative motion value 86 for a plurality of intervals over a period of time.” (heart rate derivative 84)) (Par. 34, (heart rate estimation module – 70)) (Fig. 5A (heart rate derivative calculation)) (Examiner's Note: Disturbance stimulus as indicated in Par. 25 of the applicant’s spec. that includes time measurements)).
Regarding claims 10, 11, 12, 13, 14, 15, 16, 17, and 18, Modified Kelner fails to explicitly disclose wherein the evaluation value storage further stores a prediction model generated on a basis of the reproducibility evaluation value and the mental evaluation value.
However, Kelner does disclose a prediction model generated on a basis of the motion evaluation value and the mental evaluation value (Kelner (Par. 36, “After classifying the heart rate derivative 84 into one of the plurality of quantized derivative states 89, the statistical filter 88 may then be configured to construct a data pair…” (data pair that is used for further analysis for the correspondence))(Fig. 5A, step 506 (correspondence computed))).
Su further teaches storage further stores a prediction model (Su (Par. 220, “In some embodiments, the step may be performed by the processing device 110. In some embodiments, the processing device 110 and/or the processing module 220 may extract the movement recognition model. In some embodiments, the movement recognition model may be stored to the processing device 110, the processing module 220, or a mobile terminal.”) (Par. 213, “The step may be performed by the processing device 110. In some embodiments, the movement recognition model may include one or more machine learning models…”) (Par. 224, “As yet another example, the machine learning model that recognizes the fatigue index of the user performing the movement may use the movement signal (e.g., the frequency of the electro-cardio signal) of the user as input data and output the fatigue index of the user…”) (Par. 202 (machine learning))).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the device of Kelner and Su with that of Su to include wherein the evaluation value storage further stores a prediction model generated on a basis of the reproducibility evaluation value and the mental evaluation value through the combination of references as it would have yielded the predictable result of automating the analysis.
Modified Kelner fails to explicitly disclose wherein the result outputter further outputs a result of predicting, on the basis of the prediction model, the mental evaluation value corresponding to the reproducibility evaluation value indicating a state in which the reproducibility is good.
However, Kelner does teach in an alternate embodiment wherein the result outputter further outputs a result of predicting, on the basis of the prediction model, the mental evaluation value corresponding to the motion evaluation value indicating a state in which the reproducibility is good (Kelner (Par. 33, “estimated heart rate 72 based on the remote data. The processor 76 may be further configured to operate the heart rate estimation module 70 in a remote mode in which motion sensor 64 is a remote sensor in a remote device connected by the cloud 81. The processor 76 may be configured to receive motion of the user 68 as remote data from the remote sensor and compute the estimated heart rate 72…”(estimated heart rate 72)) (Par. 39, Fig. 4 (estimated heart rate) (Par. 40, “The statistical filter 88 may be next configured to calculate an estimated heart rate derivative for the representative motion value 86 based on the characteristic values 106…”)) (Par. 28, “he heart rate estimation module 70 may be further configured to send the estimated heart rate 72 to memory 78 and the wearable electronic device 10 may then be configured to send the estimated heart rate 72 to the display 80 so as to be viewable by the user.”)).
Therefore, it would have been obvious to a person of ordinary skill in the art to modify the device of Kelner and Su with an embodiment of Kelner to include wherein the result outputter further outputs a result of predicting, on the basis of the prediction model, the mental evaluation value corresponding to the reproducibility evaluation value indicating a state in which the reproducibility is good through the combination of embodiments as it would have yielded the predictable result of allowing for a determination to be made in the absence of current heart rate data (Kelner (Par. 24)).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ARI SINGH KANE PADDA whose telephone number is (571)272-7228. The examiner can normally be reached Monday - Friday 8:00 am - 5:00 pm.
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/ARI S PADDA/Examiner, Art Unit 3791
/JASON M SIMS/Supervisory Patent Examiner, Art Unit 3791