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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 19 December 2025 has been entered.
The Examiner acknowledges the amendments to claims 1-2 and 12, and the cancellation of claims 6 and 10. Claims 1-5, 7-9, and 11-12 are pending.
Drawings
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(4) because: reference characters “1”,“2”,“3”,“4”,“5”, “10”, “21”, “22”, “23”, “24”, “25”, “31”, “32” are configured to each refer to an element of the block diagram in Fig. 1 and a feature point in Fig. 2; reference characters “1”,“2”,“3”,“4”,“5” are configured to each refer to an element of the block diagram in Fig. 1 and an extracted motion of a feature point in Fig. 5B.
Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). 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.
Specification
The abstract of the disclosure is objected to because of undue length. The Examiner notes that the Abstract is greater than 150 words. A corrected abstract of the disclosure is required and must be presented on a separate sheet, apart from any other text. See MPEP § 608.01(b).
Claim Objections
Claim(s) 1-2 and 12 is/are objected to because of the following informalities:
The Examiner notes that the amendments to claims 1-2 and 12 and maintained cancellation of claims 6 and 10 are not considered to be in proper form, as the amendments submitted are not made in accordance with 37 CFR § 1.530, which states “Any changes relative to the patent being reexamined which are made to the specification, including the claims, must include the following markings: (1) The matter to be omitted by the reexamination proceeding must be enclosed in brackets; and (2) The matter to be added by the reexamination proceeding must be underlined”. The claims filed 19 December 2025 appear to be amendments to the claims submitted 18 November 2025, which were noted in the Advisory Action dated 26 November 2025 as NOT ENTERED [see item 3.a. of Advisory Action cited]. As such, the Applicant’s amendments to the claims should be amendments to the claims filed 9 June 2025.
Appropriate correction is required.
Claim Interpretation
Examiner’s Note Regarding § 112(f): The interpretations under § 112(f) applied in the Non-Final Rejection dated 17 March 2025 [p. 2-8] are maintained.
Examiner’s Note Regarding Conditional Language: The interpretations regarding conditional language applied in the Non-Final Rejection dated 17 March 2025 [p. 8] are maintained.
Claim Rejections - 35 USC § 112
Examiner’s Note Regarding Machine Learning: The Examiner’s note regarding sufficient written description support for the machine learning mechanism as presently claimed applied in the Final Rejection dated 25 July 2025 [p. 2-3] is maintained.
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.
Claim(s) 1-5, 7-9, and 11-12 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception without significantly more. Each claim has been analyzed to determine whether it is directed to any judicial exceptions.
Representative claim(s) 1 [representing all independent claims] recite(s):
A chewing assistance system comprising an information processing device that includes:
chewing information storage means that stores information about chewing quality;
moving image obtaining means that obtains a moving image of a region including at least a mouth or a peripheral portion of the mouth in a face during chewing;
analysis means that analyzes a chewing action that includes an action based on the moving image of the region during the chewing obtained by the moving image obtaining means, to determine a chewing rhythm and occlusal balance between anterior and posterior sides and between left and right sides;
quality determination means that determines chewing quality of the chewing action based on information of the chewing action analyzed by the analysis means; and
extraction means that extracts assistance information corresponding to the chewing quality determined by the quality determination means, from the chewing information storage means to determine an improving state of the chewing quality.
(Emphasis added: abstract idea, additional element)
Step 2A Prong 1
Representative claim(s) 1 recites the following abstract ideas, which may be performed in the mind or by hand with the assistance of pen and paper:
“obtains a moving image of a region including at least a mouth or a peripheral portion of the mouth in a face during chewing” – may be performed by merely observing a moving image or collecting previously collected images [The moving image obtaining unit21 obtains two-dimensional or three-dimensional moving image information, of a region including at least a mouth or a peripheral portion of the mouth in a face of a user, which is obtained and transmitted by the imaging means4 (Applicant’s Specification ¶0028)], wherein the Examiner notes that the claim as presently written fails to positively recite any step of data gathering or use of any particular sensor
“analyzes a chewing action that includes an action based on the moving image of the region during the chewing obtained by the moving image obtaining means, to determine a chewing rhythm and occlusal balance between anterior and posterior sides and between left and right sides” – may be performed by merely observing previously collected images and drawing conclusions therefrom [the action analysis processing unit22c can more directly analyze mouth opening behavior during chewing, for example, analyze motion of the mouth which represents a size or a shape of the opened mouth, or the like (Applicant’s Specification ¶0038)]
“determines chewing quality of the chewing action based on information of the chewing action analyzed by the analysis means” – may be performed by merely observing previously collected images and drawing conclusions therefrom based on known or previously derived metrics [quality based on determination as to whether the number of chewing times is large or small, whether or not chewing rhythm is proper, whether or not mouth opening behavior is proper, whether or not chewing balance between the left side and the right side is proper, whether or not eating behavior (motion of a mouth) is proper, and whether or not use of masseter is proper (Applicant’s Specification ¶0044)]
“extracts assistance information corresponding to the chewing quality determined by the quality determination means, from the chewing information storage means to determine an improving state of the chewing quality” – may be performed by merely observing previously collected or known information [extracts information such as age-based oral cavity function information, and information about a device for growing/improving purpose and a medical specialist based on a residence of the user (Applicant’s Specification ¶0046)]
If a claim, under BRI, covers performance of the limitations in the mind but for the mere recitation of extra-solutionary activity (and otherwise generic computer elements) then the claim falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea under Step 2A Prong 1 of the Mayo framework as set forth in the 2019 PEG.
No limitations are provided that would force the complexity of any of the identified evaluation steps to be non-performable by pen-and-paper practice.
Alternatively or additionally, these steps describe the concept of using implicit mathematical formula(s) [i.e., Furthermore, the motions of the respective feature points are defined as patterns based on position coordinates, of mouth corners, the jaw, the vertexes of the upper lip and the lower lip, and the like, calculated by the feature quantity calculation] to derive a conclusion based on input of data, which corresponds to concepts identified as abstract ideas by the courts [Diamond v. Diehr. 450 U.S. 175, 209 U.S.P.Q. 1 (1981), Parker v. Flook. 437 U.S. 584, 19 U.S.P.Q. 193 (1978), and In re Grams. 888 F.2d 835, 12 U.S.P.Q.2d 1824 (Fed. Cir. 1989)]. The concept of the recited limitations identified as mathematical concepts above is not meaningfully different than those mathematical concepts found by the courts to be abstract ideas.
The dependent claims merely include limitations that either further define the abstract idea [e.g. limitations relating to the data gathered or particular steps which are entirely embodied in the mental process] and amount to no more than generally linking the use of the abstract idea to a particular technological environment or field of use because they are merely incidental or token additions to the claims that do not alter or affect how the process steps are performed.
Thus, these concepts are similar to court decisions of abstract ideas of itself: collecting, displaying, and manipulating data [Int. Ventures v. Cap One Financial], collecting information, analyzing it, and displaying certain results of the collection and analysis [Electric Power Group], collection, storage, and recognition of data [Smart Systems Innovations].
Step 2A Prong 2
The judicial exception is not integrated into a practical application.
Representative claim 1 only recites additional elements of extra-solutionary activity – in particular, extra-solution activity [generic computer function] – without further sufficient detail that would tie the abstract portions of the claim into a specific practical application (2019 PEG p. 55 – the instant claim, for example does not tie into a particular machine, a sufficiently particular form of data or signal collection – via the claimed extra-solution activity, or a sufficiently particular form of display or computing architecture/structure).
Dependent claim(s) 2-5 and 7-8 merely add detail to the abstract portions of the claim but do not otherwise encompass any additional elements which tie the claim(s) into a particular application/integration [the dependent claim(s) recite generic ‘units’ or ‘steps’ which encompass mere computer instructions to carry out an otherwise wholly abstract idea].
Dependent claim(s) 11 encounter substantially the same issues as the independent claim(s) from which they depend in that they encompass further generic extra-solutionary activity [generic data gathering] and/or generic computer elements [storage, memory per se].
Accordingly, the claim(s) are not integrated into a practical application under Step 2A Prong 2.
Step 2B
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Independent claims 1 and 12 as individual wholes fail to amount to significantly more than the judicial exception at Step 2B. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of extra-solutionary activity [i.e., generic computer functions] and generic computer elements cannot amount to significantly more than an abstract idea [MPEP § 2106.05(f)] and is further considered to merely implement an abstract idea on a generic computer [MPEP § 2106.05(d)(II) establishes computer-based elements which are considered to be well understood, routine, and conventional when recited at a high level of generality].
For the independent claim portions and dependent claims which provide additional elements of extra-solutionary data gathering, MPEP § 2106.05(g) establishes that mere data gathering for determining a result does not amount to significantly more. The extra-solutionary activity of processor steps [acquiring, storing signals, etc.] as presently recited, cannot provide an inventive concept which amounts to significantly more than the recited abstract idea.
For the independent claims as well as the dependent claims merely reciting generic computer elements and functions [information processing device, information storage means, each recited at a high level of generality and generic functions therein], MPEP § 2106.05(d)(II) establishes computer-based elements which are considered to be well understood, routine, and conventional when recited at a high level of generality.
Accordingly, the information processing device and information storage means and generic functions therein, as presently limited, cannot provide an inventive concept since they fall under a generic structure and/or function that does not add a meaningful additional feature to the judicial exception(s) of the claim(s).
Claim 9 recites “a machine learning mechanism”. Such a machine learning mechanism is considered well-understood, routine, and conventional, as known by at least:
Hu (“Intelligent Sensor Networks”, NPL previously presented) [In supervised learning, the learner is provided with labeled input data. This data contains a sequence of input/output pairs of the form xi, yi, where xi is a possible input and yi is the correctly labeled output associated with it. The aim of the learner in supervised learning is to learn the mapping from inputs to outputs. The learning program is expected to learn a function f that accounts for the input/output pairs seen so far, f (xi) = yi, for all i. This function f is called a classifier if the output is discrete and a regression function if the output is continuous. The job of the classifier/regression function is to correctly predict the outputs of inputs it has not seen before (Hu, Page 5)]
Huang (“Kernel Based Algorithms for Mining Huge Data Sets”, NPL previously presented) [In supervised learning, the learner is provided with labeled input data. This data contains a sequence of input/output pairs of the form xi, yi, where xi is a possible input and yi is the correctly labeled output associated with it. The aim of the learner in supervised learning is to learn the mapping from inputs to outputs. The learning program is expected to learn a function f that accounts for the input/output pairs seen so far, f (xi) = yi, for all i. This function f is called a classifier if the output is discrete and a regression function if the output is continuous. The job of the classifier/regression function is to correctly predict the outputs of inputs it has not seen before (Huang, Page 1)]
Mitchell (“The Discipline of Machine Learning”, NPL previously presented) [For example, we now have a variety of algorithms for supervised learning of classification and regression functions; that is, for learning some initially unknown function f : X [Calibri font/0xE0] Y given a set of labeled training examples {xi; yi} of inputs xi and outputs yi = f(xi) (Mitchell, Pages 3-4)]
Examiner’s Note Regarding Particular Treatment or Prophylaxis: Claim(s) 1, 8, and 12 recite subject matter regarding “determines chewing quality of the chewing actions… and… extracts assistance information corresponding to the chewing quality determined by the quality determination means, from the chewing information storage means to determine an improving state of the chewing quality” and “determines whether the chewing action has improved”, which the Examiner notes is not considered to be a particular treatment or prophylaxis, as none of the identified claims positively recite or include language that is considered to be a particular treatment or prophylaxis as an additional element to integrate the judicial exception into a practical application or allow the identified claims to amount to significantly more than the judicial exception [MPEP § 2106.04(d)(2)].
Accordingly, the claim(s) as whole(s) fail amount to significantly more than the judicial exception under Step 2B.
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) 1-5, 7-9, and 11-12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Nakajima (WO-2019225243-A1, previously presented) in view of Bourdiol (“Only severe malocclusion correlates with mastication deficiency”, NPL attached) and Trench (“Dentofacial deformities: orofacial myofunctional characteristic”, NPL attached).
Regarding claim 1, Nakajima teaches
A chewing assistance system comprising an information processing device [the swallowing function evaluation apparatus 100 is, for example, a personal computer, but may be a server apparatus (Nakajima Translated p. 4)] that includes:
chewing information storage means that stores information about chewing quality [The storage unit 160 includes reference data 161 that indicates the relationship between the feature amount and the person's swallowing function, proposal data 162 that indicates the relationship between the evaluation result of the swallowing function and the proposed content… The storage unit 160 is realized by, for example, a ROM (Read Only Memory), a RAM (Random Access Memory), a semiconductor memory, an HDD (Hard Disk Drive), or the like (Nakajima p. 5)];
moving image obtaining means that obtains a moving image of a region including at least a mouth or a peripheral portion of the mouth in a face during chewing [The acquisition unit 110 acquires an image obtained by imaging the face or neck of the person to be evaluated U in a non-contact manner (Nakajima p. 4); The feature amount indicates a feature such as a face movement of the evaluated person U calculated from an image used by the evaluation unit 130 to evaluate the eating and swallowing function of the evaluated person U (Nakajima p. 5), wherein the image being evaluated based on the facial movement of the evaluated person is considered to define obtaining a “moving image”, as defined by the Applicant’s Specification ¶0010];
analysis means that analyzes a chewing action based on the moving image of the region during chewing obtained by the moving image obtaining means [The calculation unit 120 calculates a feature amount from the image acquired by the acquisition unit 110. The feature amount indicates a feature such as a face movement of the evaluated person U calculated from an image used by the evaluation unit 130 to evaluate the eating and swallowing function of the evaluated person U or a position of a laryngeal protuberance on the neck. It is a numerical value (Nakajima p. 5)];
quality determination means that determines chewing quality of the chewing action based on information of the chewing action analyzed by the analysis means [The evaluation unit 130 compares the feature amount calculated by the calculation unit 120 with the reference data 161 stored in the storage unit 160, and evaluates the eating / swallowing function of the person to be evaluated U (Nakajima p. 5)]; and
extraction means that extracts assistance information corresponding to the chewing quality determined by the quality determination means [The proposing unit 150 makes a proposal regarding swallowing to the person to be evaluated U by collating the evaluation result output by the output unit 140 with predetermined proposal data 162. In addition, the suggestion unit 150 may collate the personal information acquired by the acquisition unit 110 with the proposal data 162 and make a proposal regarding swallowing to the evaluated person U (Nakajima p. 5), wherein determining a proposal or suggestion based on the evaluated eating/swallowing function is considered to read on the BRI of “extracting assistance information” based on chewing quality], from the chewing information storage means [The proposal data 162 is referred to by the suggestion unit 150 when a proposal related to swallowing for the person to be evaluated U is made (Nakajima p. 5)] to determine an improving state of the chewing quality [For example, the reference data 161 is predetermined data, but may be updated based on an evaluation result obtained when an expert actually diagnoses the swallowing function of the person to be evaluated U. Thereby, the evaluation precision of a swallowing function can be improved (Nakajima p. 14), wherein evaluating a person over time or with reference to previous data of the same person in order to provide updated evaluations is considered to be equivalent to determining “an improving state”].
However, while Nakajima does acknowledge that the occlusal state of the subject’s teeth affect masticatory function [Tongue recognition function, or tongue movement function to push food to teeth or mix finely mixed food with saliva, occlusal state of teeth to chew and crush food, tooth and The cheek movement function that prevents food from entering between the cheeks, the movement function of the masticatory muscles (such as the masseter and temporal muscles), which is the generic name of the muscles used for mastication, and the fine food For example, the saliva secretion function. The masticatory function is affected by the occlusal state of the teeth, the function of the masticatory muscles, the function of the tongue, and the like (Nakajima p. 2)], Nakajima fails to explicitly disclose wherein the analysis of the chewing action is to determine a chewing rhythm and occlusal balance between anterior and posterior sides and between left and right sides.
Bourdiol discloses methods for assessing chewing kinematics and mastication efficiency using moving images of a subject [Video recording was used to evaluate the kinematic parameters (Nicolas, Veyrune, Lassauzay, Peyron, & Hennequin, 2007). A digital camera (SONY DCR-PC330E, Japan) positioned in front of the subject recorded a video of facial movements. The subjects were first asked to chew until deglutition three replicates of the model foods of each hardness level presented in a random order (Bourdiol p. 16)], wherein Bourdiol discloses that malocclusions of overbite and underbite result in quantifiable differences in a number of chewing times, chewing rhythm [Values (mean ± sd) of cycle number (or chewing stroke number) at deglutition and values of duration in second and frequency (cycle number/sequence duration in hertz) at deglutition and after 15 cycles when chewing raw carrots in the three groups: NoDFD (no treatment need), ModDFD (indication for orthodontic treatment alone), SevDFD (indication for surgical treatment) (Bourdiol p. 17, Table 2)], and visibly observable lower chewing quality based on measured chewing kinematics [The SevDFD group comprised 15 skeletal class III (among them 5 open-bites, 4 deep-bites, 6 normal-bites), with hypomaxilla (n = 3), mandible prognathism (n = 6) and maxilla-mandible prognathism (n = 6) (Bourdiol p. 15), wherein the Examiner notes that hypomaxilla, mandible prognathism, and maxilla-mandible prognathism are considered to define different types of malocclusions that affect occlusal balance in at least anterior and posterior directions; This study confirms that SevDFD subjects are unable to compensate for their deficient occlusion during mastication. The SevDFD subjects had clearly impaired mastication as shown by two main criteria: (i) the individual d50 of SevDFD subjects was always above MNI cut-off and (ii) the cycle frequency when chewing either carrots or gelatines was significantly lower in SevDFD than in NoDFD. The SevDFD subjects appear similar to patients or subjects displaying severe mastication impairment… Impaired mastication in our SevDFD subjects was not due to having fewer teeth, tooth number being similar in all the groups, but rather to interarch discrepancy, as indicated by the significantly reduced functional area (Bourdiol p. 18)].
Trench discloses methods for assessing chewing function using moving images of a subject [The characteristics of masticatory function were assessed by examining the ability to chew French bread by each individual, who was instructed to proceed as usual with daily life. The performance of this function was filmed with a SONY DSC - W 620 digital camera; the obtained results were evaluated by counting the number of chewing cycles, and the vertical or lateral mandibular movements were analyzed (Trench p. 1203)], wherein Trench discloses that malocclusions of crossbite result in visibly observable lower chewing quality based on measured chewing motions [In patients with skeletal bilateral posterior cross bite DFD, the unilateral left chewing pattern was observed in 80% of subjects, which was followed by unilateral right (20%)… there was inefficient chewing in 80% of subjects evaluated (Trench p. 1209, Table 8), wherein crossbite is considered to define a type of malocclusion that affects occlusal balance in at least left and right directions].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system of Nakajima to employ wherein the analysis of the chewing action is to determine a chewing rhythm and occlusal balance between anterior and posterior sides and between left and right sides, so as to further assess chewing quality, as chewing rhythm and occlusal balance between anterior and posterior sides and between left and right sides are considered to be indicative of a measure of chewing quality [Bourdiol p. 17-18, Table 2; Trench p. 1209, Table 8].
Regarding claim 2, Nakajima in view of Bourdiol and Trench teaches
The chewing assistance system according to claim 1, wherein the analysis means includes
feature detection means that detects at least one feature point in the face from the image of the region [the calculation unit 120 calculates the continuous image (moving image). The movement of the mouth at is calculated as a feature amount. Specifically, the calculation unit 120 calculates a difference between the movement amount on the left side of the mouth and the movement amount on the right side(referred to as a mouth left / right difference) as a feature amount (Nakajima p. 6)], and
action analysis means that analyzes an action based on change of the at least one feature point detected by the feature detection means [Nakajima p. 6].
Regarding claim 3, Nakajima in view of Bourdiol and Trench teaches
The chewing assistance system according to claim 2, wherein
the action analysis means determines, in a case where a quantity of change of the feature point indicates a value that exceeds a predetermined threshold value, that the change is caused by chewing, and analyzes the action of the chewing [A large difference between the left and right mouths (greater than or equal to the threshold value)indicates, for example, that there is paralysis on the left or right side of the mouth, that is, an expression for taking food into the oral cavity without spilling food during the preparation period (Nakajima p. 6)].
Regarding claim 4, Nakajima in view of Bourdiol and Trench teaches
The chewing assistance system according to claim 2, wherein
the feature point includes at least one of a nasal tip, a nasion, a corner of the mouth, a vertex of an upper lip, a vertex of a lower lip, a vertex of a jaw, and a point along an outline of a cheek near masseter [in the case where the image acquired by the acquisition unit 110 is a plurality of continuous images obtained by imaging the cheek when the person to be evaluated U closes his mouth and expands his cheek, the calculation unit 120 The cheek movement in a continuous image(moving image) is calculated as a feature amount. Specifically, the calculation unit 120 calculates whether or not the cheek bulge can be maintained as a feature amount (Nakajima p. 7)].
Regarding claim 5, Nakajima in view of Bourdiol and Trench teaches
The chewing assistance system according to claim 2, wherein
the change of the feature point includes at least one of change of a position of the feature point [in the case where the image acquired by the acquisition unit 110 is a plurality of continuous images obtained by imaging the cheek when the person to be evaluated U closes his mouth and expands his cheek, the calculation unit 120 The cheek movement in a continuous image(moving image) is calculated as a feature amount. Specifically, the calculation unit 120 calculates whether or not the cheek bulge can be maintained as a feature amount (Nakajima p. 7)], change of a distance between two feature points, and change of an area surrounded by three or more feature points.
Regarding claim 7, Nakajima in view of Bourdiol and Trench teaches
The chewing assistance system according to claim 1, wherein
the quality of the chewing action determined by the quality determination means includes quality based on at least one of determinations as to whether a total number of chewing times is large or small [Bourdiol p. 17, Table 2], whether chewing rhythm is proper [Bourdiol p. 17, Table 2], whether mouth opening behavior is proper [Small mouth openness (below the threshold), that is, not opening the mouth wide, for example, during the preparation period, the facial muscle function and masseter muscles for taking food into the mouth without spilling It shows that the occlusal function of temporal muscles (masticatory muscles) is reduced. That is, by evaluating the degree of opening of the person to be evaluated U, the motor function of the facial muscles and the motor function of the masticatory muscles in the preparation period can be evaluated (Nakajima p. 7); In the evaluation results shown in FIG. 8, all swallowing functions are NG. In this case, the swallowing function may be reduced in the preparation period, the oral period, and the pharyngeal period. For example, the muscular strength of the lips declines due to the decline in the motor function of the facial muscles during the preparation period, the masseter muscles decline due to the decline in the movement function of the masticatory muscles during the preparation period (Nakajima p. 10); the preparation period, for example, recognizes the motor function of facial muscles (such as lip muscles and cheek muscles) that take food into the oral cavity without spilling it (Nakajima p. 2)], whether chewing balance between a left side and a right side is proper [the calculation unit 120 calculates a difference between the movement amount on the left side of the mouth and the movement amount on the right side (referred to as a mouth left / right difference) as a feature amount (Nakajima p. 6)], whether eating behavior (motion of a mouth) is proper [Nakajima p. 6], and whether use of masseter is proper [Nakajima p. 7], wherein the eating behavior is at least a motion of the mouth [Nakajima p. 7].
Regarding claim 8, Nakajima in view of Bourdiol and Trench teaches
The chewing assistance system according to claim 1, wherein
the quality determination means compares the chewing action with a previous chewing action of the same person and determines whether the chewing action has improved [For example, the reference data 161 is predetermined data, but may be updated based on an evaluation result obtained when an expert actually diagnoses the swallowing function of the person to be evaluated U. Thereby, the evaluation precision of a swallowing function can be improved (Nakajima p. 14)].
Regarding claim 9, Nakajima in view of Bourdiol and Trench teaches
The chewing assistance system according to claim 1, wherein
the quality determination means has a machine learning mechanism, which processes and provides a learning result [the evaluation result of the swallowing function may be stored as big data together with personal information and used for machine learning. Moreover, the proposal content regarding swallowing may be accumulated as big data together with personal information and used for machine learning (Nakajima p. 14)], and
the chewing quality of the chewing action is determined by the quality determination means with reference to the learning result processed and provided by the machine learning mechanism [Nakajima p. 14].
Regarding claim 11, Nakajima in view of Bourdiol and Trench teaches
A computer-readable recording medium for use in an information processing device, the recording medium having a control program recorded thereon for causing the information processing device to function as the chewing assistance system according to claim 1, the control program including a chewing assistance program causing the information processing device to function as the moving image obtaining means, the analysis means, the quality determination means, and the extraction means [Note that the swallowing function evaluation apparatus 100 is, for example, a personal computer, but may be a server apparatus…The swallowing function evaluation apparatus100 includes an acquisition unit 110, a calculation unit 120, an evaluation unit 130, an output unit 140,a suggestion unit 150, and a storage unit 160 (Nakajima p. 4)].
Regarding claim 12, Nakajima teaches
A chewing assistance system comprising an information processing device [the swallowing function evaluation apparatus 100 is, for example, a personal computer, but may be a server apparatus (Nakajima Translated p. 4)] that includes:
chewing information storage means that stores information about chewing quality [The storage unit 160 includes reference data 161 that indicates the relationship between the feature amount and the person's swallowing function, proposal data 162 that indicates the relationship between the evaluation result of the swallowing function and the proposed content… The storage unit 160 is realized by, for example, a ROM (Read Only Memory), a RAM (Random Access Memory), a semiconductor memory, an HDD (Hard Disk Drive), or the like (Nakajima p. 5)];
moving image obtaining means that obtains a moving image of a region including at least a mouth or a peripheral portion of the mouth in a face during chewing [The acquisition unit 110 acquires an image obtained by imaging the face or neck of the person to be evaluated U in a non-contact manner (Nakajima p. 4); The feature amount indicates a feature such as a face movement of the evaluated person U calculated from an image used by the evaluation unit 130 to evaluate the eating and swallowing function of the evaluated person U (Nakajima p. 5), wherein the image being evaluated based on the facial movement of the evaluated person is considered to define obtaining a “moving image”, as defined by the Applicant’s Specification ¶0010];
analysis means that analyzes a chewing action based on the moving image of the region during chewing obtained by the moving image obtaining means [The calculation unit 120 calculates a feature amount from the image acquired by the acquisition unit 110. The feature amount indicates a feature such as a face movement of the evaluated person U calculated from an image used by the evaluation unit 130 to evaluate the eating and swallowing function of the evaluated person U or a position of a laryngeal protuberance on the neck. It is a numerical value (Nakajima p. 5)], to determine a motion of the mouth, a motion of a jaw, and a motion of the masseter [in the case where the image acquired by the acquisition unit 110 is a plurality of continuous images obtained by imaging the cheek when the person to be evaluated U closes his mouth and expands his cheek, the calculation unit 120 The cheek movement in a continuous image(moving image) is calculated as a feature amount. Specifically, the calculation unit 120 calculates whether or not the cheek bulge can be maintained as a feature amount (Nakajima p. 7), wherein analysis of movement of the evaluated person’s mouth and cheek is considered to read on each of motion of the mouth, jaw, and masseter];
quality determination means that determines chewing quality of the chewing action based on information of the chewing action analyzed by the analysis means [The evaluation unit 130 compares the feature amount calculated by the calculation unit 120 with the reference data 161 stored in the storage unit 160, and evaluates the eating / swallowing function of the person to be evaluated U (Nakajima p. 5)]; and
extraction means that extracts assistance information corresponding to the chewing quality determined by the quality determination means [The proposing unit 150 makes a proposal regarding swallowing to the person to be evaluated U by collating the evaluation result output by the output unit 140 with predetermined proposal data 162. In addition, the suggestion unit 150 may collate the personal information acquired by the acquisition unit 110 with the proposal data 162 and make a proposal regarding swallowing to the evaluated person U (Nakajima p. 5), wherein determining a proposal or suggestion based on the evaluated eating/swallowing function is considered to read on the BRI of “extracting assistance information” based on chewing quality], from the chewing information storage means [The proposal data 162 is referred to by the suggestion unit 150 when a proposal related to swallowing for the person to be evaluated U is made (Nakajima p. 5)] to determine an improving state of the chewing quality [For example, the reference data 161 is predetermined data, but may be updated based on an evaluation result obtained when an expert actually diagnoses the swallowing function of the person to be evaluated U. Thereby, the evaluation precision of a swallowing function can be improved (Nakajima p. 14), wherein evaluating a person over time or with reference to previous data of the same person in order to provide updated evaluations is considered to be equivalent to determining “an improving state”].
However, while Nakajima does acknowledge that the occlusal state of the subject’s teeth affect masticatory function [Tongue recognition function, or tongue movement function to push food to teeth or mix finely mixed food with saliva, occlusal state of teeth to chew and crush food, tooth and The cheek movement function that prevents food from entering between the cheeks, the movement function of the masticatory muscles (such as the masseter and temporal muscles), which is the generic name of the muscles used for mastication, and the fine food For example, the saliva secretion function. The masticatory function is affected by the occlusal state of the teeth, the function of the masticatory muscles, the function of the tongue, and the like (Nakajima p. 2)], Nakajima fails to explicitly disclose wherein the analysis of the chewing action is to determine a total number of chewing times, a chewing rhythm, and occlusal balance between anterior and posterior sides and between left and right sides.
Bourdiol discloses methods for assessing chewing kinematics and mastication efficiency using moving images of a subject [Video recording was used to evaluate the kinematic parameters (Nicolas, Veyrune, Lassauzay, Peyron, & Hennequin, 2007). A digital camera (SONY DCR-PC330E, Japan) positioned in front of the subject recorded a video of facial movements. The subjects were first asked to chew until deglutition three replicates of the model foods of each hardness level presented in a random order (Bourdiol p. 16)], wherein Bourdiol discloses that malocclusions of overbite and underbite result in quantifiable differences in a number of chewing times, chewing rhythm [Values (mean ± sd) of cycle number (or chewing stroke number) at deglutition and values of duration in second and frequency (cycle number/sequence duration in hertz) at deglutition and after 15 cycles when chewing raw carrots in the three groups: NoDFD (no treatment need), ModDFD (indication for orthodontic treatment alone), SevDFD (indication for surgical treatment) (Bourdiol p. 17, Table 2)], and visibly observable lower chewing quality based on measured chewing kinematics [The SevDFD group comprised 15 skeletal class III (among them 5 open-bites, 4 deep-bites, 6 normal-bites), with hypomaxilla (n = 3), mandible prognathism (n = 6) and maxilla-mandible prognathism (n = 6) (Bourdiol p. 15), wherein the Examiner notes that hypomaxilla, mandible prognathism, and maxilla-mandible prognathism are considered to define different types of malocclusions that affect occlusal balance in at least anterior and posterior directions; This study confirms that SevDFD subjects are unable to compensate for their deficient occlusion during mastication. The SevDFD subjects had clearly impaired mastication as shown by two main criteria: (i) the individual d50 of SevDFD subjects was always above MNI cut-off and (ii) the cycle frequency when chewing either carrots or gelatines was significantly lower in SevDFD than in NoDFD. The SevDFD subjects appear similar to patients or subjects displaying severe mastication impairment… Impaired mastication in our SevDFD subjects was not due to having fewer teeth, tooth number being similar in all the groups, but rather to interarch discrepancy, as indicated by the significantly reduced functional area (Bourdiol p. 18)].
Trench discloses methods for assessing chewing function using moving images of a subject [The characteristics of masticatory function were assessed by examining the ability to chew French bread by each individual, who was instructed to proceed as usual with daily life. The performance of this function was filmed with a SONY DSC - W 620 digital camera; the obtained results were evaluated by counting the number of chewing cycles, and the vertical or lateral mandibular movements were analyzed (Trench p. 1203)], wherein Trench discloses that malocclusions of crossbite result in visibly observable lower chewing quality based on measured chewing motions [In patients with skeletal bilateral posterior cross bite DFD, the unilateral left chewing pattern was observed in 80% of subjects, which was followed by unilateral right (20%)… there was inefficient chewing in 80% of subjects evaluated (Trench p. 1209, Table 8), wherein crossbite is considered to define a type of malocclusion that affects occlusal balance in at least left and right directions].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system of Nakajima to employ wherein the analysis of the chewing action is to determine a total number of chewing times, a chewing rhythm, and occlusal balance between anterior and posterior sides and between left and right sides, as chewing kinematics are considered to be indicative of total number of chewing times, chewing rhythm, and occlusal balance between anterior and posterior sides and between left and right sides, which are further indicative of a measure of chewing quality [Bourdiol p. 17-18, Table 2; Trench p. 1209, Table 8].
Response to Arguments
Applicant’s arguments, see Applicant’s Remarks p. 8, filed 18 November 2025, with respect to the previously applied rejection(s) under § 112(b) have been fully considered and are persuasive. The § 112(b) rejection of claim 2 has been withdrawn.
Applicant’s arguments, see Applicant’s Remarks p. 7-9, filed 19 December 2025, with respect to the rejection(s) of claim(s) 1 and 12 under § 102 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Nakajima (WO-2019225243-A1, previously presented) in view of Bourdiol (“Only severe malocclusion correlates with mastication deficiency”, NPL attached) and Trench (“Dentofacial deformities: orofacial myofunctional characteristic”, NPL attached).
The Applicant asserts that the amendments to claim 1 regarding “analysis means that analyzes a chewing action based on the moving image of the region during the chewing obtained by the moving image obtaining means, to determine a chewing rhythm and occlusal balance between anterior and posterior sides and between left and right sides” distinguish the Applicant’s claimed analysis means over the teachings of Nakajima. The Applicant asserts that the amendments to claim 12 regarding “analysis means that analyzes a chewing action based on the moving image of the region during the chewing obtained by the moving image obtaining means, to determine a total number of chewing times, a chewing rhythm, a motion of the mouth, a motion of a jaw, occlusal balance between anterior and posterior sides and between left and right sides, and a motion of masseter” distinguish the Applicant’s claimed analysis means over the teachings of Nakajima. Applicant’s arguments with respect to claim(s) 1 and 12 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. Nakajima is further modified by Bourdiol and Trench, as Bourdiol indicates that malocclusions of overbite and underbite result in quantifiable differences in a number of chewing times, chewing rhythm [Values (mean ± sd) of cycle number (or chewing stroke number) at deglutition and values of duration in second and frequency (cycle number/sequence duration in hertz) at deglutition and after 15 cycles when chewing raw carrots in the three groups: NoDFD (no treatment need), ModDFD (indication for orthodontic treatment alone), SevDFD (indication for surgical treatment) (Bourdiol p. 17, Table 2)], and visibly observable lower chewing quality based on measured chewing kinematics [The SevDFD group comprised 15 skeletal class III (among them 5 open-bites, 4 deep-bites, 6 normal-bites), with hypomaxilla (n = 3), mandible prognathism (n = 6) and maxilla-mandible prognathism (n = 6) (Bourdiol p. 15), wherein the Examiner notes that hypomaxilla, mandible prognathism, and maxilla-mandible prognathism are considered to define different types of malocclusions that affect occlusal balance in at least anterior and posterior directions; This study confirms that SevDFD subjects are unable to compensate for their deficient occlusion during mastication. The SevDFD subjects had clearly impaired mastication as shown by two main criteria: (i) the individual d50 of SevDFD subjects was always above MNI cut-off and (ii) the cycle frequency when chewing either carrots or gelatines was significantly lower in SevDFD than in NoDFD. The SevDFD subjects appear similar to patients or subjects displaying severe mastication impairment… Impaired mastication in our SevDFD subjects was not due to having fewer teeth, tooth number being similar in all the groups, but rather to interarch discrepancy, as indicated by the significantly reduced functional area (Bourdiol p. 18)]; and Trench indicates that malocclusions of crossbite result in visibly observable lower chewing quality based on measured chewing motions [In patients with skeletal bilateral posterior cross bite DFD, the unilateral left chewing pattern was observed in 80% of subjects, which was followed by unilateral right (20%)… there was inefficient chewing in 80% of subjects evaluated (Trench p. 1209, Table 8), wherein crossbite is considered to define a type of malocclusion that affects occlusal balance in at least left and right directions].
Applicant's arguments, Applicant’s Remarks p. 10, filed 19 December 2025, with respect to the previously applied rejections under § 101 have been fully considered but they are not persuasive.
The Applicant cites the USPTO announcement regarding “updated to the MPEP reaffirm that examiners must consider the claimed invention as a whole, including any described technological advance, when determining whether the claim integrates a judicial exception into a practical application [to qualify as patentable subject matter under 35 U.S.C. § 101]”. The Applicant further cites Aatrix Software Inc. v. Green Shades Software, Inc., 882 F.3d 112 (Fed. Cir. 2018), regarding if it is simply established that the Applicant’s claimed invention improves another technology, such improvement should be sufficient to overcome a non-patentable subject matter under 35 U.S.C. § 101; and such improvement cannot be rejected as “well-understood, routine, conventional activity” in rejecting the claimed invention as non-patentable subject matter under 35 U.S.C. § 101. The Examiner notes that while the most recently filed Applicant’s Remarks filed 19 December 2025 do not specifically cite the Applicant’s argued improvements as recited anywhere in the instant disclosure, based on the previous Applicant’s Remarks filed 9 June 2025, the argued improvement is considered to refer to the instant invention not requiring any attachment of a device to the body and causing a user to feel uncomfortable and applying a load on the user, which is accomplished by having a quality determination means that determines the quality of a user’s chewing action based on information of the user’s chewing action, which has been extracted and analyzed. However, the Examiner disagrees with the Applicant’s arguments, as the Examiner notes that revised MPEP § 2106.04(d)(1) recites “In short, first the specification should be evaluated to determine if the disclosure provides sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement in the functioning of a computer, or an improvement to other technology or a technical field… Conversely, if the specification explicitly sets forth an improvement but only in a conclusory manner (i.e., a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art), the examiner should not determine that the claim improves technology or a technical field. Second, if the specification sets forth an improvement in technology or a technical field, the claim must be evaluated to ensure that the claim itself reflects the disclosed improvement… See, e.g., Ex Parte Desjardins, Appeal No. 2024-000567 (PTAB September 26, 2025, Appeals Review Panel Decision) (precedential), in which the specification identified the improvement to machine learning technology by explaining how the machine learning model is trained to learn new tasks while protecting knowledge about 2 previous tasks to overcome the problem of “catastrophic forgetting,” and that the claims reflected the improvement identified in the specification. Indeed, enumerated improvements identified in the Desjardins specification included disclosures of the effective learning of new tasks in succession in connection with specifically protecting knowledge concerning previously accomplished tasks; allowing the system to reduce use of storage capacity; and the enablement of reduced complexity in the system. Such improvements were tantamount to how the machine learning model itself would function in operation and therefore not subsumed in the identified mathematical calculation.” As such, the Examiner notes that the Applicant’s arguments related to the Applicant’s noted improvements as recited in the Specification are not considered to be directed towards the functioning of a computer or technology and are considered conclusory, as the Applicant fails to provide necessary details as to how the alleged improvement improves the functioning of a computer or technology [the Examiner notes ¶0029 refers to the use of a well-understood, routine, and conventional smartphone for imaging; ¶0031 refers to the use of well-known methods for detecting a face feature point; and at least ¶¶0042-0043, 0045 fail to describe to how the Applicant’s invention may improve computer technology, functionality, or training the disclosed machine learning model in any particular way beyond mere input and output of information].
Conclusion
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/SEVERO ANTONIO P LOPEZ/Examiner, Art Unit 3791