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 .
Status of the Claims
The office action is in response to the claim amendments and remarks filed on July 23, 2026 for the application filed February 12, 2024 which claims priority to a foreign application filed on August 13, 2021. Claims 1-25 and 28 are currently pending and have been examined.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-25 and 28 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.
Claims 1 and 28 recite the limitation "the computing circuit is configured to transmit the information to be provided to the target customer ". There is insufficient antecedent basis for the limitation “the information” in the claim.
Claims 2-25 are rejected based on their dependency on claim 1.
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 1-25 and 28 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Eligibility Step 1:
Under step 1 of the 2019 Revised Patent Subject Matter Eligibility Guidance, claims 1-25 and 28 are directed towards an information providing system (i.e. a machine), which is a statutory category. Since the claims are directed toward statutory categories, it must be determined if the claims are directed towards a judicial exception (i.e. a law of nature, a natural phenomenon, or an abstract idea). In the instant application, the claims are directed towards an abstract idea.
Eligibility Step 2A, Prong One:
Under step 2A, prong one of the 2019 Revised Patent Subject Matter Eligibility Guidance, independent claims 1 and 28 are determined to be directed to an judicial exception because an abstract idea is recited in the claims which fall within the subject matter groupings of abstract ideas.
The abstract idea (identified in bold) recited in representative claim 1 is identified as:
An information providing system comprising:
a server device; and
an information terminal, wherein:
the server device comprises a computing circuit, an input device, a storage, and an output interface, wherein the computing circuit is configured to execute a computer program stored in the storage;
the input device is configured to accept an input of risk data that indicates a degree of a health risk of a target customer, the input device is a communication terminal that is configured to execute data communication and receive the risk data that indicates the degree of the health risk of the target customer transmitted from the information terminal, the risk data is the data that indicates a segmentation to which the target customer belongs, based on personal data and a classification criterion that is prepared in advance, from a plurality of segmentations each indicating a class that corresponds to at least a degree of a health condition;
the storage is configured to store therein the computer program for operating the server device, a plurality of contents, and provision order information prepared in advance that defines order of providing the plurality of contents corresponding to the segmentation and corresponding to a respective degree of the health risk of the target customer;
the output interface is configured to be connected to one or more displaying devices being disposed outside the server device, the one or more displaying devices comprises a display of the information terminal, the computing circuit is configured to transmit the information to be provided to the target customer, to the information terminal from the output interface through a communication network, the information is displayed on the display of the information terminal, with the plurality of contents and in the order that corresponds to the respective degree of the health risk of the target customer based on the risk data and the provision order information; and
the server device is configured to execute communication with another device through the output interface.
The identified limitations of the abstract idea of claims 1 and 28 fall within the subject matter grouping of certain methods of organizing human activity related and the sub grouping of managing personal behavior or relationships or interactions between people, (including social activities, teaching, and following rules or instructions). The claims are directed to the abstract idea of providing predetermined information in a predetermined order based on predetermined segmentations, which at its core is a the human activity of providing information to a customer based on a determined classification of the customer.
The identified limitation of “the risk data is the data that indicates a segmentation to which the target customer belongs, based on personal data and a classification criterion that is prepared in advance, from a plurality of segmentations each indicating a class that corresponds to at least a degree of a health condition” falls within the subject matter grouping of mental processes as indicating a segmentation based on risk data, personal data and classification criterion can be performed in the human mind using observations, evaluations, judgments and opinions.
Accordingly, claims 1 and 28 recite an abstract idea under step 2A, prong one.
Eligibility Step 2A, Prong Two:
Under step 2A, prong two of the 2019 Revised Patent Subject Matter Eligibility Guidance, it must be determined whether the identified abstract ideas are integrated into a practical application. After evaluation, there is no identified additional element and the combination of elements does not integrate the abstract idea into a practical application, such as through: an additional element that reflects an improvement to the functioning of a computer, or an improvements to any other technology or technical field; an additional element that applies or uses a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition; an additional element that implements the judicial exception with, or uses the judicial exception in connection with, a particular machine or manufacture that is integral to the claim; an additional element that effects a transformation or reduction of a particular article to a different state or thing; or an additional element that applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.
The additional elements (identified in italics) recited in representative claim 1 are identified as:
An information providing system comprising:
a server device; and
an information terminal, wherein:
the server device comprises a computing circuit, an input device, a storage, and an output interface, wherein the computing circuit is configured to execute a computer program stored in the storage;
the input device is configured to accept an input of risk data that indicates a degree of a health risk of a target customer, the input device is a communication terminal that is configured to execute data communication and receive the risk data that indicates the degree of the health risk of the target customer transmitted from the information terminal, the risk data is the data that indicates a segmentation to which the target customer belongs, based on personal data and a classification criterion that is prepared in advance, from a plurality of segmentations each indicating a class that corresponds to at least a degree of a health condition;
the storage is configured to store therein the computer program for operating the server device, a plurality of contents, and provision order information prepared in advance that defines order of providing the plurality of contents corresponding to the segmentation and corresponding to a respective degree of the health risk of the target customer;
the output interface is configured to be connected to one or more displaying devices being disposed outside the server device, the one or more displaying devices comprises a display of the information terminal, the computing circuit is configured to transmit the information to be provided to the target customer, to the information terminal from the output interface through a communication network, the information is displayed on the display of the information terminal, with the plurality of contents and in the order that corresponds to the respective degree of the health risk of the target customer based on the risk data and the provision order information; and
the server device is configured to execute communication with another device through the output interface.
The additional limitations of: “An information providing system comprising:”; “a server device”; “an information terminal”; “wherein: the server device comprises a computing circuit, an input device, a storage, and an output interface, wherein the computing circuit is configured to execute a computer program stored in the storage”; “the input device is configured to”; “the input device is a communication terminal that is configured to execute data communication and receive the risk data that indicates the degree of the health risk of the target customer transmitted from the information terminal”; “the storage is configured to store therein the computer program for operating the server device, a plurality of contents, and provision order information prepared in advance that defines order of providing the plurality of contents corresponding to the segmentation and corresponding to a respective degree of the health risk of the target customer”; the output interface is configured to be connected to one or more displaying devices being disposed outside the server device, the one or more displaying devices comprises a display of the information terminal, the computing circuit is configured to” “to the information terminal from the output interface through a communication network, the information is displayed on the display of the information terminal”; and “the server device is configured to execute communication with another device through the output interface” are determined to be mere instructions to apply an abstract idea under MPEP §2106.05(f). As discussed in paragraphs [0041]-[0047] and [0112]-[0124], The information terminal and service device are described as generic devices having generic input devices, storage and output interface which communicate in known ways of generic networks and are used in their ordinary capacity to accept information, receive information, store information, transmit information, and display information (i.e. generic client-server architecture/functionality). Therefore, these additional elements amount to no more than a recitation of the words "apply it" (or an equivalent) or no more than mere instructions to implement an abstract idea or other exception on a computer or no more than merely using a computer as a tool to perform an abstract idea.
Accordingly, claims 1 and 28 do not recite additional elements which integrate the abstract idea into a practical application.
Eligibility Step 2B:
Under step 2B of the 2019 Revised Patent Subject Matter Eligibility Guidance, it must be determined whether provide an inventive concept by determining if the claims include additional elements or a combination of elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional limitations amount to mere instructions to apply an abstract idea under MPEP §2106.05(f), which does not amount to significantly more than the abstract idea. Furthermore, looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements amounts to an inventive concept.
Dependent Claims:
The dependent claims merely present additional abstract information in tandem with further details regarding the elements from the independent claims and are, therefore, directed to an abstract idea for similar reasons as given above. Dependent claims 2-25 merely define the unique health care data, segmentations and correlations used in the determinations and are encompassed by the abstract ideas above. None of these limitations are deemed to integrate the claims into a practical application or to amount to significantly more than the abstract idea because, as stated above, they are directed to the abstract idea without any additional elements.
Therefore, whether taken individually or as an ordered combination, 1-25 and 28 are rejected under 35 U.S.C. 101 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 factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-3, 8, 10-11, 25 and 28 are rejected under 35 U.S.C. 103 as being unpatentable over Minturn (U.S. Pub. No. 2019/0088159) in view of Nazem et al. (U.S. Pub. No. 2020/0058404).
Regarding claim 1, Minturn discloses an information providing system comprising:
a server device (Paragraph [0193], a processing computer. Also see paragraph [0078]. A computer which receives data from a phone app, processes the data and generates/sends an output to a phone app over the internet is construed as a server device.); and
an information terminal (Paragraph [0193], a phone App, tablet device, PC or kiosk computer.), wherein:
the server device comprises a computing circuit, an input device, a storage, and an output interface, wherein the computing circuit is configured to execute a computer program stored in the storage (Paragraph [0185], quantifiable scientific well-being and optimal wellness database software. Paragraph [0193], transmit said data to a processing computer which then assesses, evaluates, compares and contrasts the data. Quantified, correlated, validated and frequently updated and revised proprietary super-health, scientific well-being, optimal wellness and ideal fitness databases Paragraph [0078], The software systems and programs are capable of rapid data input of quantifiable well-being, objective wellness and laboratory data entry and processing. Also see paragraphs [0074 and [0077]. A computer which receives data from a phone app, processes the data and generates/sends an output to a phone app over the internet using software/programs and data stored in a database is construed as a server device comprising a computing circuit, an input device, a storage, and an output interface.);
the input device is configured to accept an input of risk data that indicates a degree of a health risk of a target customer, the input device is a communication terminal that is configured to execute data communication and receive the risk data that indicates the degree of the health risk of the target customer transmitted from the information terminal, the risk data is the data that indicates a segmentation to which the target customer belongs, based on personal data and a classification criterion that is prepared in advance, from a plurality of segmentations each indicating a class that corresponds to at least a degree of a health condition (Paragraph [0193], the present invention consists of the arrangement, combination and implementation of the various Super-Health, Quantifiable Scientific Well-Being, Optimal Wellness and Ideal Fitness Tests and Measurements providing raw data which can be inputted into a phone App, tablet device, PC or kiosk computer screen which when connected to the Internet can transmit said data to a processing computer which then assesses, evaluates, compares and contrasts the data to the quantified, correlated, validated and frequently updated and revised proprietary super-health, scientific well-being, optimal wellness and ideal fitness databases, resulting in the processing of the data to create an individualized output report which graphically indicates each rank and rating of comprehensive self-reported and/or certified wellness technician or laboratory measured super-health, quantifiable scientific well-being, optimal wellness and ideal fitness levels on a series of up to 40 or more special 10-Point Scales with simple graphics, appropriately ranked personalized evaluative comments and suggestions in layman like language and figures. Paragraph [0089], All of these Bio-Physiological Parameters are ranked on a scale from “One” to “Ten.” The combination of these tests and measurements objectively determine a person's true level of Quantifiable Well-Being and Scientific Wellness. Figs. 3A-5F show that the level of Quantifiable Well-Being and Scientific Wellness indicating numerical ratings from 1-10 and ranks danger, poor, fair, good or excellent class/segment of a health condition, construed as risk of a participant. Also see paragraphs [0078] and [0185] discussing that the criterion for rating and ranking is stored in a database, construed as prepared in advance and paragraph [0052].);
the storage is configured to store therein the computer program for operating the server device, a plurality of contentsParagraph [0077], Quantifiable Well-Being and Scientific Optimal Wellness Database System. Paragraph [0078], The software systems and programs are capable of rapid data input of quantifiable well-being, objective wellness and laboratory data entry and processing. Paragraph [0185], The knowledge and data that comes from these three types of individual assessments are actuarially correlated via quantifiable scientific well-being and optimal wellness database software in order to create a unique series of individualized detailed VR Games, clear output reports and visually accented graphs with graduated ranking numerical scales based on 10-Point Quantifiable Scientific Well-Being and Optimal Wellness Scales and Custom Factoring Formuli that also includes quantifiable evaluations, suggestions for improvement, recommendations and proven protocols for interventions, and risk reduction strategies for improving a person's scientific well-being rankings. Paragraph [0193], quantified, correlated, validated and frequently updated and revised proprietary super-health, scientific well-being, optimal wellness and ideal fitness databases. Also see Figs. 3A-5F.);
the output interface is configured to be connected to one or more displaying devices being disposed outside the server device, the one or more displaying devices comprises a display of the information terminal, the computing circuit is configured to transmit the information to be provided to the target customer, to the information terminal from the output interface through a communication network, the information is displayed on the display of the information terminal, with the plurality of contents Paragraph [0078], The software systems and programs are capable of rapid data input of quantifiable well-being, objective wellness and laboratory data entry and processing. The individualized output, quantifiable scientific well-being and optimal wellness reports contain a series of visual depictions each having analysis information categorized on the 10-Point Quantifiable Scientific Well-Being, Optimal Wellness and Ideal Fitness Scales as well as highlighted suggestions, recommendations and improvement protocols that are graphically portrayed and can either be sent to a computer, tablet or phone App, printed on compatible printers or downloaded for processing by a high-speed computerized printing service company. Also see paragraph [0193] and Figs. 3A-5F.); and
the server device is configured to execute communication with another device through the output interface (Paragraph [0078], sent to a computer, tablet or phone App, printed on compatible printers or downloaded for processing by a high-speed computerized printing service company. Also see Fig. 2.).
Minturn does not appear to explicitly disclose to store provision order information prepared in advance that defines order of providing the plurality of contents; and transmit information in the order that corresponds to the provision order information.
Nazem teaches that it was old and well known in the art of providing health recommendations at the time of the filing to store provision order information prepared in advance that defines order of providing the plurality of contents; and transmit information in the order that corresponds to the provision order information (Paragraph [0104], The content engine 140 determines what should be displayed next on the application 123 to a particular user based on a list including display items identified in the order in which each item should be displayed. This list as well as the order is specific to each user, and the content unit 108 can prepare this list and order based on user's current health profile. Also see fig. 16.) to provide interactive and user-friendly guidance to users (Paragraph [0003]).
Therefore, it would have been obvious to one of ordinary skill in the art of providing health recommendations at the time of the filing to modify the system of Minturn such that the storage store provision order information prepared in advance that defines order of providing the plurality of contents; and such that the output interface transmits information in the order that corresponds to the provision order information, as taught by Nazem, in order to provide interactive and user-friendly guidance to users.
Regarding claim 2, Minturn further discloses wherein the degree of the health condition is classified in a plurality of numerical ranges (Figs. 3A-5F show the degrees classified in a plurality of numerical rating ranges.),
each of the plurality of segmentations is correlated in advance with a numerical range that corresponds to the degree of the health condition (Figs. 3A-5F),
a degree of a potential health condition of the target customer is indicated by a numerical value (Figs. 3A-5F), and
the degree of the potential health condition of the target customer is predicted by determining the segmentation that corresponds to the numerical value, based on the numerical range to which the numerical value belongs (Figs. 3A-5F).
Regarding claim 3, Minturn further discloses wherein the plurality of segmentations are three or more segmentations (Figs. 3A-5F, showing danger, poor, fair, good and excellent segments/rankings).
Regarding claim 8, Minturn further discloses wherein the health condition of the target customer is one or more selected from a change of a physical condition and a lack of exercise accompanied by a lifestyle-related disease and/or obesity, obesity, and a variation of a body weight in a specific time period (Fig. 3B and paragraphs [0094]-[0099] show and discuss the health condition a body mass index which can indicate a degree of obesity.).
Regarding claim 10, Minturn further discloses wherein the health condition of the target customer is one or more selected from a health problem caused by a weakened immunity, being easily catch colds, an SIgA concentration, an allergy symptom, and a condition of oral cavity health (Paragraphs [0052], [0173]-[0174] and Fig. 5F discuss and show that the provided health information is selected based on a health problem associated/caused by quantifiable accurate laboratory evaluations of immuno-vitality, construed as a weekend immunity.).
Regarding claim 11, Minturn further discloses wherein the health condition of the target customer is one or more selected from a health problem relating to nutrition, poor nutrition, a nutritional bias, and a dietary habit (Paragraphs [0052], [0123]-[0128] and Fig. 4C discuss and show that the provided health information is selected from on a health problem associated/related to nutrition, poor nutrition, nutritional attitudes/bias and eating habits.)
Regarding claim 25, Minturn further discloses wherein the plurality of segmentations further comprise classes that each correspond to a daily behavior, and the plurality of pieces of unique data comprised in the personal data further comprise health data that reflects a health condition of the target customer (Paragraph [0103]-[0105] and Fig. 3D discuss and show that the ratings and rankings of the health condition correspond to daily habits, such as smoking and health data that reflects a health condition of the participant.).
Claim 28 is rejected based on the same rationale as claim 1.
Claims 4-5 and 7 are rejected under 35 U.S.C. 103 as being unpatentable over Minturn (U.S. Pub. No. 2019/0088159) in view of Nazem et al. (U.S. Pub. No. 2020/0058404) and Kawai et al. (U.S. Pub. No. 2016/0335402).
Regarding claim 4, Minturn further discloses, wherein Figs. 3A-5F show that the ratings and rankings for the health condition are correlated with health recommendations and the provided health information includes recommendations/offerings. Paragraphs [0075]-[0076] discuss that the recommendations include specific intervention programs, construed as services and RXs, construed as products. Also see paragraphs [0078], [0185] and [0193] discusses that the output is generated based on health data in databases prepared in advance as shown in Figs. 3A-5F.).
Minturn does not appear to explicitly disclose correlations of each of the segmentations, and a service and/or a product that suit(s) the health condition of each of the segmentations with each other are provided by a table is prepared in advance.
Kawai teaches that it was old and well known in the art of information processing systems at the time of the filing to provide a table is prepared in advance, that correlates therein each of the segmentations, and a service and/or a product that suit(s) the health condition of each of the segmentations with each other (Fig. 24 and paragraph [0395]-[0400] show and discuss a table stored in advance which correlated segmented classes of a health condition with products and services as further discussed in paragraphs [0110]-[0113]).
Therefore it would have been obvious to one of ordinary skill in the art of information processing systems at the time of the filing to modify the correlations of each of the segmentations, and a service and/or a product that suit(s) the health condition of each of the segmentations with each other of Minturn to be provided by a table is prepared in advance, as taught by Kawai, as this is merely applying the known technique of table based data storage/correlation to the known method of software implemented data correlation ready for the improvement of specific data storage structure to yield predictable results organized and correlated data.
Regarding claim 5, Minturn further discloses wherein the health information and/or the proposal are/is provided through a text message in an e- mail, a display on one or more displaying devices, printing on a receipt, or a message presented on an app executed by an electronic device (Paragraph [0078], The individualized output, quantifiable scientific well-being and optimal wellness reports contain a series of visual depictions each having analysis information categorized on the 10-Point Quantifiable Scientific Well-Being, Optimal Wellness and Ideal Fitness Scales as well as highlighted suggestions, recommendations and improvement protocols that are graphically portrayed and can either be sent to a computer, tablet or phone App, printed on compatible printers or downloaded for processing by a high-speed computerized printing service company.).
Regarding claim 7, Minturn does not appear to explicitly disclose, but Kawai teaches that it was old and well known in the art of information processing systems at the time of the filing wherein the health condition of the target customer is one or more selected from a health problem caused by an unfavorable sleeping condition determined in advance, worsening of a sleeping condition, unsteadiness of a sleep rhythm, and an improper sleeping time (Paragraphs [0173]-[0182] discusses that the health condition may be a fatigue index caused by unsteady sleep rhythms and improper sleep time.) to provide useful information and/or services to a user (Paragraph [0005]).
Therefore, it would have been obvious to one of ordinary skill in the art of information processing systems at the time of the filing to modify the method of Minturn such that the health condition of the target customer is one or more selected from a health problem caused by an unfavorable sleeping condition determined in advance, worsening of a sleeping condition, unsteadiness of a sleep rhythm, and an improper sleeping time, as taught by Kawai, in order to provide useful information and/or services to a user.
Claims 6 is rejected under 35 U.S.C. 103 as being unpatentable over Minturn (U.S. Pub. No. 2019/0088159) in view of Nazem et al. (U.S. Pub. No. 2020/0058404) and Sano (U.S. Pub. No. 2017/0319184).
Regarding claim 6, Minturn does not appear to explicitly disclose, but Sano teaches that it was old and well known in the art of information processing systems at the time of the filing wherein the health condition of the target customer is one or more selected from a health problem of a woman in her old age, a climacteric symptom, and a premenstrual syndrome or a premenstrual dysphoric disorder (PMS, PMDD) symptom (Paragraphs [0002], [0021] and [0093]-[0095] discuss providing women who are concerned about pregnancy and childbirth with information on a user’s health state for health conditions including premenstrual syndrome (PMS), menopausal disorder, corpus luteum insufficiency, endometriosis, and the like.).
Therefore, it would have been obvious to one of ordinary skill in the art of information processing systems at the time of the filing to modify the method of Minturn such that t the health condition of the target customer is one or more selected from a health problem of a woman in her old age, a climacteric symptom, and a premenstrual syndrome or a premenstrual dysphoric disorder, as taught by Sano, in order to provide health information to women concerned about pregnancy and childbirth.
Claims 9 and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Minturn (U.S. Pub. No. 2019/0088159) in view of Nazem et al. (U.S. Pub. No. 2020/0058404) and Kinoshita et al. (The measurement of axillary moisture for the assessment of dehydration among older patients: A pilot study).
Regarding claim 9, Minturn does not appear to explicitly disclose, but Kinoshita teaches that it was old and well known in the art of early diagnosis and intervention at the time of the filing wherein the health condition of the target customer is one or more selected from a health condition caused by a water shortage, a high value of serum Na, and a high value of a BUN/creatinine ratio (Page 256, section 2.2 and pages 257, section 4 discuss the importance of early diagnosis of dehydration caused by consumption of too little water in order to lower mortality rate. Patients can be classified as dehydrated or non-dehydrated based on high values of serum NA and/or BUN/Creatinine ratios.).
Therefore, it would have been obvious to one of ordinary skill in the art of early diagnosis and intervention at the time of the filing at the time of the filing to modify the method of Minturn such that the health condition of the target customer is one or more selected from a health condition caused by a water shortage, a high value of serum Na, and a high value of a BUN/creatinine ratio, as taught by Kinoshita, in order to provide early diagnosis of dehydration and intervention to lower mortality rates.
Regarding claim 19, Minturn further disclose wherein the personal data on the target customer comprise: an age of the target customer; and Paragraphs [0092], [0167]-[0168] discuss that the participant’s health data includes age and lab evaluations of the pH, sugars and color of a person's urine.).
Minturn does not appear to explicitly disclose wherein the personal data on the target customer comprise: a serum Na value and a BUN/creatinine ratio of the target customer; or the serum Na value, and a urine specific gravity of the target customer.
Kinoshita teaches that it was old and well known in the art of early diagnosis and intervention at the time of the filing wherein the plurality of pieces of unique data on the target customer comprise: a serum Na value and a BUN/creatinine ratio of the target customer (Page 256, section 2.2 and pages 257, section 4 discuss the importance of early diagnosis of dehydration caused by consumption of too little water in order to lower mortality rate. Patients can be classified as dehydrated or non-dehydrated based on high values of serum NA and/or BUN/Creatinine ratios.).
Therefore, it would have been obvious to one of ordinary skill in the art of early diagnosis and intervention at the time of the filing at the time of the filing to modify the method of Minturn such that the plurality of pieces of unique data on the target customer comprise: a serum Na value and a BUN/creatinine ratio of the target customer, as taught by Kinoshita, in order to provide early diagnosis of dehydration and intervention to lower mortality rates.
Regarding claim 20, Minturn does not appear to explicitly disclose, but Kinoshita teaches that it was old and well known in the art of early diagnosis and intervention at the time of the filing wherein the plurality of segmentations are classified corresponding to combinations each of the serum Na value and whether being equal to or older than, or younger than a predetermined age, and each of the segmentations is correlated with health information prepared in advance corresponding to a degree of a problem relating to a water amount shortage as the health condition (Page 256, section 2.2 and pages 257, section 4 discuss the importance of early diagnosis of dehydration caused by consumption of too little water in order to lower mortality rate. Patients over 65 can be classified as dehydrated or non-dehydrated based on high values of serum NA and/or BUN/Creatinine ratios which is then severity of dehydration.).
Therefore, it would have been obvious to one of ordinary skill in the art of early diagnosis and intervention at the time of the filing at the time of the filing to modify the method of Minturn such that the plurality of segmentations are classified corresponding to combinations each of the serum Na value and whether being equal to or older than, or younger than a predetermined age, and each of the segmentations is correlated with health information prepared in advance corresponding to a degree of a problem relating to a water amount shortage as the health condition, as taught by Kinoshita, in order to provide early diagnosis of dehydration and intervention to lower mortality rates.
Claims 12-14 are rejected under 35 U.S.C. 103 as being unpatentable over Minturn (U.S. Pub. No. 2019/0088159) in view of Nazem et al. (U.S. Pub. No. 2020/0058404) and Yoshikata et al. (Relationship between equol producer status and metabolic parameters in 743 Japanese women: equol producer status is associated with antiatherosclerotic conditions in women around menopause and early postmenopause).
Regarding claim 12, Minturn further discloses wherein the target customer is a woman, the personal data on the target customer comprise: an age of the target customer; and Paragraphs [0092] and [0097] discuss that the participant may be a woman and that the participant’s age is used to rate and rank the participant.).
Minturn does not appear to explicitly disclose wherein the personal data on the target customer comprise a value indicating an ability for equol production of the target customer.
Yoshikata teaches that it was old and well known in the art of women’s health at the time of the filing to acquire unique data on a patient comprising a value indicating an ability for equol production (Page 3, materials and methods) to examine the relationship between Equol producer status and the parameters related to lifestyle related diseases in women of different age groups (Page 3, Objectives).
Therefore, it would have been obvious to one of ordinary skill in the art of women’s health at the time of the filing to modify the method of Minturn such that the personal data on the target customer comprise a value indicating an ability for equol production of the target customer, as taught by Yoshikata, in order to examine the relationship between Equol producer status and the parameters related to lifestyle related diseases in women of different age groups. For example, the wellness the health conditions and provided health information of Minturn would be related to equal production and age.
Regarding claim 13, Minturn does not appear to explicitly disclose, but Yoshikata teaches that it was old and well known in the art of women’s health at the time of the filing wherein the plurality of segmentations are classified corresponding to combinations of a plurality of life stages each determined corresponding to the age, and presence or absence of the ability for equol production, and each of the segmentations is correlated with health information prepared in advance (Page 2-3 discuss equol production as a health condition which is segmented into producers and non-producers and menopause and early postmenopause life stages based on age, with each segment being associated with predetermined health information, such as information related to arterial stiffness and uric acid levels, and a high ratio of eicosapentaenoic acid to arachidonic acid; and lower urinary N-telopeptides) to examine the relationship between Equol producer status and the parameters related to lifestyle related diseases in women of different age groups (Page 3, Objectives).
Therefore, it would have been obvious to one of ordinary skill in the art of women’s health at the time of the filing to modify the method of Minturn such that the personal data on the target customer comprise a value indicating an ability for equol production of the target customer, as taught by Yoshikata, in order to examine the relationship between Equol producer status and the parameters related to lifestyle related diseases in women of different age groups.
Regarding claim 14, Minturn does not appear to explicitly disclose, but Yoshikata teaches that it was old and well known in the art of women’s health at the time of the filing wherein the presence or the absence of the ability for equol production is determined based on a relation between the value indicating the ability for equol production and a threshold value (Page 3, Materials and methods, Equal production stats (urine test), Summary of Resulsts producer non-producer. Equol production status is determined by comparing a EQ/DE ration to a cutoff.) to examine the relationship between Equol producer status and the parameters related to lifestyle related diseases in women of different age groups (Page 3, Objectives).
Therefore, it would have been obvious to one of ordinary skill in the art of women’s health at the time of the filing to modify the method of Minturn such that the personal data on the target customer comprise a value indicating an ability for equol production of the target customer, as taught by Yoshikata, in order to examine the relationship between Equol producer status and the parameters related to lifestyle related diseases in women of different age groups. For example, the wellness the health conditions and provided health information of Minturn would be related to equal production and age.
Claims 15-16 and 21-22 are rejected under 35 U.S.C. 103 as being unpatentable over Minturn (U.S. Pub. No. 2019/0088159) in view of Nazem et al. (U.S. Pub. No. 2020/0058404) and Wiard et al. (U.S. Pub. No. 2017/0146386).
Regarding claim 15, Minturn further discloses wherein the personal data on the target customer comprises: an age, a sex, a body height, a body weight, Paragraphs [0092], [0097], [0099] and [0105] discuss that the participant’s age, sex, height, weight and smoking habits are used to rate and rank the participant.).
Minturn does not appear to explicitly disclose wherein the peronsal data on the target customer comprises a variation of the body weight in a specific time period, of the target customer; or number of steps of the target customer.
Wiard teaches that it was old and well known in the art of health assessments at the time of the filing to acquire personal data on the target customer comprisParagraph [0068], The user-corresponding data includes information about the user (that is or is not obtained using the physiologic sensors 108,) such as demographic information or historical information. Example user-corresponding data includes height, gender, age, ethnicity, exercise habits, eating habits, cholesterol levels, previous health conditions or treatments, family medical history, and/or a historical record of variations in one or more of the listed data. Paragraph [0070], The user data, in some embodiments, includes the raw signals, bodyweight, body mass index, heart rate, body-fat percentage, cardiovascular age, balance, tremors, among other non-regulated physiologic data. Paragraph [0082], user data, including but not limited to scale-obtained physiological data, demographic data, lifestyle data (e.g., user habits include eating, drinking, smoking, sleeping, exercise, prescription medication, etc.), and diagnosis data. Paragraph [0083], a percentage change in the user's weight over a period of time. Paragraph [0084], the amount of exercise can include a number of steps per week.) to provide earlier detection of health related issues (Paragraph [0049]).
Therefore, it would have been obvious to one of ordinary skill in the art of health assessments at the time of the filing to modify the method of Minturn such that the personal data on the target customer comprises a variation of the body weight in a specific time period, of the target customer; and a number of steps of the target customer, as taught by Wiard, in order to provide earlier detection of health related issues.
Regarding claim 16, Minturn does not appear to explicitly disclose, but Wiard teaches that it was old and well known in the art of health assessments at the time of the filing wherein the plurality of segmentations are classified corresponding to combinations each of the age, the sex, a body-mass index, the variation of the body weight in a specific time period, and the behavior data on the number of steps, and the presence or the absence of the smoking habit, and each of the segmentations is correlated with health information prepared in advance (Paragraph [0078], uses the user-specific knowledge database 112 to identify users with correlations. The correlation, in some embodiments, includes patterns and/or trends, risks, and/or parameter values associated with and/or indicative of particular conditions that are common between different users. For example, the external circuitry identifies other users that have correlated user data and identify patterns of risks for conditions or diseases based on the correlation. Identifying correlated user data, for instance, includes grouping respective sets of user data into groups based on various criteria. The criteria includes symptoms, physiological parameter values, diagnosis, prescription drug usage, lifestyle habits, medical history, family medical history, and a combination thereof. Paragraph [0079], Based on the correlated user data sets, the external circuitry in some embodiments groups the users into a social group and generates a forum, blog, and/or webpage for the users of the social group to access. Paragraph [0080], In various embodiments, the forum, blog, and/or webpage includes reports and/or dashboards automatically generated and displayed by the external circuitry using the user-specific knowledge database 112. Paragraph [0082], user data, including but not limited to lifestyle data (e.g., user habits include eating, drinking, smoking, sleeping, exercise, prescription medication, etc.). Paragraph [0083], a percentage change in the user's weight over a period of time. Paragraph [0084], the amount of exercise can include a number of steps per week; user data can include body fat (or body-mass-index (bmi)). Paragraph [0068], height, gender, age.) to provide earlier detection of health related issues (Paragraph [0049]).
Therefore, it would have been obvious to one of ordinary skill in the art of health assessments at the time of the filing to modify the method of Minturn such that the personal data on the target customer comprise a variation of the body weight in a specific time period, of the target customer; and a number of steps of the target customer, as taught by Wiard, in order to provide earlier detection of health related issues.
Regarding claim 21, Minturn further discloses wherein the personal data on the target customer comprises: Paragraphs [0092], [0097] and [0099] discuss that the participant’s age, sex, height and weight and smoking habits are used to rate and rank the participant.).
Minturn does not appear to explicitly disclose wherein the personal data on the target customer comprises: an ideal body weight that the target customer regards as being ideal.
Wiard teaches that it was old and well known in the art of health assessments at the time of the filing to acquire a plurality of pieces of unique data on the target customer comprise: an ideal body weight that the target customer regards as being ideal (Paragraph [0049], weight goals.) to provide earlier detection of health related issues (Paragraph [0049]).
Therefore, it would have been obvious to one of ordinary skill in the art of health assessments at the time of the filing to modify the method of Minturn such that the personal data on the target customer comprises: an ideal body weight that the target customer regards as being ideal, as taught by Wiard, in order to provide earlier detection of health related issues.
Regarding claim 22, Minturn does not appear to explicitly disclose, but Wiard teaches that it was old and well known in the art of health assessments at the time of the filing wherein the plurality of segmentations are classified corresponding to combinations each of an age group determined corresponding to an age, a current body-mass index, and an ideal body mass index calculated from the body height and the ideal body weight, and each of the segmentations is correlated with health information prepared in advance corresponding to a degree of a problem relating to nutrition as the health condition (Paragraph [0078], uses the user-specific knowledge database 112 to identify users with correlations. The correlation, in some embodiments, includes patterns and/or trends, risks, and/or parameter values associated with and/or indicative of particular conditions that are common between different users. For example, the external circuitry identifies other users that have correlated user data and identify patterns of risks for conditions or diseases based on the correlation. Identifying correlated user data, for instance, includes grouping respective sets of user data into groups based on various criteria. The criteria includes symptoms, physiological parameter values, diagnosis, prescription drug usage, lifestyle habits, medical history, family medical history, and a combination thereof. Paragraph [0079], Based on the correlated user data sets, the external circuitry in some embodiments groups the users into a social group and generates a forum, blog, and/or webpage for the users of the social group to access. Paragraph [0080], In various embodiments, the forum, blog, and/or webpage includes reports and/or dashboards automatically generated and displayed by the external circuitry using the user-specific knowledge database 112. Paragraph [0082], user data, including but not limited to lifestyle data (e.g., user habits include eating, drinking, smoking, sleeping, exercise, prescription medication, etc.). Paragraph [0083], a percentage change in the user's weight over a period of time. Paragraph [0084], the amount of exercise can include a number of steps per week; user data can include body fat (or body-mass-index (bmi)). Paragraph [0068], height, gender, age. Paragraph [0109], identifies various correlations between the user data stored in the user-specific knowledge database 112 and associated with different users. The correlation, in some embodiments, includes patterns and/or trends, risks, and/or parameter values and/or various demographic information and user goals. Paragrph [0049], weight goals.) to provide earlier detection of health related issues (Paragraph [0049]).
Therefore, it would have been obvious to one of ordinary skill in the art of health assessments at the time of the filing to modify the method of Minturn such that the plurality of segmentations are classified corresponding to combinations each of an age group determined corresponding to an age, a current body-mass index, and an ideal body mass index calculated from the body height and the ideal body weight, and each of the segmentations is correlated with health information prepared in advance corresponding to a degree of a problem relating to nutrition as the health condition, as taught by Wiard, in order to provide earlier detection of health related issues.
Claims 17-18 are rejected under 35 U.S.C. 103 as being unpatentable over Minturn (U.S. Pub. No. 2019/0088159) in view of Nazem et al. (U.S. Pub. No. 2020/0058404) and Benson et al. (U.S. Pub. No. 2015/0164409).
Regarding claim 17, Minturn does not appear to explicitly disclose, but Benson teaches that it was old and well known in the art of sleep disorders at the time of the filing wherein the personal data on the target customer comprises: an insomnia score, and a time period value indicating the sleeping time, of the target customer; and a time period value indicating a social jet lag of the target customer as the health data (Paragraph [0248], generate an insomnia likelihood score which indicates the likelihood that the occupant has insomnia. In at least some embodiments, this insomnia likelihood score may be expressed as a probability. In some embodiments, if the insomnia likelihood score exceeds a threshold, then the processor may determine that an occupant has insomnia. Paragraph [0283], the processor may also consider sleep quality when determining whether an occupant has DSPS. Sleep quality may, for example, be determined based on the number of times the occupant wakes up during their sleep session and/or the amount of time elapsed between when the occupant falls asleep and when they wake up. Paragraph [0284], when the number of consecutive sleeps with excessive sleep onset latency reaches a first predetermined threshold, then the processor may determine that the likelihood of DSPS is at a first level (e.g. 60%). When the number of consecutive sleeps with excessive sleep onset latency reaches a second predetermined threshold, then the processor may determine that the likelihood of DSPS is at a second level (e.g. 70%).) to alert a user of sleep disorders (Paragraph [0241]).
Therefore, it would have been obvious to one of ordinary skill in the art of sleep disorders at the time of the filing to modify the method of Minturn such that the personal data on the target customer comprises: an insomnia score, and a time period value indicating the sleeping time, of the target customer; and a time period value indicating a social jet lag of the target customer as the health symptom data, as taught by Benson, in order to alert a user of sleep disorders.
Regarding claim 18, Minturn does not appear to explicitly disclose, but Benson teaches that it was old and well known in the art of sleep disorders at the time of the filing wherein the plurality of segmentations are classified corresponding to combinations each of a degree of insomnia and presence or absence of the social jet lag, and each of the segmentations is correlated with health information prepared in advance corresponding to a degree of a problem relating to sleeping as the health condition (Paragraph [0129], a processor 117 may cause a display 390 to display sleep disorder information for an occupant. As noted above, this information may indicate whether a user has or is likely to have a sleep disorder. The sleep disorder may, for example, include and one or combination of: insomnia, narcolepsy, sleep apnea, bruxism, delayed sleep phase syndrome, advanced sleep phase syndrome, periodic limb movement disorder, sleep walking, sleep talking, bed wetting, etc.. In at least some embodiments, the display screens 1500 may provide access to one or more tips 1504 for dealing with and/or preventing one or more of these sleep disorders. In the example of FIG. 15, the tips 1504 are provided as a selectable interface element which may be activated by an input interface 1282 of the mobile device 1200 (e.g. a touchscreen display) to cause the processor of the mobile device 1200 to generate a display screen (not shown) which includes text describing the tip.) to alert a user of sleep disorders (Paragraph [0241]).
Therefore, it would have been obvious to one of ordinary skill in the art of sleep disorders at the time of the filing to modify the method of Minturn such that the plurality of segmentations are classified corresponding to combinations each of a degree of insomnia and presence or absence of the social jet lag, and each of the segmentations is correlated with health information prepared in advance corresponding to a degree of a problem relating to sleeping as the health condition, as taught by Benson, in order to alert a user of sleep disorders.
Claims 23-24 are rejected under 35 U.S.C. 103 as being unpatentable over Minturn (U.S. Pub. No. 2019/0088159) in view of Nazem et al. (U.S. Pub. No. 2020/0058404) and Janket et al. (Salivary Immunoglobulins and Prevalent Coronary Artery Disease).
Regarding claim 23, Minturn further discloses wherein the personal data on the target customer comprise salivary lab tests (Paragraphs [0169]-[0172]), but does not appear to explicitly disclose that the salivary lab test are for salivary IgA.
Janket teaches that it was old and well known in the art of health assessment at the time of the filing to acquire salivary IgA data to perform risk assessment (Abstract).
Therefore, it would have been obvious to one of ordinary skill in the art of health assessment at the time of the filing to modify the method of Minturn such that the personal data on the target customer comprise salivary IgA, as taught by Janket, in order to perform risk assessment.
Regarding claim 24, Minturn does not appear to explicitly disclose, but Janket teaches that it was old and well known in the art of health assessment at the time of the filing wherein the plurality of segmentations are classified corresponding to values of the salivary IgA, and each of the segmentations is correlated with health information prepared in advance corresponding to a degree of a problem relating to an immunity as the health condition (Page 390, Statistical Methods, Cut-off values for each quartile of salivary IgG levels were < 5.75, 5.75-11.50, 11.50-20.78, and ≥ 20.78 µg/mL, and for each quartile of salivary IgA, they were < 43.5, 43.5-61.5, 61.5-95.4, and ≥ 95.4 µg/mL. Using multivariable logistic regression methods, we calculated odds ratios (OR) of CAD for each quartile of salivary immunoglobulins, salivary IgG, and salivary IgA, compared with the reference (lowest) quartile, adjusting for other established risk factors. Page 391, Results, increased likelihood of CAD for those in the third (odds ratios [OR] = 1.97) or fourth (OR = 1.37) quartile of salivary IgA, compared with those in the combined two lowest quartiles (p for trend = 0.06). We also found a decreased likelihood of CAD for those in the second (OR = 0.77), third (OR = 0.60), and fourth (OR = 0.51) highest quartiles of salivary IgG (p for trend = 0.02).).
Therefore, it would have been obvious to one of ordinary skill in the art of health assessment at the time of the filing to modify the method of Minturn such that the plurality of segmentations are classified corresponding to values of the salivary IgA, and each of the segmentations is correlated with health information prepared in advance corresponding to a degree of a problem relating to an immunity as the health condition, as taught by Janket, in order to perform risk assessment.
Response to Arguments
Applicant's arguments filed July 23, 2026 regarding claim 1-25 and 28 being rejected under 35 U.S.C. §101 have been fully considered but they are not persuasive.
Applicant argues that the claims have been amended to recite specific hardware elements and the processing and interaction executed by these hardware elements which integrate any abstract idea into a practical application by improving the functioning of a computer and the relevant technological field. Specifically, it is argued that by adopting the specific hardware and data architecture which prepares and stores the fixed provision order information for each segmentation in the storage in advance, the claims eliminate the need for dynamic, continuous calculations and reduce processing load and computation burden on the server device.
In response, the specification does not describe this problem or that the hardware and data architecture provide this improvement. As discussed in the instant rejection, the hardware and data architecture are descried at a high level of generality and used in their ordinary capacity to perform the abstract idea such that these limitations are determined to mere instructions to apply an abstract idea under MPEP §2106.05(f).
Applicant's arguments filed July 23, 2026 regarding claim 1-25 and 28 being rejected under 35 U.S.C. §102/103 have been fully considered but they are not persuasive.
Applicant argues that Minturn or Nazem do not teach “the storage is configured to store therein… provision order information prepared in advance that defines order of providing the plurality of contents corresponding to the segmentation and corresponding to a respective degree of the health risk of the target customer. Specifically, it is argued Nazem discusses that the provision order information is dynamically prepared and constantly updated and is specific to a user, not a segmentation.
In response, the claims do not define what “prepared in advance” is in reference to. In Nazem, the list including display items identified in the order in which each item should be displayed (i.e. provision order information) is prepared based on a user’s current profile and may be updated when a user views the displayed items, construed as the list being prepared in advance of displaying the display items.
Regarding the argument pertaining to the provision order information being specific to the user and not a segmentation, this is an argument against the references individually and one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986). Minturn discloses providing predetermined content based on a determined user ranking (i.e. segmentation). When modified by Nazem, the content would also include provision order information correlated to the same ranking.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/DEVIN C HEIN/Examiner, Art Unit 3686
