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 claims filed on February 12, 2024 for the application filed February 12, 2024 which claims priority to a foreign application filed on August 13, 2021. Claims 1-27 are currently pending and have been examined.
Claim Objections
Claims 21 are objected to because of the following informalities: Claim 21 recited “am age” which should recite “an age”. Appropriate correction is required.
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 1-27 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 1-27 are directed towards a information providing method (i.e. a process), 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 26 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 claim 1 is identified as:
An information providing method comprising:
acquiring personal data of a target customer;
determining a segmentation to which the target customer belongs, based on the 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; and
providing health information that corresponds to the determined segmentation to the target customer,
the personal data comprising a plurality of pieces of unique data on the target customer,
at least one of the plurality of pieces of unique data being health data that reflects a health condition of the target customer,
the plurality of segmentations being classified corresponding to degrees of the health condition, and
each of the segmentations being correlated with health information prepared in advance corresponding to the health condition.
The abstract idea (identified in bold) recited in claim 26 is identified as:
An information providing method comprising:
preparing in advance a plurality of contents to be presented to a customer, and provision order information that defines order of providing the plurality of contents corresponding to a degree of a health risk of the customer;
acquiring risk data that indicates a degree of a health risk of a target customer; and
providing the plurality of contents in order that corresponds to the degree of the health risk of the target customer based on the risk data and the provision order information.
The identified limitations of the abstract idea of claims 1 and 26 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 health information based in a predetermined order based on predetermined degrees of health conditions as determined based on personal data, which at its core is a the human activity of providing information to a customer based on a determine health condition classification.
The identified limitation of “determining a segmentation to which the target customer belongs, based on the 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” fall within the subject matter grouping of mental processes as this can be performed in the human mind using observations, evaluations, judgments and opinions
Accordingly, claims 1 and 26 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.
Accordingly, claims 1 and 26 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. After evaluation, there are no identified additional elements and the combination of elements is not sufficient to amount to significantly more than the judicial exception.
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 2-24 and 27 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, 1-27 are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
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 6 and 9-11 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 6 recites the limitation "potential health condition". There is insufficient antecedent basis for this limitation in the claims.
Claims 9, 10, 11 recites the limitation "potential health information". There is insufficient antecedent basis for this limitation in the claims.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-3, 5, 8, 10-11 and 25 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Minturn (U.S. Pub. No. 2019/0088159).
Regarding claim 1, Minturn discloses an information providing method comprising:
acquiring personal data of a target customer (Claim 1, collecting a variety of self-reported subjective and somewhat objective input data from a participant, such as: answers to a Well-Being 10-Point Ranked Questionnaire, self-reported test results of physiological or lab data submitted via a smart phone, tablet, kiosk, a special App or a Secure Internet Transmission that the participant has submitted or experienced. Also see paragraphs [0052].);
determining a segmentation to which the target customer belongs, based on the 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 [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 segments/ranks a participant into class corresponding to a degree of a health condition, such as a danger, poor, fair, good or excellent class/segment of cardio-Diastolic health condition. Also see paragraph [0078] discussing that the criterion for rating and ranking is stored in a database, construed as prepared in advance.); and
providing health information that corresponds to the determined segmentation to the target customer (Figs. 3A-5F show that a participant is provided with health information based on the rating a ranking, such as a rating of 7 and the ranking of “good” corresponds to the health information depicted in Fig. 3A.) ,
the personal data comprising a plurality of pieces of unique data on the target customer (Paragraph [0052]),
at least one of the plurality of pieces of unique data being health data that reflects a health condition of the target customer (Paragraph [0052]),
the plurality of segmentations being classified corresponding to degrees of the health condition (Figs. 3A-5F), and
each of the segmentations being correlated with health information prepared in advance corresponding to the health condition (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. Also see Figs 3A-5F.).
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 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 a displaying device, 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 8, Minturn further discloses wherein the potential 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 potential health information 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 potential health information 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 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 4 and 7 are rejected under 35 U.S.C. 103 as being unpatentable over Minturn (U.S. Pub. No. 2019/0088159) in view of Kawai et al. (U.S. Pub. No. 2016/0335402).
Regarding claim 4, Minturn further discloses, wherein and a proposal relating to the service and/or the product that suit(s) the health condition in the determined segmentation class, together with the health information, is further provided (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.).
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 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 potential 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 potential 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 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 potential 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 potential 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 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 potential health information 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 potential health information 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 plurality of pieces of unique 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 plurality of pieces of unique 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 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 plurality of pieces of unique 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 plurality of pieces of unique 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 plurality of pieces of unique 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 plurality of pieces of unique 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 plurality of pieces of unique 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 Wiard et al. (U.S. Pub. No. 2017/0146386).
Regarding claim 15, Minturn further discloses wherein the plurality of pieces of unique data on the target customer comprise: 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 plurality of pieces of unique data on the target customer comprise 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 a plurality of pieces of unique 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 plurality of pieces of unique 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 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 plurality of pieces of unique 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 plurality of pieces of unique data on the target customer comprise: 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 plurality of pieces of unique data on the target customer comprise: 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 plurality of pieces of unique data on the target customer comprise: 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 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 plurality of pieces of unique data on the target customer comprise: 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 plurality of pieces of unique data on the target customer comprise: 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 the presence or the 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 the presence or the 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 Janket et al. (Salivary Immunoglobulins and Prevalent Coronary Artery Disease).
Regarding claim 23, Minturn further discloses wherein the plurality of pieces of unique 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 plurality of pieces of unique 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.
Claims 26-27 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 26 Minturn discloses information providing method comprising:
preparing in advance a plurality of contents to be presented to a customer,Paragraph [0078], quantifiable well-being and optimal wellness databases. 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. Also see figs. 3A-5F which show predetermined content for participants based their rating and ranking (i.e. risk) of a health condition.);
acquiring risk data that indicates a degree of a health risk of a target customer (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.).; and
providing the plurality of contentsFigs. 3A-5F show that a participant is provided with health information based on the rating a ranking.).
Minturn does not appear to explicitly disclose preparing provision order information that defines order of providing the plurality of contents; or that the contents are provided in 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 prepare provision order information that defines order of providing a plurality of contents; and provide the contents in 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 method of Minturn to prepare provision order information that defines order of provide a plurality of contents and providing the contents in 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 27 Minturn further discloses wherein the risk data is data indicating a segmentation selected from a plurality of segmentations each representing a class that corresponds to at least a degree of a health condition based on personal data of the target customer and a classification criterion that is prepared in advance (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 segments/ranks a participant into class corresponding to a degree of a health condition, such as a danger, poor, fair, good or excellent class/segment of cardio-Diastolic health condition. Also see paragraph [0078] discussing that the criterion for rating and ranking is stored in a database, construed as prepared in advance.),
the personal data comprises a plurality of pieces of unique data on the target customer (Paragraph [0052]),
at least one of the plurality of pieces of unique data is health data that reflects a health condition of the target customer (Paragraph [0052]),
the plurality of segmentations are classified corresponding to degrees of the health condition (Figs. 3A-5F), and
each of the segmentations is correlated with health information prepared in advance corresponding to the health condition (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. Also see Figs 3A-5F.).
Conclusion
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/DEVIN C HEIN/Examiner, Art Unit 3686