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 .
Notice to Applicant
Receipt of Applicant’s Amendment filed May 7, 2026 is acknowledged.
Response to Amendment
Claims 1, 2, and 19 have been amended. Claims 12, 15, and 21 have not been modified. Claims 3-11, 13-14, 16-18, and 20 have been cancelled. Claims 22-25 have been added. Claims 1, 2, 12, 15, 19, and 21-25 are pending and are provided to be examined upon their merits.
Response to Arguments
Applicant’s arguments filed May 7, 2026 have been fully considered but they are not persuasive. A response is provided below.
Applicant argues 35 U.S.C. §112 Rejections and Claim Interpretation, pg. 7 of Remarks:
Regarding the prior §112b rejection, Examiner acknowledges Applicant amendment and argument and withdraws the rejection.
Regarding the claim interpretation, Examiner disagrees with Applicant assertion that the body composition obtaining section is the controller/CPU. [0049] of Applicant specification recites: “The control unit 36 is a control device that controls the input unit 32, the memory unit 35, the output unit 33, the weight measuring section 361, the bioelectrical impedance measuring section 362, the body composition measuring section 363, and the positioning information determination section 364. The control unit 36 is equipped with a central processing section (CPU). The control unit 36 is connected to each section and controls the operation of each section. The control unit 36 realizes the functions of each part by executing the body composition measurement program of the present embodiment stored in the memory unit 35. The functions of each part may be realized by individual hardware such as an ASIC (Application Specific Integrated Circuit).”
As recited by Applicant specification, the controller/CPU controls each of the sections, which may be embodied by a program stored in the memory unit. Thus, Examiner maintains the interpretation that each section, as claimed, may not be hardware, and may instead be software enacted by the controller/CPU.
Examiner further notes that a claim interpretation under §112(f) is not a rejection.
Applicant argues 35 U.S.C. §101 Rejections, pg. 7 of Remarks:
Applicant argues that seeing where a person is currently positioned against a population of similarity situated people is a technical challenge. Examiner respectfully disagrees. The identified problem is abstract in nature and is not one rooted in technology. Seeing how an individual’s body measurements compare to other people addresses an abstract problem of statistics.
Applicant further notes that automatically updating populations and adding a user’s values to a plurality of populations cannot be done mentally. However, the claims were not characterized under mental processes.
Applicant further argues that the whether the additional elements are well-understood, routine, or conventional is irrelevant to the consideration under Step 2A. Thus, the outlined improvement to the claimed devices should not be dismissed as the performance is not conventional. As noted in previous actions as well as above, Examiner maintains that the performance outlined in the claims is directed to an improvement in the abstract idea of seeing where a person is positioned compared to a population, not to any specific, technical improvement to the devices recited in the claim. An improvement to an abstract idea does not amount to an improvement to technology or a technical field (see MPEP § 2106.05(a)(III) stating “it is important to keep in mind that an improvement in the abstract idea itself (e.g. a recited fundamental economic concept) is not an improvement in technology. For example, in Trading Technologies Int’l v. IBG, 921 F.3d 1084, 1093-94, 2019 USPQ2d 138290 (Fed. Cir. 2019), the court determined that the claimed user interface simply provided a trader with more information to facilitate market trades, which improved the business process of market trading but did not improve computers or technology.”).
Furthermore, the art provided for the devices being well-understood, routine, or conventional is to address Step 2B, not 2A.
Regarding the amendment of a “bioelectrical impedance measurement” to further specify a particularly described machine, Examiner acknowledges the amendment. However, such an amendment does not provide any specific, technical improvements to bioelectrical/body composition measurement devices. As claimed, any generic body composition analyzer may be applied to perform an insignificant extra-solution activity of gathering data; MPEP 2106.05(g).
Examiner notes that if there are any improvements to how a body composition analyzer functions, such as technical improvements to the sensors that cause the analyzer to function better than others currently available, that may be a consideration for the 35 U.S.C. 101 rejection.
Applicant argues 35 U.S.C. §103 Rejections, pg. 8 of Remarks:
Applicant argues that Sato in view of Chetham does not teach the amended claim of “add[ing] the measured values to a plurality of corresponding populations to which each user belongs”, as Chetham only contemplates adding a user’s values to one population. Examiner respectfully disagrees.
Chetham recites: [0429], “the process can also be used to add data to the normal population table. This is achieved by performing the measurement process outlined above, and in the event that the subject does not suffer from oedema, for example if surgery has not yet been performed, importing the data into the normal population table. This can be performed in addition to adding the measurements to the subject record, so that measurements collected from a healthy individual can be used for subsequent longitudinal analysis and/or as a normal population reference.”
Sato recites: [0074], “. A number of such regression formulae are set according to, e.g., genders and ages, and an appropriate regression formula is automatically selected and retrieved based on the gender and age set in setting of physical data in STEP S1. For example, when the subject is a male of 30's, a regression formula prepared by using normal adult males as a population is read in.” [0078], “Thereby, for example, when the subject is an athlete, determination of the body type of the subject as an athlete can be made by selecting an appropriate object for comparison from objects for comparison which are classified according to the types of sports.”
Sato in view Chetham may not explicitly teach wherein the measured values are added to the plurality of populations to which the user belongs; however, the noted features would have been prima facie obvious to one of ordinary skill in the art at the time of the invention in view of the teaching of Sato and Chetham based on the duplication of parts rationale (see In re Harza, MPEP 2144.04(VI)(B)). Sato teaches a plurality of populations to which the user belongs (genders and ages [0074] and type of sports played [0078]), and Chetham teaches adding patient values to a population to which the user belongs ([0429] above). The application of the recited method to add measured values to a plurality of populations produces no new and unexpected result which would result in patentable significance over the teaching of Sato and Chetham, as it would be obvious to one of ordinary skill in the art to add the measured values as taught by Chetham to the plurality of populations as taught by Sato; the addition of measured values to a plurality of patient populations is simply a duplication of the existing functionality of adding a patient’s values to a population.
Thus, Examiner maintains the 35 U.S.C. 103 rejection.
Claim Objections
Claims 1-2, 12, 15, 19 , and 21-25 are objected to because of the following informalities:
Claim 1 should be amended to recite: “wherein each of the body composition analyzers obtaining section are”.
Claims 2, 12, 15, 21-22, and 24 are objected to by virtue of their dependency on claim 1.
Both last “and” in claims 1 and 19 have been removed by amendment. However, each “and” should be restored.
Claims 2, 12, 15, and 21-25 are objected to by virtue of their dependency on claims 1 and 19.
Appropriate correction is required.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitations uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitations are:
“a body composition obtaining section” in claims 1, 2, and 19
“a positioning information determination section” in claims 1, 12, 15, 19, and 21
[0053], "The positioning information determination section 364 may be provided in any of the terminal devices such as the server 20, the body composition analyzer 30, the tablet computer, the smartphone, and the like.”
“an evaluation section” in claim 19
[0087], "The positioning information determination section 364 of the above-described system is one example of the evaluation section.”
Because these claim limitations are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph they are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof. For the purposes of examination, the Examiner interprets the determination and evaluation sections to be any software program or module that contains computer-executable instructions to perform the function of each unit.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 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 1-2, 12, 15, 19, and 21-25 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.
Subject Matter Eligibility Criteria – Step 1:
The claims recite subject matter within a statutory category as a machine (1-2, 12, 15, 19, and 21-25). Accordingly, claims 1-2, 12, 15, 19, and 21-25 are all within at least one of the four statutory categories.
Subject Matter Eligibility Criteria – Step 2A – Prong One:
Regarding Prong One of Step 2A of the Alice/Mayo test, the claim limitations are to be analyzed to determine whether, under their broadest reasonable interpretation they “recite” a judicial exception or in other words whether a judicial exception is “set forth” or “described” in the claims. MPEP §2106.04(II)(A)(1). An “abstract idea” judicial exception is subject matter that falls within at least one of the following groupings: a) certain methods of organizing human activity, b) mental processes, and /or c) mathematical concepts. MPEP §2106.04(a).
The Examiner has identified system claim 1 and system claim 19 as the claims that represent the claimed invention for analysis.
Claim 1:
A body composition measurement system, comprising:
a plurality of body composition analyzers, each body composition analyzer including a main unit on which a user stands for measuring a weight of the user;
a bioelectrical impedance measurement section configured to measure bioelectrical impedance of the user standing on the main unit; and
a body composition obtaining section configured to obtain a measured value of a body composition of a user standing on the main unit, based on the measured bioelectrical impedance;
a server configured to store a plurality of populations of body composition with different categories; and
a positioning information determination section configured to determine positioning information, which is information indicating the position of the measured value of the user in a population;
wherein the positioning information is at least one of the following: body fat percentage, muscle mass, bone mass, basal metabolism, and visceral fat,
wherein each of the body composition analyzers is configured to send the obtained measured value to the server,
wherein the server is configured to receive the measured value from the plurality of body composition analyzers and add the measured values to a plurality of corresponding populations to which the user belongs, automatically in response to receiving the measured values,
thereby adding the measured values obtained by the plurality of body composition analyzers to the population in the server,
wherein the server is configured to generate a deviation value formula or a deviation value table from each population of different categories, each population comprising a plurality of measured values of body composition, to specify a relationship between the measured values of the body composition and the positioning information,
wherein the positioning information determination section is configured to determine the positioning information of the measured value of the body composition of the user by using the deviation value formula or the deviation value table derived from the population in a selected category,
wherein categories of the population include categories relating to at least one of age, gender, region, country, race, sport species, occupation, and company.
These above limitations, under their broadest reasonable interpretation, cover performance of the limitation as mathematical concepts. The claim elements are directed towards “generat[ing] a deviation value formula or a deviation value table from each population of different categories,…, to specify a relationship between the measured values of the body composition and the positioning information” and “using the deviation value formula or the deviation value table derived from the population in a selected category”, which is directed towards mathematical formula as well as mathematical relationships.
These above limitations, under their broadest reasonable interpretation, also cover performance of the limitation as certain methods of organizing human activity. The claim elements are directed towards “obtain[ing] a measured value of body composition of a user” in order “to determine positioning information, which is information indicating the position of the measured value of the body composition of the user in a population”, which is analogous to diagnosing or determining a patient’s health status in comparison to others. Diagnosing or determining a patient’s health status falls under the abstract concept of managing personal behaviors of people, as evaluating health based on data is regularly performed by doctors for their patients. It is important to note that the examples provided by the MPEP such as social activities, teaching, and following rules or instructions are provided as examples and not an exclusive listing. Additionally, the claim is also directed towards “select[ing] at least one among the plurality of populations”, which is an action performed by the user.
Accordingly, the claim recites an abstract idea.
Claim 19:
A body composition measurement system comprising:
a plurality of body composition analyzers, each body composition analyzer including a main unit on which a user stands for measuring a weight of the user;
a bioelectrical impedance measurement section configured to measure bioelectrical impedance of the user standing on the main unit, each of the body composition analyzers configured to obtain a measured value of body composition of a user standing on the main unit based on the measured bioelectrical impedance;
a server configured to store a plurality of populations of body composition with different categories; and
an evaluation section configured to select at least one among the plurality of populations with different categories and to obtain an evaluation of the measured value with respect to body composition in the selected population;
wherein the evaluation is at least one of the following: body fat percentage, muscle mass, bone mass, basal metabolism, and visceral fat,
wherein the body composition analyzer is configured to send the obtained measured value to the server, and
wherein the server is configured to receive the measured value from the plurality of body composition analyzers and add the measured values to the plurality of populations to which the user belongs automatically in response to receiving the measured values, thereby adding the measured values obtained by the plurality of body composition analyzers to the population in the server,
wherein the server is configured to generate a deviation value formula or a deviation value table from each population of different categories, each population comprising a plurality of measured values of body composition, to specify a relationship between the measured values of the body composition and the positioning information,
wherein the positioning information determination section is configured to determine the positioning information of the measured value of the body composition of the user by using the deviation value formula or the deviation value table derived from the population in a selected category,
wherein categories of the population include categories relating to at least one of age, gender, region, country, race, sport species, occupation, and company.
These above limitations, not in bold, under their broadest reasonable interpretation, cover performance of the limitation as mathematical concepts. The claim elements are directed towards “generat[ing] a deviation value formula or a deviation value table from each population of different categories,…, to specify a relationship between the measured values of the body composition and the positioning information” and “using the deviation value formula or the deviation value table derived from the population in a selected category”, which is directed towards mathematical formula as well as mathematical relationships.
These above limitations, under their broadest reasonable interpretation, also cover performance of the limitation as certain methods of organizing human activity. The claim elements are directed towards “obtain[ing] a measured value of body composition of a user” in order “to obtain an evaluation of the measured value with respect to body composition in the selected population”, which is analogous to diagnosing or determining a patient’s health status in comparison to others. Diagnosing or determining a patient’s health status falls under the abstract concept of managing personal behaviors of people, as evaluating health based on data is regularly performed by doctors for their patients. Additionally, the claim is also directed towards “select[ing] at least one among the plurality of populations”, which is an action performed by the user.
Accordingly, the claim recites an abstract idea.
Subject Matter Eligibility Criteria – Step 2A – Prong Two:
Regarding Prong Two of Step 2A of the Alice/Mayo test, it must be determined whether the claim as a whole integrates the idea into a practical application. As noted at MPEP §2106.04 (ID)(A)(2), it must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.” MPEP §2106.05(I)(A).
Additional elements in the claims:
plurality of body composition analyzers (1,19); main unit (1,19); bioelectrical impedance measurement section (1,19); server (1,19); body composition obtaining section (1-2,19); positioning information determination section (1, 12, 15,21-22); evaluation section (19,23); display (24-25)
The body composition analyzers and corresponding main units are taught at a high level of generality. [0003] of Applicant specification recites: “Conventionally, body composition analyzers are known to obtain measured values of body composition based on information such as height, weight, age, and gender, and bioelectrical impedance of each part of the human body obtained by measurement.” No specific, technical improvements are being made to the technology of body composition analyzers.
Any computing devices that would be able to perform the method are taught at a high level of generality such that the claim elements amounts to no more than mere instructions to apply the exception using any generic component capable of performing the claim limitations. The Examiner cites [0081] of Applicant specification: “The information processing device may be, for example, an information processing device such as a smartphone or a tablet computer.” No specific, technical improvements are being made to the technology of computing devices as generic computing devices are simply applied to perform the abstract idea.
The server is also taught at a high level of generality such that the claim elements amount to no more than mere instructions. The Examiner cites [0016] of Applicant specification: “The positioning formula or positioning table may be generated by a terminal device such as a body composition analyzer, a tablet computer, a smartphone, or the like, or may be generated by a server computer.” No specific, technical improvements are being made to the technology of server devices.
The body composition obtaining section, positioning information determination section, and evaluation section are software stored within and executed by the computing device to perform the abstract functions described in the Prong One analysis. Thus, instant claims seem analogous to "apply it" (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f).
The bioelectrical impedance measurement section is also taught at a high level of generality. [0050] recites: “The bioelectrical impedance measurement section 362 obtains the value of the bioelectrical impedance by measurement. The bioelectrical impedance measurement section 362 obtains the value of bioelectrical impedance by passing a weak current through the body via the electrodes 341L and 341R for current flow and the electrodes 342L and 342R for measurement shown in Fig. 2.” No specific, technical improvements are being made to bioelectrical measurement sensors as generic electrodes are applied to perform the insignificant extra-solution activity of gathering data; MPEP 2106.05(g).
Displays are also taught at a high level of generality. [0050] recites: “The output unit 33 is, for example, a display panel equipped with an LCD (Liquid Crystal Display) or an OLED (Organic Light Emitting Diode).” No specific, technical improvements are being made to display technologies as generic display devices are applied to perform the insignificant extra-solution of outputting data.
Looking at the additional elements as an ordered combination adds nothing that is not already present when looking at the elements taken individually. For instance, there is no indication that the additional elements, when considered as a whole with the limitations reciting the at least one abstract idea, reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, apply or use the above-noted judicial exception with a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of 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 does not integrate the abstract idea into a practical application of the abstract idea. MPEP §2106.05(I)(A) and §2106.04(IID)(A)(2).
The remaining dependent claim limitations not addressed above fail to integrate the abstract idea into a practical application as set forth below:
Claim 2: This claim recites wherein each body composition obtaining section is configured to obtain the measured value by measuring the body composition of the user; which teaches the body composition obtaining sections at a high level of generality such that they are only applied to measure body composition and perform an insignificant extra-solution activity of obtaining data from.
Claim 12: This claim recites wherein the positioning information determination section is configured to select a population of a category to which the user belongs; which only serves to limit the abstract idea of selecting the population.
Claims 15: This claim recites wherein the positioning information determination section is configured to select the population of a category selected by the user; which only serves to limit the abstract idea of selecting the population.
Claim 21: This claim recites wherein the positioning information determination section is configured to select any one population from a plurality of populations including populations to which the user does not belong; which only serves to limit the abstract idea of selecting the population.
Claim 22: This claim recites wherein the positioning information determination section is configured to determine positioning information indicating the position of the measured value of the body composition of the user in a population to which the user does not belong; which further teaches an abstract idea of determining position of a user within a population.
Claim 23: This claim recites wherein the evaluation section is configured to obtain the evaluation of the measured value of the user in a population to which the user does not belong; which further teaches an abstract idea of determining position of a user within a population as well as an insignificant extra-solution activity of gathering data.
Claims 24 and 25: These claims recite the system further comprising a display configured to display the positioning information; which teaches the displays at a high level of generality such that they are only applied to perform an insignificant extra-solution activity of outputting data.
Subject Matter Eligibility Criteria – Step 2B:
Regarding Step 2B of the Alice/Mayo test, representative independent claims do not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for reasons the same as those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application.
These claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to discussion of integration of the abstract idea into a practical application, the additional elements amount to no more than mere instructions to apply an exception, add insignificant extra-solution activity to the abstract idea, and generally link the abstract idea to a particular technological environment or field use. Additionally, the additional limitations, other than the abstract idea per se, amount to no more than limitations which:
Amount to elements that have been recognized as activities in particular fields
(Receiving or transmitting data over a network, e.g., using the Internet to gather data,
MPEP §2106.05(d)(II)(i); Storing and retrieving information in memory, Versata Dev.
Group, MPEP §2106.05(d)(II)(iv)).
References are provided below to demonstrate that a body composition analyzer that communicates with a remote server/computing device has been known for a long period of time:
[0176] of Ozawa (US 20130172775): “The condition information processing apparatus 100B is a personal computer, or a mobile terminal apparatus such as a smart phone, which is capable of communicating with the body composition analyzer 200 through a communication network NET such as the Internet or a LAN.”
[0488] of Chetham (US 20170209066): “The above examples have been described on the basis of the selection of the preferred impedance measurements and analysis being performed by a first processing system 10 provided as part of the measuring device 1. However, this is not essential and that any or all of the functionality described could be performed by a processing system that is remotely located to the measuring device 1, as will now be described with respect to FIG. 13.”
[0489] further recites: “a base station 1300 is coupled to a number of measuring devices 1, and a number of end stations 1303 via a communications network 1302, such as the Internet, and/or via communications networks 1304, such as local area networks (LANs), or wide area networks (WANs).”
Dependent claims recite additional subject matter which, as discussed above with respect to integration of the abstract idea into a practical application, amount to invoking computers as a tool to perform the abstract idea. Dependent claims recite additional subject matter which amount to limitations consistent additional subject matter which amount to limitations consistent with the additional elements in the independent claims (such as claims 2, 12, 15, and 21-25, additional limitations which amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields, claims 2, 12, 15, and 21-25, e.g., performing repetitive calculations, Flook, MPEP §2106.05(d)(II)(ii); claims 2, 12, 15, and 21-25, e.g., storing and retrieving information in memory, Versata Dev. Group, MPEP §2106.05(d)(II)(iv). 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 improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation.
Therefore, whether taken individually or as an ordered combination, claims 1-2, 12, 15, 19, and 21-25 are nonetheless rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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.
Claims 1-2, 12, 15, 19, 21, and 24-25 are rejected under 35 U.S.C. 103 as being unpatentable over Sato (US 20050080352) in view of Chetham (US 20170209066).
Regarding claim 1, Sato teaches a body composition measurement system, comprising:
a body composition analyzer including a main unit on which a user stands for measuring a weight of the user ([0068], “As shown in FIG. 1, a body type determining apparatus 10 comprises a scale-incorporated bioelectrical impedance meter 20 and a control box 40 which are connected to each other via electric cables 30.” [0069], “it incorporates a body weight measuring unit 25, and the body weight measuring unit 25 as well as the voltage measuring circuit 24 are connected to an A/D converter 26 which converts an analog signal into a digital signal.”);
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a bioelectrical impedance measurement section configured to measure bioelectrical impedance of the user standing on the main unit ([0068], “on the top surface of the bioelectrical impedance meter 20, constant current applying electrodes 21a and 21b and voltage measuring electrodes 22a and 22b are provided.”); and
a body composition obtaining section configured to obtain a measured value of body composition of a user standing on the main unit, based on the measured bioelectrical impedance ([0061-0062], “the impedance measuring unit measures a bioelectrical impedance, the calculation unit calculates a body mass index and a body composition index based on the personal physical data and the bioelectrical impedance” [0083], “the scale-incorporated bioelectrical impedance meter 20”). The Examiner interprets the impedance measuring unit, which receives measurements that are used to calculate body composition, to encompass the body composition obtaining section. Furthermore, the impedance meter is incorporated in a weight scale, which a patient must stand on to be measured.
a server configured to store a plurality of populations of body composition with different categories ([0070], “the HIGH-FREQUENCY constant current circuit 23 and the A/D converter 26 are connected to a CPU 45 which controls calculations, determinations, display and storage of various data in the control box 40 via the electric cables 30. The CPU 45 is connected to a data input unit 41 which inputs data by means of the operation keys, a display unit 42 which displays the results of calculations and determinations in numerical values or as graphs, a storage unit 43 which stores a number of regression formulae preset as determination standards and various data, and a calculation unit 44 which sets body type determination standards by calculations of various data and calculations of normal values by the regression formulae and determines body types.” [0074], “For example, when the subject is a male of 30's, a regression formula prepared by using normal adult males as a population is read in.” [0078], “Further, by setting a determination standard prepared by using top athletes as a population for each type of sports”). The Examiner notes that one of ordinary skill in the art would recognize that a CPU is an integral part of any server device.
And a positioning information determination section configured to determine positioning information, which is information indicating the position of the measured value of the body composition of the user in a population ([0043], “The standard setting unit sets a number of body type determination standards for different objects for comparison. Thus, a more appropriate body type determination standard for a subject can be selected, and more accurate determination can be made. Further, the physical condition of a subject with respect to a variety of objects for comparison can be known.” [0077], “While the regression formulae prepared by using normal adult males as a population are automatically selected as determination standards according to gender and age in the above STEPS S6 and S7, a number of determination standards set for more specific objects for comparison can be selected manually in STEP S9. The objects for comparison are classified by, for example, races, the types of athletes or ages which are more specific than notions such as elderly people and children, and regression formulae corresponding to these objects for comparison are stored in the storage unit 43.”). The Examiner interprets comparing the measured values with the determination standard, which is determined using a regression formula for a specific population, to encompass positioning information, as it would determine a person’s position compared to a standard athlete, for example.
wherein the positioning information is at least one of the following: body fat percentage, muscle mass, bone mass, basal metabolism, and visceral fat ([0073], “a body fat percentage, a body fat mass and a lean mass are calculated from the above measured body weight and bioelectrical impedance value”),
wherein the positioning information determination section is configured to determine the positioning information of the measured value of the body composition of the user by using the deviation value formula or the deviation value table derived from the population in a selected category ([0043], “The standard setting unit sets a number of body type determination standards for different objects for comparison. Thus, a more appropriate body type determination standard for a subject can be selected, and more accurate determination can be made. Further, the physical condition of a subject with respect to a variety of objects for comparison can be known.” [0029], “The body type determining unit sets a proper range or abnormal range of a body type based on at least one statistical technique out of the percentile value of the body composition index based on the normal value, or standard deviation of the body composition index based on the normal value, or Z score based on the standard deviation and determines a body type by a range to which the body composition index belongs.” [0077], “While the regression formulae prepared by using normal adult males as a population are automatically selected as determination standards according to gender and age in the above STEPS S6 and S7,”). The Examiner interprets comparing the measured values with standard deviations of indexes, which is determined using a regression formula for a specific population, to encompass positioning information derived from a deviation value formula or table, as it would determine a person’s position compared to a standard athlete, for example. Furthermore, in Fig. 4 above, a user can extrapolate one’s position within a population by identifying their body composition index value.
wherein categories of the population include categories relating to at least one of age, gender, region, country, race, sport species, occupation, and company ([0074], “. A number of such regression formulae are set according to, e.g., genders and ages, and an appropriate regression formula is automatically selected and retrieved based on the gender and age set in setting of physical data in STEP S1. For example, when the subject is a male of 30's, a regression formula prepared by using normal adult males as a population is read in.” [0078], “Thereby, for example, when the subject is an athlete, determination of the body type of the subject as an athlete can be made by selecting an appropriate object for comparison from objects for comparison which are classified according to the types of sports.”).
Sato does not teach a plurality of body composition analyzers, wherein each of the body composition obtaining section is configured to send the obtained measured value to the server, and wherein the server is configured to receive the measured value from the plurality of body composition analyzers and add the measured values to a plurality of corresponding populations to which each user belongs automatically in response to receiving the measured values, thereby adding the measured values obtained by the plurality of body composition analyzers to the population in the server, and wherein the server is configured to generate a deviation value formula or a deviation value table from each population of different categories, each population comprising a plurality of measured values of body composition, to specify a relationship between the measured values of the body composition and the positioning information.
However, Sato in view of Chetham does teach a plurality of body composition analyzers (Chetham, [0489], “a base station 1300 is coupled to a number of measuring devices 1” [0303], “At step 140 the measuring device, operates to digitise and sample the voltage and current signals across the subject S, allowing these to be used to determine instantaneous bioimpedance values for the subject S at step 150.”),
wherein each of the body composition analyzers are configured to send the obtained measured value to the server (Chetham, [0492], “Once impedance measurements have been collected, these are transferred via the external interface 23 to the end station 1303” [0509], “the base station 1300 includes a processing system 1310, coupled to a database 1311... It will be appreciated that the processing system 1310 may therefore be a server or the like.” [0496], “the end station 1303 can effectively perform the tasks to performed by the first processing system 10 in the examples throughout the specification.” [0488], “any or all of the functionality described could be performed by a processing system that is remotely located to the measuring device 1, as will now be described with respect to FIG. 13.”). Examiner notes that as the end system may perform all functionality of a processing system, which is a base station that comprises a server, it would be obvious to one of ordinary skill in the art that the end system may also be a server that performs all functions of the base station.
wherein the server is configured to receive the measured values from a plurality of the body composition obtaining sections of a plurality of devices and add the measured values to a plurality of corresponding populations to which each user belongs automatically in response to receiving the measured values, thereby adding the measured values obtained by the plurality of devices to the population in the server (Chetham, [0429], “the process can also be used to add data to the normal population table. This is achieved by performing the measurement process outlined above, and in the event that the subject does not suffer from oedema, for example if surgery has not yet been performed, importing the data into the normal population table. This can be performed in addition to adding the measurements to the subject record, so that measurements collected from a healthy individual can be used for subsequent longitudinal analysis and/or as a normal population reference.” Sato, [0074], “. A number of such regression formulae are set according to, e.g., genders and ages, and an appropriate regression formula is automatically selected and retrieved based on the gender and age set in setting of physical data in STEP S1. For example, when the subject is a male of 30's, a regression formula prepared by using normal adult males as a population is read in.” [0078], “Thereby, for example, when the subject is an athlete, determination of the body type of the subject as an athlete can be made by selecting an appropriate object for comparison from objects for comparison which are classified according to the types of sports.”). Sato in view Chetham may not explicitly teach wherein the measured values are added to the plurality of populations to which the user belongs; however, the noted features would have been prima facie obvious to one of ordinary skill in the art at the time of the invention in view of the teaching of Sato and Chetham based on the duplication of parts rationale (see In re Harza, MPEP 2144.04(VI)(B)). Sato teaches a plurality of populations to which the user belongs (genders and ages [0074] and type of sports played [0078]), and Chetham teaches adding patient values to a population to which the user belongs ([0429] above). The application of the recited method to add measured values to a plurality of populations produces no new and unexpected result which would result in patentable significance over the teaching of Sato and Chetham, as it would be obvious to one of ordinary skill in the art to add the measured values as taught by Chetham to the plurality of populations as taught by Sato; the addition of measured values to a plurality of patient populations is simply a duplication of the existing functionality of adding a patient’s values to a population.
and wherein the server is configured to generate a deviation value formula or a deviation value table from each population of different categories, each population comprising a plurality of measured values of body composition, to specify a relationship between the measured values of the body composition and the positioning information (Chetham, [0465], “In addition to simply displaying the absolute reference value determined, it is also possible to display standard deviations as shown at 1059 to thereby provide an indication of the degree of variation from the base line.” [0464], “An example of the use of a subject's specific reference value is shown in FIG. 11F. In this instance the reference value is based on R.sub.0 as shown at 1058. Accordingly, it can be seen that variation of the value R.sub.0 compared to the reference is indicative of oedema. The generation of a report by comparison to normal population data will be performed in a similar manner.” [0463], “reference values can also be displayed based either on the normalised population reference or subject specific reference.”).
Sato in view Chetham are considered analogous to the claimed invention because they are in the field of body composition systems. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Sato with Chetham for the advantage of “add[ing] data to the… population table” (Chetham; [0429]).
Regarding claim 2, Sato in view of Chetham teaches the body composition measurement system of claim 1. Sato further teaches wherein each body composition obtaining section is configured to obtain the measured value by measuring the body composition of the user ([0061-0062], “the impedance measuring unit measures a bioelectrical impedance, the calculation unit calculates a body mass index and a body composition index based on the personal physical data and the bioelectrical impedance,”).
Regarding claim 12, Sato in view of Chetham teaches the body composition measurement system of claim 1. Sato further teaches wherein the positioning information determination section is configured to select a population of a category to which the user belongs ([0077], “While the regression formulae prepared by using normal adult males as a population are automatically selected as determination standards according to gender and age in the above STEPS S6 and S7, a number of determination standards set for more specific objects for comparison can be selected manually in STEP S9. The objects for comparison are classified by, for example, races, the types of athletes or ages which are more specific than notions such as elderly people and children, and regression formulae corresponding to these objects for comparison are stored in the storage unit 43.”).
Regarding claim 15, Sato in view of Chetham teaches the body composition measurement system of claim 1. Sato further teaches wherein the positioning information determination section is configured to select a population of a category selected by the user ([0077], “While the regression formulae prepared by using normal adult males as a population are automatically selected as determination standards according to gender and age in the above STEPS S6 and S7, a number of determination standards set for more specific objects for comparison can be selected manually in STEP S9. The objects for comparison are classified by, for example, races, the types of athletes or ages which are more specific than notions such as elderly people and children, and regression formulae corresponding to these objects for comparison are stored in the storage unit 43.”).
Regarding claim 19, Sato teaches a body composition measurement system comprising:
a body composition analyzer including a main unit on which a user stands for measuring a weight of the user ([0068], “As shown in FIG. 1, a body type determining apparatus 10 comprises a scale-incorporated bioelectrical impedance meter 20 and a control box 40 which are connected to each other via electric cables 30.” [0069], “it incorporates a body weight measuring unit 25, and the body weight measuring unit 25 as well as the voltage measuring circuit 24 are connected to an A/D converter 26 which converts an analog signal into a digital signal.”);
a bioelectrical impedance measurement section configured to measure bioelectrical impedance of the user standing on the main unit ([0068], “on the top surface of the bioelectrical impedance meter 20, constant current applying electrodes 21a and 21b and voltage measuring electrodes 22a and 22b are provided.”);
each of the body composition analyzers configured to obtain a measured value of body composition of a user standing on the main unit based on the measured bioelectrical impedance([0061-0062], “the impedance measuring unit measures a bioelectrical impedance, the calculation unit calculates a body mass index and a body composition index based on the personal physical data and the bioelectrical impedance,” [0083], “the scale-incorporated bioelectrical impedance meter 20”). The Examiner interprets the impedance measuring unit, which receives measurements that are used to calculate body composition, to encompass the body composition obtaining section. Furthermore, the impedance meter is incorporated in a weight scale, which a patient must stand on to be measured.
a server configured to store a plurality of populations of body composition with different categories ([0070], “the HIGH-FREQUENCY constant current circuit 23 and the A/D converter 26 are connected to a CPU 45 which controls calculations, determinations, display and storage of various data in the control box 40 via the electric cables 30. The CPU 45 is connected to a data input unit 41 which inputs data by means of the operation keys, a display unit 42 which displays the results of calculations and determinations in numerical values or as graphs, a storage unit 43 which stores a number of regression formulae preset as determination standards and various data, and a calculation unit 44 which sets body type determination standards by calculations of various data and calculations of normal values by the regression formulae and determines body types.” [0074], “For example, when the subject is a male of 30's, a regression formula prepared by using normal adult males as a population is read in.” [0078], “Further, by setting a determination standard prepared by using top athletes as a population for each type of sports”). The Examiner notes that one of ordinary skill in the art would recognize that a CPU is an integral part of any server device.
And an evaluation section configured to select at least one among the plurality of populations with different categories and to obtain an evaluation of the measured value with respect to body composition in the selected population ([0071], “FIGS. 4 and 5 are graphs illustrating regression formulae which are statistically determined from measured data obtained by using normal adult males as a population. FIG. 4 is a graph illustrating the relationship between FMI and BMI which represents a determination standard for a body fat mass, and FIG. 5 is a graph illustrating the relationship between LMI and BMI which represents a determination standard for a lean mass.” [0077], “While the regression formulae prepared by using normal adult males as a population are automatically selected as determination standards according to gender and age in the above STEPS S6 and S7, a number of determination standards set for more specific objects for comparison can be selected manually in STEP S9. The objects for comparison are classified by, for example, races, the types of athletes or ages which are more specific than notions such as elderly people and children, and regression formulae corresponding to these objects for comparison are stored in the storage unit 43.”). The Examiner interprets Fig. 4, below, to be an example of an evaluation of the measured value with respect to body composition in a selected population.
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wherein the positioning information is at least one of the following: body fat percentage, muscle mass, bone mass, basal metabolism, and visceral fat ([0073], “a body fat percentage, a body fat mass and a lean mass are calculated from the above measured body weight and bioelectrical impedance value”),
wherein the positioning information determination section is configured to determine the positioning information of the measured value of the body composition of the user by using the deviation value formula or the deviation value table derived from the population in a selected category ([0043], “The standard setting unit sets a number of body type determination standards for different objects for comparison. Thus, a more appropriate body type determination standard for a subject can be selected, and more accurate determination can be made. Further, the physical condition of a subject with respect to a variety of objects for comparison can be known.” [0029], “The body type determining unit sets a proper range or abnormal range of a body type based on at least one statistical technique out of the percentile value of the body composition index based on the normal value, or standard deviation of the body composition index based on the normal value, or Z score based on the standard deviation and determines a body type by a range to which the body composition index belongs.” [0077], “While the regression formulae prepared by using normal adult males as a population are automatically selected as determination standards according to gender and age in the above STEPS S6 and S7,”). The Examiner interprets comparing the measured values with the determination standard, which is determined using a regression formula for a specific population, to encompass positioning information, as it would determine a person’s position compared to a standard athlete, for example. Furthermore, in Fig. 4 above, a user can extrapolate one’s position within a population by identifying their body composition index value.
wherein categories of the population include categories relating to at least one of age, gender, region, country, race, sport species, occupation, and company ([0074], “. A number of such regression formulae are set according to, e.g., genders and ages, and an appropriate regression formula is automatically selected and retrieved based on the gender and age set in setting of physical data in STEP S1. For example, when the subject is a male of 30's, a regression formula prepared by using normal adult males as a population is read in.” [0078], “Thereby, for example, when the subject is an athlete, determination of the body type of the subject as an athlete can be made by selecting an appropriate object for comparison from objects for comparison which are classified according to the types of sports.”).
Sato does not teach a plurality of body composition analyzers, wherein the body composition analyzer is configured to send the obtained measured value to the server, and wherein the server is configured to receive the measured values from the plurality of body composition analyzers and add the measured values to the plurality of populations to which the user belongs automatically in response to receiving the measured values, thereby adding the measured values obtained by the plurality of body composition analyzers to the populations in the server, and wherein the server is configured to generate a deviation value formula or a deviation value table from each population of different categories, each population comprising a plurality of measured values of body composition, to specify a relationship between the measured values of the body composition and the positioning information.
However, Sato in view of Chetham does teach a plurality of body composition analyzers (Chetham, [0489], “a base station 1300 is coupled to a number of measuring devices 1” [0303], “At step 140 the measuring device, operates to digitise and sample the voltage and current signals across the subject S, allowing these to be used to determine instantaneous bioimpedance values for the subject S at step 150.”),
wherein the body composition analyzer is configured to send the obtained measured value to the server ([0492], “Once impedance measurements have been collected, these are transferred via the external interface 23 to the end station 1303” [0509], “the base station 1300 includes a processing system 1310, coupled to a database 1311... It will be appreciated that the processing system 1310 may therefore be a server or the like.” [0496], “the end station 1303 can effectively perform the tasks to performed by the first processing system 10 in the examples throughout the specification.” [0488], “any or all of the functionality described could be performed by a processing system that is remotely located to the measuring device 1, as will now be described with respect to FIG. 13.”),
wherein the server is configured to receive the measured values from a plurality of body composition analyzers and add the measured values to the plurality of populations to which the user belongs automatically in response to receiving the measured values, thereby adding the measured values obtained by the plurality of body composition analyzers to the population in the server (Chetham, [0429], “the process can also be used to add data to the normal population table. This is achieved by performing the measurement process outlined above, and in the event that the subject does not suffer from oedema, for example if surgery has not yet been performed, importing the data into the normal population table. This can be performed in addition to adding the measurements to the subject record, so that measurements collected from a healthy individual can be used for subsequent longitudinal analysis and/or as a normal population reference.” Sato, [0074], “. A number of such regression formulae are set according to, e.g., genders and ages, and an appropriate regression formula is automatically selected and retrieved based on the gender and age set in setting of physical data in STEP S1. For example, when the subject is a male of 30's, a regression formula prepared by using normal adult males as a population is read in.” [0078], “Thereby, for example, when the subject is an athlete, determination of the body type of the subject as an athlete can be made by selecting an appropriate object for comparison from objects for comparison which are classified according to the types of sports.”). Sato in view Chetham may not explicitly teach wherein the measured values are added to the plurality of populations to which the user belongs; however, the noted features would have been prima facie obvious to one of ordinary skill in the art at the time of the invention in view of the teaching of Sato and Chetham based on the duplication of parts rationale (see In re Harza, MPEP 2144.04(VI)(B)). Sato teaches a plurality of populations to which the user belongs (genders and ages [0074] and type of sports played [0078]), and Chetham teaches adding patient values to a population to which the user belongs ([0429] above). The application of the recited method to add measured values to a plurality of populations produces no new and unexpected result which would result in patentable significance over the teaching of Sato and Chetham, as it would be obvious to one of ordinary skill in the art to add the measured values as taught by Chetham to the plurality of populations as taught by Sato; the addition of measured values to a plurality of patient populations is simply a duplication of the existing functionality of adding a patient’s values to a population.
and wherein the server is configured to generate a deviation value formula or a deviation value table from each population of different categories, each population comprising a plurality of measured values of body composition, to specify a relationship between the measured values of the body composition and the positioning information (Chetham, [0465], “In addition to simply displaying the absolute reference value determined, it is also possible to display standard deviations as shown at 1059 to thereby provide an indication of the degree of variation from the base line.” [0464], “An example of the use of a subject's specific reference value is shown in FIG. 11F. In this instance the reference value is based on R.sub.0 as shown at 1058. Accordingly, it can be seen that variation of the value R.sub.0 compared to the reference is indicative of oedema. The generation of a report by comparison to normal population data will be performed in a similar manner.” [0463], “reference values can also be displayed based either on the normalised population reference or subject specific reference.”).
Sato in view Chetham are considered analogous to the claimed invention because they are in the field of body composition systems. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Sato with Chetham for the advantage of “add[ing] data to the… population table” (Chetham; [0429]).
Regarding claim 21, Sato in view of Chetham teaches the body composition measurement system of claim 1. Sato further teaches wherein the positioning information determination section is configured to select any one population from a plurality of populations including populations to which the user does not belong ([0077], “While the regression formulae prepared by using normal adult males as a population are automatically selected as determination standards according to gender and age in the above STEPS S6 and S7, a number of determination standards set for more specific objects for comparison can be selected manually in STEP S9. The objects for comparison are classified by, for example, races, the types of athletes or ages which are more specific than notions such as elderly people and children, and regression formulae corresponding to these objects for comparison are stored in the storage unit 43.” [0079], “when the subject is an elderly person, the body type of the subject can be expressed as muscle age or the like by use of determination based on a standard for the young as well as determination based on a standard for people of the same age as the subject.”). The Examiner notes that an elderly person is not young. Therefore, the ability to show an elderly person’s muscle age with respect to a youthful population exemplifies the above claim limitation.
Regarding claim 24, Sato in view of Chetham teaches the body composition measurement system of claim 1. Sato further teaches further comprising a display configured to display the positioning information ([0070], “a display unit 42 which displays the results of calculations and determinations in numerical values or as graphs”).
Claim 25 is rejected for the same reasons as claim 24, as described above.
Claims 22 and 23 are rejected under 35 U.S.C. 103 as being unpatentable over Sato (US 20050080352) in view of Chetham (US 20170209066) further in view of Duffy (Duffy; Jill E, Site of the Day: Global Fat Scale, 9 Jul 2013, jilleduffy) as evidenced by BBC (BBC, Where are you on the global fat scale?, 12 Jul 2012, BBC).
Regarding claim 22, Sato in view of Chetham teaches the body composition measurement system of claim 1. Sato in view of Chetham does not teach wherein the positioning information determination section is configured to select any one population from a plurality of populations including populations to which the user does not belong.
However, Sato in view of Duffy does teach wherein the positioning information determination section is configured to select any one population from a plurality of populations including populations to which the user does not belong (Sato, [0043], “The standard setting unit sets a number of body type determination standards for different objects for comparison.” Duffy, pg. 1, “You key in your age, sex, height, weight, and country in which you live, and it spits back out your BMI and some stats about how you compare to others in your country and across the world.”). A user may key in/select any population, including those that a user does not belong to. As noted by the Author biography, Duffy lived in India in 2013 when the article was published. Thus, the ability to select any country, not just India, as evidenced by BBC below (red box shows wherein countries such as Chad, Chile, and China to which the author has no connection to may be selected as the reference population), encompasses a functionality that allows a user to select any one population from a plurality of populations including populations to which the user does not belong to. It would be obvious to one of ordinary skill in the art that combining the positioning information determination section as taught by Sato with the functionality of selecting a population that the user does not belong to as taught by Duffy (as evidenced by BBC) would encompass the above claim limitation.
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Sato in view Chetham further in view of Duffy are considered analogous to the claimed invention because they are in the field of patient data analysis. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Sato in view Chetham with Duffy for the advantage of “compar[ing] to others … across the world” (Duffy; pg. 1).
Regarding claim 23, Sato in view of Chetham teaches the body composition measurement system of claim 19. Sato in view of Chetham does not teach wherein the evaluation section is configured to obtain the evaluation of the measured value of the user in a population to which the user does not belong.
However, Sato in view of Duffy does teach wherein the evaluation section is configured to obtain the evaluation of the measured value of the user in a population to which the user does not belong (Sato, [0071], “FIGS. 4 and 5 are graphs illustrating regression formulae which are statistically determined from measured data obtained by using normal adult males as a population. FIG. 4 is a graph illustrating the relationship between FMI and BMI which represents a determination standard for a body fat mass, and FIG. 5 is a graph illustrating the relationship between LMI and BMI which represents a determination standard for a lean mass.” Duffy, pg. 1, “You key in your age, sex, height, weight, and country in which you live, and it spits back out your BMI and some stats about how you compare to others in your country and across the world… I am most similarly sized with women of my age in Niger. If I gain a pound, I'm more like women in Liberia.”). As noted by the Author biography, Duffy is originally from New York and was living in India when the article was published. Examiner submits that Duffy has no obvious connection to Niger or Liberia. Thus, comparison of Duffy’s BMI with countries such as Niger and Liberia encompass an evaluation of the measured value of the user in a population to which the user does not belong. It would be obvious to one of ordinary skill in the art that combining the evaluation section as taught by Sato with the functionality of obtaining an evaluation of the measured value of the user in a population to which the user does not belong as taught by Duffy would encompass the above claim limitation.
Sato in view Chetham further in view of Duffy are considered analogous to the claimed invention because they are in the field of patient data analysis. Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified Sato in view Chetham with Duffy for the advantage of “compar[ing] to others … across the world” (Duffy; pg. 1).
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DAVID CHOI whose telephone number is (571)272-3931. The examiner can normally be reached M-Th:8:30-5:30 ET.
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/D.C./Examiner, Art Unit 3684
/Shahid Merchant/Supervisory Patent Examiner, Art Unit 3684
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