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 .
DETAILED ACTION
This action is in reference to the communication filed on 3 JUL 2025.
Claims 16-17, 23, 26-33, 35-37, 39-42 are pending and examined.
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 16-17, 23, 26-33, 35-37, 39-42 rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. As explained below, the claim(s) are directed to an abstract idea without significantly more.
With respect to claims 16-17, 23, 26-33, 35-37, 39-42 the independent claims 16, 33, each recite a process which is a statutory category of invention.
With respect to claims 16-17, 23, 26-33, 35-37, 39-42, the independent claims (claims 16, 33, 38) are directed, in part, to: measuring weight of a body to generate measured weight change data over a given timespan for the body; performing an analysis to generate a measured change in fat mass over the given timespan for the body; generating a measurement based efficiency parameter value using the measured weight change data and the measured change in fat mass; receiving the measurement based efficiency parameter value…; for a subsequent timespan, receiving energy consumption data and weight change data for the body; generating an estimated efficiency parameter…; generating…comprising a diet efficiency indicator for feedback of diet performance, wherein the diet efficiency indicator is based on….and defined at last in part with respect to muscle loss and muscle gain…receiving input as to a meal for consumption by the body, and responsive to the input generating a feedback signal for the body based at least in part on the diet performance trend” These claim elements are considered to be abstract ideas because they are directed to a method of organizing human activity which include managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions). Determining or considering a body’s efficiency parameter is management of a personal behavior. Further, the claims are directed to a mental process which includes concepts performed in the human mind (including an observation, evaluation, judgment, opinion). Receiving data and using it to generate an efficiency parameter and an output of said parameter involves observation, evaluation, judgement. Further, the claims as amended recite a mathematical concept in the efficiency indicator being based on (presumably) a relationship to a value, i.e. a mathematical relationship, formula, equation, or calculation. If a claim limitation, under its broadest reasonable interpretation, covers managing personal behaviors , then it falls within the “method of organizing human activity” grouping of abstract ideas. Further, if a claim covers concepts performed in the human mind, then it falls within the “mental processes” grouping of abstract ideas. If a claim recites mathematical relationships, then it falls within the “mathematical concepts” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim recites additional elements – Claims 16 includes the use of a smart phone with a display, and generating a graphic render able via a graphical user interface of a display, and rendering said graphic via a graphical interface, with claim 33 including a system and a processor, and both claims have been amended to recite a weight scale that “performs an electrical resistance analysis”. The smart phone/generation of a graphic interface/display thereon common to claims 16, 33, are at best insignificant extra solution activity to the judicial exception (see MPEP 2106.05G). The processor, memory, and computer readable medium in claims 33 are recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using a generic computer component (see MPEP 2106.05f). Examiner finds no improvements to the functioning of the computer elements nor to any other technology or technical field to any of the mobile device and/or scale and associated elements (See MPEP 2106.05a), and at best finds only a general link between the use of the judicial exception(s) identified above and any technological environment or field of use (see MPEP 2106.05h). As per the scale itself, Examiner again does not find anything beyond mere instructions to apply the exception using a generic computer component (see MPEP 2106.05f). Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The independent claims are additionally directed to claim elements: Claim 16 includes the use of a smart phone with a display, and generating a graphic renderable via a graphical user interface of a display, and rendering said graphic via a graphical interface, with claim 33 including a system and a processor, and both claims have been amended to recite a scale that performs an electrical resistance analysis of the body. When considered individually, the processor, memory and compute readable medium in claims 33, only contribute generic recitations of technical elements to the claims. It is readily apparent, for example, that the claim is not directed to any specific improvements of these elements. Examiner looks to Applicant’s specification in:
[fig 1 and related text]
As shown, a device 190 can include one or more processors 192, memory 194 accessible to at least one of the one or more processors 192, power 195 (e.g., a battery, a solar cell, a power outlet, etc.) and one or more interfaces 196.
At [0125] :
As an example, a device may be a mobile device that includes one or more network interfaces for communication of information. For example, a mobile device may include a wireless network interface (e.g., operable via IEEE 802.11, ETSI GSM, 5G, BLUETOOTH, satellite, etc.). As an example, a mobile device may include components such as a main processor, memory, a display, display graphics circuitry (e.g., optionally including touch and gesture circuitry), a SIM slot, audio/video circuitry, motion processing circuitry (e.g., accelerometer, gyroscope), wireless LAN circuitry, smart card circuitry, transmitter circuitry, GPS circuitry, and a battery. As an example, a mobile device may be configured as a cell phone, a tablet, etc. As an example, a method may be implemented (e.g., wholly or in part) using a mobile device. As an example, a system may include one or more mobile devices.
At [0109]:
FIG. 12 also shows instruction blocks 1293, 1295 and 1297, which can be computer-readable storage media instructions (e.g., a computer-program product, etc.), which can be stored in a non-transitory medium or media that is not a carrier wave nor a signal and executable by one or more processors, etc. For example, the computing system 1300 of FIG. 13 (e.g., and/or the device 190 of FIG. 1, etc.), can include such instructions for performing a method, a portion of a method, etc.
At [0063]
As an example, a method, device, assembly, system, etc., may utilized and/or may include one or more types of machinery (e.g., a spreadsheet, computer program, personal activity tracker, mobile phone app, smart watch, standalone “smart” weight scale, etc.), which may allow a user to manually and/or automatically enter (e.g., estimated and/or measured) measurement quantities of a) weight change, b) activity level (measured in e.g. calories per unit time) and c) consumed energy in a given period (measured e.g. in calories).
At [069]
As an example, a “smart” weight scale can include one or more types of circuitry that can provide for output of DE. For example, a smart weight scale can be configured where information other than weight can be entered/estimated through additional information (possibly pre-provided, like sex, age, activity level, diet profile) provided by a user (e.g., via a user interface, with keys, touchscreen, voice commands, etc.). Such a scale may then provide an estimate of DE. As an example, a smart scales may include a network interface or network interfaces (e.g., BLUETOOTH, WIFI, etc.)… as an example, if weight change can be estimated by other means (e.g. manual readings from “dumb” weight scales, “gut feeling”, empirical tables, etc.)
These passages, as well as others, makes it clear that the invention is not directed to a technical improvement. Any additional elements are disclosed in functional terms only – the disclosure surrounding the scale mechanism is applicable to either a smart scale or a dumb/manual scale. When the claims are considered individually and as a whole, the additional elements noted above, appear to merely apply the abstract concept to a technical environment in a very general sense – i.e. a generic computer receives information from another generic computer, processes the information and then sends information back. The most significant elements of the claims, that is the elements that really outline the inventive elements of the claims, are set forth in the elements identified as an abstract idea. The fact that the generic computing devices are facilitating the abstract concept is not enough to confer statutory subject matter eligibility.
Dependent claims 17, 23, 26-32, 35-37, 39-42 are not directed any additional abstract ideas and are also not directed to any additional non-abstract claim elements than those identified above. Rather, these claims offer further descriptive limitations of elements found in the independent claims and addressed above – such as the data used to calculate one or more values, mathematical calculations, and as well as the types of data collected, inferred or displayed. While these descriptive elements may provide further helpful context for the claimed invention these elements do not serve to confer subject matter eligibility to the invention since their individual and combined significance is still not heavier than the abstract concepts at the core of the claimed invention.
Claim Rejections - 35 USC § 102
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 (i.e., changing from AIA to pre-AIA ) 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 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.
Claim(s) 16-19, 23, 24, 26-33, 35-38 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Baarman et al (US 20150093725 A1, hereinafter Baarman).
In reference to claim 16, 33, 38:
Baarman teaches: A method comprising, (claim 16), a system comprising a processor, a memory operatively coupled to the processor, and processor executable instructions stored in the memory to instruct the system (at least [fig 9, 10 and related text]), one or more computer readable media comprising processor executable instructions executable (at least [086]) to cause a system to (claim 33),
Measuring weight of a body using a scale to generate measured weight change data over a given timespan for the body (at least [fig 5 and related text including 057] scale 110: “For an initial period of time (e.g., a week), the weight of the user is determined on a periodic basis, such as on a daily basis, and the user wears the personal device 10. The weight of the user may be determined using a scale, such as the scale 110, which automatically reports the user's weight to a component within the system 100, such as the personal device 10 or the external server 150.”)
Performing an electrical resistance analysis of the body using the scale to generate a measured change in fat mass over the given timespan for the body (at least [fig 4 and related text] “…the biometric tracking circuitry 16 may include bio-impedance measurement circuitry 34. The biometric tracking circuitry 16 may include bio-resonance measurement circuitry in addition to our alternative to the bio-impedance measurement circuitry 34. The bio-impedance measurement circuitry 34 or bio-resonance measurement circuitry, or both, may enable the device to sense information related to a body composition of the user. Based on this body composition information, the processor 28, or another component, may make a determination regarding Fat Mass and Fat Free Mass.” At [058] “The system 100 may also track a variety of additional characteristics or obtain additional information related to the user during the initial period, including tracking one or more of body composition (e.g., FM/FFM ratio), BMI (Body Mass Index),” – i.e. the FM/FFM in fig 4 is bio-impedance, which is conducted for the initial period);
Generating a measurement based efficiency parameter value using the measured weight change and the measured change in fat mass (at least [057-065] during the initial period, the user’s information is used to estimate energy expenditures/effects thereof – i.e. efficiency, and at [064] this information is used to determine a plan for the user based off the prediction from the initial monitoring period);
Receiving the measurement based efficiency parameter value via mobile device (at least [fig 5 and related text] the information is sent to either smart phone 130, wearable device 10, or computer 120 via connectivity hub 140).
For a subsequent timespan receiving energy consumption and weight change data for a body via a smart phone (at least [fig 3A/3B and related text] during the “dieting” phase, after the initial period, at 316 and on, the system re-determines adherence to the program, recommends continue/change program. [009] “…b) measuring the user's caloric expenditure and change in body composition or body mass during the user's participation in the weight loss program…” at [0041] “As discussed below, the system and method of the present invention can include measurements of one or more values. These values can include for example caloric expenditure, caloric intake, body mass, body composition, body mass index, ratio of fat mass to fat-free mass, heart rate, height, weight, temperature, and a change over time to any of the foregoing.”);
generating an estimated efficiency parameter value using the received data, wherein the estimated efficiency parameter depends on a difference of an amount of water in two different types of body tissues of the body, wherein the two different types of body tissue of the body comprise muscle and fat (at least [012] “…the system may determine the ratio of fat mass ("FM") to fat-free mass ("FFM") using bio-impedance sensors or other devices capable of providing such information. The system may collect or otherwise obtain additional information that may be relevant to making accurate predictions of weight loss or change in body composition that may be useful in setting a healthy and realistic diet objective for the user…hydration sensor that may be used to make more accurate measurements of body composition.” See also [061-066, fig 15 and related text] discussion of efficiency calculations and/or a score: “The system may monitor the user to determine a more efficient or optimal ratio and timing between energy intake and energy expenditure to achieve a target weight.” See also [048-050, 082] bio impedance sensors measure the to determine body composition; see figure 1 and related text for discussion of smartphone 130) ; and
generating a graphic renderable via a graphical user interface of a display of the mobile device, wherein the graphic comprises a diet efficiency indicator for feedback of a diet performance trend, wherein the diet efficiency indicator is based on the measurement based efficiency parameter value and the estimated efficiency parameter value and defined at least in part with respect to fat loss and fait gain and defined at least in part with respect to muscle loss and muscle gain (at least [fig 6, 7 and related text] Ffm/FM values, current weight, with the FFM ratio corresponding to fat free mass levels, at [041, 061-067] “For example, to "measure" a caloric expenditure includes directly or indirectly determining an actual caloric expenditure or an estimated caloric expenditure, optionally in conjunction with a method for determining adherence with a weight loss program. As also used herein, a "measured" value includes at least one of the actual value and the estimated value. For example, a measured caloric expenditure includes an actual caloric expenditure or an estimated caloric expenditure as determined either directly or indirectly, optionally in conjunction with a method for determining adherence with a weight loss program.” - see additional paragraphs cited for discussion of efficiency/the ratio of tissue types, see also [fig 15 and related text] for discussion of expenditure and weight as in EE/EI) ; and
rendering the graphic via the graphical user interface to the display of the mobile device (at least [figs 6, 7 and related text] various graphical interfaces of a user’s activities as compared to the user’s weight, and FFM/FM ratio).
Receiving input via the mobile device as to a meal for consumption by the body (at least [fig 5 and related text] “the personal device 10 may be part of a larger system (or network) of products or components that collect information about user activities, such as diet, exercise and other factors that may be relevant to health and well-being. By collecting this information, the system may be able to assist a user in making choices that improve health and well-being. It is well known that by tracking consumption of food, water, and nutrition and activity, we can get a better picture of our health needs”) ; and
Responsive to the input, generating a feedback signal for the body based at least in part on the diet performance trend (at least [fig 5, 9 and related text] “ The recipe and replacements database 554 may be a database containing a collection of recipes, as well as substitute ingredients that might be useful in following a specific diet regimen. For example, the database may provide substitute ingredients that provide a low-sodium recipe or a low-fat recipe. This database 554 may provide data to the recipe recommender system 506. For example, the recipe recommender system 506 may interact with the recipe and recommender database 554 each time that it makes a recommendation…In this embodiment, the DNA predisposition assessment device 556 is configured to assess a user's DNA predisposition and make recommendations intended to address those predispositions. For example, the device 556 may assess family history of heart disease and may recommend actions that could help the user lower blood pressure or cholesterol. For example, the system may recommend an exercise regimen and/or a diet that is low in fat or low in cholesterol.” See also [fig 6 and related text] “The user interface available on the remote device 130 may include information about the user such as a breakdown of the user's activity for the day 620, 630, including for example energy expended while running, standing, sitting, or being seated. The user interface may indicate to the user energy expended during their activities using metaphorical comparisons 640 to other activities, such as eating a quarter cheeseburger,”).
In reference to claim 17:
Baarman further teaches: comprising receiving additional data, generating another efficiency parameter value, and comparing the efficiency parameter values to determine a trend his middle panel is realized when the user selects weight on the dashboard. (at least [067, 071] “The panel on the right is realized when a user is prompted to click on the data (shown as a star). Based on trends in the data, the system recommends an action. In this example, the system realized the user was losing weight, but this weight loss was attributed to FFM and not FM so the system recommends that the user try protein powder.” At [041, 086] “…expected change in body composition or body mass based on the health program selected by the individual and based on the individual's gender, age, height, weight, and other factors. The modification can include a change in the dietary regimen, including one or more new or modified meal plans and/or recipes having a caloric content tailored to assist the individual in meeting his or her health goals.”)
In reference to claim 23:
Baarman further teaches: transmitting the at least the efficiency parameter via a network interface to a computing system wherein the computing system utilizes at least the efficiency parameter to train a predictive machine learning model (at least [fig 16 and related text] “As shown in FIG. 16, the model may be utilized to develop a predicted weight for the user over time. The predicted weight loss shown in FIG. 16 is computed based on the model described in connection with FIGS. 1 and 2. Once the EI for the target weight loss is calculated, the system 100 may provide a corresponding recommendation to the user. As in the example recommendation outlined above, the recommendation may include a caloric restriction of 500 kcal/day to achieve the target weight loss.”).
In reference to claim 26:
Baarman further teaches: comprising adjusting one or more variables for the two different types of body tissues of the body (at least [061-068] FM/FFM are tracked separately and recommendations are updated: “f a large proportion of weight loss is associated with a loss in FFM, or the user dips below a healthy BMI, the system may provide a recommendation to attempt to correct the situation.” See also [fig 18 and related text]).
In reference to claim 27:
Baarman further teaches: comprising generating a hydration indicator using at least the efficiency parameter value (at least [076-079] average hydration levels of a user determined via a plurality of means).
In reference to claim 28:
Baarman further teaches: wherein the body is subject to a diet and wherein the efficiency parameter value is indicative of an efficiency of the diet (at least [067] efficiency of the diet/ratio, see at least [009-012, 059] “For example, an objective may be a diet objective selected based on ideal weight. Additionally or alternatively, the objectives may be related to achieving one or more of a target BMI and a target Fat Mass or body composition. As an example, the system 100 may recommend a healthy weight loss target, such as losing 20 pounds in 4 months, based on factors or characteristics related to the user, including average daily energy expenditure, age, gender, BMI, and body composition.”).
In reference to claim 29:
Baarman further teaches: wherein the graphic comprises a diet efficiency dimension and a build efficiency dimension (at least [fig 7 and related text as well as 070-072] “This healthy ratio may be used to set a maximum threshold for the faction of weight loss that can occur as FFM. If the system 100 determines that an individual is losing too much FFM using the equation shown, it may provide a recommendation accordingly, such as to increase protein intake to overcome the loss in FFM.” – i.e. the system indicates that the efficiency of the diet is such that the FFM is decreasing, and therefore the build efficiency needs to be increased by addition of the protein).
In reference to claim 30:
Baarman further teaches: wherein the diet efficiency dimension is defined at least in part with respect to fat loss and fat gain and wherein the build efficiency dimension is defined at least in part with respect to muscle loss and muscle gain (at least [fig 7 and related text, as well as 070-072] “In one embodiment, the system 100 may provide a recommendation based on a determination that the progression of weight loss associated with a user includes a loss of FFM considered excessive or to exceed a threshold. In this way, the system 100 may try to ensure the user maintains a healthy ratio of FFM to FM. As shown in FIG. 18, the system may calculate a threshold ratio between loss of FFM and weight loss. The plot shows an example of what may be considered healthy weight loss of FFM as a fraction of total weight loss (WL) over time on a diet. This healthy ratio may be used to set a maximum threshold for the faction of weight loss that can occur as FFM. If the system 100 determines that an individual is losing too much FFM using the equation shown, it may provide a recommendation accordingly, such as to increase protein intake to overcome the loss in FFM…the system recommends an action. In this example, the system realized the user was losing weight, but this weight loss was attributed to FFM and not FM so the system recommends that the user try protein powder.”).
In reference to claim 31:
Baarman further teaches: wherein the graphic comprises at least one region representative of a state of a health of the body (at least [fig. 6 and related text] “The user interface 610, 710 may also provide information related to the user's activities, including a daily activity log similar to the log shown in FIG. 11, which shows the relative amount of time spent performing an activity throughout the day. For example, between 8-10 a.m., the daily activity log indicates the user spends a greater amount of time sitting than walking or standing over a period of two or more days. As shown in FIG. 12, the daily activity log may provide similar information but using a pie chart instead. The daily activity log may also break down the distribution of food intake based on times of the day, such as breakfast, lunch, dinner, and snack times. If the user understands these interactions they can look back on historical data and optimize the ratio of intake and expenditure to best adhere to the prescribed health management program. FIG. 13 illustrates yet another manner of conveying and analyzing the user's food intake and source of nutrition in relation to times of the day. By understanding this ratio and how energy expenditure interacts with this, the user can better optimize their health management program.”).
In reference to claim 32:
Baarman further teaches: wherein the graphic comprises an unhealthy weight loss region and a healthy weight loss region (at least [fig 14 and related text] “The table or database of information may also account for the likelihood of user adherence such that, for example, the system 100 may avoid providing unachievable or unhealthy recommendations or recommendations that the user would consider unreasonable. For example, the database may utilize information based on a healthy BMI for a given height and weight, such as those identified in FIG. 14. The recommendations, such as a caloric restriction, may be based on prior clinical determinations. For example, a caloric restriction recommendation may not result in a diet of less than 1200 kcal for a woman, or less than 1800 kcal for a man. As another example, the target BMI objective may be selected to be above a weight considered healthy for the user.”).
In reference to claim 35:
Baarman further teaches the scale (at least [fig 5 and related text] “…one of the devices in the system 100 is a scale 110 capable of weighing the user, and communicating the weight of the user to another device of the system 100…”) see [fig 4 and related text’] for applicability of circuitry).
In reference to claim 36:
Baarman further teaches: wherein the graphic comprises a graphic of a gauge (see at least [fig 6 and related text] element 620).
In reference to claim 37:
Baarman further teaches: wherein the diet efficiency indicator is represented by a needle of a gauge (at least [fig 6, 12, and related text] both figures show a progress gauge, with the progress to date reflected in the “needle”).
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 (i.e., changing from AIA to pre-AIA ) 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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 39-42 is/are rejected under 35 U.S.C. 103 as being unpatentable over Baarman in view of Edman et al (US 20180000391 A1, hereinafter Edman).
In reference to claim 39, 41:
Baarman teaches all the limitations above, as well as providing feedback to the user, but does not explicitly teach biofeedback. Edman however, does teach: Wherein the feedback signal for the body comprises a biofeedback signal (at least [0104] “Such recommendations may be in the forms of text messages, alert sounds, mechanical (vibrations) or combinations of these forms of delivery. These recommendations may include detailed instructions or recommendations for activity, etc. or simply serve as alerts or reminders at certain time points throughout the day.” At [099] “Display units may receive this data directly or indirectly from one or more comparators. Displays may include visual images, textual messages, sounds and synthetic voices, or mechanical signals, e.g. vibrations.” Edman and Baarman are analogous as both references disclose a means of monitoring a user’s fitness goals/progress. As Baarman teaches providing the same type of information to the user, one of ordinary skill in the art would find the additional means of biofeedback as taught by Edman to be obvious. Edman teaches that such alerts provide support to a user reaching his/her fitness goals, and “Supportive actions providing oversight in diet management while not being directly observed by others is an advantageous feature of such embodiments of the present invention.” (see 0104). As such the incorporation of biofeedback would have been obvious to one of ordinary skill.
In reference to claim 40, 42:
Baarman teaches all the limitations above, as well as providing feedback to the user, but does not explicitly teach biofeedback. Edman however, does teach: wherein the biofeedback signal comprises one or more of an electrical stimulus and a mechanical stimulus (at least [0104] “Such recommendations may be in the forms of text messages, alert sounds, mechanical (vibrations) or combinations of these forms of delivery. These recommendations may include detailed instructions or recommendations for activity, etc. or simply serve as alerts or reminders at certain time points throughout the day.” At [099] “Display units may receive this data directly or indirectly from one or more comparators. Displays may include visual images, textual messages, sounds and synthetic voices, or mechanical signals, e.g. vibrations.” Edman and Baarman are analogous as both references disclose a means of monitoring a user’s fitness goals/progress. As Baarman teaches providing the same type of information to the user, one of ordinary skill in the art would find the additional means of biofeedback as taught by Edman to be obvious. Edman teaches that such alerts provide support to a user reaching his/her fitness goals, and “Supportive actions providing oversight in diet management while not being directly observed by others is an advantageous feature of such embodiments of the present invention.” (see 0104). As such the incorporation of biofeedback would have been obvious to one of ordinary skill.
Response to Arguments
Applicant’s arguments as filed on 3 JUL 2025 are noted.
Applicant’s remarks on page 7 are noted, Examiner respectfully notes that the processing errors referenced are addressed separately from this office action.
Applicant’s further remarks on page 7 are noted, Examiner respectfully disagrees in view of the rejection maintained above. Examiner makes reference to the prior final rejection as mailed 10/11/2024.
As per Applicant’s remarks on page 8, Examiner respectfully submits that the Amendments as filed were addressed in the prior rejection with regard to the 101 and 103 rejection(s) previously raised and still maintained in this action.
Applicant’s remarks regarding compact prosecution are noted.
Applicant’s remarks on page 9 are noted. Examiner does not find analogy between the pending claims and the Diehr case. Specifically, Diehr was found eligible for effecting a transformation of an article to a different thing state or thing, i.e. from raw uncured rubber to a cured precise product. Examiner finds that while measurements are being taken, there is no transformation effected by the claims as written.
Further on page 9, Applicant discusses the “opening” of the press in Diehr in analogy to the “feedback system”, and the “diet performance trend” as more complex than the Arrhenius equation. Examiner respectfully disagrees, at least as the diet performance trend is not currently claimed as an algorithm or equation. Examiner also notes that Applicant appears to be relying on claiming the human body’s automatic operation as analogous to the controlled “opening the press automatically” in Diehr – this is not found to be an analogous comparison as the opening in Diehr was specifically controlled by the equation and the collected data as applied, versus Applicant’s own admission that the body’s own operation in producing the feedback signal itself.
Applicant’s remarks regarding Alice/SAP/Financial markets on page 10 are noted, Examiner agrees that the presence of an abstract idea itself does not preclude eligibility. Examiner respectfully submits that eligibility in Diehr was found in the practical application of a transformation.
Applicant discusses the streamlined analysis on page 11; at the outset, Examiner respectfully disagrees that no abstract idea exists in the pending claims. The elements identified are considered as additional elements, which are not found to be sufficient to support a conclusion of a practical application. Applicant’s discussion of the electrical resistance analysis is noted; Examiner respectfully submits that the price or prevalence of such a device does not preclude the idea that the technology itself is an application of the technology TO the abstract idea. Applicant goes on to note several locations that might have access to said machine, using which the abstract idea(s) identified in the claims may be “applied.” The problem of “eating while traveling/out” is not itself a technical problem for the purposes of the analysis, even if the solution provided is technical. For example, people have long tracked food and exercise input data manually in order to affect positive change.
As per Applicant’s final analogy to Diehr, on page 12, Examiner again respectfully submits that the opening of the press in Diehr was found to recite eligible subject matter as a transformation occurred as a result. Examiner does not find a similar analogy to a transformation in the present claims.
Applicant summarizes the rejections present in the non-final action mailed on 3 FEB 2025 on page 12.
Examiner notes Applicant’s remarks regarding the length of claim 1, Examiner assumes Applicant intended to reference claim 16 as claim 1 is indicated as canceled.
As per Applicant’s discussion regarding Baarman, Applicant appears to be arguing a measurement of the difference in water in types of tissue. Examiner reiterates that as claimed, a value “depends” on this measurement, not that such a measurement is actually taken. This efficiency parameter is not quantified or measured in any way, nor is the value of the water in the tissue(s). Examiner notes the Baarman discloses bioimpedance sensors, which use a combination of electricity and water to measure the conductivity of a tissue – a more hydrated tissue, i.e. a higher water content, will conduct electricity more easily, i.e. less resistance. The measured impedance is used to estimate the amount of water in the tissue/body. Such sensors are commonly used in wearable devices for a hydration status.
Applicant’s remarks as per the FM and FFM including water are noted, Examiner suggests incorporating language from [0027] if that is believed to be differentiating.
Applicant’s remarks regarding Baarman on page 14 are noted, Examiner respectfully disagrees in view of the discussion above. Similarly, Examiner respectfully disagrees with the remarks regarding the including of the Edman reference.
Relevant Prior Art
The following prior art not cited is made a part of the record:
US 20140164611 A1 to Molettiere et al, discloses a means of tracking activity and/or diet progress across a plurality of devices.
US 20170143268 A1 to Kovacs et al, discloses a user specific health, weight, and activity monitoring system providing a plurality of interactive interfaces.
Conclusion
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/KATHERINE . KOLOSOWSKI-GAGER/
Primary Examiner
Art Unit 3687
/KATHERINE KOLOSOWSKI-GAGER/Primary Examiner, Art Unit 3687