DETAILED ACTION
Remarks
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
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 1-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
STEP 1 = YES: The claimed invention is to a process and product, and thus fall under one of the four statutory categories (Step 1: YES).
STEP 2A, Prong 1 = YES: The claims recite a series of steps which can be practically performed by one or more humans through mental process (i.e., observation, evaluation, judgement, and/or opinion)(see MPEP § 2106.04(a)(2), subsection III), certain methods of organizing human activity (i.e., managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions) (see MPEP § 2106.04(a)(2), subsection II), and/or mathematical concepts (i.e., mathematical relationships, mathematical formulas or equations, mathematical calculations)(see MPEP § 2106.04(a)(2), subsection I). Moreover, the claims recite steps akin to “collecting information, analyzing it, and displaying certain results of the collection and analysis,” where the data analysis steps are recited at a high level of generality such that they could practically be performed in the human mind, which the court in Electric Power Group held to recite a mental process. Electric Power Group v. Alstom, S.A., 830 F.3d 1350, 1353-54, 119 USPQ2d 1739, 1741-42 (Fed. Cir. 2016). This includes a system and method for body-centric analysis of patient health and nutritional status comprising:
… specifies instructions to manually determine and enter body metric measurements for a patient (certain method of organizing human activity: interaction between individuals, including requesting information);
receiving… inputs …, the inputs providing one or more of (i) the body metric for the patient, (ii) pedometer data for the patient, and (iii) physical activity level data for the patient (mental process: observation and evaluation of the requested information; certain method of organizing human activity: interaction between individuals);
populating a personalized risk monitoring profile for the patient by:
calculating anthropometric indicators of central body fat mass by comparing the body metric measurements received at the system with age-group percentiles (mental process: evaluation; mathematical concept: calculation);
determining a physical activity level for the patient using the received pedometer data or physical activity level data or both (mental process: evaluation);
determining a body type based on one or more of: (i) height, (ii) neck circumference, (iii) size, and (iv) waist-to-height ratio for the patient as represented within the body metric measurements received (mental process: evaluation);
calculating a physiological lean body mass and percentage of body fat for the patient (mental evaluation; mathematical concept: calculation);
calculating a target physiological weight for the patient (mental evaluation; mathematical concept: calculation); and
… display the personalized risk monitoring profile for the patient based on the inputs received, determined calculated factors populated into the personalized risk monitoring profile, wherein the personalized risk monitoring profile specifies guidance for the patient to achieve the calculated target physiological weight (certain method of organizing human activity: interaction between individuals, including teaching); and
wherein the personalized risk monitoring profile … further displays one or more of: a complete nutritional status assessment, and a self-monitoring and maintenance assessment, wherein the complete nutritional status assessment is based on a greater number of body metric measurements than the self- monitoring and maintenance (further defines abstract idea identified above, and thus falls under same judicial exception grouping); and
wherein the physical activity level data for the patient includes one or more of: number of daily steps for the patient; a basal metabolism for the patient; a daily energy expenditure (DET) for the patient; medical data for the patient; social data for the patient; dietary history data for the patient; and activity level assessment data for the patient (further defines abstract idea identified above, and thus falls under same judicial exception grouping); and
wherein body metric measurements include one or more of: (i) height, (ii) weight, (iii) neck circumference, (iv) mid-arm circumference, (v) forearm circumference, (vi)wrist circumference, (vii)waist circumference, (viii) abdomen circumference, (ix) hip circumference, (x) median thigh circumference, and (xi) pedometer data (further defines abstract idea identified above, and thus falls under same judicial exception grouping); and
wherein calculating anthropometric indicators based on the body metric measurements includes one or more of: body type indicators, body mass and composition indicators, fat free mass indicators, fat mass indicators, risk factor indicators, and lean mass functionality indicators (further defines abstract idea identified above, and thus falls under same judicial exception grouping); and
wherein the body type includes one or a combination of two or more of: (i) ectomorph, (ii) leptosomic, (iii) mesomorph, and (iv) endomorph biotypes (further defines abstract idea identified above, and thus falls under same judicial exception grouping); and
wherein lean body mass is total body weight minus weight due to body fat mass, wherein lean body mass is adjusted with an assessment for estimating subcutaneous fat (further defines abstract idea identified above, and thus falls under same judicial exception grouping); and
wherein the individual risk monitoring profile is based on one or more risk factors includes: (i) metabolic syndrome risk, (ii) cardiovascular risk, (iii) adiposity-muscle waist-thigh risk, and (iv) neck-height ratio night apnea risk (further defines abstract idea identified above, and thus falls under same judicial exception grouping); and
wherein muscle loss (sarcopenia) is evaluated via a handgrip functional test (further defines abstract idea identified above, and thus falls under same judicial exception grouping); and
wherein patient protein intake is customized to modify the physiological lean body mass (further defines abstract idea identified above, and thus falls under same judicial exception grouping); and
wherein the physiological lean mass estimates a lean mass deficit (further defines abstract idea identified above, and thus falls under same judicial exception grouping);
wherein the target physiological weight represents a weight after losing excess fat to balance physiological lean body mass with physiological fat percentage for a patient (further defines abstract idea identified above, and thus falls under same judicial exception grouping); and
wherein either the patient or a clinician authenticates … and receives … the personalized risk monitoring profile for the patient (further defines abstract idea identified above, and thus falls under same judicial exception grouping).
The steps identified above are akin to organizing human activity, mental processes, and/or mathematical concepts, and thus fall within an enumerated category of abstract ideas. Note that even if most humans would use a physical aid (e.g., pen and paper, a slide rule, or a calculator) to help them complete the recited steps above, the use of such physical aid does not negate the mental nature of these limitations. Therefore, the claims recite an abstract idea (Step 2A, Prong 1: YES).
STEP 2A, Prong 2 = NO: This judicial exception is not integrated into a practical application.
To the extent the claims recite additional elements related to defining a computer environment to implement the abstract idea above (i.e., A system comprising: a memory to store instructions; a processor to execute the instructions stored in the memory; wherein the system is specially configured to execute the instructions stored in the memory via the processor to cause the system to perform operations including: executing instructions at the system to perform the steps identified under Prong 1 as an abstract idea; A method … performed by a system of a host organization having at least a processor and a memory therein to execute instructions, wherein the method comprises: executing instructions at the system to perform the steps identified under Prong 1 as an abstract idea; and Non-transitory computer readable storage media having instructions stored thereupon that, when executed by a system having at least a processor and a memory therein, the instructions cause the system to perform operations including: executing instructions at the system to perform the steps identified under Prong 1 as an abstract idea; and performing steps identified as an abstract idea under Prong 1 at the user device), they are recited at a high level of generality such that they do not amount to a particular machine or technical improvement thereof, nor do they represent an improvement in any other technology. Rather, the generic manner which these additional elements are claimed amount to mere instructions to implement the abstract idea in a computer environment, i.e., field of use, and thus do not integrate the judicial exception into a practical application.
To the extent the claims recite additional elements related to a physical component for providing data collection and data output (i.e., wherein the instructions include transmitting a GUI for display via a user device, wherein the GUI performs steps identified as an abstract idea under Prong 1; wherein the receiving step identified as an abstract idea under Prong 1 is performed at the system, inputs received via the GUI displayed to the user device and transmitted to the system; and using the GUI to display information identified under Prong 1 as an abstract idea, including re-transmitting the GUI to the user-device updated to display;), the claims do not recite limitations that define any particular graphical user interface, or any specific details defining an improvement to how the graphical user interface operates to perform the claimed data gathering and data output steps. Rather, the graphical user interface is merely recited at a high level of generality to achieve the claimed result-based functions of receiving inputs and displaying outputs, the inputs and outputs interpreted as part of the abstract idea under Prong 1 because the information associated with the inputs and outputs could be practically received and conveyed by a human, through mental evaluation and interactions between individuals, using pen and paper or speaking. Moreover, the claimed user device is also recited at a high level of generality, referred to by name alone, to also perform insignificant pre and post solution activity, i.e., data gathering and data output. Neither of the claimed GUI or user device are defined in an unconventional manner or by any other details defining the underlying operations that represent a technical improvement. Therefore, the claimed GUI and user device do not offer meaningful limitations beyond merely defining a generic field of use or technological environment in which to implement the abstract idea. Therefore, these additional elements do not integrate the judicial exception into a practical application.
It should be noted that because the courts have made it clear that mere physicality or tangibility of an additional element or elements is not a relevant consideration in the eligibility analysis, the physical nature of the physical components identified above does not affect this analysis. See MPEP 2106.05(I) for more information on this point, including explanations from judicial decisions including Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 224-26 (2014). Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application and the claim is directed to the judicial exception. Therefore, the claims are directed to an abstract idea (Step 2A, Prong 2: YES).
STEP 2B = NO: The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because as provided under Prong 2, the additional elements are recited at a high level of generality, and for the purpose of insignificant pre and post-solution activity. Moreover, the specification of the instant application further demonstrates that the additional elements are recited for their well-understood, routine and conventional functionality, which refers to elements of the computer system in a manner that indicates that the additional elements are sufficiently well-known that the specification does not need to describe the particulars of such additional elements to satisfy 35 U.S.C. § 112(a)(e.g., see 0048 which states “Embodiments may be provided as a computer program product, or software, that may include a machine-readable medium having stored thereon instructions, which may be used to program a computer system (or other electronic devices) to perform a process according to the disclosed embodiments. A machine-readable medium includes any mechanism for storing or transmitting information in a form readable by a machine (e.g., a computer). For example, a machine-readable (e.g., computer-readable) medium includes a machine (e.g., a computer) readable storage medium (e.g., read only memory ("ROM"), random access memory ("RAM"), magnetic disk storage media, optical storage media, flash memory devices, etc.), a machine (e.g., computer) readable transmission medium (electrical, optical, acoustical), etc.”; see also par. 0299 which states “Certain embodiments of the machine may be in the form of a personal computer (PC), a tablet PC, a set-top box (STB), a Personal Digital Assistant (PDA), a cellular telephone, a
web appliance, a server, a network router, switch or bridge, computing system, or any machine capable of executing a set of instructions (sequential or otherwise) that specify and mandate the specifically configured actions to be taken by that machine pursuant to stored instructions.”). Thus, the written description as indicated above relies on conventional hardware to perform the claimed steps, and thus does not represent a technical improvement. Rather, the additional elements defining the field of use as a computer-implemented environment with a GUI and user device to collect and display information for a user amount to merely automating a manual process based on the lack of technical detail, which the courts have held to be insufficient in showing an improvement in computer-functionality. See Credit Acceptance Corp. v. Westlake Services, 859 F.3d 1044, 1055, 123 USPQ2d 1100, 1108-09 (Fed. Cir. 2017); see also LendingTree, LLC v. Zillow, Inc., 656 Fed. App'x 991, 996-97 (Fed. Cir. 2016) (non-precedential).
Therefore, the claims are not directed to significantly more than the abstract idea (Step 2B: NO).
Therefore, claims 1-21 are not directed to patent eligible subject matter.
Claim Rejections – 35 USC 102 (AIA )
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-5, 8, 10, 12-16, and 18-20 are rejected under 35 U.S.C. 102(a)(1) and (a)(2) as being anticipated by US 2005/0113650 A1 to PACIONE.
Regarding claim 1, 14, and 18, PACIONE teaches:
a system comprising: a memory to store instructions; a processor to execute the instructions stored in the memory; wherein the system is specially configured to execute the instructions stored in the memory via the processor to cause the system to perform operations; a method for body-centric analysis of patient health and nutritional status performed by a system of a host organization having at least a processor and a memory therein to execute instructions; and a non-transitory computer readable storage media having instructions stored thereupon that, when executed by a system having at least a processor and a memory therein, the instructions cause the system to perform operations (Abstract and par. 0152: a nutrition and activity management system is disclosed that monitors energy expenditure of an individual through the use of a body-mounted sensing apparatus; Opening Health Manager web page providing information regarding the user's height, weight, body measurements, body mass index or BMI or any of the identified physiological parameters; par. 0027, 0260: software stored; the data storage device receives the derived data from the processor and retrievably stores the derived data therein; software stored by the sensor device and executed by the processor; software stored by the sensor device and executed by the processor; par. 0078: processors or processing devices can be programmed to perform the functionality);
comprising:
executing instructions at the system for transmitting a GUI for display via a user device, wherein the GUI specifies instructions to manually determine and enter body metric measurements for a patient (par. 0101, 0104, 0258: software stored by the sensor device and executed by the processor; display of certain graphical data output; the program displays how the device should be worn; software stored by the sensor device and executed by the processor; all Figures, Abstract, and par. 0152: measured or derived or manually input physiological contextual parameters are provided; data entry may be in the form of selection from pre-defined lists or general free form text input; opening Health Manager web page may include Body Stats section which may provide information regarding the user's height, weight, body measurements, body mass index or BMI, and vital signs such as heart rate, blood pressure or any of the identified physiological parameters);
receiving, at the system, inputs received via the GUI displayed to the user device and transmitted to the system, the inputs providing one or more of (i) the body metric for the patient, (ii) pedometer data for the patient, and (iii) physical activity level data for the patient (par. 0101, 0104, 0152: display of certain graphical data output; the program displays how the device should be worn; data entry may be in the form of selection from pre-defined lists or general free form text input; Abstract and par. 0152: measured or derived or manually input physiological contextual parameters are provided; data entry may be in the form of selection from pre-defined lists or general free form text input; opening Health Manager web page may include Body Stats section which may provide information regarding the user's height, weight, body measurements, body mass index or BMI, and vital signs such as heart rate; blood pressure or any of the identified physiological parameters);
populating a personalized risk monitoring profile for the patient (par. 0114: screen may also display risk factor bars that show the risk of certain conditions such as diabetes, heart disease, hypertension, stroke and premature death at the user's current weight in comparison to the risk at the goal weight; the current and goal risk factors of each disease state may be displayed side-by-side for the user) by:
calculating anthropometric indicators of central body fat mass by comparing the body metric measurements received at the system with age-group percentiles (par. 0114, 0152, 0174: screen may also display risk factor bars that show the risk of certain
conditions such as diabetes, heart disease, hypertension, stroke and premature death at the user's current weight in comparison to the risk at the goal weight; the current and goal risk factors of each disease state may be displayed side-by-side for the user; opening Health Manager web page may include Body Stats section which may provide information regarding the user's body measurements, body mass
index or BMI; predictive analysis of the data regarding negatively positively or neutrally oriented situations may be based on aggregate data of similar data from other users in the population; population data may be based on the data gathered from users of any of the embodiments of the system);
determining a physical activity level for the patient using the received pedometer data or physical activity level data or both (Fig. 10, Abstract, and par. 0072: generates data indicative of various physiological parameters of an individual, such as the individual's activity level);
determining a body type based on one or more of: (i) height, (ii) neck circumference, (iii) size, and (iv) waist-to-height ratio for the patient as represented within the body metric measurements received (par. 0152: opening Health Manager web page may include Body Stats section which may provide information regarding the user's height, weight, body measurements, body mass index or BMI or any of the identified physiological parameters);
calculating a physiological lean body mass and percentage of body fat for the patient (par. 0114, 0152: the system will then calculate the following: body mass index at the user's current weight, the body mass index at the goal weight, weight loss per week required to reach goal weight by the target date; opening Health Manager web page may include Body Stats section which may provide information regarding the user's body mass index or BMI or any of the identified physiological parameters);
calculating a target physiological weight for the patient (par. 0114: the system will then calculate the following: body mass index at the user's current weight, the body mass index at the goal weight, weight loss per week required to reach goal weight by the target date); and
re-transmitting the GUI to the user-device updated to display the personalized risk monitoring profile for the patient based on the inputs received (par. 0113, 0114: if any information on the body parameter screen is modified, an armband update button allows the user to start the upload process for armband configuration; if the user selects this option, the user will be asked to enter the following information to establish these goals: current weight, goal weight; the screen may also display risk factor bars that show the risk of certain conditions; help users monitor certain health and safety related activities and risks and is based in part on data input by the user), determined calculated factors populated into the personalized risk monitoring profile (par. 0114, 0145: the screen may also display risk factor bars that show the risk of certain conditions such as diabetes, heart disease, hypertension, stroke and premature death at the user's current weight in comparison to the risk at the goal weight; the current and goal risk factors of each disease state may be displayed side-by-side for the user; help users monitor certain health and safety related activities and risks and is based in part on data input by the user), wherein the personalized risk monitoring profile specifies guidance for the patient to achieve the calculated target physiological weight (par. 0114, 0176: the system will then calculate the following: weight loss per week required to reach goal weight by the target date; if the user has experienced a negative situation that has caused an increase in weight, the system may determine that the user's risk for heart disease is now elevated; this current elevated risk is displayed accordingly in the risk factor bar for that condition and compared to the risk at the user's goal level).
Regarding claim 2, PACIONE further teaches wherein the personalized risk monitoring profile displayed to the user device via the re-transmitted GUI further displays (par. 0113, 0114: if any information on the body parameter screen is modified, an armband update button allows the user to start the upload process for armband configuration; if the user selects this option, the user will be asked to enter the following information to establish these goals: current weight, goal weight; the screen may also display risk factor bars that show the risk of certain conditions; help users monitor certain health and safety related activities and risks and is based in part on data input by the user) one or more of: a complete nutritional status assessment (Abstract and par. 0106: a nutrition and activity management
system; a nutritional tracking system is utilized to obtain data regarding food consumed; the Nutrition category relates to what, when and how much a person eats and drinks), and a self-monitoring and maintenance assessment (par. 0145: health maintenance, that tracks whether the user is taking prescribed medication or supplements and allows the user to monitor tobacco and alcohol consumption and automobile safety such as seat belt use), wherein the complete nutritional status assessment is based on a greater number of body metric measurements than the self- monitoring and maintenance (Abstract and par. 0106: weight (body metric) management is directed to achieving an optimum or preselected energy balance between calories consumed (nutritional assessment) and energy expended by the
user; the Nutrition category relates to what, when and how much a person eats and drinks; provide information regarding the user's height, weight, body measurements, body mass index or BMI or any of the identified physiological parameters).
Regarding claim 3, PACIONE further teaches wherein the physical activity level data for the patient (par. 0072: activity level) includes one or more of: number of daily steps for the patient (par. 0021, 0131: the number of steps taken and the duration of physical activity; minute-by-minute estimates of the energy expenditure values, the number of steps); a basal metabolism for the patient (par. 0133: estimate the calories burned during any particular activity); a daily energy expenditure (DET) for the patient (par. 0196: energy expenditure information; caloric burn of that individual from midnight until that time of day); medical data for the patient (par. 0036: specific health conditions or preferences of the user); social data for the patient; dietary history data for the patient (par. 0201: eating patterns may also be similar from day to day); and activity level assessment data for the patient (par. 0196: energy expenditure information; caloric burn of that individual from midnight until that time of day).
Regarding claim 4, 15, and 19, PACIONE further teaches wherein body metric measurements (par. 0152: provide information regarding the user's height, weight, body measurements) include one or more of: (i) height (par. 0152: provide information regarding the user's height), (ii) weight (par. 0152: provide information regarding the user's weight), (iii) neck circumference, (iv) mid-arm circumference, (v) forearm circumference, (vi)wrist circumference, (vii)waist circumference (par. 0113: waistline measurement), (viii) abdomen circumference, (ix) hip circumference, (x) median thigh circumference, and (xi) pedometer data (par. 0021, 0131: the number of steps taken and the duration of physical activity; minute-by-minute estimates of the energy expenditure values, the number of steps).
Regarding claim 5, 16, and 20, PACIONE further teaches wherein calculating anthropometric indicators based on the body metric measurements (par. 0152: provide information regarding the user's height, weight, body measurements (anthropometric), body mass index or BMI) includes one or more of: body type indicators, body mass and composition indicators (par. 0152: provide information regarding the user's weight, body measurements, body mass index or BMI), fat free mass indicators, fat mass indicators, risk factor indicators (par. 0114, 0145: the screen may also display risk factor bars that show the risk of certain conditions such as diabetes, heart disease, hypertension, stroke and premature death at the user's current weight in comparison to the risk at the goal weight; the current and goal risk factors of each disease state may be displayed side-by-side for the user), and lean mass functionality indicators (par. 0151: provide information regarding the user's weight, body measurements, body mass index or BMI).
Regarding claim 8, PACIONE further teaches wherein the individual risk monitoring profile is based on one or more risk factors includes: (i) metabolic syndrome risk, (ii) cardiovascular risk, (iii) adiposity-muscle waist-thigh risk, and (iv) neck-height ratio night apnea risk (par. 0114, 0145: the screen may also display risk factor bars that show the risk of certain conditions such as diabetes, heart disease, hypertension, stroke and premature death at the user's current weight in comparison to the risk at the goal weight; the current and goal risk factors of each disease state may be displayed side-by-side for the user).
Regarding claim 10, PACIONE further teaches wherein patient protein intake is customized to modify the physiological lean body mass (par. 0072, 0109, 0165-0167: generates data indicative of various physiological parameters of an individual, such as muscle (interpreted to include lean mass); routine may be adjusted based on information about the user, such as weight; certain nutritional targets may also be set by the user or for the user, relating to daily calories, protein and percentages of total consumption; if the user is not losing weight according to the preset goals, the user may be presented with an option to decrease (adjust) the daily caloric intake to reach energy balance goals or reset goals to be more achievable; if the user chooses to increase total energy expenditure and decrease daily caloric intake to reach the preset goals, the meal plan and exercise choices may be adjusted).
Regarding claim 12, PACIONE further teaches wherein the target physiological weight represents a weight after losing excess fat to balance physiological lean body mass with physiological fat percentage for a patient (par. 0126: weight tracking subsystem is the estimation of the date at which the user's weight should equal the defined goal value input by the user during the registration or as updated at a later time; an algorithm calculates a rate of weight change based on the sequence of the user's recorded weight entries. A Kalman smoother is applied to the sequence to eliminate the effects of noise due to scale imprecision and day to day weight variability; tee date at which the user will reach their weight goal is predicted based on the rate of weight change).
Regarding claim 13, PACIONE further teaches wherein either the patient or a clinician authenticates at the user device (par. 0093: chosen middleware server authenticates the user) and receives the GUI transmitted from the system at the user-device displaying the personalized risk monitoring profile for the patient (par. 0114, 0145: the screen may also display risk factor bars that show the risk of certain conditions such as diabetes, heart disease, hypertension, stroke and premature death at the user's current weight in comparison to the risk at the goal weight; the current and goal risk factors of each disease state may be displayed side-by-side for the user).
Claim Rejections - 35 USC § 103 (AIA )
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 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 6, 17, and 21 are rejected under 35 U.S.C. 103 as being obvious over PACIONE, as applied to claim 1, 14, and 18, respectively, in view of US 2013/0325493 A1 to WONG.
Regarding claim 6, 17, and 21, PACIONE teaches the elements above, but fails to expressly disclose wherein the body type includes one or a combination of two or more of: (i) ectomorph, (ii) leptosomic, (iii) mesomorph, and (iv) endomorph biotypes.
However, WONG teaches wherein the body type includes one or a combination of two or more of (i) ectomorph, (ii) leptosomic, (iii) mesomorph, and (iv) endomorph biotypes (par. 0041: body types include the following or a combination of the following: ectomorph, mesomorph, and endomorph).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate wherein the body type includes one or a combination of two or more of (i) ectomorph, (ii) leptosomic, (iii) mesomorph, and (iv) endomorph biotypes, as taught by WONG, into the invention of PACIONE, in order to provide software that allows users to manipulate the controllers for all the body parts of their medical avatars to match the size and shape of their own bodies in order to visualize desired improvements to their current bodies (WONG: Abstract, par. 0007-0008, 0043).
Claim 7 is rejected under 35 U.S.C. 103 as being obvious over PACIONE, as applied to claim 1, in view of US 2005/0240444 A1 to WOOTEN.
Regarding claim 7, PACIONE teaches the elements above, but fails to expressly disclose wherein lean body mass is total body weight minus weight due to body fat mass, wherein lean body mass is adjusted with an assessment for estimating subcutaneous fat.
However, WOOTEN teaches wherein lean body mass is total body weight minus weight due to body fat mass, wherein lean body mass is adjusted with an assessment for estimating subcutaneous fat (par. 0009, 0112: comparing a patients mass as measured underwater to their mass as measured out of the water, their body composition (lean body mass and percent body fat) may be more accurately determined; patient's body composition data comprising measured lean body mass, percentage of lean body mass, lean body mass to fat ratio, total body water, optimal lean body mass to fat ratio, weight of body fat, desired range of percent body fat, percentage of body fat, and fat free mass).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate wherein lean body mass is total body weight minus weight due to body fat mass, wherein lean body mass is adjusted with an assessment for estimating subcutaneous fat, as taught by WOOTEN, into the invention of PACIONE, in order to provide a more accurately determined body composition that is lean body mass and percent body fat (WOOTEN: par. 0009).
Claim 9 is rejected under 35 U.S.C. 103 as being obvious over PACIONE, as applied to claim 1, in view of US 2011/0256132 A1 to ASHMAN.
Regarding claim 9, PACIONE teaches the elements above, but fails to expressly disclose wherein muscle loss (sarcopenia) is evaluated via a handgrip functional test.
However, ASHMAN teaches wherein muscle loss (sarcopenia) is evaluated via a handgrip functional test (par. 0250, 0272: condition associated with muscle wasting, myopathy, or muscle loss; demonstrate changes in muscle mass, muscle strength, and muscle function via a hand grip test, manual muscle testing scales).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate wherein muscle loss (sarcopenia) is evaluated via a handgrip functional test, as taught by ASHMAN, into the invention of PACIONE, in order to provide a device for assessing and/or demonstrating changes in muscle mass, muscle strength, and muscle function (ASHMAN: par. 0085, 0272).
Claim 11 is rejected under 35 U.S.C. 103 as being obvious over PACIONE, as applied to claim 1, in view of US 2023/0131906 A1 to RAWADI.
Regarding claim 11, PACIONE teaches the elements above, but fails to expressly disclose wherein the physiological lean mass estimates a lean mass deficit.
However, RAWADI teaches wherein the physiological lean mass estimates a lean mass deficit (par. 0025: "loss of pathological muscle mass" or "loss of muscle mass" or "pathological muscle loss" within the meaning is meant as an abnormal, pathological decrease in muscle mass (lean mass deficit) due to a decrease in protein synthesis, in particular of skeletal muscle mass).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate wherein the physiological lean mass estimates a lean mass deficit, as taught by RAWADI, into the invention of PACIONE, in order to provide a device for observing decreasing muscle loss in order to prevent and/or treat pathological loss of muscle mass (RAWADI: par. 0025).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to James Hull whose telephone number is 571-272-0996. The examiner can normally be reached on Monday-Friday from 8:00am to 5:00pm MST.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Xuan Thai, can be reached at telephone number 571-272-7147. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) Form at https://www.uspto.gov/patents/uspto-automated- interview-request-air-form.
/JAMES B HULL/Primary Examiner, Art Unit 3715