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 .
Response to Arguments
Claim Objections
Applicant's arguments filed 05/30/2025 have been fully considered. Applicant argues that the amendment resolves the issue and the objection should be withdrawn. Due to the amendment, the objection is withdrawn.
Rejection Under 101
Applicant's arguments filed 05/30/2025 have been fully considered.
Applicant argues that the independent claims do not merely cover management of personal behavior or interactions within the “certain methods of organizing human activity” grouping of abstract ideas. The claims are unlike following rules or instructions to be considered managing personal behavior or interactions like the examples given in the MPEP.
In response to Applicant’s arguments, the list of examples that fall under this grouping is not exhaustive. Therefore, steps to organize information to determine a patient’s metabolic status in order to determine a solution for improving their metabolic status is understood to be following rules to process patient sensor information to provide the patient with a solution falls under organizing human activity.
The claims integrate the judicial exception into a practical application by reciting an improvement. See references to the specification, Remarks filed 5/30/2025 pgs. 19-20.
In response to Applicant’s arguments, the additional elements recited do not amount to a practical application since, the additional elements merely invokes use of computer and other machinery, such as a sensor, as a tool. See MPEP 2106.05(f).
Rejection Under 102/103
Applicant's arguments filed 05/30/2025 have been fully considered.
Applicant argues that the specification unambiguously defines “health capacity” as resilience of a system. Examiner erroneously construed the meaning of the team in order to use Teller to teach a parameter relating to health.
In response to Applicant’s arguments, the published specification at [0066] states that the health capacity may be considered, for example, to be the energy and information contained in a living system or an organism that enables persistence or function or health of that system or organism. By this example, the teachings of Teller about the health of a subject falls within the alternative examples given in the specification and read on the term “health capacity,” which is information related to health of a system or organism. See below for further clarification.
Teller teaches health indicators or indices as well as known metrics, such as caloric intake, stress levels, and sleep patterns. Teller does not associate those known metrics with quantifying the resilience, adaptivity, fitness, or frailty or a biological system.
In response to Applicant’s arguments, as discussed above, the health capacity is construed to relate to the health of the system or organism as was provided by the specification. Teller reads on this limitation. See below for further clarification.
Emergent factor is defined as “may be related to, or form a basis for assessing, the health capacity of the system.” ([0125]). Therefore, quantifying a health capacity of a biological system. Teller merely measures predicting energy expenditure based on measurements from sensers and user inputs. None of the energy expenditure measurements relates to assessing the health capacity.
In response to Applicant’s arguments, as discussed above, the health capacity is construed to relate to the health of the system or organism as was provided by the specification. Teller reads on this limitation of assessing the energy expenditure during the sleep of an individual by looking at sensor data for measuring skin temperature since the health capacity as taught by Teller looked at the health related to the individual’s sleep. See below for further clarification.
Claims 23 and 25 recite quantifying a health capacity of a biological system which Teller does not disclose. And Claim 25 recites sensing one emergent factor of the biological system and generating data from the emergent factor, which Teller does not disclose.
In response to Applicant’s arguments, as discussed above, the health capacity is construed to relate to the health of the system or organism as was provided by the specification. And the emergent factor relates to the health capacity, which Teller teaches in view of the definition of the specification. Teller reads on these limitations. See below for further clarification.
Claim 78 recites measuring emergent factor of the human, wherein the emergent factor is the temporal alignment of heat production and heat elimination of the human, the temporal alignment relating to the circadian rhythm of the human.
In response to Applicant’s arguments, Teller is used to teach using sensors, such as a heat flux and accelerometer, to determine energy expenditure over time. See Teller [0012]-[0014], [0175], [0234], [0243]. Claim 34 was one of the claims recited to teach independent claim 78. Claim 34 includes the teaches of claim 31 where the above paragraphs are recited from Teller. The heat flux sensor measures heat elimination and accelerometer measures heat production, which is done over a time period and thus reads on applicant’s claim language.
The dependent claims are allowable in view of the reasons recited above in relations to the independent claims.
In response to Applicant’s arguments, the dependent claims are rejected for reasons given below in the rejection since the independent claim rejection is maintained. See below for the rejections.
Burton does not cure the deficiencies of Teller and thus Examiner failed to make a prima facie case of obviousness.
In response to Applicant’s arguments, as discussed above, Teller teaches the independent claims and thus the rejection is maintained. Therefore, the combination of the Teller and Burton references teaches the recited claims.
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, 7-13, 19-26, 30-34, 37, 40-42, 62-71, 74-75, 77-78, 81, 83 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., an abstract idea) without significantly more.
Step 1 of the Alice/Mayo Test
Claims 25-26, 30-34, 37, 40-42, 62-69 are drawn to a method, which is within the four statutory categories (i.e. process). Claims 1-2, 7-13, 19-24, 70-71, 74-75, 77-78, 81, 83 are drawn to a system, which is within the four statutory categories (i.e. apparatus).
Step 2A of the Alice/Mayo Test - Prong One
The independent claims recite an abstract idea. For example, independent claim 78 (and substantially similar with independent claim 1, 23, 25) recites:
A system for quantifying and improving a metabolic status of a human, comprising:
at least one wearable thermodynamic sensor configured to:
measure an emergent factor of the human, wherein the emergent factor is the temporal alignment of heat production and heat elimination of the human, the temporal alignment relating to the circadian rhythm of the human, and
based on the emergent factor, generate measured data comprising heat flux data over time; and
a processing system comprising a processor and an interface, the processing system configured to:
receive the measured data from the at least one wearable thermodynamic sensor,
based on the measured data, quantify a metabolic status of the human relating to the heat production and heat elimination,
based on the measured data, determine one or more stimuli that influence the metabolic status of the human,
compute a solution for maximizing the metabolic status of the human, and
generate and output at least one indicator for improving the metabolic status of the human by modulating the heat production and heat elimination of the human.
These underlined elements recite an abstract idea that can be categorized, under its broadest reasonable interpretation, to cover the management of personal behavior or interactions (i.e., following rules or instructions), but for the recitation of generic computer components. For example, but for the processing system, a processor, an interface, and thermodynamic sensor, the limitations in the context of this claim encompass an organizing patient information to determine the patient’s metabolic status based on their sensor data and to compute a solution for improving their metabolic status. If a claim limitation, under its broadest reasonable interpretation, covers management of personal behavior or interactions but for the recitation of generic computer components, then the limitations fall within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. See MPEP § 2106.04(a).
Dependent claims recite additional subject matter which further narrows or defines the abstract idea embodied in the claims (such as claims 2, 7-13, 19-22, 24, 26, 30-34, 37, 40-42, 62-71, 74-75, 77, 81, 83 reciting particular aspects of the abstract idea).
Step 2A of the Alice/Mayo Test - Prong Two
For example, independent claim 78 (and substantially similar with independent claim 1, 23, 25) recites:
A system for quantifying and improving a metabolic status of a human, comprising:
at least one wearable thermodynamic sensor configured to: (merely invokes use of computer and other machinery as a tool as noted below, see MPEP 2106.05(f))
measure an emergent factor of the human, wherein the emergent factor is the temporal alignment of heat production and heat elimination of the human, the temporal alignment relating to the circadian rhythm of the human, and
based on the emergent factor, generate measured data comprising heat flux data over time; and
a processing system comprising a processor and an interface, the processing system configured to: (merely invokes use of computer and other machinery as a tool as noted below, see MPEP 2106.05(f))
receive the measured data from the at least one wearable thermodynamic sensor, (merely invokes use of computer and other machinery as a tool as noted below, see MPEP 2106.05(f))
based on the measured data, quantify a metabolic status of the human relating to the heat production and heat elimination,
based on the measured data, determine one or more stimuli that influence the metabolic status of the human,
compute a solution for maximizing the metabolic status of the human, and
generate and output at least one indicator for improving the metabolic status of the human by modulating the heat production and heat elimination of the human.
The judicial exception is not integrated into a practical application. In particular, the additional elements do not integrate the abstract idea into a practical application, other than the abstract idea per se, because the additional elements amount to no more than limitations, which:
amount to mere instructions to apply an exception (such as recitations of the processing system, a processor, an interface, and thermodynamic sensor, thereby invoking computers as a tool to perform the abstract idea, see applicant’s specification 11, 26-27, 69, 81, see MPEP 2106.05(f))
Dependent claims recite additional subject matter which amount to limitations consistent with the additional elements in the independent claims (such as claims 2, 7-13, 19-22, 24, 26, 30-34, 37, 40-42, 62-71, 74-75, 77, 81, 83 recite additional limitations which further narrow the abstract idea, claims 2, 7-13, 19-22, 24, 26, 30-34, 37, 40-42, 62-71, 74-75, 77, 81, 83 additional limitations which generally link the abstract idea to a particular technological environment or field of use). 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 and do not impose a meaningful limit to integrate the abstract idea into a practical application.
Step 2B of the Alice/Mayo Test for Claims
The 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 of use. Additionally, the additional elements, other than the abstract idea per se, amount to no more than elements which:
amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields (such as using the processing system, a processor, an interface, and thermodynamic sensor, e.g., Applicant’s spec describes the computer system with it being well-understood, routine, and conventional because it describes in a manner that the additional elements are sufficiently well-known that the specification does not need to describe the particulars of such elements to satisfy 112a. (See Applicant’s Spec. pg. 11, 26-27, 69, 81); using a processing system, processor, interface, sensors, e.g., merely adding a generic computer, generic computer components, or a programmed computer to perform generic computer functions, Alice Corp. Pty. Ltd. v. CLS Bank Int’l, 134 S. Ct. 2347, 2358-59, 110 USPQ2d 1976, 1983-84 (2014).
Dependent claims recite additional subject matter which, as discussed above with respect to integration of the abstract idea into a practical application, amount to further narrowing the abstract idea and generally linking the abstract idea to a particular field of environment. 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, the claims are not patent eligible, and are rejected under 35 U.S.C. § 101.
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.
Claims 1-2, 7-9, 19, 21-23, 25-26, 30-34, 37, 40-42, 62-71, 74-75, 77-78, 81, 83 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by (Teller et al. (US 2014/0221769).
Regarding claim 1, Teller discloses a system for quantifying a health capacity of a biological system, comprising: (Teller [0001], [0101], [0112], [0115]: calculating health indicators and health indices {a parameter relating to the health of a subject is construed as the health capacity})
at least one sensor configured to measure an emergent factor of the biological system and generate measured data based on the emergent factor; and (Teller [0012]-[0014]: sensors for measuring energy expenditure of an individual including a body motion sensor, a heat flux sensory, and a skin temperature sensor, etc. {a measured value obtained from the sensor is construed as the emergent factor})
a processing system comprising a processor and an interface for receiving the measured data from the at least one sensor and determining one or more factors that quantify the health capacity of the biological system based on the measured data. (Teller [0101], [0112], [0115], [0150]: computing device for providing health index based on the measured sensor data; [0244]: algorithms to detect individual’s state based on the sensor data, e.g., health or metabolic status).
Regarding claim 2, Teller discloses the system of Claim 1, and further discloses wherein the processor computes a solution for maximizing the health capacity of the biological system according to machine readable instructions. (Teller [0103] discloses using stimuli for creating healthy plans and routines for the patient, where the stimuli can be nutrition, exercise, sleep, etc. [0013] discloses using software including instructions for collecting data in order to analyze the data and make health determinations).
Regarding claim 7, Teller discloses the system of Claim 1, and further discloses further comprising a storage component in communication with the processing system and for storing the measured data. (Teller [0089] discloses storing all data gathered for each user in a database which is connected to a multiprocessor server).
Regarding claim 8, Teller discloses the system of Claim 1, and further discloses wherein the measured data is an energy budget of the biological system. (Teller 204-207 caloric expenditure of a subject).
Regarding claim 9, Teller discloses the system of Claim 1, and further discloses wherein processing system comprises a plurality of transmitters configured to transmit the measured data as data streams optimized with respect to properties of the at least one sensor and the emergent factors to be reported. (Teller [0150] disclose the gathered sensor data can be transmitted and output).
Regarding claim 19, Teller discloses the system of Claim 1, and further discloses wherein the at least one sensor comprises a plurality of wearable devices for sensing data comprising at least one of heat flux data, calorimetry data, osmometry data, and physiometry data. (Teller [0012]-[0014]: sensors for measuring energy expenditure of an individual including a body motion sensor, a heat flux sensory, and a skin temperature sensor, etc.).
Regarding claim 21, Teller discloses the system of Claim 1, and further discloses wherein the interface transmits the measured data via wireless communication. (Teller [0150] disclose the gathered sensor data can be transmitted and output using a wireless communication).
Regarding claim 22, Teller discloses the system of Claim 1, and further discloses wherein the processing system further comprises: an application program interface that controls storage of the measured data, access to the measured data, security configurations, user inputs, and output of any results. (Teller [0089] discloses storing all data gathered for each user in a database which is connected to a multiprocessor server; [0150] disclose the gathered sensor data can be transmitted and output using a wireless communication).
Regarding claim 23, the claim recites substantially similar limitations as those already addressed in the rejection of claim 1, and, as such, is rejected for similar reasons as given above. Additionally, Teller further discloses a plurality of measuring devices, wherein at least one measuring device measures a thermodynamic property of the biological system. (Teller [0012]-[0014]: sensors for measuring energy expenditure of an individual including a body motion sensor, a heat flux sensory, and a skin temperature sensor, etc. {measuring heat flux is construed as measuring thermodynamic property}).
Regarding claim 25, the claim recites substantially similar limitations as those already addressed in the rejection of claim 1, and, as such, is rejected for similar reasons as given above. Additionally, Teller further discloses determining, based on the measured data, one or more stimuli that influence the health capacity of the biological system. (Teller [0103] teaches using stimuli that would impact a user’s health for creating healthy plans and routines for the patient, where the stimuli can be nutrition, exercise, sleep, etc.).
Regarding claim 26, Teller discloses the method of claim 25, and further discloses further comprising generating a solution for maximizing the health capacity by modifying one or more stimuli that influence the health capacity of the biological system, wherein the stimuli are selected from sleep patterns, sleep durations, nutritional intakes, and exercise regimens. (Teller [0103] teaches using stimuli that would impact a user’s health for creating healthy plans and routines for the patient, where the stimuli can be nutrition, exercise, sleep, etc. [0105]-[0106] teaches nutritional intakes [0107]-[0108] teaches exercise regimens [0113] teaches sleep patterns [0114] teaches sleep amount or duration).
Regarding claim 30, Teller discloses the method of Claim 25, and further discloses wherein the measured data comprise surface temperature and physical activity of the biological system over time. (Teller [0012]-[0014]: sensors for measuring energy expenditure of an individual including a body motion sensor, a heat flux sensory, and a skin temperature sensor, etc. [0107] discloses measuring movement data over a time period as well as other relevant sensed data in connection to their movement [0111] The Mind Centering Health Index piston level is preferably calculated with respect to a suggested healthy daily routine that includes participating each day in an activity that allows the body to achieve profound relaxation while the mind stays highly focused for at least fifteen minutes. Parameters utilized in the calculation of the relevant piston level include the amount of time spent in a mind centering activity, and the percent change in skin temperature, heart rate, respiration rate, heat flow or GSR as sensed by sensor device 10 compared to a baseline which is an indication of the depth or quality of the mind centering activity).
Regarding claim 31, Teller discloses the method of claim 30, and further discloses further comprising: estimating heat elimination of the biological system over time based on differential surface temperature; estimating heat production of the biological system over time based on physical activity; and estimating a basal metabolic status of the biological system based on temporal alignment of heat elimination and heat production. (Teller [0012]-[0014]: sensors for measuring energy expenditure of an individual including a body motion sensor, a heat flux sensory, and a skin temperature sensor, etc.; [0175] detect real time energy expenditure of the wearer as well as the type of activity in which the wearer is engaging, such as running or riding a bike [0234] Such variables may include, without limitation, energy expenditure, including resting, active and total values, daily caloric intake, sleep states, including in bed, sleep onset, sleep interruptions, wake, and out of bed, and activity states, including exercising, sitting, traveling in a motor vehicle, and lying down, and the algorithms for generating values for such variables may be based on data from, for example, the 2-axis accelerometer, the heat flux sensor, the GSR sensor, the skin temperature sensor, the near-body ambient temperature sensor, and the heart rate sensor in the embodiment described above. {variable for activity states construed looking at expenditure based on exercise} [0243] Referring to FIG. 48, an example algorithm for measuring energy expenditure of an individual is shown conceptually. This example algorithm may be run on sensor device 1201 having at least an accelerometer, a heat flux sensor… {heat flux sensor measures heat elimination and accelerometer measures heat production} the energy expenditure is limited for that time period to a value equal to some factor (e.g. 1.3) times their minute by minute basal metabolic rate).
Regarding claim 32, Teller discloses the method of claim 30, and further discloses further comprising: obtaining a quasiperiodic rhythm of the biological system based on the measured data, wherein the quasiperiodic rhythm is of seconds-timescale, of minutes-timescale, ultradian, circadian, circalunar, or of yearly timescale. (Teller [0113] The Sleep category of Health Index 155 is designed to help users monitor their sleep patterns and the quality of their sleep. It is intended to help users learn about the importance of sleep in their healthy lifestyle and the relationship of sleep to circadian rhythms, being the normal daily variations in body functions [0079] detection by sensor device 10 of a heart rate below a certain level, or can be initiated by the individual user or some third party authorized by the user, preferably according to some periodic schedule, such as every day at 10:00 p.m.).
Regarding claim 33, Teller discloses the method of claim 32, and further discloses further comprising: obtaining a variability of the quasiperiodic rhythm across a predetermined amount of time; and determining the health capacity based on the variability of the quasiperiodic rhythm. (Teller [0113] The Sleep category of Health Index 155 is designed to help users monitor their sleep patterns and the quality of their sleep. It is intended to help users learn about the importance of sleep in their healthy lifestyle and the relationship of sleep to circadian rhythms, being the normal daily variations in body functions [0079] detection by sensor device 10 of a heart rate below a certain level, or can be initiated by the individual user or some third party authorized by the user, preferably according to some periodic schedule, such as every day at 10:00 p.m.).
Regarding claim 34, Teller discloses the method of claim 32, recites substantially similar limitations as those recited in the rejection of claim 31, and, as such, is rejected for similar reasons as given above. Additionally, Teller further discloses determining the health capacity by applying a time-dependent function to the estimated basal metabolic status, wherein the time-dependent function is derived from the quasiperiodic rhythm of the biological system. (Teller [0113] The Sleep category of Health Index 155 is designed to help users monitor their sleep patterns and the quality of their sleep. It is intended to help users learn about the importance of sleep in their healthy lifestyle and the relationship of sleep to circadian rhythms, being the normal daily variations in body functions [0079] detection by sensor device 10 of a heart rate below a certain level, or can be initiated by the individual user or some third party authorized by the user, preferably according to some periodic schedule, such as every day at 10:00 p.m.).
Regarding claim 37, Teller discloses the method of claim 25, and further discloses wherein the measured data comprises exhaust streams of the biological system. (Teller [0012]-[0014]: sensors for measuring energy expenditure of an individual including a body motion sensor, a heat flux sensory, and a skin temperature sensor, etc.)
Regarding claim 40, Teller discloses the method of claim 37, and further discloses further comprising: analyzing functional aspects of thermoregulation in the biological system based on the measured data. (Teller [0012] discloses predicting energy expenditure of the individual where considerations are heat flux and basal metabolic rate for the individual).
Regarding claim 41, Teller discloses the method of claim 40, and further discloses further comprising: generating and outputting indicators for understanding, improving, modulating, repurposing, or any combination thereof, one or more functions of the biological system. (Teller [0103] When each member user completes the initial survey described above, a profile is generated that provides the user with a summary of his or her relevant characteristics and life circumstances. A plan and/or set of goals is provided in the form of a suggested healthy daily routine. The suggested healthy daily routine may include any combination of specific suggestions for incorporating proper nutrition, exercise, mind centering, sleep, and selected activities of daily living in the user's life.)
Regarding claim 42, Teller discloses the method of claim 41, and further discloses wherein the indicators are used to manage weight, blood pressure, circadian rhythm, sleep quality, sleep duration, or any combination thereof, of the biological system. (Teller [0103] When each member user completes the initial survey described above, a profile is generated that provides the user with a summary of his or her relevant characteristics and life circumstances. A plan and/or set of goals is provided in the form of a suggested healthy daily routine. The suggested healthy daily routine may include any combination of specific suggestions for incorporating proper nutrition, exercise, mind centering, sleep, and selected activities of daily living in the user's life.)
Regarding claim 62, Teller discloses the method of claim 25, and further discloses wherein the measured data comprises heat flux data. (Teller [0012]-[0014]: sensors for measuring energy expenditure of an individual including a body motion sensor, a heat flux sensory, and a skin temperature sensor, etc.)
Regarding claim 63, Teller discloses the method of claim 62, and further discloses wherein: at least one health capacity is a basal metabolic status, and at least one emergent factor is the temporal alignment of heat production and heat elimination. (Teller [0012] discloses predicting energy expenditure of the individual where considerations are heat flux and basal metabolic rate for the individual).
Regarding claim 64, Teller discloses the method of claim 63, and further discloses wherein the temporal alignment is related to at least one quasiperiodic rhythm of the biological system. (Teller [0113] The Sleep category of Health Index 155 is designed to help users monitor their sleep patterns and the quality of their sleep. It is intended to help users learn about the importance of sleep in their healthy lifestyle and the relationship of sleep to circadian rhythms, being the normal daily variations in body functions).
Regarding claim 65, Teller discloses the method of Claim 64, and further discloses wherein the at least one quasiperiodic rhythm is a circadian rhythm. (Teller [0113] The Sleep category of Health Index 155 is designed to help users monitor their sleep patterns and the quality of their sleep. It is intended to help users learn about the importance of sleep in their healthy lifestyle and the relationship of sleep to circadian rhythms, being the normal daily variations in body functions).
Regarding claim 66, Teller discloses the method of Claim 25, and further discloses further comprising the step of further comprising: generating and outputting at least one indicator for improving or modulating the temporal alignment of heat production and heat elimination of the biological system. (Teller [0115] selectable sleep graph 315 which calculates and displays one sleep related parameter over a pre-selected time interval. For illustrative purposes, FIG. 9 shows heat flow over a one-day period, which tends to be lower during sleeping hours [0122] Opening Health Manager web page 150 also may include a Problem Solver section 158 that actively evaluates the user's performance in each of the categories of Health Index 155 and presents suggestions for improvement. For example, if the system detects that a user's Sleep levels have been low, which suggest that the user has been having trouble sleeping, Problem Solver 158 can provide suggestions for way to improve sleep. Problem Solver 158 also may include the capability of user questions regarding improvements in performance).
Regarding claim 67, Teller discloses the method of Claim 66, and further discloses wherein the indicator suggests to the biological system to perform to at least one predefined action selected from the group of actions comprises: change clothes, go inside, go outside, eat a specific food, drink a specified beverage, perform certain exercises, go to sleep, or any combination thereof. (Teller [0105] The Nutrition Health Index piston level is preferably determined with respect to the following suggested healthy daily routine: eat at least three meals; eat a varied diet consisting of 6-11 servings of bread, pasta, cereal, and rice, 2-4 servings fruit, 3-5 servings of vegetables, 2-3 servings of fish, meat, poultry, dry beans, eggs, and nuts, and 2-3 servings of milk, yogurt and cheese; and drink 8 or more 8 ounce glasses of water. This routine may be adjusted based on information about the user, such as sex, age, height and/or weight. Certain nutritional targets may also be set by the user or for the user, relating to daily calories, protein, fiber, fat, carbohydrates, and/or water consumption and percentages of total consumption. Parameters utilized in the calculation of the relevant piston level include the number of meals per day, the number of glasses of water, and the types and amounts of food eaten each day as input by the user).
Regarding claim 68, Teller discloses the method of Claims 64, and further discloses further comprising the step of recommending at least one predetermined action to improve or modulate the temporal alignment of heat production and heat elimination of the biological system. (Teller [0115] selectable sleep graph 315 which calculates and displays one sleep related parameter over a pre-selected time interval. For illustrative purposes, FIG. 9 shows heat flow over a one-day period, which tends to be lower during sleeping hours [0122] Opening Health Manager web page 150 also may include a Problem Solver section 158 that actively evaluates the user's performance in each of the categories of Health Index 155 and presents suggestions for improvement. For example, if the system detects that a user's Sleep levels have been low, which suggest that the user has been having trouble sleeping, Problem Solver 158 can provide suggestions for way to improve sleep. Problem Solver 158 also may include the capability of user questions regarding improvements in performance).
Regarding claim 69, Teller discloses the method of Claim 68, and further discloses wherein the action manages circadian rhythm. (Teller [0113] The Sleep category of Health Index 155 is designed to help users monitor their sleep patterns and the quality of their sleep. It is intended to help users learn about the importance of sleep in their healthy lifestyle and the relationship of sleep to circadian rhythms, being the normal daily variations in body functions).
Regarding claim 70, Teller discloses the system of Claim 1, and further discloses wherein the measured data comprises heat flux data. (Teller [0012]-[0014]: sensors for measuring energy expenditure of an individual including a body motion sensor, a heat flux sensory, and a skin temperature sensor, etc.
Regarding claim 71, Teller discloses the system of Claim 70, and further discloses wherein: at least one health capacity is a basal metabolic status, and at least one emergent factor is the temporal alignment of heat production and heat elimination of the biological system. (Teller [0012]-[0014]: sensors for measuring energy expenditure of an individual including a body motion sensor, a heat flux sensory, and a skin temperature sensor, etc.; [0175] detect real time energy expenditure of the wearer as well as the type of activity in which the wearer is engaging, such as running or riding a bike [0234] Such variables may include, without limitation, energy expenditure, including resting, active and total values, daily caloric intake, sleep states, including in bed, sleep onset, sleep interruptions, wake, and out of bed, and activity states, including exercising, sitting, traveling in a motor vehicle, and lying down, and the algorithms for generating values for such variables may be based on data from, for example, the 2-axis accelerometer, the heat flux sensor, the GSR sensor, the skin temperature sensor, the near-body ambient temperature sensor, and the heart rate sensor in the embodiment described above. {variable for activity states construed looking at expenditure based on exercise} [0243] Referring to FIG. 48, an example algorithm for measuring energy expenditure of an individual is shown conceptually. This example algorithm may be run on sensor device 1201 having at least an accelerometer, a heat flux sensor… {heat flux sensor measures heat elimination and accelerometer measures heat production} the energy expenditure is limited for that time period to a value equal to some factor (e.g. 1.3) times their minute by minute basal metabolic rate).
Regarding claim 74, Teller discloses the system of Claim 71, and further discloses wherein the processing system is further configured to generate and output at least one indicator for improving or modulating the temporal alignment of heat production and heat elimination of the biological system. (Teller [0115] selectable sleep graph 315 which calculates and displays one sleep related parameter over a pre-selected time interval. For illustrative purposes, FIG. 9 shows heat flow over a one-day period, which tends to be lower during sleeping hours [0122] Opening Health Manager web page 150 also may include a Problem Solver section 158 that actively evaluates the user's performance in each of the categories of Health Index 155 and presents suggestions for improvement. For example, if the system detects that a user's Sleep levels have been low, which suggest that the user has been having trouble sleeping, Problem Solver 158 can provide suggestions for way to improve sleep. Problem Solver 158 also may include the capability of user questions regarding improvements in performance).
Regarding claim 75, Teller discloses the system of Claim 74, and further discloses wherein the indicator suggests to the biological system to perform to at least one predefined action selected from the group of actions comprises: change clothes, go inside, go outside, eat a specific food, drink a specified beverage, perform certain exercises, go to sleep, or any combination thereof. (Teller [0105] The Nutrition Health Index piston level is preferably determined with respect to the following suggested healthy daily routine: eat at least three meals; eat a varied diet consisting of 6-11 servings of bread, pasta, cereal, and rice, 2-4 servings fruit, 3-5 servings of vegetables, 2-3 servings of fish, meat, poultry, dry beans, eggs, and nuts, and 2-3 servings of milk, yogurt and cheese; and drink 8 or more 8 ounce glasses of water. This routine may be adjusted based on information about the user, such as sex, age, height and/or weight. Certain nutritional targets may also be set by the user or for the user, relating to daily calories, protein, fiber, fat, carbohydrates, and/or water consumption and percentages of total consumption. Parameters utilized in the calculation of the relevant piston level include the number of meals per day, the number of glasses of water, and the types and amounts of food eaten each day as input by the user).
Regarding claim 77, Teller discloses the system of Claim 74, and further discloses wherein the indicators are used to manage circadian rhythm. (Teller [0113] The Sleep category of Health Index 155 is designed to help users monitor their sleep patterns and the quality of their sleep. It is intended to help users learn about the importance of sleep in their healthy lifestyle and the relationship of sleep to circadian rhythms, being the normal daily variations in body functions).
Regarding claim 78, the claim recites substantially similar limitations as those already addressed in the rejections above (see claims 1, 19, 26, 34, 62-63, 65, 74), and, as such, is rejected for similar reasons as given above.
Regarding claim 81, Teller discloses the system of Claim 78, and further discloses wherein quantifying a metabolic status of the human is based on determining the inter-day stability and/or intraday variability of the heat production and/or heat elimination over at least one circadian cycle. (Teller [0012]-[0014]: sensors for measuring energy expenditure of an individual including a body motion sensor, a heat flux sensory, and a skin temperature sensor, etc.; [0113] The Sleep category of Health Index 155 is designed to help users monitor their sleep patterns and the quality of their sleep. It is intended to help users learn about the importance of sleep in their healthy lifestyle and the relationship of sleep to circadian rhythms, being the normal daily variations in body functions; [0175] detect real time energy expenditure of the wearer as well as the type of activity in which the wearer is engaging, such as running or riding a bike [0234] Such variables may include, without limitation, energy expenditure, including resting, active and total values, daily caloric intake, sleep states, including in bed, sleep onset, sleep interruptions, wake, and out of bed, and activity states, including exercising, sitting, traveling in a motor vehicle, and lying down, and the algorithms for generating values for such variables may be based on data from, for example, the 2-axis accelerometer, the heat flux sensor, the GSR sensor, the skin temperature sensor, the near-body ambient temperature sensor, and the heart rate sensor in the embodiment described above. {variable for activity states construed looking at expenditure based on exercise} [0243] Referring to FIG. 48, an example algorithm for measuring energy expenditure of an individual is shown conceptually. This example algorithm may be run on sensor device 1201 having at least an accelerometer, a heat flux sensor… {heat flux sensor measures heat elimination and accelerometer measures heat production} the energy expenditure is limited for that time period to a value equal to some factor (e.g. 1.3) times their minute by minute basal metabolic rate).
Regarding claim 83, Teller discloses the system of Claim 78, and further discloses wherein quantifying a metabolic status of the human is based on comparing the inter-day stability and/or intraday variability of the heat production and/or heat elimination over a particular circadian cycle to the historical value for the human. (Teller [0209] discloses the algorithm may consider may factors such as a time of day/week and the user’s past habits, and trends in the user’s reporting data {construed as comparing particular circadian and historical data for the user}).
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 10-13, 20, 24 are rejected under 35 U.S.C. 103 as being unpatentable over Teller et al. (US 2014/0221769) in view of Burton (JP 2018/505759).
Regarding claim 10, Teller discloses the system of Claim 9, but does not appear to explicitly teach the following, however, Burton teaches it is old and well known in the art of healthcare data processing wherein the processor makes pre-symptomatic detection of a disease state of the biological system based on the health metrics, according to machine readable instructions. (Burton pg. 5 teaches obtaining sensor cardiovascular measurements for cardiac functions; pgs. 189-190 teaches using machine learning to make determinations about events; Pg. 37 teaches looking at the sensor data to make cardiovascular determinations and classifications).
Therefore, it would have been obvious to one of ordinary skill in the art of healthcare data processing, before the effective filing date of the claimed invention, to modify Teller to incorporate wherein the processor makes pre-symptomatic detection of a disease state of the biological system based on the health metrics, according to machine readable instructions, as taught by Burton, in order to detect early onset of health conditions and suggesting a physician visit. Burton pg. 2.
Regarding claim 11, Teller-Burton teaches the system of Claim 10, and Burton further teaches wherein the processor makes pre-symptomatic detection of the disease state of the biological system using a supervised learning algorithm according to machine readable instructions with a collection of health metrics reported from a plurality of other objects. (Burton pg. 5 teaches obtaining sensor cardiovascular measurements for cardiac functions; pgs. 189-190 teaches using machine learning, such as supervised learning, to make determinations about events. Pg. 37 teaches looking at the sensor data to make cardiovascular determinations and classifications).
Regarding claim 12, Teller-Burton teaches the system of Claim 11, and Burton further teaches wherein the disease state is selected from aging, sepsis, cardiovascular disease, and infectious disease. (Burton pg. 5 teaches obtaining sensor cardiovascular measurements for cardiac functions; Pg. 37 teaches looking at the sensor data to make cardiovascular determinations and classifications).
Regarding claim 13, Teller-Burton teaches the system of Claim 11, and Teller further discloses wherein the disease state is an infectious disease. (Teller [0235] discloses the disease the patient has is the flu which is construed as the infectious disease).
Regarding claim 20, Teller discloses the system of Claim 1, but does not appear to explicitly teach the following, however, Burton teaches it is old and well known in the art of healthcare data processing wherein the at least one sensor is an implanted device. (Burton pg. 73 teaches any combination of monitoring one or more sleep parameters, can be done for example by an implant or attachment sensor or a wireless connection-associated sensor). The motivations to combine the references was discussed above and is incorporated herein.
Regarding claim 24, Teller discloses the system of claim 22, and further discloses wherein the output includes a solution for intercepting a disease state. (Burton pg. 2 teaches based on detection results, suggesting a physician visit in order to prevent the onset of the health condition). The motivations to combine the references was discussed above and is incorporated herein.
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 AMANDA R COVINGTON whose telephone number is (303)297-4604. The examiner can normally be reached Monday - Friday, 10 - 5 MT.
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/AMANDA R. COVINGTON/Examiner, Art Unit 3686
/JASON B DUNHAM/Supervisory Patent Examiner, Art Unit 3686
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