DETAILED ACTION
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 01/28/2026 has been entered.
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
Applicant's arguments, see Remarks pages 7-9, filed 01/28/2026, with respect to the rejection of claims 14-29 under 35 USC 101 have been fully considered but they are not persuasive.
In response to the applicant’s argument that the claims are not directed to any of the groupings of abstract ideas, the examiner respectfully disagrees. The examiner contends that the claims are drawn to mental processes and/or mathematical calculations (detailed below in the 35 USC 101 rejections), which are part of the abstract idea groupings. See MPEP 2106.04(a).
In response to the applicant’s argument that the claimed invention provides an improvement in technology, the examiner respectfully disagrees. The examiner notes that to show an improvement to technology, the claims must “include more than mere instructions to perform the method on a generic component or machinery to qualify as an improvement to an existing technology”. See MPEP 2106.05(a)(II). Instead, the examiner finds the applicant’s claimed invention similar to example iii found in MPEP 2106.05(a)(II), which the courts have indicated may not be sufficient to show an improvement to technology, which states “Gathering and analyzing information using conventional techniques and displaying the result, TLI Communications, 823 F.3d at 612-13, 118 USPQ2d at 1747-48”.
In response to the applicant’s argument that the claims as a whole amount to significantly more than the judicial exception, the examiner respectfully disagrees. The examiner notes that the claims add insignificant extra solution activities to the judicial exception (the “receiving” data and “generating an indication” steps) and are further simply appending well-understood, routine, and conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception. See MPEP 2106.05.
Therefore, the 35 USC 101 rejection of claims 14-29 is maintained.
Applicant’s arguments, see Remarks pages 9-13, filed 01/28/2026, with respect to the rejection(s) of claim(s) 14-29 under 35 USC 103 have been fully considered and are persuasive. The examiner notes that the prior art of record from the previous office action fail to teach the amended limitations. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Fleischer (US 20170368258 A1), Madl (US 20180177415 A1), and Jin (US 20180206767 A1).
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 14-29 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Independent Claim 14 recites:
A method implemented by a computing device, the method comprising: receiving glucose data describing user glucose values measured by a glucose sensor of a continuous glucose monitoring (CGM) system;
receiving non-glucose data that includes heart beat interval data captured by a heart rate sensor of the CGM system;
determining historic heart rate variability values of a user of the CGM system based on the heart-beat interval data over a moving time window;
generating a probability that the user will experience a glucose value and a confidence level corresponding to the probability, wherein the probability and the confidence level are determined based on the glucose data and historic heart-rate variability values;
determining a modification amount as a numeric correction amount based on the heart-beat interval data, the probability, and the confidence level;
generating modified glucose data by modifying the user glucose values based on the modification amount; and
generating an indication of the modified glucose data to cause a user interface of a display device to display the modified glucose data.
Independent Claim 19 recites:
A method implemented by a computing device, the method comprising:
receiving session data describing historic user glucose values measured by a glucose sensor of a continuous glucose monitoring (CGM) system;
receiving non-glucose data that includes heart-beat interval data captured by a heart-rate sensor of the CGM system;
determining historic heart rate variability values of a user of the CGM system based on the heart-beat interval data over a moving time window;
generating a probabilistic model configured to output a probability that the user will experience a glucose value and a confidence level corresponding to the probability, wherein the probability and the confidence level are determined based on the session data and the heart-rate variability values;
generating modified session data by wherein generating the modified session data comprises:
modifying the historic user glucose values based on a modification amount, the modification amount determined based on the probability and the confidence level; and
removing historic user glucose values from the session data that were measured by the glucose sensor during a temporal window that begins at a time corresponding to a timestamp of an oldest historic user glucose value described by the session data;
generating a glucose value report based on the modified session data; and
generating an indication of the glucose value report to cause a user interface of a display device to display the glucose value report.
Step 1:
The examiner determines that independent claims 14 and 19 are drawn to methods.
Step 2A Prong 1:
The above claim limitations constitute an abstract idea that is part of the Mathematical Concepts and/or Mental Processes group identified in the 2019 Revised Patent Subject Matter Eligibility Guidance published in the Federal Register (84 FR 50) on January 7, 2019.
“A mathematical relationship is a relationship between variables or numbers. A mathematical relationship may be expressed in words ….” October 2019 Update: Subject Matter Eligibility, II. A. i. “[T]here are instances where a formula or equation is written in text format that should also be considered as falling within this grouping.” Id. at II. A. ii. “[A] claim does not have to recite the word “calculating” in order to be considered a mathematical calculation.” Id. at II. A. iii. See for example, SAP Am., Inc. v. InvestPic, LLC, 898 F.3d 1161, 1163-65 (Fed. Cir. 2018).
The claimed steps of receiving, accessing, predicting, determining, and generating recite mental processes and/or mathematical concepts (i.e., mathematical relationships, mathematical formulas or equations, and mathematical calculations).
The step of “determining” historic heart rate variability values in claims 14 and 19 are part of the mathematical concepts grouping which uses concepts from statistics, signal processing, and time-series analysis to calculate how much a series fluctuates within a moving window. The step of “generating” a probabilistic model in claims 14 and 19 is part of the mathematical concepts grouping. A probabilistic model is merely a formal mathematical representation of uncertainty, mathematically describing the likelihood of events or outcomes among random variables. The steps of “determining” a modification amount in claim 14 and “generating” modified data in claims 14 and 19 are part of the mathematical concepts grouping, particularly mathematical optimization. The modification amount is merely an adjustment or correction applied to a value to achieve a desired property, such as improved signal-to-noise ratio, amplitude scaling, or error minimization. The steps of “modifying” glucose values and “removing” glucose values in claim 19 is part of the mathematical concepts grouping wherein data in mathematically manipulated by various mathematical operations (i.e. addition, subtraction, etc.).
The claimed steps of determining, generating, modifying, and removing can be practically performed in the human mind using mental steps or basic critical thinking, which are types of activities that have been found by the courts to represent abstract ideas.
“[T]he ‘mental processes’ abstract idea grouping is defined as concepts performed in the human mind, and examples of mental processes include observations, evaluations, judgments, and opinions.” MPEP 2106.04(a)(2) III. The pending claims merely recite steps for estimation that include observations, evaluations, and judgments.
Examples of ineligible claims that recite mental processes include:
• a claim 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,
Electric Power Group, LLC v. Alstom, S.A.;
• claims to “comparing BRCA sequences and determining the existence of alterations,” where the claims cover any way of comparing BRCA sequences such that the comparison steps can practically be performed in the human mind,
University of Utah Research Foundation v. Ambry Genetics Corp.
• a claim to collecting and comparing known information, which are steps that can be practically performed in the human mind, Classen Immunotherapies, Inc. v. Biogen IDEC.
See p. 7-8 of October 2019 Update: Subject Matter Eligibility.
Regarding the dependent claims 15-18, 20-21, 23-25, and 27-29, the dependent claims are directed to either 1) steps that are also abstract or 2) additional data output that is well-understood, routine and previously known to the industry. Although the dependent claims are further limiting, they do not recite significantly more than the abstract idea. A narrow abstract idea is still an abstract idea and an abstract idea with additional well-known equipment/functions is not significantly more than the abstract idea.
Step 2A Prong 2:
This judicial exception (abstract idea) in Claims 14-29 is not integrated into a practical application because:
• The abstract idea amounts to simply implementing the abstract idea on a computing device. For example, the recitations regarding the generic computing components for receiving, accessing, predicting, determining, and generating merely invoke a computer as a tool.
• The data-gathering step (“receiving” data) and the data-output (“generating” an indication) step do not add a meaningful limitation to the method as they are insignificant extra-solution activity.
• There is no improvement to a computer or other technology. “The McRO court indicated that it was the incorporation of the particular claimed rules in computer animation that "improved [the] existing technological process", unlike cases such as Alice where a computer was merely used as a tool to perform an existing process.” MPEP 2106.05(a) II. The claims recite a computing device that is used as a tool for determining, generating, modifying, and removing.
• The claims do not apply the abstract idea to effect a particular treatment or prophylaxis for a disease or medical condition. Rather, the abstract idea is utilized to determine a relationship among data to estimate bio-information.
• The claims do not apply the abstract idea to a particular machine. “Integral use of a machine to achieve performance of a method may provide significantly more, in contrast to where the machine is merely an object on which the method operates, which does not provide significantly more.” MPEP 2106.05(b). II. “Use of a machine that contributes only nominally or insignificantly to the execution of the claimed method (e.g., in a data gathering step or in a field-of-use limitation) would not provide significantly more.” MPEP 2106.05(b) III. The pending claims utilize a computing device for determining, generating, modifying, and removing. The claims do not apply the obtained prediction to a particular machine. Rather, the data is merely output in a post-solution step.
Step 2B:
The additional elements are identified as follows: heart rate monitor/sensor.
Those in the relevant field of art would recognize the above-identified additional elements as being well-understood, routine, and conventional means for data-gathering and computing, as demonstrated by
• Applicant’s specification (e.g. paragraph [0069]) which discloses that the heart rate monitor comprise generic components that are configured to perform the generic functions that are well-understood, routine, and conventional activities previously known to the pertinent industry.
• Applicant’s Background in the specification; and
• The non-patent literature of record in the application.
Thus, the claimed additional elements “are so well-known that they do not need to be described in detail in a patent application to satisfy 35 U.S.C. § 112(a).” Berkheimer Memorandum, III. A. 3.
Furthermore, the court decisions discussed in MPEP § 2106.05(d)(lI) note the well-understood, routine and conventional nature of such additional generic computer components as those claimed. See option III. A. 2. in the Berkheimer memorandum.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the units associated with the steps do not add meaningful limitation to the abstract idea. A computer, processor, memory, or equivalent hardware is merely used as a tool for executing the abstract idea(s). The process claimed does not reflect an improvement in the functioning of the computer.
When considered in combination, the additional elements (i.e. the generic computer functions and conventional equipment/steps) do not amount to significantly more than the abstract idea. Looking at the claim limitations as a whole 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.
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.
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 14-16 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Kovatchev (US 20120059353 A1) in view of Fleischer (US 20170368258 A1), Rebec (US 20210228114 A1), Madl (US 20180177415 A1), and Jin (US 20180206767 A1).
Regarding claim 14, Kovatchev teaches a method implemented by a computing device, the method comprising:
receiving glucose data describing user glucose values measured by a glucose sensor of a continuous glucose monitoring (CGM) system [0067 “The CPHS 406 takes as input the blood glucose data acquired by the CGM 404”];
receiving non-glucose data that includes heart-beat interval data [0066 “heart rate information”] captured by a heart-rate sensor of the CGM system [0113 “heart rate sensor”];
determining historic [0120 “Memory 1224 also stores blood glucose values of the patient 1212, the insulin dose values, the insulin types, and the parameters used by the microprocessor 1222 to calculate future blood glucose values, supplemental insulin doses, and carbohydrate supplements”] heart rate variability values of a user of the CGM system [0066 “…other inputs are available to the CPHS, including meal information, indications of physical activity, and heart rate information”];
determining a modification amount as a numeric correction amount based on the non-glucose data [0068 “When the CPHS (and related method and computer program product) has access to other data in addition to CGM data, an embodiment of the invention can correct the glucose signal used in the risk calculation”];
generating modified glucose data by modifying the user glucose values based on the modification amount [0068 “With the additional input data it is possible to compute a corrected glucose concentration…”]; and
generating an indication of the modified glucose data for display in a user interface of a display device [0067 “Depending on the risk of hypoglycemia, the visual indicator 410, displays a colored light (or other indicator as desired or required)”].
Kovatchev teaches receiving heart-beat interval data captured by a heart-rate sensor and determining historic heart rate variability values, but fails to teach the historic heart rate variability values are based on the heart-beat interval data over a moving time window.
Fleischer teaches the historic heart rate variability values are based on the heart-beat interval data over a moving time window [0088 “The HRV signal was analyzed with a five min, 90% overlapping sliding window calculating typical derived measures describing HRV”].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to take the teachings of Kovatchev and incorporate the teachings of Fleischer to include the historic heart rate variability values are based on the heart-beat interval data over a moving time window. Doing so configures the system to capture temporal variability and fluctuations, improve real-time detection, reduce noise, and enables detection of localized patterns and anomalies, thus improving the diagnostic efficiency of the system.
Kovatchev teaches determining a modification amount based on the non-glucose data [0068], but fails to teach determining a probability that the user will experience a particular glucose value and a confidence level corresponding to the probability, wherein the probability and the confidence level are determined based on the glucose data and the non-glucose data.
Rebec teaches determining a probability that the user will experience a particular glucose value and a confidence level corresponding to the probability, wherein the probability and the confidence level are determined based on the glucose data and the non-glucose data [0140 “…the pattern recognition module may include some estimation of probability that data newly acquired via the data acquisition module 415 corresponds to a situation where reported glucose values may be inaccurate (or accurate). This probability/likelihood may impact some aspects of method 300 as discussed with regard to FIG. 3, for example in terms of assessing whether or not compensated/corrected glucose values can be accurately reported to a user and/or with what level of confidence the user should assume the corrected glucose values correspond to”, see also 0178 “…adaptively correcting/compensating reported glucose values based on the retrieved temperature data and/or accelerometer data, in conjunction with the retrieved CGM current data”].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to take the teachings of Kovatchev and incorporate the teachings of Rebec to include determining a probability that the user will experience a particular glucose value and a confidence level corresponding to the probability, wherein the probability and the confidence level are determined based on the glucose data and the non-glucose data. Doing so configures the system to “…improve overall CAM device operation, quality of data provided via a CAM device may be enhanced, and user health and safety profile…”, as recognized by the abstract in Rebec.
Kovatchev teaches providing an indication of modified glucose data [0067], but fails to teach the system causes a user interface of a display device to display in a user interface of a display device the modified glucose data.
Rebec teaches the system causes a user interface of a display device [0034 “…a display operably linked to the computing device”] to display in a user interface of a display device the modified glucose data [0034 “…the computing device may store further instructions to send the corrected glucose values to the display device for viewing by the user, along with an indication that the values correspond to the corrected glucose values.”].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to take the teachings of Kovatchev and incorporate the teachings of Rebec to include the system causes a user interface of a display device to display in a user interface of a display device the modified glucose data. Doing so configures the system to inform the user of the results of the acquired data representing their current condition/diagnosis.
The combination of Kovatchev and Rebec teaches determining a probability that the user will experience a glucose value, but fails to explicitly teach generating a probabilistic model.
Madl teaches generating a probabilistic model [0015 “…the model may provide a probability that the user has the disease or condition in question based on how well the measured HRV information matches the model. If the HRV information matches the model (e.g., if the probability exceeds a threshold value), block 108 generates an alert”].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to take the teachings of Kovatchev and Rebec and incorporate the teachings of Madl to include generating a probabilistic model. Doing so configures the system to provide a means to inform a user/patient of the likelihood of a glucose event prior to it happening, which increases the amount of time the user/patient has to take medication or seek medical attention if needed.
Kovatchev teaches determining a modification amount based on non-glucose levels, but fails to teach the modification amount is explicitly based on heart-beat interval data.
Jin teaches the modification amount is based on heart-beat interval data [0035 “…obtain fundamental blood glucose signals in real time by correcting the pulse signal indicating the changes in the blood flow rate according to heart beats and the skin environment signal that can change according to the location of detection…”].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to take the teachings of Kovatchev and incorporate the teachings of Jin to include the modification amount is based on heart-beat interval data. Doing so configures the system to correct the glucose signals with data that would skew results, providing for an accurate assessment of the patient’s glucose levels.
Regarding claim 15, Kovatchev, Fleischer, Rebec, Madl, and Jin teach the method as described in claim 14, further comprising: identifying an error component included in the glucose data [Kovatchev 0068 “With the additional input data it is possible to compute a corrected glucose concentration…”] based on the historic heart rate variability values of the user [Kovatchev 0066 “…heart rate information”]; and
determining the modification amount based on the error component [Kovatchev 0068 “
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Regarding claim 16, Kovatchev, Fleischer, Rebec, Madl, and Jin teach the method as described in claim 14, wherein the modified glucose data does not include an error component based on the historic heart rate variability values of the user [Rebec 0178, the correction factors are disclosed as temperature and accelerometer data].
Regarding claim 18, Kovatchev, Fleischer, Rebec, Madl, and Jin teach the method as described in claim 14, wherein historic heart rate variability values [Kovatchev 0066 “…other inputs are available to the CPHS, including meal information, indications of physical activity, and heart rate information”] are measured by a heart rate monitor [Kovatchev 0113 “heart rate sensor”] of the CGM system.
Claim 17 is rejected under 35 U.S.C. 103 as being unpatentable over Kovatchev, Fleischer, Rebec, Madl, and Jin as applied to claim 15 above, and further in view of Goode (US 20050027463 A1).
Regarding claim 17, Kovatchev, Fleischer, Rebec, Madl, and Jin teach the method as described in claim 15, further comprising: determining a risk classification [Kovatchev 0067 “Based on this data, the CPHS 406 evaluates the risk of hypoglycemia and determines whether and what kind of action to take”]; and
generating an indication of the risk classification for display in the user interface of the display device [Kovatchev 0067 “…present to the user red, yellow, or green lights indicating the risk of hypoglycemia”].
Kovatchev and Rebec fail to teach the risk calculation is of an error component.
Goode teaches the risk calculation is of an error component [0263 “…an error grid analysis that assigns a specific level of clinical risk to any possible error between two time corresponding glucose measurements”].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to take the teachings of Kovatchev and Rebec and incorporate the teachings of Goode to include the risk calculation is of an error component. Doing so signifies a degree of risk posed by deviation of various parameters, as recognized by Goode para. 0263.
Claims 19 and 21 are rejected under 35 U.S.C. 103 as being unpatentable over Kovatchev in view of Enomoto (US 20200312451 A1), Rebec, Fleischer, Madl, and Jin.
Regarding claim 19, Kovatchev teaches a method implemented by a computing device, the method comprising:
receiving session data describing historic user glucose values measured by a glucose sensor of a continuous glucose monitoring (CGM) system [0120 “Each blood glucose value and insulin dose value may be stored in memory 1224 with a corresponding date and time”];
receiving non-glucose data that includes heart-beat interval data 0066 “heart rate information”] captured by a heart-rate sensor of the CGM system [0113 “heart rate sensor”];
determining historic [0120 “Memory 1224 also stores blood glucose values of the patient 1212, the insulin dose values, the insulin types, and the parameters used by the microprocessor 1222 to calculate future blood glucose values, supplemental insulin doses, and carbohydrate supplements”] heart rate variability values of a user of the CGM system [0066 “…other inputs are available to the CPHS, including meal information, indications of physical activity, and heart rate information”];
generating a glucose value report based on the modified session data [0068 “…it is possible to compute a corrected glucose concentration…”]; and
generating an indication of the glucose value report for display in a user interface of a display device [0118 “The results additionally may be displayed on a digital or analog display device”].
Kovatchev fails to teach generating modified session data by removing historic user glucose values from the session data that were measured by the glucose sensor during a temporal window that begins at a time corresponding to a timestamp of an oldest historic user glucose value described by the session data.
Enomoto teaches generating modified session data by removing historic user physiological values from the session data that were measured by the sensor [0017 “The sensors attached to the patient 21 output sensor signals corresponding to the detected physiological information”] during a temporal window that begins at a time corresponding to a timestamp of an oldest historic user glucose value described by the session data [0022 “…old data is automatically deleted, sequentially from the oldest data”].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to take the teachings of Kovatchev and incorporate the teachings of Enomoto to include generating modified session data by removing historic user glucose values from the session data that were measured by the glucose sensor during a temporal window that begins at a time corresponding to a timestamp of an oldest historic user glucose value described by the session data. Doing so configures the system to remove data that is less relevant than newer data for analysis, where data is removed at a desired amount that maximizes the amount of data used for a more informative analysis while also minimizing operating costs by limiting storage capacity.
A combination of Kovatchev and Enomoto teach determining a modification amount based on the non-glucose data [Kovatchev 0068] and generating modified session data [Enomoto 0017 and 0022], but fails to teach determining a probability that the user will experience a particular glucose value and a confidence level corresponding to the probability, wherein the probability and the confidence level are determined based on the session data; and wherein generating the modified session data comprises: modifying the historic user glucose values based on a modification amount, the modification amount determined based on the probability and the confidence level.
Rebec teaches determining a probability that the user will experience a particular glucose value and a confidence level corresponding to the probability, wherein the probability and the confidence level are determined based on the session data [0140 “…the pattern recognition module may include some estimation of probability that data newly acquired via the data acquisition module 415 corresponds to a situation where reported glucose values may be inaccurate (or accurate). This probability/likelihood may impact some aspects of method 300 as discussed with regard to FIG. 3, for example in terms of assessing whether or not compensated/corrected glucose values can be accurately reported to a user and/or with what level of confidence the user should assume the corrected glucose values correspond to”, see also 0178 “…adaptively correcting/compensating reported glucose values based on the retrieved temperature data and/or accelerometer data, in conjunction with the retrieved CGM current data”]; and
wherein generating the modified session data comprises:
modifying the historic user glucose values based on a modification amount, the modification amount determined based on the probability and the confidence level [0080 “…the process of providing corrected analyte values involves a process of learning situations/conditions where inaccurate values are expected or predicted to be reported, and instead of reporting the inaccurate values, providing corrected values that are based on some level of analysis of historical and/or current data trends”].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to take the teachings of Kovatchev and incorporate the teachings of Rebec to determining a probability that the user will experience a particular glucose value and a confidence level corresponding to the probability, wherein the probability and the confidence level are determined based on the session data; and wherein generating the modified session data comprises: modifying the historic user glucose values based on a modification amount, the modification amount determined based on the probability and the confidence level. Doing so configures the system to “…improve overall CAM device operation, quality of data provided via a CAM device may be enhanced, and user health and safety profile…”, as recognized by the abstract in Rebec.
Kovatchev teaches providing an indication of modified glucose data [0067], but fails to teach the system causes a user interface of a display device to display in a user interface of a display device the modified glucose data.
Rebec teaches the system causes a user interface of a display device [0034 “…a display operably linked to the computing device”] to display in a user interface of a display device the modified glucose data [0034 “…the computing device may store further instructions to send the corrected glucose values to the display device for viewing by the user, along with an indication that the values correspond to the corrected glucose values.”].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to take the teachings of Kovatchev and incorporate the teachings of Rebec to include the system causes a user interface of a display device to display in a user interface of a display device the modified glucose data. Doing so configures the system to inform the user of the results of the acquired data representing their current condition/diagnosis.
Kovatchev teaches receiving heart-beat interval data captured by a heart-rate sensor and determining historic heart rate variability values, but fails to teach the historic heart rate variability values are based on the heart-beat interval data over a moving time window.
Fleischer teaches the historic heart rate variability values are based on the heart-beat interval data over a moving time window [0088 “The HRV signal was analyzed with a five min, 90% overlapping sliding window calculating typical derived measures describing HRV”].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to take the teachings of Kovatchev and incorporate the teachings of Fleischer to include the historic heart rate variability values are based on the heart-beat interval data over a moving time window. Doing so configures the system to capture temporal variability and fluctuations, improve real-time detection, reduce noise, and enables detection of localized patterns and anomalies, thus improving the diagnostic efficiency of the system.
The combination of Kovatchev and Rebec teaches determining a probability that the user will experience a glucose value, but fails to explicitly teach generating a probabilistic model.
Madl teaches generating a probabilistic model [0015 “…the model may provide a probability that the user has the disease or condition in question based on how well the measured HRV information matches the model. If the HRV information matches the model (e.g., if the probability exceeds a threshold value), block 108 generates an alert”].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to take the teachings of Kovatchev and Rebec and incorporate the teachings of Madl to include generating a probabilistic model. Doing so configures the system to provide a means to inform a user/patient of the likelihood of a glucose event prior to it happening, which increases the amount of time the user/patient has to take medication or seek medical attention if needed.
Kovatchev teaches determining a modification amount based on non-glucose levels, but fails to teach the modification amount is explicitly based on heart-beat interval data.
Jin teaches the modification amount is based on heart-beat interval data [0035 “…obtain fundamental blood glucose signals in real time by correcting the pulse signal indicating the changes in the blood flow rate according to heart beats and the skin environment signal that can change according to the location of detection…”].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to take the teachings of Kovatchev and incorporate the teachings of Jin to include the modification amount is based on heart-beat interval data. Doing so configures the system to correct the glucose signals with data that would skew results, providing for an accurate assessment of the patient’s glucose levels.
Regarding claim 21, Kovatchev, Enomoto, Rebec, Fleischer, Madl, and Jin teach the method as described in claim 19, but fail to teach the temporal window ends at time that is 24 hours after the time corresponding to the timestamp. Upon review of the disclosure, the temporal window ending at 24 hours is not stated as critical or important (see par. 0134). However, Enomoto teaches a variable temporal window [Enomoto 0022-0024] wherein data that is n – 1 hours from time point t1 are deleted.
It would have been obvious to one of ordinary skill in the art at the filing date of the invention to adjust the temporal window to an optimal range/value, since it has been held that where the general conditions of a claim are disclosed in the prior art, discovering the optimum or working ranges involves only routine skill in the art. In re Aller, 105 USPQ 233. See MPEP 2144.05.II. The Examiner notes that a particular parameter must be recognized as a result effective variable, in this case, that parameter is the temporal window which achieves the recognized result of maximizing the data used in analysis to improve diagnostic accuracy whilst limiting storage capacity which lowers operating costs and processing time, therefore, one of ordinary skill in the art at the filing date of the invention would have found the claimed range through routine experimentation. In re Antonie, 559 F.2d 618, 195 USPQ 6 (CCPA 1977). See also In re Boesch, 617 F.2d 272, USPQ 215 (CCPA 1980).
Claim 20 is rejected under 35 U.S.C. 103 as being unpatentable over Kovatchev, Enomoto, Rebec, Fleischer, Madl, and Jin as applied to claim 19 above, and further in view of Cohen (US 20060031094 A1).
Regarding claim 20, Kovatchev, Enomoto, Rebec, Fleischer, Madl, and Jin teach the method as described in claim 19, but fails to teach wherein the session data is received from a virtual container that limits access to the session data based on a risk classification associated with the access to the session data.
Cohen teaches the session data is received from a virtual container [0055 “database”] that limits access to the session data based on a risk classification associated with the access to the session data [0055 “Embodiments of the database layer 28 and other components of the system 16 may employ suitable data security measures for securing personal medical information of subjects, while also allowing non-personal medical information to be more generally available for analysis”].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to take the teachings of Kovatchev, Enomoto, Rebec, Fleischer, Madl, and Jin and incorporate the teachings of Cohen to include the session data is received from a virtual container that limits access to the session data based on a risk classification associated with the access to the session data. Doing so configures the system to comply with “…suitable government regulations, industry standards, policies or the like, including, but not limited to the Health Insurance Portability and Accountability Act of 1996 (HIPAA)”, as recognized by Cohen para. 0055.
Claims 22-24 are rejected under 35 U.S.C. 103 as being unpatentable over Kovatchev, Rebec, Fleischer, Madl, and Jin as applied to claim 14 above, and further in view of Chin (US 20150272510 A1).
Regarding claim 22, Kovatchev, Rebec, Fleischer, Madl, and Jin teach the method as described in claim 14, wherein:
the non-glucose data of a user of the CGM system [Kovatchev 0066 “…other inputs are available to the CPHS, including meal information, indications of physical activity, and heart rate information”];
the modification amount based on the non-glucose data [Kovatchev 0068 “When the CPHS (and related method and computer program product) has access to other data in addition to CGM data, an embodiment of the invention can correct the glucose signal used in the risk calculation”].
The combination of Kovatchev and Rebec teach acquisition and application of non-glucose data to determine a confidence level and probability, but fails to teach the non-glucose data of a user comprises historic perspiration values.
Chin teaches the non-glucose data of a user comprises historic perspiration values [0025 “A historic physiological datum 205 may comprise a contemporary physiological datum 208 (e.g….sweat rate…) that was collected in the past”].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to take the teachings of Kovatchev and Rebec and incorporate the teachings of Chin to include the non-glucose data of a user comprises historic perspiration values. Doing so configures the system “…to correlate an historic abnormality 206 with an historic non-physiological datum 204, historic physiological datum 205, or historic biosignal datum 203 and derive or modify (e.g. refine or learn) a non-physiological risk factor 101, physiological risk indicator 202, or biosignal risk indicator 201”, as recognized by Chin para. 0029.
Regarding claim 23, Kovatchev, Rebec, Fleischer, Madl, Jin, and Chin teach the method as described in claim 22, further comprising:
identifying an error component included in the glucose data [Kovatchev 0068 “With the additional input data it is possible to compute a corrected glucose concentration…”] based on the historic perspiration values of the user [Chin 0025 “sweat rate”, with “rate” being understood as progression over time]; and
determining the modification amount based on the error component [Kovatchev 0068 “
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Regarding claim 24, Kovatchev, Rebec, Fleischer, Madl, Jin, and Chin teach the method as described in claim 22, wherein the modified glucose data does not include the error component based on the historic perspiration values of the user [Rebec 0178, the correction factors are disclosed as temperature and accelerometer data].
Claim 25 is rejected under 35 U.S.C. 103 as being unpatentable over K Kovatchev, Rebec, Fleischer, Madl, Jin, and Chin as applied to claim 23 above, and further in view of Goode.
Regarding claim 25, Kovatchev, Rebec, Fleischer, Madl, Jin, and Chin teach the method as described in claim 23, further comprising:
determining a risk classification [Kovatchev 0067 “Based on this data, the CPHS 406 evaluates the risk of hypoglycemia and determines whether and what kind of action to take”]; and
generating an indication of the risk classification for display in the user interface of the display device [Kovatchev 0067 “…present to the user red, yellow, or green lights indicating the risk of hypoglycemia”].
Kovatchev, Rebec, Fleischer, Madl, Jin, and Chin fail to teach the risk calculation is of an error component.
Goode teaches the risk calculation is of an error component [0263 “…an error grid analysis that assigns a specific level of clinical risk to any possible error between two time corresponding glucose measurements”].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to take the teachings of Kovatchev, Rebec, Fleischer, Madl, Jin, and Chin and incorporate the teachings of Goode to include the risk calculation is of an error component. Doing so signifies a degree of risk posed by deviation of various parameters, as recognized by Goode para. 0263.
Claims 26-29 are rejected under 35 U.S.C. 103 as being unpatentable over Kovatchev, Rebec, Fleischer, Madl, and Jin as applied to claim 14 above, and further in view of Constantin (US 20190252079 A1).
Regarding claim 26, Kovatchev, Rebec, Fleischer, Madl, and Jin teach the method as described in claim 14, wherein:
the non-glucose data further describes historic steps taken by the user of the CGM system [0066 “…other inputs are available to the CPHS, including meal information, indications of physical activity, and heart rate information”];
the probability and the confidence level are further determined based on the historic steps [Kovatchev 0120 “Memory 1224 also stores blood glucose values of the patient 1212, the insulin dose values, the insulin types, and the parameters used by the microprocessor 1222 to calculate future blood glucose values, supplemental insulin doses, and carbohydrate supplements”];
the method further comprises determining the glucose data [Kovatchev 0067], the non-glucose data [Kovatchev 0120], the probability [Rebec 0140], and the confidence level [Rebec 0140]; and
generating the modified glucose data [Kovatchev 0068 “With the additional input data it is possible to compute a corrected glucose concentration…”].
Kovatchev, Rebec, Fleischer, Madl, and Jin fail to teach determining that the glucose value event did not occur based on the glucose data.
Constantin teaches determining that the glucose value event did not occur based on the glucose data [0458 “…the first real-time datum may indicate a deviation in meal-time, a missed, early, or late insulin dose, a variation in physical activity (e.g. missed workout or atypical workout), or an early or late awakening”].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to take the teachings of Kovatchev, Rebec, Fleischer, Madl, and Jin and incorporate the teachings of Constantin to include determining that the glucose value event did not occur based on the glucose data. Doing so configures the system to incorporate patient behaviors and patterns into an analysis model to help predict “normal” variations in data, and alerting a user to abnormal measurements.
Regarding claim 27, Kovatchev, Rebec, Fleischer, Madl, Jin, and Constantin teach the method as described in claim 26, wherein the non- glucose data is generated at least partially from forces measured by an accelerometer [Constantin 0459 “accelerometer data”, see also Rebec 0178] of the CGM system.
Regarding claim 28, Kovatchev, Rebec, Fleischer, Madl, Jin, and Constantin teach the method as described in claim 26, wherein the glucose data includes an error component because the glucose value event did not occur [Constantin 0458 “…the first real-time datum may indicate a deviation in meal-time, a missed, early, or late insulin dose, a variation in physical activity (e.g. missed workout or atypical workout), or an early or late awakening”] and wherein the modified glucose data does not include an error component based on the probability of the glucose event [Rebec 0178, the correction factors are disclosed as temperature and accelerometer data].
Regarding claim 29, Kovatchev, Rebec, Fleischer, Madl, Jin, and Constantin teach the method as described in claim 26, further comprising generating a confirmation prompt for display in the user interface [Constantin 0590 “The components that comprise the user interface 222 may provide controls to interact with the user (e.g., the host). One or more buttons 224 may allow, for example, toggle, menu selection, option selection, status selection, yes/no response to on-screen questions, a “turn off” function (e.g., for an alarm), an “acknowledged” function (e.g., for an alarm), a reset, and/or the like”] of the display device to receive a confirmation indication from a user of the CGM system [Constantin 0354 “…the system may then inquire with the user to obtain corrected meal information…”], the confirmation indication confirming the glucose value event did not occur [Constantin 0354 “Did you eat something else?” or “Did you not eat the chicken?”].
Conclusion
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/JONATHAN M HANEY/Examiner, Art Unit 3791
/JUSTIN XU/Primary Examiner, Art Unit 3791