This Office action is in response to application filed on 11/12/2024.
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 .
Preliminary Amendment
Preliminary Amendments filed 11/12/2024 should indicate the change, e.g., if the claims have been changed, the preliminary amendment should be accompanied by a written statement indicating specific support for the change. If the support is implicit, an explanation is beneficial.
Information Disclosure Statement (IDS) Not Considered
The information disclosure statement filed on 9/06/2024 fails to comply with the provisions of 37 CFR 1.97, 1.98 and MPEP § 609 because the information listed on the IDS form under the citation numbers 1 to 3 is incorrect. It has been placed in the application file, but the information referred to therein has not been considered as to the merits. Applicant is advised that the date of any resubmission of any item of information contained in this information disclosure statement or the submission of any missing element(s) will be the date of submission for purposes of determining compliance with the requirements based on the time of filing the statement, including all requirements for statements under 37 CFR 1.97(e). See MPEP § 609.05(a)
Drawing Objections
The drawings filed on 6/19/2024 are objected to because they fail to comply with 37 CFR 1.84(p)(5), the drawings do not include:
Figures 13A-13B should be provided with the vertical text labels, i.e., what they represent .
Figures 20-21 should be provided with the vertical text labels, i.e., what they represent .
Appropriate correction is required.
Notes: Corrected drawing sheets in compliance with 37 CFR 1.121(d), or amendment to the specification to add the reference character(s) in the description in compliance with 37 CFR 1.121(b) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either "Replacement Sheet" or "New Sheet" pursuant to 37 CFR 1.121(d) If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Claim Objections
Claims 2-4 are objected to because of the following informalities:
Claim 2, line 14 recites “the application” should read “[[the]]an application”.
Claim 3 recites “engaging sensor electronics” and claim 4 recites “the engaging of the sensor electronics” should be consistent. It is suggested to rewrite claim 4 as “the engaging .
Appropriate correction is required.
Statement Regarding 35 USC § 101
The claims are analyzed based on the 2019 Revised Patent Subject Matter Eligibility Guidance (PEG) to determine whether the claim is directed to a judicial exception. Claims 2 and 21 recite a method and system for processing sensor data. However, the claims do not recite any of the judicial exceptions enumerated in the 2019 PEG. For instance, the claims do not recite a mental process because the claim, under its broadest reasonable interpretation, does not cover performance in the mind or can practically perform in the human mind. Further, the claims do not recite any method of organizing human activity. Finally, the claims do not recite a mathematical relationship, formula, or calculation. Thus, the claims are eligible because they do not recite a judicial exception.
Claim Rejections - 35 USC § 102
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 2-21 are rejected under 35 U.S.C. 102(a)(1) as being anticipated over Goode, Jr. et al., hereinafter Goode (US 2006/0258929).
As per Claim 2, Goode teaches a method for processing sensor data of an analyte sensor implanted at least partially within a body, comprising:
determining an impedance value associated with the analyte sensor based at least on a response to a stimulus signal applied to the analyte sensor ( The electrode domain 47 is provided to ensure that an electrochemical reaction occurs between the electroactive surfaces of the working electrode and the reference electrode, considered the system’s electronics using impedance measurement, and when a stimulus signal, i.e., an AC voltage/current perturbation, is applied to the analyte sensor, the system measures the resulting impedance value, see [0224], [0374]-[0375]. In addition, “electrochemical reaction” considered a central part of the process analyzed and determined by impedance monitoring, e.g., the sensitivity, “ sensor signal strength with respect to analyte concentration”, is used to determine the stability of the sensor, see [0427], the receiver processes these signals to determine additional information about the sensor and/or analyte concentration, see [0438], are considered determining an impedance value based on a response to a stimulus signal applied to the analyte sensor because the electrochemical reaction is the response to a stimulus signal applied to the analyte signal );
applying, based at least on the impedance value, a first time-dependent algorithmic function to a first sensor signal to compensate for signal drift of the analyte sensor, wherein the first sensor signal is associated with a first elapsed time since the analyte sensor was implanted (compensate for the sensitivity differences in blood sugar level, considered compensating for signal drift of the analyte sensor, see [0435], it is noted a predicted value is used to apply compensation for signal drift, see [0454]. Fig 30 shows sensor data from an un-calibrated long term sensor “upper screen” considered “first sensor signal”, see [0091], and day 1 through day 4, considered “initial function” at “first time-dependent algorithm function”, see [0496]. It is noted, signal drift as a change in the measured impedance value, e.g., baseline signal drift is considered a major component of signal drift of an analyte sensor over time, see [0355] );
applying, based at least on the impedance value, a second time-dependent algorithmic function to a second sensor signal to further compensate for signal drift of the analyte sensor, wherein the second sensor signal is associated with a second elapsed time since the analyte sensor was implanted, and wherein the second time-dependent algorithmic function is different from the first time-dependent algorithmic function (Fig 30 shows sensor data from a calibrated short term sensor “lower screen” considered “second sensor signal”, see [0091], and on Day 5 “short term sensor integration” at elapsed time considered “second time-dependent algorithm function”, see [0496]. Applying a temperature measurement to adjust the calculated glucose value is considered “second compensation”, see [0384]. Thus, a first compensation for the long term is different with a second compensation for the short term); and
adjusting a parameter of the analyte sensor based at least on a comparison between a first analyte value derived from the application of the first time-dependent algorithmic function and a second analyte value derived from the application of the second time-dependent algorithmic function ( the data from the long term sensor can be adjusted using additional reference data, i.e., reference data from a short term sensor, considered a function of the analyte sensor’s calibration parameters based on the analyte value, see [0146], correct regression if the slope and/or baseline fall outside acceptable [0441], [0444], [0472] ).
As per Claim 3, Goode teaches the method of claim 2, further comprising engaging sensor electronics associated with the analyte sensor with a housing (see [0058], [0061]-[0062], [0321]-[0323] ) to initialize the analyte sensor (see [0388]-[0389], [0418] ).
As per Claim 4, Goode teaches the method of claim 3, wherein the engaging of the sensor electronics with the housing is detected and initialization commences automatically upon detection of the engagement (see [0350], [0388]-[0389] ).
As per Claim 5, Goode teaches the method of claim 2, further comprising determining whether the analyte sensor has been previously used (e.g., sensor A was determined previously used before it was removed at 23 months, see [0147], [0418]-[0419] ).
As per Claim 6, Goode teaches the method of claim 5, wherein determining whether the analyte sensor has been previously used comprises comparing a conversion function of the analyte sensor with a conversion function of a previously removed analyte sensor (regression equation y=mx=b, where conversion function, i.e., slope and baseline calculation between the two sensors, see [0495], the conversion function comprises two different “first/second” regression lines, the first regression line “historical baseline” considered the conversion function of the previously removed analyte sensor, and a second regression line considered the conversion function of the analyte sensor, i.e., comparing two regression lines., the first regression line is applied when the estimated blood glucose concentration is below a threshold and the second regression line is applied when the estimated blood glucose concentration is higher a threshold, see [0435], [0444] ).
As per Claim 7, Goode teaches the method of claim 5, wherein determining whether the analyte sensor has been previously used comprises reading a raw signal of the analyte sensor ( see [0150], [0374], [0398] ).
As per Claim 8, Goode teaches the method of claim 5, wherein determining whether the analyte sensor has been previously used comprises comparing a sensitivity and/or baseline of the analyte sensor with a sensitivity and/or baseline of a previously removed analyte sensor (see [0438]-[0439] ).
As per Claim 9, Goode teaches the method of claim 5, wherein determining whether the analyte sensor has been previously used comprises comparing a trend in a signal from the analyte sensor with a trend in a signal from a previously removed analyte sensor (Fig 20B shows a trend graph 184, see [0412] ).
As per Claim 10, Goode teaches the method of claim 5, wherein determining whether the analyte sensor has been previously used comprises performing two or more independent tests and determining a probability that the analyte sensor has been previously used based upon results of the two or more independent tests (the results of boundary tests derived from in vivo and in vitro testing are directly used to determine the probability or confirm whether an analyte sensor has been previously used or reused, see [0444] ).
As per Claim 11, Goode teaches the method of claim 2, wherein applying the first time-dependent algorithmic function comprises applying drift compensation to the first sensor signal ( the conversion function is adapted to compensate for the sensitivity differences in blood sugar level is considered applying drift compensating for the first sensor signal, see [0435] ).
As per Claim 12, Goode teaches the method of claim 2, wherein the first time-dependent algorithmic function and the second time-dependent algorithmic function each comprise a first boundary of acceptability and a second boundary of acceptability (see [0412], [0440]-[0444] ).
As per Claim 13, Goode teaches the method of claim 12, wherein the first boundary of acceptability comprises a first sensitivity value and the second boundary of acceptability comprises a second sensitivity value (see [0440]-[0442], [0444]).
As per Claim 14, Goode teaches the method of claim 12, wherein the first boundary of acceptability comprises a first baseline value and the second boundary of acceptability comprises a second baseline value ( the regression equation y = mx + b, where m is a slope of the line showing y goes up or down for every single step across in x, when x=0, b considered a first baseline, when x>0, i.e., x=1, b considered a second baseline, see [0440]-[0442], [0444], [0495]. Fig 20B shows upper “first” boundary includes a first baseline and lower “second” boundary includes a second baseline, see [0412] ).
As per Claim 15, Goode teaches the method of claim 12, wherein the first boundary of acceptability comprises a first drift rate of sensor sensitivity over a time period and the second boundary of acceptability comprises a second drift rate of the sensor sensitivity over time (the regression equation y = mx + b, where the slope m represents the drift rate, when x = 0, m considered a first drift rate and when x >0, e.g., x=1, m considered a second drift rate, see [0438]-[0439], m is a drift rate, the rate of change and/or directional trend of the analyte concentration overtime, see [0455], i.e., mx is fluctuated overtime, i.e., when x up, m is up and when x is down m is down ).
As per Claim 16, Goode teaches the method of claim 12, wherein the first boundary of acceptability comprises a first drift rate of a baseline over a time period and the second boundary of acceptability comprises a second drift rate of the baseline over time (it is noted the regression equation over a time period is written as y(t) = m(t) + b, where t is time and b is considered a baseline, m is a slope “drift rate” varies by time, i.e., up/down, when t = 0, m considered a first drift rate and when t >0, e.g., t=1, m considered a second drift rate, see [0438]-[0439], m is a drift rate, the rate of change and/or directional trend of the analyte concentration overtime, see [0455] ).
As per Claim 17, Goode teaches the method of claim 12, wherein the first boundary of acceptability delineates acceptable slopes and baselines of a conversion function and the second boundary of acceptability delineates acceptable slopes and baselines of the conversion function (regression equation y=mx=b, where conversion function, i.e., slope and baseline calculation between the two sensors, see [0495], Fig 22A shows a regression performed on a calibration set to obtain a conversion function, regression calculates a slope 272 and an offset 274 (y=mx+b), which defines the conversion function, and matched pairs 276 “first/second” considered boundaries of acceptability. These boundaries define the acceptable tolerance for both slope and baseline, see [0433], [0442], [0448] ).
As per Claim 18, Goode teaches the method of claim 2, wherein the first time-dependent algorithmic function and the second time-dependent algorithmic function each comprise a first parameter associated with a conversion function and a second parameter associated with the conversion function (the regression equation y=mx=b, where conversion function, i.e., slope and baseline calculation between the two sensors, see [0495], measure glucose day 1 through day 4 using time-dependent algorithm with calibration parameter “first parameter”, and day 5, followed by employing a calibration short term sensor on day 5 on the same host “second parameter”, see [0496] ).
As per Claim 19, Goode teaches the method of claim 2, wherein the first time-dependent algorithmic function and the second time-dependent algorithmic function each comprise a first drift compensation function and a second drift compensation function (the regression equation y = mx + b, where the slope m represents the drift rate, when x = 0, m considered a first drift rate and when x >0, e.g., x=1, m considered a second drift rate, see [0438]-[0439], the conversion function is adapted to compensate for the sensitivity differences in blood sugar level is considered applying drift compensating for the sensor signal, i.e., high “first” vs. low “second” see [0435] )..
As per Claim 20, Goode teaches the method of claim 19, wherein the first drift compensation function and the second drift compensation function differ in an amount of applied drift compensation (i.e., predicted value “long term” considered is applied for compensation for signal drift “first drift compensation”, see [0454], applying a temperature measurement “short term” to adjust the calculated glucose value is considered temperature compensation “second drift compensation”, see [0384]. Thus, the first compensation for the long term is different with the second compensation for the short term ).
Claim 21 is rejected for the same rationale as in claim 2. It is noted that a glucose sensor is considered an analyte sensor.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
US 2009/0156924 of Shariati et al. (Systems and methods for processing sensor data).
US 2010/0064764 of Hayter et al. (Method and system for providing calibration of an analyte sensor in an analyte monitoring system).
Any inquiry concerning this communication or earlier communications from the
examiner should be directed to LYNDA DINH whose telephone number is (571) 270-
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/LYNDA DINH/Examiner, Art Unit 2857
/LINA CORDERO/Primary Examiner, Art Unit 2857
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