]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 .
Specification
The lengthy specification has not been checked to the extent necessary to determine the presence of all possible minor errors. Applicant’s cooperation is requested in correcting any errors of which applicant may become aware in the specification.
Claim Objections
Claim 14 is objected to because of the following informalities: regarding the term “based on that the” within “determining the sensor sensitivity as the second sensitivity based on that the first sensitivity is higher than or equal to the sensor sensitivity” and ”as the second sensitivity based on that the first sensitivity is lower than the sensor sensitivity.” It is suggested to revise the term “based on that the” to be either “if” or “when” to increase readability of the claim (such that “determining the sensor sensitivity as the second sensitivity based on that the first sensitivity is higher than or equal to the sensor sensitivity” reads “determining the sensor sensitivity as the second sensitivity if the first sensitivity is higher than or equal to the sensor sensitivity”, as an example). Appropriate correction is required.
Claim 15 is similarly objected to because of the following informalities: regarding the term “based on that a state in which”. It is suggested to revise the term” to be either “if” or “when” to increase readability of the claim, resulting in “determining an average value of the first sensitivity and the second sensitivity as the third sensitivity if the first sensitivity determined at a previous time point is higher or lower than the final sensitivity of the corresponding previous time point occurs continuously.” Appropriate correction is required.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitations are:
“input unit” to obtain first biometric information in Claim 1 and its dependent claims
The claim limitation is interpreted according to [Page 62, Bottom] – [Page 63, Top] with “The term ' - unit' used in the present embodiment refers to software or a hardware Component…the "~unit" refers to components such as software components… Components and functions provided within "~unit" may be combined into a smaller number of components and "~unit" or may be further separated into additional components and "~unit."; and [Page 17, Paragraph 4] “the input unit 110 may obtain the biometric information measured by the sensor module.” The “input unit” is shown as “input unit 110” in Fig. 2.
“noise removal unit” to remove noise information in Claim 1 and its dependent claims
The claim limitation is interpreted according to the aforementioned sections of [Page 62, Bottom] – [Page 63, Top] and [Page 18, Paragraph 3] with “noise removal unit 120 may perform a function of removing noise from the biometric information. “ The “noise removal unit” is shown as “noise removal unit 120” in Fig. 2.
“preprocessing unit” to preprocess the first biometric information in Claim 1 and its dependent claims
The claim limitation is interpreted according to the aforementioned sections of [Page 62, Bottom] – [Page 63, Top] and [Page 20, Paragraph 3] with “preprocessing unit 130 may perform a function of processing the biometric information from which noise has been removed.“ The “preprocessing unit” is shown as “preprocessing unit 130” in Fig. 2.
“compensation unit” to generate compensation data in Claim 1 and its dependent claims
The claim limitation is interpreted according to the aforementioned sections of [Page 62, Bottom] – [Page 63, Top], Figures 10 and 12, and [Page 36, Paragraph 5] with “compensation unit 140 may determine any one of the values of the pre-stored table data as an offset value based on the second biometric information (S 1310).“ The “compensation unit” is shown as “compensation unit 140” in Fig. 2.
“glucose level acquisition unit” to acquire a glucose level in Claim 1 and its dependent claims
The claim limitation is interpreted according to the aforementioned sections of [Page 62, Bottom] – [Page 63, Top] and [Page 4, Paragraph 3] “glucose level acquisition unit that acquires a glucose level related to the second biometric information by reflecting the calibration algorithm and a set time delay.” The “glucose level acquisition unit” is shown as “glucose level acquisition unit 150” in Fig. 2.
“apparatus for monitoring glucose” to obtain, remove, preprocess, generate, and acquire in Claim 18
The claim limitation is interpreted according to the aforementioned sections of [Page 62, Bottom] – [Page 63, Top] and [Page 12, Paragraph 4] “the system for monitoring glucose described below may be a continuous glucose monitoring system that continuously or constantly measures and provides a glucose
concentration of a subject.” The “apparatus for monitoring glucose” is shown as “apparatus 100” in Fig. 2.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 2 – 5, 7 – 10, and 13 – 17 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 2 (line 2) recites the term “determined as noise information”. It is unclear if this is intended to be the same or different than the previously-recited noise information. For the purposes of examination, the term “determined as noise information” is deemed to claim “determined as the noise information’. Claims 3 – 5 are similarly rejected due to their dependence on Claim 2.
Claim 2 (line 3) recites the term “among first data points based on a plurality of data points included in a set time interval”. It is unclear if this is intended to be the same or different than the previously-recited plurality of data points. For the purposes of examination, the term “among first data points based on a plurality of data points included in a set time interval” is deemed to claim “among first data points of the plurality of data points included in a set time interval. Claims 3 – 5 are similarly rejected due to their dependence on Claim 2.
Claim 2 (line 4) recites the term “adjusting a value of the first data point”. It is unclear if this is intended to be the same as the previously-recited first data points or the plurality of data points. For the purposes of examination, the term “adjusting a value of the first data point” is deemed to claim “adjusting a value of a first data point of the first data points”. Claims 3 – 5 are similarly rejected due to their dependence on Claim 2.
Claim 2 (line 5) recites the term “based on a plurality of data points included in a set time interval”. It is unclear if this is intended to be the same or different than the previously-recited plurality of data points. For the purposes of examination, the term “based on a plurality of data points included in a set time interval” is deemed to claim “based on the plurality of data points included in the set time interval”. Claims 3 – 5 are similarly rejected due to their dependence on Claim 2.
Claim 3 (line 3) recites the term “determining whether any one of the data points is an outlier”. There is insufficient antecedent basis for this limitation in the claim. It is unclear if this is intended to be the same or different than the previously-recited plurality of data points or first data points. For the purposes of examination, the term “determining whether any one of the data points is an outlier” is deemed to claim “determining whether any one of the plurality of data points is an outlier data point.” Claim 4 is similarly rejected due to its dependence on Claim 3.
Claim 3 (line 3) recites the term “using a data point other than any one of the plurality of data points included in the set time interval”. It is unclear if this data point is intended to be the part of the overall plurality of data points previously-recited, or if it can be a different data point than has been recited to be collected. For the purposes of examination, the term “using a data point other than any one of the plurality of data points included in the set time interval” is deemed to claim “using an outside data point, wherein the outside data point is a data point of the plurality of data points that is not one of the plurality of data points included in the set time interval.” Claim 4 is similarly rejected due to its dependence on Claim 3.
Claim 3 (lines 5 – 6) recites the term “removing any one of the data points based on being determined that any one of the data points is the outlier.” As recited, it is unclear if the “any one of the data points” is the same or different than the previously-recited plurality of data points or first data points. Furthermore, it is unclear if any data point is intended to be removed if any other data point is deemed to be an outlier, or if it is the outlier data point that is intended to be removed. For the purposes of examination, the term “removing any one of the data points based on being determined that any one of the data points is the outlier” is deemed to claim “removing the outlier data point based on determining that the one of the plurality of data points is the outlier data point.” Claim 4 is similarly rejected due to its dependence on Claim 3.
Claim 4 (lines 4 – 5) recites the term “the data point other than any one of the plurality of data points”. It is unclear if this data point is intended to be the part of the overall plurality of data points previously-recited, or if it can be a different data point than has been recited to be collected. It is also unclear if it is intended to be the same or different than the data point other than any one of the plurality of data points in the set time interval. For the purposes of examination, the term “the data point other than any one of the plurality of data points” is deemed to claim “the outside data point.”
Claim 4 (line 6) recites the term “comparing the reference value with the one data point”. There is insufficient antecedent basis for this limitation in the claim. There is no previously-recited one data point. It is unclear if this is intended to be one of the previously-recited plurality of data points, the outlier data point, the first data point, etc. For the purposes of examination, the term “comparing the reference value with the one data point” is deemed to claim “comparing the reference value with the any one of the plurality of data points to determine if the any one of the plurality of data points is the outlier data point.”
Claim 5 (lines 3, 5, and 6) each recite the term “any one of the data points”. It is unclear if this is intended to be the same or different than the previously-recited plurality of data points or first data points. It is also unclear for the limitation of lines 5 – 6 if a weight can be applied to one data point with the intention of removing a noise component included in a different data point. For the purposes of examination, the term “any one of the data points” is deemed to claim “the any one of the plurality of data points”.
Claim 5 (line 3 – 4) recites the term “using a data point other than any one of the plurality of data points”. It is unclear if it is intended to be the same or different than the data point other than any one of the plurality of data points in the set time interval. For the purposes of examination, the term “using a data point other than any one of the plurality of data points” is deemed to claim “using a data point that is not one of the plurality of data points included in the set time interval.”
Claim 7 (line 8) recites the term “as the first preprocessing data”. There is insufficient antecedent basis for this limitation in the claim. There is no previously-recited first preprocessing data. For the purposes of examination, the term “as the first preprocessing data” is deemed to claim “as a first preprocessing data”. Claims 8 – 10 are similarly rejected due to their dependence on claim 7.
Claim 9 (line 5) recites the term “related to a set upper value”. It is unclear if this is intended to be the same or different than the previously-recited set upper value. Fo the purposes of examination, the term “related to a set upper value” is deemed to claim “a second set upper value”.
Claim 9 (line 6) recites the term “related to a set lower value”. It is unclear if this is intended to be the same or different than the previously-recited set lower value. Fo the purposes of examination, the term “related to a set lower value” is deemed to claim “a second set lower value”.
Claim 13 (line 11) recites the term “the third sensitivity”. There is insufficient antecedent basis for this limitation in the claim. There is no previously-recited third sensitivity. For the purposes of examination, the term “the third sensitivity” is deemed to claim “a third sensitivity”. Claims 14 - 16 are similarly rejected due to their dependence on claim 13.
Claim 13 (line 16) recites the term “the final sensitivity”. There is insufficient antecedent basis for this limitation in the claim. There is no previously-recited final sensitivity. For the purposes of examination, the term “the final sensitivity” is deemed to claim “a final sensitivity”. Claims 14 - 16 are similarly rejected due to their dependence on claim 13.
Claim 14 (line 5) recites the term “the processed sensor sensitivity”. There is insufficient antecedent basis for this limitation in the claim. There is no previously-recited processed sensor sensitivity. For the purposes of examination, the term “the processed sensor sensitivity” is deemed to claim “a processed sensor sensitivity”.
Claim 15 (lines 1 – 5) recites the term “wherein the compensation unit performs the third sensor sensitivity determination process of determining an average value of the first sensitivity and the second sensitivity as the third sensitivity based on that a state in which the first sensitivity determined at a previous time point is higher or lower than the final sensitivity of the corresponding previous time point occurs continuously.” It is unclear what is occurring continuously, or if this term was added in error. For the purposes of examination, the term “wherein the compensation unit performs… occurs continuously.” Is deemed to claim “wherein the compensation unit performs the third sensor sensitivity determination process of determining an average value of the first sensitivity and the second sensitivity as the third sensitivity if the first sensitivity determined at a previous time point is higher or lower than the final sensitivity of the corresponding previous time point.”
Claim 16 (lines 4 – 5) recites the term “when the glucose level falls within a preset range” It is unclear if this is intended to be the same or different than the previously-recited glucose level related to the compensation data, the glucose level acquired based on the third sensitivity level, the set reference glucose level, or the glucose level related to the second biometric information. For the purposes of examination, the term “when the glucose level falls within a preset range” is deemed to claim “when the glucose level related to the compensation data falls within a preset range”. It is further suggested to revise the different recited glucose levels to be, for example, “the compensation data glucose level” or “second biometric information glucose level” to promote readability of the claims relative to the recited glucose levels.
Claim 16 (lines 7 – 8) recites the term “when the glucose level does not fall within a preset range.” It is unclear if this is intended to be the same or different than the previously-recited glucose level related to the compensation data, the glucose level acquired based on the third sensitivity level, the set reference glucose level, or the glucose level related to the second biometric information. It is also unclear if this is intended to be the same or different than the previously-recited preset range. For the purpose of examination, the term “when the glucose level does not fall within a preset range” is deemed to claim “when the glucose level related to the compensation data does not fall within the preset range”.
Claim 17 (line 2) recites the limitation "the time delay in the second biometric information". There is insufficient antecedent basis for this limitation in the claim. It is unclear if this is intended to be the same or different than the previously-recited set time delay. For the purposes of examination, the term “the time delay in the second biometric information” is deemed to claim “a second biometric information time delay”.
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 – 18 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Regarding Claim 1, the claim recites an apparatus, which is one of the statutory categories of invention (Step 1). The claim is then analyzed to determine whether it is directed to any judicial exception (Step 2A, Prong 1).
Regarding Claim 18, the claim recites "an act or step, or series of acts or steps" and is therefore a process, which is a statutory category of invention (Step 1). The claims are then analyzed to determine whether it is directed to any judicial exception (Step 2A, Prong 1).
Each of Claims 1 – 18 has been analyzed to determine whether it is directed to any judicial exceptions.
Step 2A, Prong 1
Each of Claims 1 – 18 recites at least one step or instruction for observations, evaluations, judgments, and opinions, which are grouped as a mental process under the 2019 PEG. The claimed invention involves making observations, evaluations, judgments, and opinions, which are concepts performed in the human mind under the 2019 PEG.
Accordingly, each of Claims 1 – 18 recites an abstract idea.
Specifically, Independent Claims 1 and 18 recite (underlined are observations, judgements, evaluations, or opinions, which are grouped as a mental process under the 2019 PEG) (additional elements bolded, see Step 2A, prong 2);
Claim 1
An apparatus for monitoring glucose, comprising:
an input unit that obtains first biometric information including a plurality of data points measuring glucose-related information of a subject;
a noise removal unit that removes noise information included in the first biometric information;
a preprocessing unit that preprocesses the first biometric information from which the noise information is removed to generate second biometric information having a lower sampling rate than the first biometric information;
a compensation unit that generates compensation data based on the second biometric information and generates a calibration algorithm based on the compensation data; and
a glucose level acquisition unit that acquires a glucose level related to the second biometric information by reflecting the calibration algorithm and a set time delay.
Claim 18
A method of monitoring glucose using an apparatus for monitoring glucose, comprising:
obtaining, by the apparatus for monitoring glucose, first biometric information including a plurality of data points measuring glucose-related information of a subject;
removing, by the apparatus for monitoring glucose, noise information included in the first biometric information;
preprocessing, by the apparatus for monitoring glucose, the first biometric information from which the noise information is removed to generate second biometric information having a lower sampling rate than the first biometric information;
generating, by the apparatus for monitoring glucose, compensation data based on the second biometric information; and
generating a calibration algorithm based on the compensation data; and
acquiring, by the apparatus for monitoring glucose, a glucose level related to the second biometric information by reflecting the calibration algorithm and a set time delay.
determining a blood-oxygen level of the subject in response to the signals.
(observation, judgment or evaluation, which is grouped as a mental process under the 2019 PEG);
These underlined limitations describe a mathematical calculation and/or a mental process, as a skilled practitioner is capable of performing the recited limitations and making a mental assessment thereafter. Examiner notes that nothing from the claims suggests that the limitations cannot be practically performed by a human with the aid of a pen and paper, or by using a generic computer as a tool to perform mathematical calculations and/or mental process steps in real time. Examiner additionally notes that nothing from the claims suggests and undue level of complexity that the mathematical calculations and/or the mental process steps cannot be practically performed by a human with the aid of a pen and paper, or using a generic computer as a tool to perform mathematical calculations and/or mental process steps. For example, in Independent Claims 1 and 18, these limitations include:
Observation and judgment to remove noise information included in the first biometric information;
Observation and judgment to preprocess the first biometric information from which the noise information is removed to generate second biometric information having a lower sampling rate than the first biometric information;
Observation and judgment to generate compensation data based on the second biometric information
Observation and judgment to generate a calibration algorithm based on the compensation data;
Observation and judgment of a glucose level related to the second biometric information by reflecting the calibration algorithm and a set time delay.
Similarly, the Dependent Claims include the following abstract limitations, in addition to the aforementioned limitations in Independent Claims 1 and 18 (underlined observation, judgment or evaluation, which is grouped as a mental process under the 2019 PEG):
performs a first noise removal process of removing a data point determined as noise information among first data points based on a plurality of data points included in a set time interval
Observation and judgment to perform a first noise removal process of removing a data point Observed and judged as noise information among first data points based on a plurality of data points included in a set time interval
performs a second noise removal process of adjusting a value of the first data point based on a plurality of data points included in a set time interval to remove set noise information.
Observation and judgment to perform a second noise removal process of adjusting a value of the first data point based on Observation and judgment of a plurality of data points included in a set time interval to remove set noise information.
determining whether any one of the data points is an outlier using a data point other than any one of the plurality of data points included in the set time interval
Observation and judgment to determine whether any one of the data points is an outlier using a data point other than any one of the plurality of data points included in the set time interval
removing any one of the data points based on being determined that any one of the data points is the outlier.
Observation and judgment to remove any one of the data points based on Observation and judgment that any one of the data points is the outlier.
acquiring a reference value including at least one of an average slope, a slope change value, an average value, and a standard deviation using the data point other than any one of the plurality of data points
Observation and judgment to acquire a reference value including at least one of an average slope, a slope change value, an average value, and a standard deviation using the data point other than any one of the plurality of data points
comparing the reference value with the one data point to determine whether the one data point is the outlier.
Observation and judgment to compare the reference value with the one data point to determine whether the one data point is the outlier.
acquiring a weight for any one of the data points using a data point other than any one of the plurality of data points
Observation and judgment to acquire a weight for any one of the data points using a data point other than any one of the plurality of data points
applying the weight to any one of data points to remove a noise component included in any one of data points.
Observation and judgment to apply the weight to any one of data points to remove a noise component included in any one of data points.
performs a first preprocessing process of preprocessing the first biometric information from which the noise information is removed based on the first biometric information from which the noise information is removed and a first time interval.
Observation and judgment to perform a first preprocessing process of preprocessing the first biometric information from which the noise information is removed based on Observation and judgment of the first biometric information from which the noise information is removed and a first time interval.
dividing a plurality of data points included in the first biometric information from which the noise information is removed at the first time interval;
Observation and judgment to divide a plurality of data points included in the first biometric information from which the noise information is removed at the first time interval;
removing a first data point related to a set upper value and a second data point related to a set lower value among a plurality of data points at each first time interval
Observation and judgment to remove a first data point related to a set upper value and a second data point related to a set lower value among a plurality of data points at each first time interval;
acquiring an average value of the plurality of data points from which the first data point and the second data point are removed at each first time interval as the first preprocessing data.
Observation and judgment of an average value of the plurality of data points from which the first data point and the second data point are removed at each first time interval as the first preprocessing data.
performs a second preprocessing process of preprocessing the first preprocessing data based on the first preprocessing data and a second time interval having a value greater than the first time interval.
Observation and judgment of preprocessing the first preprocessing data based on the first preprocessing data and a second time interval having a value greater than the first time interval.
dividing a plurality of average values included in the first preprocessing data at the second time interval;
Observation and judgment to divide a plurality of average values included in the first preprocessing data at the second time interval;
removing a first average value related to a set upper value and a second average value related to a set lower value among the plurality of average values at each second time interval;
Observation and judgment to remove a first average value related to a set upper value and a second average value related to a set lower value among the plurality of average values at each second time interval;
acquiring an average value for the plurality of average values from which the first average value and the second average value are removed at each second time interval as second preprocessing data;
Observation and judgment of an average value for the plurality of average values from which the first average value and the second average value are removed at each second time interval as second preprocessing data;
determining the second preprocessing data as the second biometric information.
Observation and judgment of the second preprocessing data as the second biometric information.
determines any one of values of pre-stored table data as an offset value based on the second biometric information,
Observation and judgment of any one of values of pre-stored table data as an offset value based on the second biometric information,
applies the offset value to the second biometric information to generate the compensation data.
Observation and judgment to apply the offset value to the second biometric information to generate the compensation data.
acquires an average value of data points for a set period included in the second biometric information,
Observation and judgment of an average value of data points for a set period included in the second biometric information,
applies the average value to the second biometric information to generate ideal data having a set baseline,
Observation and judgment to apply the average value to the second biometric information to generate ideal data having a set baseline,
generates a first weight and a second weight
Observation and judgment of a first weight and a second weight
adds up a value obtained by applying the first weight to the second biometric information and a value obtained by applying the second weight to the ideal data to generate the compensation data.
Observation and judgment to add up a value obtained by applying the first weight to the second biometric information and a value obtained by applying the second weight to the ideal data to generate the compensation data.
compensates for the time delay in the second biometric information to generate time-compensated biometric information
Observation and judgment to compensate for the time delay in the second biometric information to generate time-compensated biometric information
applies the time-compensated biometric information to the calibration algorithm to acquire the glucose level.
Observation and judgment of the time-compensated biometric information to the calibration algorithm to acquire the glucose level.
determining a first sensitivity based on the compensation data and a set reference glucose level
Observation and judgment of a first sensitivity based on the compensation data and a set reference glucose level
determining a second sensitivity based on a sensor sensitivity set in response to a glucose measurement sensor and the first sensitivity
Observation and judgment a second sensitivity based on a sensor sensitivity set in response to a glucose measurement sensor and the first sensitivity
determining the sensor sensitivity as the second sensitivity based on that the first sensitivity is higher than or equal to the sensor sensitivity
Observation and judgment the sensor sensitivity as the second sensitivity based on that the first sensitivity is higher than or equal to the sensor sensitivity
adjusting the second sensitivity based on a first previous time point sensitivity and a first previous time point final sensitivity that are determined at a previous time point and determining the adjusted second sensitivity as the third sensitivity
Observation and judgment to adjust the second sensitivity based on a first previous time point sensitivity and a first previous time point final sensitivity that are determined at a previous time point and determining the adjusted second sensitivity as the third sensitivity
adjusting the third sensitivity according to whether a glucose level acquired based on the third sensitivity falls within a set range and determining the adjusted third sensitivity as a fourth sensitivity
Observation and judgment to adjust the third sensitivity according to whether a glucose level acquired based on the third sensitivity falls within a set range and determining the adjusted third sensitivity as a fourth sensitivity
determining the processed sensor sensitivity, which is obtained by processing the sensor sensitivity through a set algorithm, as the second sensitivity based on that the first sensitivity is lower than the sensor sensitivity.
Observation and judgment of the processed sensor sensitivity, which is obtained by processing the sensor sensitivity through a set algorithm, as the second sensitivity based on that the first sensitivity is lower than the sensor sensitivity.
determines any one of the first sensitivity, the second sensitivity, the third sensitivity, and the fourth sensitivity as the final sensitivity
Observation and judgment of any one of the first sensitivity, the second sensitivity, the third sensitivity, and the fourth sensitivity as the final sensitivity
determining an average value of the first sensitivity and the second sensitivity as the third sensitivity based on that a state in which the first sensitivity determined at a previous time point is higher or lower than the final sensitivity of the corresponding previous time point occurs continuously.
Observation and judgment of an average value of the first sensitivity and the second sensitivity as the third sensitivity based on that a state in which the first sensitivity determined at a previous time point is higher or lower than the final sensitivity of the corresponding previous time point occurs continuously.
acquiring a glucose level related to the compensation data using the third sensitivity;
Observation and judgment of a glucose level related to the compensation data using the third sensitivity;
determining the third sensitivity as the fourth sensitivity when the glucose level falls within a preset range;
Observation and judgment of the third sensitivity as the fourth sensitivity when the glucose level falls within a preset range;
determining the fourth sensitivity based on a glucose level at the previous time point, a reference glucose level, and the compensation data when the glucose level does not fall within a preset range.
Observation and judgment of the fourth sensitivity based on a glucose level at the previous time point, a reference glucose level, and the compensation data when the glucose level does not fall within a preset range.
the glucose level acquisition unit compensates for the time delay in the second biometric information to generate time-compensated biometric information
Observation and judgment to compensate for the time delay in the second biometric information to generate time-compensated biometric information
applies the time-compensated biometric information to the calibration algorithm to acquire the glucose level
Observation and judgment to apply the time-compensated biometric information to the calibration algorithm to acquire the glucose level
all of which are grouped as mental processes or mathematical algorithms under the 2019 PEG.
Accordingly, as indicated above, each of the above-identified claims recite an abstract idea.
Step 2A, Prong 2
The above-identified abstract ideas in each of Independent Claims 1 and 18 (and their respective Dependent Claims) are not integrated into a practical application under 2019 PEG because the additional elements (identified in Claims 1 – 18), either alone or in combination, generally link the use of the above-identified abstract ideas to a particular technological environment or field of use. More specifically, the additional elements of:
“apparatus for monitoring glucose”
“input unit”
“noise removal unit”
“preprocessing unit”
“compensation unit”
“glucose level acquisition unit”
Additional elements recited include “apparatus for monitoring glucose”, “input unit”, “noise removal unit”, “preprocessing unit”, “compensation unit”, and “glucose level acquisition unit” in Independent Claims 1 and 18 (and their respective Dependent Claims). These components are recited at a high level of generality, i.e., as a processor performing a generic function of processing data (the obtaining, removing, preprocessing, generating, and acquiring); These generic hardware component limitations “apparatus for monitoring glucose”, “input unit”, “noise removal unit”, “preprocessing unit”, “compensation unit”, and “glucose level acquisition unit” are no more than mere instructions to apply the exception using generic computer and hardware components. As such, these additional elements do not impose any meaningful limits on practicing the abstract idea.
Further additional elements from Claims 1 – 18 include pre-solution activity limitations, such as:
an input unit that obtains first biometric information including a plurality of data points measuring glucose-related information of a subject;
obtaining, by the apparatus for monitoring glucose, first biometric information including a plurality of data points measuring glucose-related information of a subject;
wherein the first weight and the second weight have a negative correlation.
These pre-solution measurement elements are insignificant extra-solution activity, setting up the parameters of the system, and serve as data-gathering for the subsequent steps.
The “apparatus for monitoring glucose”, “input unit”, “noise removal unit”, “preprocessing unit”, “compensation unit”, and “glucose level acquisition unit” as recited in Independent Claims 1 and 18 (and their respective Dependent Claims) are generically recited computer and hardware elements which do not improve the functioning of a computer, or any other technology or technical field. Nor do these above-identified additional elements serve to apply the above-identified abstract idea with, or by use of, a particular machine, effect a transformation or apply or use the above-identified abstract idea in some other meaningful way beyond generally linking the use thereof to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception. Furthermore, the above-identified additional elements do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer. For at least these reasons, the abstract ideas identified above in Independent Claims 1 and 18 (and their dependent claims) is not integrated into a practical application under 2019 PEG.
Moreover, the above-identified abstract idea is not integrated into a practical application under 2019 PEG because the claimed method and system merely implements the above-identified abstract idea (e.g., mental process and certain method of organizing human activity) using rules (e.g., computer instructions) executed by a computer processor as claimed. In other words, these claims are merely directed to an abstract idea with additional generic computer elements which do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer. Additionally, Applicant’s specification does not include any discussion of how the claimed invention provides a technical improvement realized by these claims over the prior art or any explanation of a technical problem having an unconventional technical solution that is expressed in these claims. That is, like Affinity Labs of Tex. v. DirecTV, LLC, the specification fails to provide sufficient details regarding the manner in which the claimed invention accomplishes any technical improvement or solution. Thus, for these additional reasons, the abstract idea identified above in Independent Claims 1 and 18 (and their dependent claims) is not integrated into a practical application under the 2019 PEG.
Accordingly, Independent Claims 1 and 18 (and their dependent claims) are each directed to an abstract idea under 2019 PEG.
Step 2B –
None of Claims 1 – 18 include additional elements that are sufficient to amount to significantly more than the abstract idea for at least the following reasons.
These claims require the additional elements of: “apparatus for monitoring glucose”, “input unit”, “noise removal unit”, “preprocessing unit”, “compensation unit”, and “glucose level acquisition unit” as recited in Independent Claim 1 (and their dependent claims).
The additional elements of the “apparatus for monitoring glucose”, “input unit”, “noise removal unit”, “preprocessing unit”, “compensation unit”, and “glucose level acquisition unit” in Independent Claims 1 and 18 (and their dependent claims), as discussed with respect to Step 2A Prong Two, amounts to no more than mere instructions to apply the exception using generic computer and hardware components. The same analysis applies here in 2B, i.e., mere instructions to apply an exception using a generic computer component cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
The above-identified additional elements are generically claimed computer components which enable the above-identified abstract idea(s) to be conducted by performing the basic functions of automating mental tasks. The courts have recognized such computer functions as well understood, routine, and conventional functions when claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity. See, Versata Dev. Group, Inc. v. SAP Am., Inc. , 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); and OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93.
Per Applicant’s specification and the 112f interpretation above, the “apparatus for monitoring glucose” is described generically on [Page 62, Bottom] – [Page 63, Top] and [Page 12, Paragraph 4] “the system for monitoring glucose described below may be a continuous glucose monitoring system that continuously or constantly measures and provides a glucose concentration of a subject.” The “apparatus for monitoring glucose” is shown as “apparatus 100” in Fig. 2.
Per Applicant’s specification and the 112f interpretation above, the “input unit” is described generically at to [Page 62, Bottom] – [Page 63, Top] with “The term ' - unit' used in the present embodiment refers to software or a hardware Component…the "~unit" refers to components such as software components… Components and functions provided within "~unit" may be combined into a smaller number of components and "~unit" or may be further separated into additional components and "~unit."; and [Page 17, Paragraph 4] “the input unit 110 may obtain the biometric information measured by the sensor module.” The “input unit” is shown as generic box element “input unit 110” in Fig. 2.
Per Applicant’s specification and the 112f interpretation above, the “noise removal unit” is described generically on [Page 62, Bottom] – [Page 63, Top] and [Page 18, Paragraph 3] with “noise removal unit 120 may perform a function of removing noise from the biometric information. “ The “noise removal unit” is shown as generic box element “noise removal unit 120” in Fig. 2.
Per Applicant’s specification and the 112f interpretation above, the “preprocessing unit” is described generically at [Page 62, Bottom] – [Page 63, Top] and [Page 20, Paragraph 3] with “preprocessing unit 130 may perform a function of processing the biometric information from which noise has been removed.“ The “preprocessing unit” is shown as generic box element “preprocessing unit 130” in Fig. 2.
Per Applicant’s specification and the 112f interpretation above, the “compensation unit” is described generically at [Page 62, Bottom] – [Page 63, Top], Figures 10 and 12, and [Page 36, Paragraph 5] with “compensation unit 140 may determine any one of the values of the pre-stored table data as an offset value based on the second biometric information (S 1310).“ The “compensation unit” is shown as generic box element “compensation unit 140” in Fig. 2.
Per Applicant’s specification and the 112f interpretation above, the “glucose level acquisition unit” is described generically at [Page 62, Bottom] – [Page 63, Top] and [Page 4, Paragraph 3] “glucose level acquisition unit that acquires a glucose level related to the second biometric information by reflecting the calibration algorithm and a set time delay.” The “glucose level acquisition unit” is shown as “glucose level acquisition unit 150” in Fig. 2.
Accordingly, in light of Applicant’s specification, the claimed terms “apparatus for monitoring glucose”, “input unit”, “noise removal unit”, “preprocessing unit”, “compensation unit”, and “glucose level acquisition unit” are reasonably construed as a generic computing and hardware devices. Like SAP America vs Investpic, LLC (Federal Circuit 2018), it is clear, from the claims themselves and the specification, that these limitations require no improved computer resources, just already available computers, with their already available basic functions, to use as tools in executing the claimed process.
Furthermore, Applicant’s specification does not describe any special programming or algorithms required for “apparatus for monitoring glucose”, “input unit”, “noise removal unit”, “preprocessing unit”, “compensation unit”, and “glucose level acquisition unit.” This lack of disclosure is acceptable under 35 U.S.C. §112(a) since this hardware performs non-specialized functions known by those of ordinary skill in the computer arts. By omitting any specialized programming or algorithms, Applicant's specification essentially admits that this hardware is conventional and performs well understood, routine and conventional activities in the computer industry or arts. In other words, Applicant’s specification demonstrates the well-understood, routine, conventional nature of the above-identified additional elements because it describes these additional elements in a manner that indicates that the additional elements are sufficiently well-known that the specification does not need to describe the particulars of such additional elements to satisfy 35 U.S.C. § 112(a) (see Berkheimer memo from April 19, 2018, (III)(A)(1) on page 3). Adding hardware that performs “‘well understood, routine, conventional activit[ies]’ previously known to the industry” will not make claims patent-eligible (TLI Communications).
The recitation of the above-identified additional limitations in Independent Claims 1 and 18 (and their dependent claims) amounts to mere instructions to implement the abstract idea on a computer. Simply using a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general-purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); and TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Moreover, implementing an abstract idea on a generic computer, does not add significantly more, similar to how the recitation of the computer in the claim in Alice amounted to mere instructions to apply the abstract idea of intermediated settlement on a generic computer.
A claim that purports to improve computer capabilities or to improve an existing technology may provide significantly more. McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314-15, 120 USPQ2d 1091, 1101-02 (Fed. Cir. 2016); and Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335-36, 118 USPQ2d 1684, 1688-89 (Fed. Cir. 2016). However, a technical explanation as to how to implement the invention should be present in the specification for any assertion that the invention improves upon conventional functioning of a computer, or upon conventional technology or technological processes. That is, the disclosure must provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. Here, Applicant’s specification does not include any discussion of how the claimed invention provides a technical improvement realized by these claims over the prior art or any explanation of a technical problem having an unconventional technical solution that is expressed in these claims. Instead, as in Affinity Labs of Tex. v. DirecTV, LLC 838 F.3d 1253, 1263-64, 120 USPQ2d 1201, 1207-08 (Fed. Cir. 2016), the specification fails to provide sufficient details regarding the manner in which the claimed invention accomplishes any technical improvement or solution.
For at least the above reasons, the method and apparatus of Claims 1 – 18 are directed to applying an abstract idea as identified above on a general-purpose computer without (i) improving the performance of the computer itself, or (ii) providing a technical solution to a problem in a technical field. None of Claims 1 – 18 provides meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that these claims amount to significantly more than the abstract idea itself.
Taking the additional elements individually and in combination, the additional elements do not provide significantly more. Specifically, when viewed individually, the above-identified additional elements for Step 2A Prong 2 in Independent Claim 1 (and their dependent claims) do not add significantly more because they are simply an attempt to limit the abstract idea to a particular technological environment. That is, neither the general computer elements nor any other additional element adds meaningful limitations to the abstract idea because these additional elements represent insignificant extra-solution activity. When viewed as a combination, these above-identified additional elements simply instruct the practitioner to implement the claimed functions with well-understood, routine and conventional activity specified at a high level of generality in a particular technological environment. As such, there is no inventive concept sufficient to transform the claimed subject matter into a patent-eligible application. When viewed as whole, the above-identified additional elements do not provide meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that the claims amount to significantly more than the abstract idea itself. Thus, Claims 1 – 18 apply an abstract idea to a computer and do not (i) improve the performance of the computer itself (as in Bascom and Enfish), or (ii) provide a technical solution to a problem in a technical field (as in DDR).
Therefore, none of the Claims 1 – 18 amounts to significantly more than the abstract idea itself. Accordingly, Claims 1 – 18 are not patent eligible and 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 – 9 and 18 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Lee et. al., (US 2022/0330895 A1).
Regarding Claims 1 and 18, Lee discloses
For Claim 1: An apparatus for monitoring glucose (Fig 1., [0046] “continuous blood glucose measurement system”; [Abstract]), comprising:
For Claim 18: A method of monitoring glucose using an apparatus for monitoring glucose (Fig 1., [0046] “continuous blood glucose measurement system”; [Abstract]), comprising:
For both Claims 1 and 18, Lee discloses:
an input unit that obtains first biometric information including a plurality of data points measuring glucose-related information of a subject ([0078] “sensor controller (117) controls the sensor module (111) to measure blood glucose information”; Fig. 6);
a noise removal unit that removes noise information included in the first biometric information (Fig. 5; [0062] “The first pre-processing process processes noise…calculating an average value of the measured blood glucose information data…”; Fig. 6);
a preprocessing unit that preprocesses the first biometric information from which the noise information is removed to generate second biometric information having a lower sampling rate than the first biometric information ([0084] “The trimmed average value (A) can be generated every ten (10) seconds, and as illustrated, six (6) trimmed average values (A1 to A6) can be generated for one (1) minute.”; [0084] – [0087]; [0086] “the first pre-processing process generates one second trimmed average value (B) for one (1) minute…”; [0113] – [0014] including “the second preprocessing process generates one trimmed average value (Vl) every five (5) minutes…”; Fig. 6; Fig. 8);
a compensation unit that generates compensation data based on the second biometric information and generates a calibration algorithm based on the compensation data ([0069] “If the blood glucose information data processed by the second pre-processing process is verified as data which can be trusted, calibration to the verified blood glucose information data is performed (S115)…”; [0134] “…calibration can be performed using relation between the measured blood collection blood glucose value and the generated blood glucose information data (V)…”; Fig. 6; Fig. 8; [0093]); and
a glucose level acquisition unit that acquires a glucose level related to the second biometric information by reflecting the calibration algorithm and a set time delay ([0011] “extracting a representative value from the biometric information data measured for a certain time period and a calibration step for time delay…”; [0093] “..The terminal controller (127) performs various processing processes…calibration…”; Fig. 6; Fig. 8, Fig. 5)
Regarding Claim 2, Lee discloses as described above, The apparatus of claim 1. For the remainder of Claim 2, Lee discloses wherein the noise removal unit performs a first noise removal process of removing a data point determined as noise information among first data points based on a plurality of data points included in a set time interval (Fig. 5; [0062] “The first pre-processing process processes noise…a trimmed average value which is calculated by removing a certain proportion of a top portion and a bottom portion of the measured blood glucose information data…”;[0082] - [0084] “…trimmed average value (a) can be generated every ten (10) seconds…”) and
performs a second noise removal process of adjusting a value of the first data point based on a plurality of data points included in a set time interval to remove set noise information ([0066] “second pre-processing process is performed by the communication terminal (120), and is performed by calculating an average value of the blood glucose information data processed by the low pass filtering…a trimmed average value can be used…“; [0113] “…receives a trimmed average value of the measured blood glucose information data from the sensor transmitter (110) every minute...”; [00114] “…generates one trimmed average value (V!) every five (5) minutes…”).
Regarding Claim 3, Lee discloses as described above, The apparatus of claim 2. For the remainder of Claim 3, Lee discloses wherein the noise removal unit performs the first noise removal process ([0018] “outlier processing filtering performed by the communication terminal…”) of:
determining whether any one of the data points is an outlier using a data point other than any one of the plurality of data points included in the set time interval ([0018] “outlier processing filtering performed by the communication terminal determines whether one of data is an outlier value or not using a plurality of data before the one of the data with respect to the one of the data…”)and
removing any one of the data points based on being determined that any one of the data points is the outlier ([0018] “…outlier processing filtering performed by the communication terminal …processing by deleting the determined outlier value.”);
Regarding Claim 4, Lee discloses as described above, The apparatus of claim 3. For the remainder of Claim 4, Lee discloses wherein the noise removal unit performs the first noise removal process ([0018] “outlier processing filtering performed by the communication terminal…”) of:
acquiring a reference value including at least one of an average slope, a slope change value, an average value, and a standard deviation using the data point other than any one of the plurality of data points ([0019] “determining whether the one of the data is the outlier value…using any one of an average gradient, a gradient change value, and an average and a standard deviation of the plurality of data before the one of the data.”); and
comparing the reference value with the one data point to determine whether the one data point is the outlier ([0019] “determining whether the one of the data is the outlier value…using any one of an average gradient, a gradient change value, and an average and a standard deviation of the plurality of data before the one of the data.”; [0103] “…if the value of B6 is out of the standard deviation of B1 to B5, it is determined that B6 is an outlier value.”).
Regarding Claim 5, Lee discloses as described above, The apparatus of claim 2. For the remainder of Claim 5, Lee discloses wherein the noise removal unit performs the second noise removal process ([0106] – [0110] “…communication terminal (120)”) of:
acquiring a weight for any one of the data points using a data point other than any one of the plurality of data points ([0107] “the communication terminal (120) sets a weight to each data of which outlier value is processed…with respect to one datum…”; [0108] “…weight of B7 can be set using the values changed to B1’ to B6’…”) and
applying the weight to any one of data points to remove a noise component included in any one of data points ([0107] “…sets a weight to each data of which outlier value is processed…changes a value of each data…”; [0109] “…the value of B7 can be changed to B7’”) .
Regarding Claim 6, Lee discloses as described above, The apparatus of claim 1. For the remainder of Claim 6, Lee discloses wherein the preprocessing unit performs a first preprocessing process of preprocessing the first biometric information from which the noise information is removed ([0078] “…measure blood glucose information at a predetermined time interval…”; [0062] “first pre-processing process processes noise…”) based on the first biometric information from which the noise information is removed and a first time interval ([0078] “…measure blood glucose information at a predetermined time interval…”; [0062] “first pre-processing process processes noise…calculating an average value of the measured blood glucose information data… the average value used in the first pre-processing process may be a trimmed average value which is calculated by removing a certain proportion of a top portion and a bottom portion of the measured blood glucose information data and then calculating an average of the remaining data…”)
Regarding Claim 7, Lee discloses as described above, The apparatus of claim 6. For the remainder of Claim 7, Lee discloses wherein the preprocessing unit performs the first preprocessing process ([0061] – [0062] “sensor transmitter (110)…first pre-processing process…”) of:
dividing a plurality of data points included in the first biometric information from which the noise information is removed at the first time interval ([0062] “…processes noise by calculating an average value of the measured blood glucose information data…trimmed average value”)
removing a first data point related to a set upper value ([0062] “first pre-processing process…removing a certain proportion of a top portion…of the measured blood glucose information data”) and a second data point related to a set lower value among a plurality of data points at each first time interval ([0062] “first pre-processing process…removing a certain proportion of…a bottom portion…of the measured blood glucose information data”); and
acquiring an average value of the plurality of data points from which the first data point and the second data point are removed at each first time interval as the first preprocessing data ([0062] “…calculating an average of the remaining data…”).
Regarding Claim 8, Lee discloses as described above, The apparatus of claim 7. For the remainder of Claim 8, Lee discloses wherein the preprocessing unit ([0061] – [0062] “sensor transmitter (110)…first pre-processing process…”) performs a second preprocessing process (Fig. 5, “2nd pre-processing”) of preprocessing the first preprocessing data based on the first preprocessing data and a second time interval having a value ([0114] “second pre-processing process…generates one trimmed average value (V1) every five (5) minutes…”; Fig. 5., 1st pre-processing is an input to 2nd pre-processing; [0063] – [0066]) greater than the first time interval ([0086] “the first pre-processing process generates one second trimmed average value (B) for one (1) minute.”)
Regarding Claim 9, Lee discloses as described above, The apparatus of claim 8. For the remainder of Claim 9, Lee discloses wherein the preprocessing unit performs the second preprocessing process ([0112] – [0113] “)…second pre-processing process…communication terminal (120)… sensor transmitter (110)”) of:
dividing a plurality of average values included in the first preprocessing data ([0062] “average value used in the first pre-processing process may be a trimmed average value”; [0063] – [0066] describing how the “blood glucose information data processed by the first pre-processing process” is transmitted and becomes the low pass data input to the “second pre-processing process”; Fig. 5; [0067] “…a trimmed average value can be used in the second pre-processing process.”; [0113] – [0115]) at the second time interval ([0114] “second pre-processing process…generates one trimmed average value (V1) every five (5) minutes…”);
removing a first average value related to a set upper value ([0114] “…performs the second pre-processing process on the trimmer average value…the second pre-processing process removes a maximum value…among five (5) trimmed average values (Bl to B5)…”) and a second average value related to a set lower value ([0114] “…the second pre-processing process removes…a minimum value among five (5) trimmed average values (Bl to B5)…”) among the plurality of average values at each second time interval ([0114] “second pre-processing process…generates one trimmed average value (V1) every five (5) minutes…”);
acquiring an average value for the plurality of average values from which the first average value and the second average value are removed at each second time interval as second preprocessing data ([0114] “second pre-processing process…generates one trimmed average value (V1) every five (5) minutes…”); and
determining the second preprocessing data as the second biometric information ([0068] “…blood
glucose information data processed by the second preprocessing process”).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Lee in view of Hogan, (US 2008/0039704 A1).
Regarding Claim 10, Lee discloses as described above, The apparatus of claim 8. For the remainder of Claim 10, Lee discloses the compensation unit ([0093] “…the terminal controller (127) may perform outlier processing filtering, low pass filtering, second pre-processing…”) and the second biometric information ([0114] “second pre-processing process…generates one trimmed average value (V1) every five (5) minutes…”; Fig. 5., 1st pre-processing is an input to 2nd pre-processing; [0063] – [0066])
Lee does not particularly disclose determines any one of values of pre-stored table data as an offset value based on the second biometric information, and applies the offset value to the second biometric information to generate the compensation data.
Hogan teaches a calibration system for calibrating continuous glucose monitor systems, including a look-up table of gain and offset values for calibration ([Abstract]; [0037] – [0038]). Specifically for Claim 10, Hogan teaches wherein the compensation unit ([0029] “makes the glucose level information available to an electronic memory and processor 109…”) determines any one of values of pre-stored table data as an offset value based on the biometric information ([0037] “…conventional electronic gain and offset values; tables of values, such as PROM tables…”; [0038]) and
applies the offset value to the biometric information to generate the compensation data ([0037] “Calibration data will be used to adjust such parameters by electronic circuitry in the monitor that has access to the calibration data and modifies the monitor in its measurement of glucose levels”).
Lee and Hogan both disclose analyzing glucose measurement information, Lee with glucose measurement information that is first and second pre-processed then further calibrated (Figure 5), and Hogan with calibrating glucose measurement data output with an offset value. Hogan provides a motivation to combine at [0034] “The temporal offset information acquired by concurrently measuring glucose levels in two different regions can thus be used to gain information about the actual glucose
concentration level.” A person having ordinary skill in the art before the effective filing date of the claimed invention would recognize that using an offset value compensation factor would be useful to obtain more accurate results from a continuous glucose monitor of the actual glucose concentration level for a subject.
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the continuous glucose monitor that performs calibration on the noise-processed glucose data disclosed by Lee with the measurement at locations to obtain an offset value to correct the measured glucose level taught by Hogan, creating a single continuous glucose monitor that uses an offset value compensation factor to obtain more accurate results from a continuous glucose monitor of the actual glucose concentration level for a subject.
Claims 11 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over Lee in view of Hayter et. al., (US 2018/0008201 A1), as evidenced by Lacoste (“Introduction to IIR Filters”, Ref U on PTO-892)
Regarding Claim 11, Lee discloses as described above, The apparatus of claim 1. For the remainder of Claim 11, Lee discloses wherein the compensation unit ([0093] “…the terminal controller (127) may perform outlier processing filtering, low pass filtering, second pre-processing…”) acquires an average value of data points for a set period included in the second biometric information ([0015] “average of a plurality of biometric information data measured a certain time period…”; [0066] “…trimmed average value can be used in the second pre-processing process….”),
Lee does not particularly disclose applies the average value to the second biometric information to generate ideal data having a set baseline, generates a first weight and a second weight, and adds up a value obtained by applying the first weight to the second biometric information and a value obtained by applying the second weight to the ideal data to generate the compensation data. Lee does broadly disclose low pass filter and linear regression filtering for filtering a datum using a plurality of past data at [0017] and [0125].
Hayter teaches methods and apparatus for determining a glucose value for a continuous glucose monitor including using an FIR filter to ([Abstract]; [0076]; Fig. 7). Specifically for Claim 11, Hayter teaches applies the average value to the second biometric information to generate ideal data having a set baseline, generates a first weight and a second weight, and adds up a value obtained by applying the first weight to the second biometric information and a value obtained by applying the second weight to the ideal data to generate the compensation data ([0046] “…one or more filters such as a finite impulse response (FIR) filter may be used to determine the best estimate at a predetermined time using a finite window of monitored sensor data up to the current or most recent monitored sensor data point.”; [0052] “…rate of change of the monitored data…with infinite impulse response (IIR) filter, finite impulse response (FIR) filter, backward and/or forward smoothing techniques (e.g., Kalman filtering technique), or any other equivalent one or more causal filters that balance signal noise reduction with lag correction…)(Examiner notes that as evidenced by Lacoste and as would be known by a person with ordinary skill in the art at the time of filing, these steps are the algorithmic signal processing steps that occur when using a weighted moving average filter with two weights. In the titular figure of Lacoste, there is a moving average filtered signal with weights that sum to 1, such that they have a negative correlation, and the output is smoothed data. Further, as described in Applicant’s specification at] Page 37, Paragraph 3], it appears to be described that this process can be accomplished using “…at least one of a low pass filter (LPF), a high pass filter (HPF), a band pass filter (BPF), and a band rejection filter (BRF) according to frequency characteristics. Alternatively, the compensation unit 140 may include a finite impulse response (FIR) filter or an infinite impulse response (IIR) filter as a digital filter.” This is consistent with the weighted moving average filter on the signal with 2 weights.)
Lee and Hayter both use filtering to process and smooth glucose data to compensate for signal errors. Hayter provides a motivation to combine at [0052] with “the rate of change of the monitored data at the calibration time…may be determined using one or more filters including… infinite impulse response (IIR) filter, finite impulse response (FIR) filter, backward and/or forward smoothing techniques (e.g., Kalman filtering technique), or any other equivalent one or more causal filters that balance signal noise reduction with lag correction.” A person having ordinary skill in the art before the effective filing date of the claimed invention would recognize that using a weighted moving average filter to process signal data would be useful for smoothing the signal and minimizing signal drift effects.
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the continuous glucose monitor with filtering to increase accuracy of the measured data disclosed by Lee with the weighted moving average (FIR) filtering taught by Hayter as evidenced by Lacoste, creating a single continuous glucose monitor that uses an FIR filter to minimize error due to baseline drift in the glucose measurement signal over time.
Regarding Claim 12, Lee discloses as described above, The apparatus of claim 11. For the remainder of Claim 12, Lee does not disclose wherein the first weight and the second weight have a negative correlation.
Hayter teaches wherein the first weight and the second weight have a negative correlation ([0046] “…one or more filters such as a finite impulse response (FIR) filter may be used to determine the best estimate at a predetermined time using a finite window of monitored sensor data up to the current or most recent monitored sensor data point.”)(Examiner notes that as evidenced by Lacoste (described in more detail in Claim 11), these steps are the processes that occur when using a weighted moving average filter with two weights, and a weighted moving average is a type of FIR. The weights sum to 1, such that if two weights are chosen, they change with negative correlation, such as the 0.8 and 0.2 in the titular figure of Lacoste.).
The motivation for Claim 12 to combine Lee with Hayter as evidenced by Lacoste is the same as that described in more detail above in Claim 11. In summary, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the continuous glucose monitor with filtering to increase accuracy of the measured data disclosed by Lee with the weighted moving average (FIR) filtering taught by Hayter as evidenced by Lacoste, creating a single continuous glucose monitor that uses an FIR filter to minimize error due to baseline drift in the glucose measurement signal over time.
Claims 13 - 16 are rejected under 35 U.S.C. 103 as being unpatentable over Lee in view of Shin et. al., (US 2005/0027177 A1).
Regarding Claim 13, Lee discloses as described above, The apparatus of claim 1. For the remainder of Claim 13, Lee discloses the compensation unit performs ([0069] “calibration to the verified blood glucose information data is performed (S115)…”; [0093] “..The terminal controller (127) performs various processing processes…calibration…”)
Lee does not disclose at least one of: a first sensor sensitivity determination process of determining a first sensitivity based on the compensation data and a set reference glucose level; a second sensor sensitivity determination process of determining a second sensitivity based on a sensor sensitivity set in response to a glucose measurement sensor and the first sensitivity; a third sensor sensitivity determination process of adjusting the second sensitivity based on a first previous time point sensitivity and a first previous time point final sensitivity that are determined at a previous time point and determining the adjusted second sensitivity as the third sensitivity; and a fourth sensor sensitivity determination process of adjusting the third sensitivity according to whether a glucose level acquired based on the third sensitivity falls within a set range and determining the adjusted third sensitivity as a fourth sensitivity, and determines any one of the first sensitivity, the second sensitivity, the third sensitivity, and the fourth sensitivity as the final sensitivity.
Shin teaches a glucose monitor for which calibration occurs by determining sensitivities of the sensor in multiple ways, including SPSR (single-point sensitivity ratio), MSPSR (modified single-point sensitivity ratio), averaging, LRSR (linear regression sensitivity ratio), and MLRSR (modified linear regression sensitivity ratio). Specifically for Claim 13, Shin teaches wherein the compensation unit performs at least one of ([0015] “the processor includes software to calculate calibration characteristics…”)
a first sensor sensitivity determination process ([0072] “single-point calibration equation…SPSR…”) of determining a first sensitivity ([0072] “…calibration factor SPSR…”) based on the compensation data ([0072] “single paired calibration point 700…”) and a set reference glucose level ([0072] “…single-point (0,0)”, “single-point calibration equation to calculate the calibration factor SPSR…”);
a second sensor sensitivity determination process ([0077] “…modified SPSR (MSPSR)…”) of determining a second sensitivity ([0077] “…calculate the MSPSR…”) based on a sensor sensitivity set in response to a glucose measurement sensor and the first sensitivity ([0077] “…When the initial calculation of the SPSR (shown above) is less than 7…offset value of 3 is used to calculate the MSPSR…initial calculation of SPSR yields a value of 7 or greater, then the offset value is 0… calibration factor (MSPSR) is calculated using the offset value in the modified single-point calibration equation…”);
a third sensor sensitivity determination process of adjusting the second sensitivity based on a first previous time point sensitivity and a first previous time point final sensitivity that are determined at a previous time point and determining the adjusted second sensitivity as the third sensitivity ([0125] “…SRn is the new sensitivity ratio calculated at the beginning of time period, n, using data from time period (n−1)”)(Examiner notes that if the sensitivities being averaged are different values, such as would be the case to yield “the new sensitivity ratio”, then the first sensitivity is broadly higher or lower than the one with which it is averaged.); and
a fourth sensor sensitivity determination process of adjusting the third sensitivity ([0130] “…readings are compared…calibration cancellation event…re-calibration…”; [0074] “…single-point calibration equation to calculate the calibration factor SPSR is as follows: SPSR=Blood Glucose Reference Reading/Valid ISIG…”; [0122] “… a sensitivity ratio (SPSR, MSPSR, LRSR, or MLRSR) calculated from data collected…”) according to whether a glucose level acquired based on the third sensitivity falls within a set range and determining the adjusted third sensitivity as a fourth sensitivity ([0130] “…once calibration is complete…blood glucose readings are compared to an out-of-range limit…If the resulting calculated blood glucose level is greater than a maximum out-of-range limit of 200 mg/dl…This is a calibration cancellation event… ISIG values are no longer valid…re-calibration is needed…”), and
determines any one of the first sensitivity ([0072] “…calibration factor SPSR…”), the second sensitivity ([0077] “…calibration factor (MSPSR) is calculated…”), the third sensitivity ([0125] “…SRn is the new sensitivity ratio calculated…”), and the fourth sensitivity ([0130] “…readings are compared…calibration cancellation event…re-calibration…”) as the final sensitivity ([0102] “…real-time calibration adjustment can be performed to account for changes in the sensor sensitivity during the lifespan of the glucose sensor….”; [0122] “ a sensitivity ratio (SPSR, MSPSR, LRSR, or MLRSR) calculated from data collected…”)
Shin teaches calibration for a continuous glucose monitor using multiple processes of SPSR, MSPSR, LRSR, MLRSR, averaging, and re-calibration to account for changing sensitivity in the sensor over time ([Abstract]; [0122]) Shin provides a motivation to combine at [0047] with “Glucose sensors are replaced periodically to avoid infection, decaying enzyme coating and therefore sensor sensitivity, deoxidization of the electrodes, and the like.” and [0102] “real-time calibration adjustment can be performed to account for changes in the sensor sensitivity during the lifespan of the glucose sensor 12 and to detect when a sensor fails…” A person having ordinary skill in the art before the effective filing date of the claimed invention would recognize that using multiple processes of SPSR, MSPSR, LRSR, MLRSR, averaging, and re-calibration to determine the sensor sensitivity for the continuous glucose monitor over time would be useful for obtaining a more accurate sensitivity level for calibration as the sensor degrades or eventually fails over time.
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the continuous glucose monitor that performs calibration on the noise-processed glucose data disclosed by Lee with the sensitivity determination processes of SPSR, MSPSR, LRSR, MLRSR, averaging, and re-calibration taught by Shin, creating a single continuous glucose monitor that is calibrated based on sensitivity over time to ensure more accurate measurements as the sensors sensitivity changes.
Regarding Claim 14, Lee discloses as described above, The apparatus of claim 13. For the remainder of Claim 14, Lee discloses the compensation unit performs ([0069] “calibration to the verified blood glucose information data is performed (S115)…”; [0093] “..The terminal controller (127) performs various processing processes…calibration…”)
Lee does not disclose the second sensor sensitivity determination process of: determining the sensor sensitivity as the second sensitivity based on that the first sensitivity is higher than or equal to the sensor sensitivity; and determining the processed sensor sensitivity, which is obtained by processing the sensor sensitivity through a set algorithm, as the second sensitivity based on that the first sensitivity is lower than the sensor sensitivity.
Shin teaches the second sensor sensitivity determination process ([0077] “MSPSR”) of:
determining the sensor sensitivity as the second sensitivity based on that the first sensitivity is higher than or equal to the sensor sensitivity ([0077] “when…initial calculation of SPSR yields a value of 7 or greater, then the offset value is 0… calibration factor (MSPSR) is calculated using the offset value in the modified single-point calibration equation…”); and
determining the processed sensor sensitivity, which is obtained by processing the sensor sensitivity through a set algorithm, as the second sensitivity based on that the first sensitivity is lower than the sensor sensitivity ([0077] “…When the initial calculation of the SPSR (shown above) is less than 7…offset value of 3 is used to calculate the MSPSR…calibration factor (MSPSR) is calculated using the offset value in the modified single-point calibration equation…”).
The motivation for Claim 14 to combine Lee with Shin is similar to that described above in more detail in Claim 13. In summary, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the continuous glucose monitor that performs calibration on the noise-processed glucose data disclosed by Lee with the sensitivity determination processes of SPSR and MSPSR taught by Shin, creating a single continuous glucose monitor that is calibrated based on sensitivity over time to ensure more accurate measurements as the sensors sensitivity changes.
Regarding Claim 15, Lee discloses as described above, The apparatus of claim 13. For the remainder of Claim 15, Lee discloses the compensation unit performs ([0069] “calibration to the verified blood glucose information data is performed (S115)…”; [0093] “..The terminal controller (127) performs various processing processes…calibration…”)
Lee does not disclose the third sensor sensitivity determination process of determining an average value of the first sensitivity and the second sensitivity as the third sensitivity based on that a state in which the first sensitivity determined at a previous time point is higher or lower than the final sensitivity of the corresponding previous time point occurs continuously.
Shin teaches the third sensor sensitivity determination process of determining an average value of the first sensitivity and the second sensitivity as the third sensitivity ([0122] – [0124] including “…weighted average using a sensitivity ratio (SPSR,MSPSR, LRSR, or MLRSR)…So the initial sensitivity ratio (SR1) is calculated immediately after initialization/stabilization…”, “…an average of SR1 and the sensitivity ratio as calculated using the paired calibration data points since the initial calibration…an average of SR2 and the sensitivity ratio…”) based on that a state in which the first sensitivity determined at a previous time point is higher or lower than the final sensitivity of the corresponding previous time point occurs continuously ([0125] “…SRn is the new sensitivity ratio calculated at the beginning of time period, n, using data from time period (n−1)”)(Examiner notes that if the sensitivities being averaged are different values, such as would be the case to yield “the new sensitivity ratio”, then the first sensitivity is broadly higher or lower than the one with which it is averaged.)
The motivation for Claim 15 to combine Lee with Shin is similar to that described above in more detail in Claim 13. In summary, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the continuous glucose monitor that performs calibration on the noise-processed glucose data disclosed by Lee with the sensitivity determination processes of SPSR, MSPSR, LRSR, MLRSR, averaging, and re-calibration taught by Shin, creating a single continuous glucose monitor that is calibrated based on sensitivity over time to ensure more accurate measurements as the sensors sensitivity changes.
Regarding Claim 16, Lee discloses as described above, The apparatus of claim 15. For the remainder of Claim 16, Lee discloses the compensation unit performs ([0069] “calibration to the verified blood glucose information data is performed (S115)…”; [0093] “..The terminal controller (127) performs various processing processes…calibration…”)
Lee does not disclose the fourth sensor sensitivity determination process of: acquiring a glucose level related to the compensation data using the third sensitivity; determining the third sensitivity as the fourth sensitivity when the glucose level falls within a preset range; and determining the fourth sensitivity based on a glucose level at the previous time point, a reference glucose level, and the compensation data when the glucose level does not fall within a preset range.
Shin teaches the fourth sensor sensitivity determination process of: acquiring a glucose level related to the compensation data using the third sensitivity ([0130] “…once calibration is complete…blood glucose readings are compared to an out-of-range limit…”);
determining the third sensitivity as the fourth sensitivity when the glucose level falls within a preset range ([0130] “…once calibration is complete…blood glucose readings are compared to an out-of-range limit…If the resulting calculated blood glucose level is greater than a maximum out-of-range limit of 200 mg/dl…This is a calibration cancellation event… ISIG values are no longer valid…re-calibration is needed…”)(Examiner notes that if the values are not out-of-range, then a calibration cancellation event has not occurred, and the sensitivity value remains in use/is confirmed as currently “valid”); and
determining the fourth sensitivity based on a glucose level at the previous time point, a reference glucose level, and the compensation data when the glucose level does not fall within a preset range ([0122] “after the first calibration is performed on a particular glucose sensor 12, subsequent calibrations employ a weighted average using a sensitivity ratio (SPSR, MSPSR, LRSR, or MLRSR) calculated from data collected since the last calibration, and previous sensitivity ratios calculated for previous calibrations…”; [0130] “…re-calibration is needed”; [0074] “…single-point calibration equation to calculate the calibration factor SPSR is as follows: SPSR=Blood Glucose Reference Reading/Valid ISIG…”)
The motivation for Claim 16 to combine Lee with Shin is similar to that described above in more detail in Claim 13. In summary, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the continuous glucose monitor that performs calibration on the noise-processed glucose data disclosed by Lee with the sensitivity determination processes of SPSR, MSPSR, LRSR, MLRSR, averaging, and re-calibration taught by Shin, creating a single continuous glucose monitor that is calibrated based on sensitivity over time to ensure more accurate measurements as the sensors sensitivity changes.
Claim 17 is rejected under 35 U.S.C. 103 as being unpatentable over Lee in view of Hayter et. al., (US 2018/0008201 A1).
Regarding Claim 17, Lee discloses as described above, The apparatus of claim 1. For the remainder of Claim 17, Lee does not specifically disclose the glucose level acquisition unit compensates for the time delay in the second biometric information to generate time-compensated biometric information, and applies the time-compensated biometric information to the calibration algorithm to acquire the glucose level. Lee does broadly disclose at [0011] “…a calibration step for time delay and accuracy improvement.”
Hayter teaches methods and apparatus for determining a glucose value for a continuous glucose monitor including a time constant to correct calibration and glucose calculations for time lag effects ([Abstract]; [0076]; Fig. 7). Specifically for Claim 17, Hayter teaches wherein the glucose level acquisition unit compensates for the time delay in the biometric information to generate time-compensated biometric information (Fig. 7; [0064] “these pairs are used to estimate the lag time constant (740)….”; [0065] – [0066]) and
applies the time-compensated biometric information to the calibration algorithm to acquire the glucose level ([0076] “subsequently use this time constant in real time to correct calibration and glucose calculations for lag effects…”; Fig. 7 “Correct continuous glucose data for lag effects using time constant estimate”).
Lee and Hayter both disclose and teach continuous glucose monitors with calibration processes, Lee with the noise removal that culminates in second biometric information which can be calibrated, and Hayter with measurements filtered for noise ([0052]) and calibrated with a time constant to correct calibration and glucose calculations for lag effects. Hayter provides a motivation to combine at [0004] with “Due to a lag factor between the monitored data and the measured blood glucose values , an error may be introduced in the monitored data.” and [0016] with “…provided method and system for calibrating subcutaneous or transcutaneously positioned analyte sensors to compensate for time lag errors associated with an analyte sensor…” A person having ordinary skill in the art before the effective filing date of the claimed invention would recognize that using a compensation factor would be useful to obtain more accurate results from a continuous glucose monitor by compensating for the time lag between monitored data and the measured blood glucose values.
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the continuous glucose monitor that performs calibration on the noise-processed glucose data disclosed by Lee with the time lag effect compensation taught by Hayter, creating a single continuous glucose monitor that is calibrated with consideration for time lag effect between the monitored data and the measured blood glucose values to ensure more accurate glucose measurement results.
Conclusion
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/MELISSA JO MONTGOMERY/Examiner, Art Unit 3791 /ALEX M VALVIS/Supervisory Patent Examiner, Art Unit 3791
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