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 .
Claim Status: Claims 1-25 are pending.
Claim Objections
Claim 4 is objected to because of the following informalities: “the movement sensor glucose” has a typographical error.
Claim 22 is objected to because of the following informalities: “a controller configured to configured to” has a typographical error.
Appropriate correction is required.
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.
Claim 10, 13, 14, and 24 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.
Re Claim 10, the term “a significant change” in claim 10 is a relative term which renders the claim indefinite. The term “a significant change” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention.
Re Claim 13, “a current … glucose level” is indefinite, because it is unclear whether it is referring to a new current glucose level or “a current glucose level” in claim 1.
Indefiniteness of claim 13 renders its dependent claim indefinite.
Re Claim 24, “the movement sensor output signal” is indefinite, because it lacks antecedent basis. It is unclear whether it is referring to “an accelerometer output signal” or something else.
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 1-16 are rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract idea without significantly more. The claim(s) recite(s) a glucose monitoring system.
To determine whether a claim satisfies the criteria for subject matter eligibility, the claim is evaluated according to a stepwise process as described in MPEP 2106(III) and 2106.03-2106.04.
The instant claims are evaluated according to such analysis.
Step 1: Is the claim to a process, machine, manufacture or composition of matter?
Yes, Claim 1 is directed towards a machine.
Step 2A (Prong 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon?
Yes, the judicial exception relied upon by the instantly claimed invention is an abstract idea, and the limitation that sets forth or describes the abstract idea is: “a controller configured to generate an estimate of a current glucose level of the user based on the glucose sensor output signal and the movement sensor output signal.”
The reason that the above limitation is considered an abstract idea is because it is directed to mental processes (observation, evaluation, judgment, opinion). The above steps can be performed in the mind or by hand.
The 2019 revised§ 101 guidance makes clear that the "mental process" category of abstract ideas does not only apply to steps actually carried out mentally; it also applies to the types of processes that could be carried out mentally, but are instead carried out using generic processing/collection technology.
Please see the following analogous types of data manipulations that courts have found to be abstract ideas (all taken from MPEP § 2106.04):
collecting information, analyzing it, and displaying certain results of the collection and analysis, Electric Power Group, LLC v. Alstom, S.A., 830 F.3d 1350, 1351-52, 119 USPQ2d 1739, 1740 (Fed. Cir. 2016)
Step 2A (Prong 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
No, the claim recites “a controller” which can be interpreted as a generic processor. The processing device and the programmable processor do not integrate the judicial exception into a practical application, because it is merely using a generic processor as a tool to perform an abstract idea (see MPEP 2106.05(f)).
The claim also recites “a glucose sensor configured to output a glucose sensor output signal indicative of an estimate of a glucose level of a user of the glucose monitoring system” and “a movement sensor configured to output a movement sensor output signal indicative of detected movement of the user,” which are using a generic glucose sensor and a generic movement sensor to collect data with already well-known technology.
The following are relevant examples of similar limitations which courts have found not to constitute improvements to computers or improvements to other technology or technical field:
Gathering and analyzing information using conventional techniques and displaying the result, TIJ Communications, 823 F.3d at 612-13, 118 USPQ2d at 1747-48.
It is further noted that merely collecting the necessary data using known, generic sensors (or other data gathering components) only amounts to insignificant extrasolution activity; see MPEP § 2106.05(g). Applicant's claimed invention does not affect/change the functionality of the technology being used. Rather, Applicant's claimed invention uses the claimed technology for its standard, well-known purpose, e.g. known sensors are used to collect data which they are known to be capable of collecting, known generic processing circuitry is used to perform data calculations/ comparisons, etc. Applicant's invention does not result in improved performance of the sensors, the processing circuitry, etc.
Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
No, the claim recites additional elements “a glucose sensor configured to output a glucose sensor output signal indicative of an estimate of a glucose level of a user of the glucose monitoring system” and “a movement sensor configured to output a movement sensor output signal indicative of detected movement of the user”.
The additional elements do not amount to significantly more than the judicial exception, because it is simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception (See MPEP 2106.05(d)) and Berkheimer Memo.
Halleck (US 20030088160 A1) discloses sensor 1025 illustratively shown as a plural-axis (dual shown) acceleration measuring device suitably mounted on a single monolithic integrated circuit (one conventional sensor is an accelerometer available from Analog Devices, Inc., located at One Technology Way, Norwood, Mass., United States of America, namely, Model No. ADXL 202) (para. [0119]).
Lichter (US 20040167381 A1) discloses a non-invasive blood glucose sensor 403 that may comprise any conventional means for measuring a blood glucose concentration of a patient, such as, for example, a patch adapted to be attached to a person's skin or an optical measuring apparatus (para. [0087]).
Therefore, the claim is not patent eligible.
With regards to the instantly rejected dependent claims 2-16, these claims when analyzed as a whole are also held to be patent ineligible under 35 U.S.C. 101 because the additional recited limitation(s) fail(s) to establish that the claim(s) is/are not directed to a judicial exception and/or do not add significantly more to the judicial exception. Therefore, the claim(s) is/are not patent eligible.
Claims 17-19 are rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract idea without significantly more. The claim(s) recite(s) a glucose monitoring system.
To determine whether a claim satisfies the criteria for subject matter eligibility, the claim is evaluated according to a stepwise process as described in MPEP 2106(III) and 2106.03-2106.04.
The instant claims are evaluated according to such analysis.
Step 1: Is the claim to a process, machine, manufacture or composition of matter?
Yes, Claim 17 is directed towards a machine.
Step 2A (Prong 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon?
Yes, the judicial exception relied upon by the instantly claimed invention is an abstract idea, and the limitations that set forth or describe the abstract idea are: “a controller operable to: monitor a wearer glucose level estimate generated based on the glucose sensor output signal; monitor a wearer movement estimate generated based on the accelerometer output signal; determine a wearer health marker based on the monitored wearer movement estimate; and combine the monitored wearer glucose level estimate with the wearer health marker to generate a prediction of a current and/or future glucose level of the wearer.”
The reason that the above limitation is considered an abstract idea is because it is directed to mental processes (observation, evaluation, judgment, opinion). The above steps can be performed in the mind or by hand.
The 2019 revised§ 101 guidance makes clear that the "mental process" category of abstract ideas does not only apply to steps actually carried out mentally; it also applies to the types of processes that could be carried out mentally, but are instead carried out using generic processing/collection technology.
Please see the following analogous types of data manipulations that courts have found to be abstract ideas (all taken from MPEP § 2106.04):
collecting information, analyzing it, and displaying certain results of the collection and analysis, Electric Power Group, LLC v. Alstom, S.A., 830 F.3d 1350, 1351-52, 119 USPQ2d 1739, 1740 (Fed. Cir. 2016)
Step 2A (Prong 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
No, the claim recites “a controller” which can be interpreted as a generic processor. The processing device and the programmable processor do not integrate the judicial exception into a practical application, because it is merely using a generic processor as a tool to perform an abstract idea (see MPEP 2106.05(f)).
The claim also recites “a glucose sensor configured to output a glucose sensor output signal indicative of an estimate of a glucose level of a wearer of the glucose monitoring system” and “an accelerometer configured to output an accelerometer output signal indicative of movement of a wearer of the glucose monitoring system,” which are using a generic glucose sensor and a generic accelerometer to collect data with already well-known technology.
The following are relevant examples of similar limitations which courts have found not to constitute improvements to computers or improvements to other technology or technical field:
Gathering and analyzing information using conventional techniques and displaying the result, TIJ Communications, 823 F.3d at 612-13, 118 USPQ2d at 1747-48.
It is further noted that merely collecting the necessary data using known, generic sensors (or other data gathering components) only amounts to insignificant extrasolution activity; see MPEP § 2106.05(g). Applicant's claimed invention does not affect/change the functionality of the technology being used. Rather, Applicant's claimed invention uses the claimed technology for its standard, well-known purpose, e.g. known sensors are used to collect data which they are known to be capable of collecting, known generic processing circuitry is used to perform data calculations/ comparisons, etc. Applicant's invention does not result in improved performance of the sensors, the processing circuitry, etc.
Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
No, the claim recites additional elements “a glucose sensor configured to output a glucose sensor output signal indicative of an estimate of a glucose level of a wearer of the glucose monitoring system” and “an accelerometer configured to output an accelerometer output signal indicative of movement of a wearer of the glucose monitoring system.”
The additional elements do not amount to significantly more than the judicial exception, because it is simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception (See MPEP 2106.05(d)) and Berkheimer Memo.
Halleck (US 20030088160 A1) discloses sensor 1025 illustratively shown as a plural-axis (dual shown) acceleration measuring device suitably mounted on a single monolithic integrated circuit (one conventional sensor is an accelerometer available from Analog Devices, Inc., located at One Technology Way, Norwood, Mass., United States of America, namely, Model No. ADXL 202) (para. [0119]).
Lichter (US 20040167381 A1) discloses a non-invasive blood glucose sensor 403 that may comprise any conventional means for measuring a blood glucose concentration of a patient, such as, for example, a patch adapted to be attached to a person's skin or an optical measuring apparatus (para. [0087]).
Therefore, the claim is not patent eligible.
With regards to the instantly rejected dependent claims 18-19, these claims when analyzed as a whole are also held to be patent ineligible under 35 U.S.C. 101 because the additional recited limitation(s) fail(s) to establish that the claim(s) is/are not directed to a judicial exception and/or do not add significantly more to the judicial exception. Therefore, the claim(s) is/are not patent eligible.
Claim 20 is rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract idea without significantly more. The claim(s) recite(s) an integrated circuit for a glucose monitoring system.
To determine whether a claim satisfies the criteria for subject matter eligibility, the claim is evaluated according to a stepwise process as described in MPEP 2106(III) and 2106.03-2106.04.
The instant claims are evaluated according to such analysis.
Step 1: Is the claim to a process, machine, manufacture or composition of matter?
Yes, Claim 20 is directed towards a machine.
Step 2A (Prong 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon?
Yes, the judicial exception relied upon by the instantly claimed invention is an abstract idea, and the limitations that set forth or describe the abstract idea are: “a controller, wherein the controller is configured to: receive a movement output signal indicative of detected movement of a user of the glucose monitoring system; receive, from a glucose sensor of the glucose monitoring system, a glucose sensor output signal indicative of an estimate of a glucose level of the user; and generate an estimate of a current and/or future glucose level of the user based on the glucose sensor output signal and the movement sensor output signal.”
The reason that the above limitation is considered an abstract idea is because it is directed to mental processes (observation, evaluation, judgment, opinion). The above steps can be performed in the mind or by hand.
The 2019 revised§ 101 guidance makes clear that the "mental process" category of abstract ideas does not only apply to steps actually carried out mentally; it also applies to the types of processes that could be carried out mentally, but are instead carried out using generic processing/collection technology.
Please see the following analogous types of data manipulations that courts have found to be abstract ideas (all taken from MPEP § 2106.04):
collecting information, analyzing it, and displaying certain results of the collection and analysis, Electric Power Group, LLC v. Alstom, S.A., 830 F.3d 1350, 1351-52, 119 USPQ2d 1739, 1740 (Fed. Cir. 2016)
Step 2A (Prong 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
No, the claim recites “a controller” which can be interpreted as a generic processor. The processing device and the programmable processor do not integrate the judicial exception into a practical application, because it is merely using a generic processor as a tool to perform an abstract idea (see MPEP 2106.05(f)).
The claim also recites “a movement sensor,” which is a generic movement sensor to collect data with already well-known technology.
The following are relevant examples of similar limitations which courts have found not to constitute improvements to computers or improvements to other technology or technical field:
Gathering and analyzing information using conventional techniques and displaying the result, TIJ Communications, 823 F.3d at 612-13, 118 USPQ2d at 1747-48.
It is further noted that merely collecting the necessary data using known, generic sensors (or other data gathering components) only amounts to insignificant extrasolution activity; see MPEP § 2106.05(g). Applicant's claimed invention does not affect/change the functionality of the technology being used. Rather, Applicant's claimed invention uses the claimed technology for its standard, well-known purpose, e.g. known sensors are used to collect data which they are known to be capable of collecting, known generic processing circuitry is used to perform data calculations/ comparisons, etc. Applicant's invention does not result in improved performance of the sensors, the processing circuitry, etc.
Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
No, the claim recites an additional element “a movement sensor.”
The additional elements do not amount to significantly more than the judicial exception, because it is simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception (See MPEP 2106.05(d)) and Berkheimer Memo.
Halleck (US 20030088160 A1) discloses sensor 1025 illustratively shown as a plural-axis (dual shown) acceleration measuring device suitably mounted on a single monolithic integrated circuit (one conventional sensor is an accelerometer available from Analog Devices, Inc., located at One Technology Way, Norwood, Mass., United States of America, namely, Model No. ADXL 202) (para. [0119]).
Therefore, the claim is not patent eligible.
Claim 21 is rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract idea without significantly more. The claim(s) recite(s) a glucose monitoring system.
To determine whether a claim satisfies the criteria for subject matter eligibility, the claim is evaluated according to a stepwise process as described in MPEP 2106(III) and 2106.03-2106.04.
The instant claims are evaluated according to such analysis.
Step 1: Is the claim to a process, machine, manufacture or composition of matter?
Yes, Claim 21 is directed towards a machine.
Step 2A (Prong 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon?
Yes, the judicial exception relied upon by the instantly claimed invention is an abstract idea, and the limitations that set forth or describe the abstract idea are: “the system is configured to produce feedback for the user based on the glucose sensor output signal and the movement sensor output signal.”
The reason that the above limitation is considered an abstract idea is because it is directed to mental processes (observation, evaluation, judgment, opinion). The above steps can be performed in the mind or by hand.
The 2019 revised§ 101 guidance makes clear that the "mental process" category of abstract ideas does not only apply to steps actually carried out mentally; it also applies to the types of processes that could be carried out mentally, but are instead carried out using generic processing/collection technology.
Please see the following analogous types of data manipulations that courts have found to be abstract ideas (all taken from MPEP § 2106.04):
collecting information, analyzing it, and displaying certain results of the collection and analysis, Electric Power Group, LLC v. Alstom, S.A., 830 F.3d 1350, 1351-52, 119 USPQ2d 1739, 1740 (Fed. Cir. 2016)
Step 2A (Prong 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
No, the claim recites “a system” which can be interpreted to comprise a generic processor. The processing device and the programmable processor do not integrate the judicial exception into a practical application, because it is merely using a generic processor as a tool to perform an abstract idea (see MPEP 2106.05(f)).
The claim also recites “a glucose sensor configured to output a glucose sensor output signal indicative of an estimate of a glucose level of a user of the glucose monitoring system” and “a movement sensor configured to output a movement sensor output signal indicative of movement of the user,” which are using a generic glucose sensor and a generic accelerometer to collect data with already well-known technology.
The following are relevant examples of similar limitations which courts have found not to constitute improvements to computers or improvements to other technology or technical field:
Gathering and analyzing information using conventional techniques and displaying the result, TIJ Communications, 823 F.3d at 612-13, 118 USPQ2d at 1747-48.
It is further noted that merely collecting the necessary data using known, generic sensors (or other data gathering components) only amounts to insignificant extrasolution activity; see MPEP § 2106.05(g). Applicant's claimed invention does not affect/change the functionality of the technology being used. Rather, Applicant's claimed invention uses the claimed technology for its standard, well-known purpose, e.g. known sensors are used to collect data which they are known to be capable of collecting, known generic processing circuitry is used to perform data calculations/ comparisons, etc. Applicant's invention does not result in improved performance of the sensors, the processing circuitry, etc.
Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
No, the claim recites additional elements “a glucose sensor configured to output a glucose sensor output signal indicative of an estimate of a glucose level of a user of the glucose monitoring system” and “a movement sensor configured to output a movement sensor output signal indicative of movement of the user.”
The additional elements do not amount to significantly more than the judicial exception, because it is simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception (See MPEP 2106.05(d)) and Berkheimer Memo.
Halleck (US 20030088160 A1) discloses sensor 1025 illustratively shown as a plural-axis (dual shown) acceleration measuring device suitably mounted on a single monolithic integrated circuit (one conventional sensor is an accelerometer available from Analog Devices, Inc., located at One Technology Way, Norwood, Mass., United States of America, namely, Model No. ADXL 202) (para. [0119]).
Lichter (US 20040167381 A1) discloses a non-invasive blood glucose sensor 403 that may comprise any conventional means for measuring a blood glucose concentration of a patient, such as, for example, a patch adapted to be attached to a person's skin or an optical measuring apparatus (para. [0087]).
Therefore, the claim is not patent eligible.
Claim 24 is rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract idea without significantly more. The claim(s) recite(s) a glucose monitoring system.
To determine whether a claim satisfies the criteria for subject matter eligibility, the claim is evaluated according to a stepwise process as described in MPEP 2106(III) and 2106.03-2106.04.
The instant claims are evaluated according to such analysis.
Step 1: Is the claim to a process, machine, manufacture or composition of matter?
Yes, Claim 24 is directed towards a machine.
Step 2A (Prong 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon?
Yes, the judicial exception relied upon by the instantly claimed invention is an abstract idea, and the limitations that set forth or describe the abstract idea are: “a predictor configured to generate a prediction of a current and/or future glucose level of the user based on the glucose sensor output signal and the movement sensor output signal.”
The reason that the above limitation is considered an abstract idea is because it is directed to mental processes (observation, evaluation, judgment, opinion). The above steps can be performed in the mind or by hand.
The 2019 revised§ 101 guidance makes clear that the "mental process" category of abstract ideas does not only apply to steps actually carried out mentally; it also applies to the types of processes that could be carried out mentally, but are instead carried out using generic processing/collection technology.
Please see the following analogous types of data manipulations that courts have found to be abstract ideas (all taken from MPEP § 2106.04):
collecting information, analyzing it, and displaying certain results of the collection and analysis, Electric Power Group, LLC v. Alstom, S.A., 830 F.3d 1350, 1351-52, 119 USPQ2d 1739, 1740 (Fed. Cir. 2016)
Step 2A (Prong 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
No, the claim recites “a predictor” which can be interpreted as a generic processor. The processing device and the programmable processor do not integrate the judicial exception into a practical application, because it is merely using a generic processor as a tool to perform an abstract idea (see MPEP 2106.05(f)).
The claim also recites “a glucose sensor configured to output a glucose sensor output signal indicative of an estimate of a glucose level of a user of the glucose monitoring system” and “an accelerometer configured to output an accelerometer output signal indicative of movement of the user,” which are using a generic glucose sensor and a generic accelerometer to collect data with already well-known technology.
The following are relevant examples of similar limitations which courts have found not to constitute improvements to computers or improvements to other technology or technical field:
Gathering and analyzing information using conventional techniques and displaying the result, TIJ Communications, 823 F.3d at 612-13, 118 USPQ2d at 1747-48.
It is further noted that merely collecting the necessary data using known, generic sensors (or other data gathering components) only amounts to insignificant extrasolution activity; see MPEP § 2106.05(g). Applicant's claimed invention does not affect/change the functionality of the technology being used. Rather, Applicant's claimed invention uses the claimed technology for its standard, well-known purpose, e.g. known sensors are used to collect data which they are known to be capable of collecting, known generic processing circuitry is used to perform data calculations/ comparisons, etc. Applicant's invention does not result in improved performance of the sensors, the processing circuitry, etc.
Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
No, the claim recites additional elements “a glucose sensor configured to output a glucose sensor output signal indicative of an estimate of a glucose level of a user of the glucose monitoring system” and “an accelerometer configured to output an accelerometer output signal indicative of movement of the user.”
The additional elements do not amount to significantly more than the judicial exception, because it is simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception (See MPEP 2106.05(d)) and Berkheimer Memo.
Halleck (US 20030088160 A1) discloses sensor 1025 illustratively shown as a plural-axis (dual shown) acceleration measuring device suitably mounted on a single monolithic integrated circuit (one conventional sensor is an accelerometer available from Analog Devices, Inc., located at One Technology Way, Norwood, Mass., United States of America, namely, Model No. ADXL 202) (para. [0119]).
Lichter (US 20040167381 A1) discloses a non-invasive blood glucose sensor 403 that may comprise any conventional means for measuring a blood glucose concentration of a patient, such as, for example, a patch adapted to be attached to a person's skin or an optical measuring apparatus (para. [0087]).
Therefore, the claim is not patent eligible.
Claim 25 is rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract idea without significantly more. The claim(s) recite(s) an integrated circuit for a glucose monitoring system.
To determine whether a claim satisfies the criteria for subject matter eligibility, the claim is evaluated according to a stepwise process as described in MPEP 2106(III) and 2106.03-2106.04.
The instant claims are evaluated according to such analysis.
Step 1: Is the claim to a process, machine, manufacture or composition of matter?
Yes, Claim 24 is directed towards a machine.
Step 2A (Prong 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon?
Yes, the judicial exception relied upon by the instantly claimed invention is an abstract idea, and the limitations that set forth or describe the abstract idea are: “the predictor is configured to generate a prediction of a current and/or future glucose level of user of the glucose monitoring system based on the accelerometer output signal and a glucose sensor output signal received from a glucose sensor of the glucose monitoring system.”
The reason that the above limitation is considered an abstract idea is because it is directed to mental processes (observation, evaluation, judgment, opinion). The above steps can be performed in the mind or by hand.
The 2019 revised§ 101 guidance makes clear that the "mental process" category of abstract ideas does not only apply to steps actually carried out mentally; it also applies to the types of processes that could be carried out mentally, but are instead carried out using generic processing/collection technology.
Please see the following analogous types of data manipulations that courts have found to be abstract ideas (all taken from MPEP § 2106.04):
collecting information, analyzing it, and displaying certain results of the collection and analysis, Electric Power Group, LLC v. Alstom, S.A., 830 F.3d 1350, 1351-52, 119 USPQ2d 1739, 1740 (Fed. Cir. 2016)
Step 2A (Prong 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
No, the claim recites “a predictor” which can be interpreted as a generic processor. The processing device and the programmable processor do not integrate the judicial exception into a practical application, because it is merely using a generic processor as a tool to perform an abstract idea (see MPEP 2106.05(f)).
The claim also recites “an accelerometer configured to output an accelerometer output signal indicative of movement of the user,” which is using a generic accelerometer to collect data with already well-known technology.
The following are relevant examples of similar limitations which courts have found not to constitute improvements to computers or improvements to other technology or technical field:
Gathering and analyzing information using conventional techniques and displaying the result, TIJ Communications, 823 F.3d at 612-13, 118 USPQ2d at 1747-48.
It is further noted that merely collecting the necessary data using known, generic sensors (or other data gathering components) only amounts to insignificant extrasolution activity; see MPEP § 2106.05(g). Applicant's claimed invention does not affect/change the functionality of the technology being used. Rather, Applicant's claimed invention uses the claimed technology for its standard, well-known purpose, e.g. known sensors are used to collect data which they are known to be capable of collecting, known generic processing circuitry is used to perform data calculations/ comparisons, etc. Applicant's invention does not result in improved performance of the sensors, the processing circuitry, etc.
Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
No, the claim recites an additional element “an accelerometer configured to output an accelerometer output signal indicative of movement of the user.”
The additional element does not amount to significantly more than the judicial exception, because it is simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception (See MPEP 2106.05(d)) and Berkheimer Memo.
Halleck (US 20030088160 A1) discloses sensor 1025 illustratively shown as a plural-axis (dual shown) acceleration measuring device suitably mounted on a single monolithic integrated circuit (one conventional sensor is an accelerometer available from Analog Devices, Inc., located at One Technology Way, Norwood, Mass., United States of America, namely, Model No. ADXL 202) (para. [0119]).
Therefore, the claim is not patent eligible.
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, 5-8, 11-14, and 16 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Pickus (US 2023/0136188A1).
Re Claim 1, Pickus discloses a glucose monitoring system comprising:
a glucose sensor configured to output a glucose sensor output signal indicative of an estimate of a glucose level of a user of the glucose monitoring system (para. [0027], glucose sensor);
a movement sensor configured to output a movement sensor output signal indicative of detected movement of the user (para. [0050], accelerometer. Physical activity data can be received from various sources, such as wearable glucose monitoring device 104, an activity tracking application running on computing device 106, an activity or fitness tracker worn by the user 102, and so forth); and
a controller configured to generate an estimate of a current glucose level of the user based on the glucose sensor output signal and the movement sensor output signal (para. [0030], The computing device 106 may correspond to both a wearable device (e.g., a smart watch) and a mobile phone; fig. 1, para. [0032], the computing device 106 includes glucose monitoring application 116 and storage device 118. Here, the glucose monitoring application 116 includes the glucose prediction system 120; para. [0130], [0075], the machine learning system can be trained to generate the predicted glucose measurements based on any combination of physiological parameters (e.g., raw heart rate data, relative heart rate-based intensity measures, blood pressure measures, and so forth), demographic information (e.g., age, gender, and so forth), clinical information (medication stack data, prevalence of comorbidities data, fitness level data, etc.), and so forth; para. [0076] and [0078], the machine learning system is trained to generate a number of glucose measurements following the training data that would typically be measured during a bout of physical activity (e.g., during the average duration or typical duration for a bout of physical activity); para. [0080], the glucose measurement prediction module 308 can use physiological (pharmo-kinetics) or phenomenological models. E.g., glucose uptake can be modeled using ordinary differential equations that have parameters such as glucose uptake and exercise intensity; para. [0081], [0082], fig. 4, The glucose measurements 406 are used by the glucose measurement prediction module 308 to generate predicted glucose measurements 408 that occur immediately after the glucose measurements 402. The predicted glucose measurements 408 are generated for the duration of the bout of physical activity that began at the time 404. Additionally or alternatively, the predicted glucose measurements 408 may be generated for other durations of time, such as an amount of time (e.g., 15 or 20 minutes) extending beyond the bout of physical activity; para. [0089], [0090], The discussions of the glucose prediction system 120 also include generating predicted glucose measurements 328 in response to detecting bouts of physical activity.).
Re Claim 5, Pickus discloses an output transducer subsystem configured to provide an output for the user based on the glucose sensor output signal and the movement sensor output signal (para. [0085], The UI module 310 receives the predicted glucose measurements 328 and causes the predicted glucose measurements 328 to be displayed or otherwise presented (e.g., at computing device 106). This display or other presentation can take various forms, such as a static text display, graphic or video display, audio presentation, combinations thereof, and so forth).
Re Claim 6, Pickus discloses that the output transducer subsystem comprises an audio transducer and/or a haptic transducer (para. [0085], The UI module 310 receives the predicted glucose measurements 328 and causes the predicted glucose measurements 328 to be displayed or otherwise presented (e.g., at computing device 106). This display or other presentation can take various forms, such as a static text display, graphic or video display, audio presentation, combinations thereof, and so forth).
Re Claim 7, Pickus discloses a communications subsystem configured to communicate with an external device to transmit data and/or alerts to the external device (para. [0030], The computing device 106 may correspond to both a wearable device (e.g., a smart watch) and a mobile phone. In such scenarios, both of these devices may be capable of performing at least some of the same operations, such as to receive the glucose measurements 114 from the wearable glucose monitoring device 104, communicate them via the network 112 to the glucose monitoring platform 110, display information related to the glucose measurements 114, and so forth).
Re Claim 8, Pickus discloses that the movement sensor comprises an accelerometer (para. [0050], accelerometer).
Re Claim 11, Pickus discloses that the controller is configured to trigger an output signal based on one or more of:
the glucose sensor output signal (para. [0030], display information related to the glucose measurements 114);
the movement output signal; and
a combination or fusion of the glucose sensor output signal and the movement sensor output signal (para. [0085], The UI module 310 receives the predicted glucose measurements 328 and causes the predicted glucose measurements 328 to be displayed or otherwise presented (e.g., at computing device 106). This display or other presentation can take various forms, such as a static text display, graphic or video display, audio presentation, combinations thereof, and so forth).
Re Claim 12, Pickus discloses that the output comprises one or more of:
an audio output signal for an audio output transducer of the glucose monitoring system (para. [0085], The UI module 310 receives the predicted glucose measurements 328 and causes the predicted glucose measurements 328 to be displayed or otherwise presented (e.g., at computing device 106). This display or other presentation can take various forms, such as a static text display, graphic or video display, audio presentation, combinations thereof, and so forth);
a haptic output signal for a haptic output transducer of the glucose monitoring system; and
a control signal for transmission to an external device with which the glucose monitoring system communicates via a communications subsystem of the glucose monitoring system, the control signal being configured to trigger an audible and/or visible and/or haptic output of the external device (fig. 3, para. [0085], The UI module 310 receives the predicted glucose measurements 328 and causes the predicted glucose measurements 328 to be displayed or otherwise presented (e.g., at computing device 106). This display or other presentation can take various forms, such as a static text display, graphic or video display, audio presentation, combinations thereof, and so forth; para. [0030], The computing device 106 may correspond to both a wearable device (e.g., a smart watch) and a mobile phone. In such scenarios, both of these devices may be capable of performing at least some of the same operations, such as to receive the glucose measurements 114 from the wearable glucose monitoring device 104, communicate them via the network 112 to the glucose monitoring platform 110, display information related to the glucose measurements 114, and so forth).
Re Claim 13, Pickus discloses a predictor configured to generate a prediction of a current and/or future glucose level of the user based on the glucose sensor output signal and the movement sensor output signal (para. [0030], The computing device 106 may correspond to both a wearable device (e.g., a smart watch) and a mobile phone; fig. 1, para. [0032], the computing device 106 includes glucose monitoring application 116 and storage device 118. Here, the glucose monitoring application 116 includes the glucose prediction system 120; para. [0130], [0075], the machine learning system can be trained to generate the predicted glucose measurements based on any combination of physiological parameters (e.g., raw heart rate data, relative heart rate-based intensity measures, blood pressure measures, and so forth), demographic information (e.g., age, gender, and so forth), clinical information (medication stack data, prevalence of comorbidities data, fitness level data, etc.), and so forth; para. [0076] and [0078], the machine learning system is trained to generate a number of glucose measurements following the training data that would typically be measured during a bout of physical activity (e.g., during the average duration or typical duration for a bout of physical activity); para. [0080], the glucose measurement prediction module 308 can use physiological (pharmo-kinetics) or phenomenological models. E.g., glucose uptake can be modeled using ordinary differential equations that have parameters such as glucose uptake and exercise intensity; para. [0081], [0082], fig. 4, The glucose measurements 406 are used by the glucose measurement prediction module 308 to generate predicted glucose measurements 408 that occur immediately after the glucose measurements 402. The predicted glucose measurements 408 are generated for the duration of the bout of physical activity that began at the time 404. Additionally or alternatively, the predicted glucose measurements 408 may be generated for other durations of time, such as an amount of time (e.g., 15 or 20 minutes) extending beyond the bout of physical activity; para. [0089], [0090], The discussions of the glucose prediction system 120 also include generating predicted glucose measurements 328 in response to detecting bouts of physical activity.).
Re Claim 14, Pickus discloses that the predictor comprises a trained neural network, artificial intelligence or machine learning processor trained to generate the prediction of the current and/or future glucose level of the wearer based on the glucose sensor output signal and the movement sensor output signal (para. [0072], [0075], the machine learning system can be trained to generate the predicted glucose measurements based on any combination of physiological parameters (e.g., raw heart rate data, relative heart rate-based intensity measures, blood pressure measures, and so forth), demographic information (e.g., age, gender, and so forth), clinical information (medication stack data, prevalence of comorbidities data, fitness level data, etc.), and so forth.).
Re Claim 16, Pickus discloses that the glucose monitoring system is a wearable glucose monitoring system (para. [0030], The computing device 106 may correspond to both a wearable device (e.g., a smart watch) and a mobile phone; fig. 1, para. [0032], the computing device 106 includes glucose monitoring application 116 and storage device 118. Here, the glucose monitoring application 116 includes the glucose prediction system 120.).
Claims 20 and 21 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Derdzinski (US 2021/0378563A1)
Re Claim 20, Derdzinski discloses an integrated circuit for a glucose monitoring system (para. [0049], [0046], computing device 108), the integrated circuit comprising:
a movement sensor (para. [0091], activity data from various sensors (e.g., step data, workouts performed, or other data indicative of user activity or exercise); para. [0046], the computing device 108 represents separate devices, (e.g., a smart watch and a mobile phone) one device may be configured with various sensors and functionality to measure a variety of physiological markers (e.g., heartrate, breathing, rate of blood flow, and so on) and activities (e.g., steps, elevation changes, and the like) of the person 102; para. [0046], the computing device 108 represents separate devices, (e.g., a smart watch and a mobile phone) one device may be configured with various sensors and functionality to measure a variety of physiological markers (e.g., heartrate, breathing, rate of blood flow, and so on) and activities (e.g., steps, elevation changes, and the like) of the person 102.); and
a controller (para. [0078], the data analytics platform 122, para. [0086], prediction system 310; para. [0049], Although depicted as separate from the computing device 108, portions or an entirety of the data analytics platform 122 may alternatively or additionally be implemented at the computing device 108.),
wherein the controller is configured to:
receive a movement output signal indicative of detected movement of a user of the glucose monitoring system (para. [0091], activity data from various sensors (e.g., step data, workouts performed, or other data indicative of user activity or exercise));
receive, from a glucose sensor of the glucose monitoring system, a glucose sensor output signal indicative of an estimate of a glucose level of the user (para. [0061], a glucose sensor configured to detect analytes in blood or interstitial fluid that are indicative of glucose level using one or more measurement techniques); and
generate an estimate of a current and/or future glucose level of the user based on the glucose sensor output signal and the movement sensor output signal (para. [0091], [0101], [0195], The prediction system 310 additionally obtains additional data 404 from one or more sources. The additional data 404 is representative of information useable to describe various aspects that may impact future glucose levels of the person 102. The additional data 404 may be correlated in time with glucose measurements 118 (e.g., based on timestamps associated with the additional data 404). Such additional data 404 may include data describing insulin administered (e.g., timing and insulin doses), data describing food consumed (e.g., timing of food consumption, type of food, and/or amount of carbohydrates consumed, activity data from various sensors (e.g., step data, workouts performed, or other data indicative of user activity or exercise), glucose level responses to stress, combinations thereof and so forth; para. [0092], [0093], aspects that may be indicative of a person's future glucose levels may include data describing aspects of exercise (e.g., workout frequency, duration, intensity, and so forth), sleep (e.g., duration, quality, etc.), stress (e.g., blood pressure, heart rate, and the like), to name just a few.).
Re Claim 21, Derdzinski discloses a glucose monitoring system comprising:
a glucose sensor configured to output a glucose sensor output signal indicative of an estimate of a glucose level of a user of the glucose monitoring system (para. [0061], a glucose sensor configured to detect analytes in blood or interstitial fluid that are indicative of glucose level using one or more measurement techniques); and
a movement sensor configured to output a movement sensor output signal indicative of detected movement of the user (para. [0091], activity data from various sensors (e.g., step data, workouts performed, or other data indicative of user activity or exercise)),
wherein the system is configured to produce feedback for the user based on the glucose sensor output signal and the movement sensor output signal (para. [0091], [0101], [0195], The prediction system 310 additionally obtains additional data 404 from one or more sources. The additional data 404 is representative of information useable to describe various aspects that may impact future glucose levels of the person 102. The additional data 404 may be correlated in time with glucose measurements 118 (e.g., based on timestamps associated with the additional data 404). Such additional data 404 may include data describing insulin administered (e.g., timing and insulin doses), data describing food consumed (e.g., timing of food consumption, type of food, and/or amount of carbohydrates consumed, activity data from various sensors (e.g., step data, workouts performed, or other data indicative of user activity or exercise), glucose level responses to stress, combinations thereof and so forth; para. [0092], [0093], aspects that may be indicative of a person's future glucose levels may include data describing aspects of exercise (e.g., workout frequency, duration, intensity, and so forth), sleep (e.g., duration, quality, etc.), stress (e.g., blood pressure, heart rate, and the like), to name just a few.).
Claims 22 and 23 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Tran (US 2021/0106281A1)
Re Claim 22, Tran discloses a glucose monitoring system comprising:
a glucose sensor configured to output a glucose sensor output signal indicative of an estimate of a glucose level of a user of the glucose monitoring system (para. [0008], [0009], [0037], [0044], [0063], glucose sensor);
a movement sensor configured to output a movement sensor output signal indicative of detected movement of the user (para. [0013], [0044], [0072], accelerometer); and
a controller configured to configured to control activation of the movement sensor and/or to control reading of data from the movement sensor based on the glucose sensor output signal (para. [0003], a system to monitor a subject includes sensing a glucose level; if the glucose level is above a predetermined limit, requesting the subject to exercise or perform one or more activities; detecting physical activity or exercise; and repeating the steps until the glucose level is below the predetermined limit; para. [0008], A glucose sensor communicates data to a remote device to coordinate physical activity or exercise proximal to a meal to adjust glucose level without medication.).
Re Claim 23, Tran discloses an integrated circuit for a glucose monitoring system (fig. 1B, para. [0032], external unit 18 has its own sensors such as accelerometer; para. [0041], [0042], the processor is at the remote monitoring system 18), the integrated circuit comprising:
a movement sensor (para. [0013], [0032], [0044], [0072], accelerometer); and
a controller, wherein the controller is configured to control activation of the movement sensor and/or to control reading of data from the movement sensor based a glucose sensor output signal received from a glucose sensor of the glucose monitoring system (para. [0003], a system to monitor a subject includes sensing a glucose level; if the glucose level is above a predetermined limit, requesting the subject to exercise or perform one or more activities; detecting physical activity or exercise; and repeating the steps until the glucose level is below the predetermined limit; para. [0008], A glucose sensor communicates data to a remote device to coordinate physical activity or exercise proximal to a meal to adjust glucose level without medication; para. [0008], [0009], [0037], [0044], [0063], glucose sensor).
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.
Claim 15 is rejected under 35 U.S.C. 103 as being unpatentable over Pickus (US 2023/0136188A1) in view of Derdzinski (US 2021/0378563A1).
Re Claim 15, Pickus discloses the claimed invention substantially as set forth in claim 1.
Pickus is silent regarding that the glucose monitoring system is configured to output a signal to an external insulin pump to control an amount of insulin delivered to the user by the external insulin pump based on the glucose sensor output signal and the movement sensor output signal.
However, Derdzinski discloses that the glucose monitoring system is configured to output a signal to an external insulin pump to control an amount of insulin delivered to the user by the external insulin pump based on the glucose sensor output signal and the movement sensor output signal (para. [0028], [0029], [0030], [0047], [0091], [0195], glucose level prediction based on glucose output signal and the movement sensor output signal, [0041], insulin delivery system 106, para. [0091], [0092], a subsequently generated prediction 312 can be used to recommend a correct dose and/or type of insulin to be administered in a manner that mitigates potential health consequences).
Therefore, it would have been obvious to one of ordinary skill in the art, at the time of filing, to modify Pickus, by configuring the glucose monitoring system to output a signal to an external insulin pump to control an amount of insulin delivered to the user by the external insulin pump based on the glucose sensor output signal and the movement sensor output signal, as taught by Derdzinski, for the purpose of providing a correct dose and/or type of insulin to be administered in a manner that mitigates potential health consequences (para. [0092]).
Claims 2, 3, and 4 are rejected under 35 U.S.C. 103 as being unpatentable over Pickus (US 2023/0136188A1) in view of Tran (US 2021/0106281A1).
Re Claims 2, 3, and 4, Pickus discloses the claimed invention substantially as set forth in claim 1.
Pickus is silent regarding the controller is configured to control activation of the movement sensor and/or to control reading of data from the movement sensor based on the glucose sensor output signal, wherein the glucose monitoring system is configured to activate the movement sensor if: a glucose level of the user, as determined based on the glucose sensor output signal, changes by more than a threshold amount; or a glucose level of the user, as determined based on the glucose sensor output signal, is either above a first threshold or below a second threshold, wherein the second threshold is lower than the first threshold, wherein the controller is configured to read data from the movement sensor glucose if: a glucose level of the user, as determined based on the glucose sensor output signal, changes by more than a threshold amount; or a glucose level of the user, as determined based on the glucose sensor output signal, is either above a first threshold or below a second threshold, wherein the second threshold is lower than the first threshold.
However, Tran discloses a glucose monitoring system comprising:
a glucose sensor configured to output a glucose sensor output signal indicative of an estimate of a glucose level of a user of the glucose monitoring system (para. [0008], [0009], [0037], [0044], [0063], glucose sensor);
a movement sensor configured to output a movement sensor output signal indicative of detected movement of the user (para. [0013], [0044], [0072], accelerometer); and
a controller configured to control activation of the movement sensor and/or to control reading of data from the movement sensor based on the glucose sensor output signal, wherein the glucose monitoring system is configured to activate the movement sensor if: a glucose level of the user, as determined based on the glucose sensor output signal, changes by more than a threshold amount; or a glucose level of the user, as determined based on the glucose sensor output signal, is either above a first threshold or below a second threshold, wherein the second threshold is lower than the first threshold, wherein the controller is configured to read data from the movement sensor glucose if: a glucose level of the user, as determined based on the glucose sensor output signal, changes by more than a threshold amount; or a glucose level of the user, as determined based on the glucose sensor output signal, is either above a first threshold or below a second threshold, wherein the second threshold is lower than the first threshold (para. [0003], a system to monitor a subject includes sensing a glucose level; if the glucose level is above a predetermined limit, requesting the subject to exercise or perform one or more activities; detecting physical activity or exercise; and repeating the steps until the glucose level is below the predetermined limit; para. [0008], A glucose sensor communicates data to a remote device to coordinate physical activity or exercise proximal to a meal to adjust glucose level without medication.).
Therefore, it would have been obvious to one of ordinary skill in the art, at the time of filing, to modify Pickus, by configuring the controller to control activation of the movement sensor and/or to control reading of data from the movement sensor based on the glucose sensor output signal, wherein the glucose monitoring system is configured to activate the movement sensor if: a glucose level of the user, as determined based on the glucose sensor output signal, changes by more than a threshold amount; or a glucose level of the user, as determined based on the glucose sensor output signal, is either above a first threshold or below a second threshold, wherein the second threshold is lower than the first threshold, wherein the controller is configured to read data from the movement sensor glucose if: a glucose level of the user, as determined based on the glucose sensor output signal, changes by more than a threshold amount; or a glucose level of the user, as determined based on the glucose sensor output signal, is either above a first threshold or below a second threshold, wherein the second threshold is lower than the first threshold, as taught by Tran, for the purpose of managing the glucose level to an ideal range (para. [0003]).
Claims 9 and 10 are rejected under 35 U.S.C. 103 as being unpatentable over Pickus (US 2023/0136188A1) in view of Yoshioka (US 2022/0223030 A1).
Re Claims 9 and 10, Pickus discloses the claimed invention substantially as set forth in claims 1 and 8.
Pickus is silent regarding wherein the accelerometer is configured to generate an analog output signal, and wherein an output of the accelerometer is coupled to an analog to digital converter (ADC), wherein the ADC is configured to output an ADC output signal on detection of a significant change in the analog output signal of the accelerometer. However, Yoshioka discloses data acquisition method and signal measurement system (abstract) and teaches that an accelerometer is configured to generate an analog output signal, and wherein an output of the accelerometer is coupled to an analog to digital converter (ADC), wherein the ADC is configured to output an ADC output signal on detection of a significant change in the analog output signal of the accelerometer (para. [0110], example of application of the biosensor 2 includes an adhering-type accelerometer; para. [0104], In a case where the adhering-type biosensor 2 is an electrocardiograph, the electric signal of the heart (changes in the potential) is detected by the sensor unit 5, the electric signal (analog signal) thereof is transmitted to the ADC 23, and the ADC 23 converts the electric signal into a digital signal.).
Therefore, it would have been obvious to one of ordinary skill in the art, at the time of filing, to modify Pickus, by configuring the accelerometer to generate an analog output signal, and wherein an output of the accelerometer is coupled to an analog to digital converter (ADC), wherein the ADC is configured to output an ADC output signal on detection of a significant change in the analog output signal of the accelerometer, as taught by Yoshioka, for the purpose of converting the analog signal to a digital signal (para. [0104]).
Claims 17-19, 24 and 25 are rejected under 35 U.S.C. 103 as being unpatentable over Derdzinski (US 2021/0378563A1) in view of Pickus (US 2023/0136188A1).
Re Claim 17, Derdzinski discloses a glucose monitoring system comprising:
a glucose sensor configured to output a glucose sensor output signal indicative of an estimate of a glucose level of a wearer of the glucose monitoring system (para. [0061], a glucose sensor configured to detect analytes in blood or interstitial fluid that are indicative of glucose level using one or more measurement techniques);
a movement sensor configured to output a movement output signal indicative of movement of a wearer of the glucose monitoring system (para. [0091], activity data from various sensors (e.g., step data, workouts performed, or other data indicative of user activity or exercise)); and
a controller (para. [0078], the data analytics platform 122, para. [0086], prediction system 310; para. [0049], Although depicted as separate from the computing device 108, portions or an entirety of the data analytics platform 122 may alternatively or additionally be implemented at the computing device 108.) operable to:
monitor a wearer glucose level estimate generated based on the glucose sensor output signal (para. [0061], a glucose sensor configured to detect analytes in blood or interstitial fluid that are indicative of glucose level using one or more measurement techniques);
monitor a wearer movement estimate generated based on the movement sensor output signal (para. [0091], activity data from various sensors (e.g., step data, workouts performed, or other data indicative of user activity or exercise));
determine a wearer health marker based on the monitored wearer movement estimate (para. [0091], [0092], changes occur in muscles that affect the person 102's sensitivity to insulin for many hours (e.g., 48 hours or more) following exercise, information confirming when the person 102 previously exercised is critical in generating an accurate prediction 312 pertaining to a future insulin administration event.); and
combine the monitored wearer glucose level estimate with the wearer health marker to generate a prediction of a current and/or future glucose level of the wearer (para. [0091], [0101], [0195], The prediction system 310 additionally obtains additional data 404 from one or more sources. The additional data 404 is representative of information useable to describe various aspects that may impact future glucose levels of the person 102. The additional data 404 may be correlated in time with glucose measurements 118 (e.g., based on timestamps associated with the additional data 404). Such additional data 404 may include data describing insulin administered (e.g., timing and insulin doses), data describing food consumed (e.g., timing of food consumption, type of food, and/or amount of carbohydrates consumed, activity data from various sensors (e.g., step data, workouts performed, or other data indicative of user activity or exercise), glucose level responses to stress, combinations thereof and so forth; para. [0092], [0093], aspects that may be indicative of a person's future glucose levels may include data describing aspects of exercise (e.g., workout frequency, duration, intensity, and so forth), sleep (e.g., duration, quality, etc.), stress (e.g., blood pressure, heart rate, and the like), to name just a few.).
Derdzinski does not expressly disclose that accelerometer of smart watch (para. [0091]) is used to obtain activity data (e.g., step data, workouts performed, or other data indicative of user activity or exercise) in para. [0091].
Pickus discloses glycemic impact prediction for improving diabetes management (abstract) and is relied on to teach that accelerometer is used to obtain activity data (movement of a wearer) (para. [0050], physical activity data, such as a number of steps walked over a particular range of time (e.g., every 10 seconds, every minute), heart rate over a particular range of time (e.g., at regular or irregular intervals, such as every 15 seconds) with timestamps, speed of movement with timestamp (e.g., at regular or irregular intervals, such as every 15 seconds), raw or filtered accelerometer data, and so forth.).
Therefore, it would have been obvious to one of ordinary skill in the art, at the time of filing, to modify Derzinski, by adding an accelerometer configured to output an accelerometer output signal indicative of movement of a wearer of the glucose monitoring system and configuring the controller to monitor a wearer movement estimate generated based on the accelerometer output signal, as taught by Pickus, for the purpose of measuring physical activity data (para. [0050]).
Re Claim 18, Derdzinski discloses that the glucose monitoring system comprises a predictor configured to predict the current and/or future glucose level of the wearer based on the monitored wearer glucose level estimate and the wearer health marker (para. [0091], [0101], [0195], The prediction system 310 additionally obtains additional data 404 from one or more sources. The additional data 404 is representative of information useable to describe various aspects that may impact future glucose levels of the person 102. The additional data 404 may be correlated in time with glucose measurements 118 (e.g., based on timestamps associated with the additional data 404). Such additional data 404 may include data describing insulin administered (e.g., timing and insulin doses), data describing food consumed (e.g., timing of food consumption, type of food, and/or amount of carbohydrates consumed, activity data from various sensors (e.g., step data, workouts performed, or other data indicative of user activity or exercise), glucose level responses to stress, combinations thereof and so forth; para. [0092], [0093], aspects that may be indicative of a person's future glucose levels may include data describing aspects of exercise (e.g., workout frequency, duration, intensity, and so forth), sleep (e.g., duration, quality, etc.), stress (e.g., blood pressure, heart rate, and the like), to name just a few.).
Re Claim 19, Derdzinski discloses that the predictor comprises a trained neural network, artificial intelligence or machine learning processor trained to generate the prediction of the current and/or future glucose level of the wearer based on the monitored wearer glucose level estimate and the wearer health marker (para. [0030], [0032], [0033], [0036], glucose prediction using multiple machine learning models arranged in a stacked configuration is leveraged).
Re Claim 24, Derdzinski discloses a glucose monitoring system comprising:
a glucose sensor configured to output a glucose sensor output signal indicative of an estimate of a glucose level of a user of the glucose monitoring system (para. [0061], a glucose sensor configured to detect analytes in blood or interstitial fluid that are indicative of glucose level using one or more measurement techniques);
a movement sensor configured to output a movement sensor output signal indicative of detected movement of the user (para. [0091], activity data from various sensors (e.g., step data, workouts performed, or other data indicative of user activity or exercise)); and
a predictor configured to generate a prediction of a current and/or future glucose level of the user based on the glucose sensor output signal and the movement sensor output signal (para. [0091], [0101], [0195], The prediction system 310 additionally obtains additional data 404 from one or more sources. The additional data 404 is representative of information useable to describe various aspects that may impact future glucose levels of the person 102. The additional data 404 may be correlated in time with glucose measurements 118 (e.g., based on timestamps associated with the additional data 404). Such additional data 404 may include data describing insulin administered (e.g., timing and insulin doses), data describing food consumed (e.g., timing of food consumption, type of food, and/or amount of carbohydrates consumed, activity data from various sensors (e.g., step data, workouts performed, or other data indicative of user activity or exercise), glucose level responses to stress, combinations thereof and so forth; para. [0092], [0093], aspects that may be indicative of a person's future glucose levels may include data describing aspects of exercise (e.g., workout frequency, duration, intensity, and so forth), sleep (e.g., duration, quality, etc.), stress (e.g., blood pressure, heart rate, and the like), to name just a few.).
Derdzinski does not expressly disclose that accelerometer of smart watch (para. [0091]) is used to obtain activity data (e.g., step data, workouts performed, or other data indicative of user activity or exercise) in para. [0091].
Pickus discloses glycemic impact prediction for improving diabetes management (abstract) and is relied on to teach that accelerometer is used to obtain activity data (movement of a wearer) (para. [0050], physical activity data, such as a number of steps walked over a particular range of time (e.g., every 10 seconds, every minute), heart rate over a particular range of time (e.g., at regular or irregular intervals, such as every 15 seconds) with timestamps, speed of movement with timestamp (e.g., at regular or irregular intervals, such as every 15 seconds), raw or filtered accelerometer data, and so forth.).
Therefore, it would have been obvious to one of ordinary skill in the art, at the time of filing, to modify Derzinski, by adding an accelerometer configured to output an accelerometer output signal indicative of movement of the user, as taught by Pickus, for the purpose of measuring physical activity data (para. [0050]).
Re Claim 25, Derdzinski discloses an integrated circuit for a glucose monitoring system (para. [0049], [0046], computing device 108), the integrated circuit comprising:
a movement sensor configured to output a movement sensor output signal indicative of detected movement of the user (para. [0091], activity data from various sensors (e.g., step data, workouts performed, or other data indicative of user activity or exercise); para. [0046], the computing device 108 represents separate devices, (e.g., a smart watch and a mobile phone) one device may be configured with various sensors and functionality to measure a variety of physiological markers (e.g., heartrate, breathing, rate of blood flow, and so on) and activities (e.g., steps, elevation changes, and the like) of the person 102.); and
a predictor (para. [0078], the data analytics platform 122, para. [0086], prediction system 310; para. [0049], Although depicted as separate from the computing device 108, portions or an entirety of the data analytics platform 122 may alternatively or additionally be implemented at the computing device 108.),
wherein the predictor is configured to generate a prediction of a current and/or future glucose level of user of the glucose monitoring system based on the movement sensor output signal and a glucose sensor output signal received from a glucose sensor of the glucose monitoring system (para. [0061], a glucose sensor configured to detect analytes in blood or interstitial fluid that are indicative of glucose level using one or more measurement techniques; para. [0091], [0101], [0195], The prediction system 310 additionally obtains additional data 404 from one or more sources. The additional data 404 is representative of information useable to describe various aspects that may impact future glucose levels of the person 102. The additional data 404 may be correlated in time with glucose measurements 118 (e.g., based on timestamps associated with the additional data 404). Such additional data 404 may include data describing insulin administered (e.g., timing and insulin doses), data describing food consumed (e.g., timing of food consumption, type of food, and/or amount of carbohydrates consumed, activity data from various sensors (e.g., step data, workouts performed, or other data indicative of user activity or exercise), glucose level responses to stress, combinations thereof and so forth; para. [0092], [0093], aspects that may be indicative of a person's future glucose levels may include data describing aspects of exercise (e.g., workout frequency, duration, intensity, and so forth), sleep (e.g., duration, quality, etc.), stress (e.g., blood pressure, heart rate, and the like), to name just a few.).
Derdzinski does not expressly disclose that accelerometer of smart watch (para. [0091]) is used to obtain activity data (e.g., step data, workouts performed, or other data indicative of user activity or exercise) in para. [0091].
Pickus discloses glycemic impact prediction for improving diabetes management (abstract) and is relied on to teach that accelerometer is used to obtain activity data (movement of a wearer) (para. [0050], physical activity data, such as a number of steps walked over a particular range of time (e.g., every 10 seconds, every minute), heart rate over a particular range of time (e.g., at regular or irregular intervals, such as every 15 seconds) with timestamps, speed of movement with timestamp (e.g., at regular or irregular intervals, such as every 15 seconds), raw or filtered accelerometer data, and so forth.).
Therefore, it would have been obvious to one of ordinary skill in the art, at the time of filing, to modify Derzinski, by adding an accelerometer configured to output an accelerometer output signal indicative of detected movement of the user and configuring the predictor to generate a prediction of a current and/or future glucose level of user of the glucose monitoring system based on the accelerometer output signal and a glucose sensor output signal received from a glucose sensor of the glucose monitoring system, as taught by Pickus, for the purpose of measuring physical activity data (para. [0050]).
Conclusion
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/JONATHAN T KUO/Primary Examiner, Art Unit 3792
/V.V.H./
Vynn Huh, June 13, 2026Examiner, Art Unit 3792
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