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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed 126-2026 has been entered.
Status of Claims
This action is a final rejection
Claims 19-37 are pending
Claims 1-18 were cancelled
Claims 19-21, 32, 35, 37 were amended
Claims 19-37 are rejected under 35 USC § 101
Claims 19-37 are rejected under 35 USC § 103
Priority
Acknowledgement is made of Applicant’s claim for a foreign priority date of 8-6-2021
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 9-13-2023, 7-11-2025, 9-26-2023 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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 19-37 are not patent eligible because the claimed invention is directed to an abstract idea without significantly more.
Analysis
First, claims are directed to one or more of the following statutory categories: a process, a machine, a manufacture, and a composition of matter. Regarding claims 19-37 the claims recite an abstract idea of “predicting blood glucose levels”.
Independent Claims 19, 20, 21 are rejected under 35 U.S.C 101 based on the following analysis.
-Step 1 (Does the claim fall within a statutory category? YES): claims 19, 20, 21 recite a saliva-based blood glucose prediction system using artificial intelligence.
-Step 2A Prong One (Does the claim fall within at least one of the groupings of abstract ideas?: YES):
claims 19, 20, 21 recite:
non-invasively collecting saliva from the user, the collecting device comprising: a specimen collecting unit for collecting saliva; a compression tube for storing and compressing the collected saliva; a filter for removing interfering substances from the stored saliva;
a biosensor configured to receive the saliva after interfering substances have been removed from the saliva and sense glucose within the received saliva;
measure a glucose concentration in the saliva;
inference model being trained with experimental data to infer blood glucose based on
predict blood glucose using the inference model based on the physical indicator.
claim 20 recites:
process and analyze data;
generate and display predicted blood glucose information on a user.
belong to the grouping of mental processes under concepts performed in the human mind (including an observation, evaluation, judgement, opinion) as it recites “predicting blood glucose levels based on a physical indicator and sugar content in saliva”. Alternatively it belongs to certain methods of organizing human activity under managing personal behavior or relationships or interactions between people as it recites “predicting blood glucose levels based on a physical indicator and sugar content in saliva” (refer to MPP 2106.04(a)(2)). Accordingly this claim recites an abstract idea.
-Step 2A Prong Two (Are there additional elements in the claim that imposes a meaningful limit on the abstract idea? NO).
Claims 19, 20, 21 recite:
a collecting device;
a measuring device;
biosensor;
detect insertion of the biosensor;
upon detecting insertion of the biosensor, apply a specimen recognizing signal to detect whether the saliva is in contact with the biosensor;
determine whether the saliva is in contact with the biosensor based on a first responding signal;
upon determining that the saliva is in contact with the biosensor, apply a specimen measuring signal to the biosensor wherein the specimen measuring signal is distinct from the specimen recognizing signal;
second responding signal;
the server is further configured to predict blood glucose using the inference model based on
Claim 19 recites:
a server configured to process and analyze data;
a terminal configured to receive and display predicted blood glucose information on a user
transmit, a second responding signal, received from the biosensor after applying the specimen measuring signal, to the server, wherein the server comprises a pre-trained inference model utilizing a machine learning algorithm.
Claim 20 recites:
transmit, a second responding signal, received from the biosensor after applying the specimen measuring signal, to the terminal, wherein the terminal comprises a pre-trained inference model utilizing a machine learning algorithm.
Claim 21 recites:
receive a second responding signal from the biosensor after applying the specimen measuring signal, wherein the measuring device comprises a pre-trained inference model utilizing a machine learning algorithm.
Amounting to additional elements that are recited at a high-level of generality such that it amounts to no more than mere instructions to implement an abstract idea on a computer, or merely use a computer as a tool to implement the abstract idea.. (refer to MPEP 2106.05(f)). Accordingly, the claim as a whole does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
-Step 2B (Does the additional elements of the claim provide an inventive concept?: NO. As discussed previously with respect to Step 2A Prong Two, claim 1 recites:
Claims 19, 20, 21 recite:
a collecting device;
a measuring device;
biosensor;
detect insertion of the biosensor;
upon detecting insertion of the biosensor, apply a specimen recognizing signal to detect whether the saliva is in contact with the biosensor;
determine whether the saliva is in contact with the biosensor based on a first responding signal;
upon determining that the saliva is in contact with the biosensor, apply a specimen measuring signal to the biosensor wherein the specimen measuring signal is distinct from the specimen recognizing signal;
second responding signal;
the server is further configured to predict blood glucose using the inference model based on
Claim 19 recites:
a server configured to process and analyze data;
a terminal configured to receive and display predicted blood glucose information on a user
transmit, a second responding signal, received from the biosensor after applying the specimen measuring signal, to the server, wherein the server comprises a pre-trained inference model utilizing a machine learning algorithm.
Claim 20 recites:
transmit, a second responding signal, received from the biosensor after applying the specimen measuring signal, to the terminal, wherein the terminal comprises a pre-trained inference model utilizing a machine learning algorithm.
Claim 21 recites:
receive a second responding signal from the biosensor after applying the specimen measuring signal, wherein the measuring device comprises a pre-trained inference model utilizing a machine learning algorithm;
Amount to additional elements that are recited at a high-level of generality such that it amounts to no more than mere instructions to implement an abstract idea on a computer, or merely use a computer as a tool to implement the abstract idea.. (refer to MPEP 2106.05(f)) Accordingly, even in combination the additional elements of the claim do not provide an inventive concept (significantly more than the abstract idea) and hence the claim is ineligible.
Dependent Claims:
Step 2A Prong One: The following dependent claims recites additional limitations that further define the abstract idea of “predicting blood glucose levels based on a physical indicator and sugar content in saliva”. The claim limitations include:
Claim 23:
wherein the at least one physical indicator comprises at least one of a body mass index (BMI) and a waist circumference.
Claims 24, 25, 26, 28, 27, 29: wherein the at least one physical indicator is input ..by the user.
Claims 32, 35: predict the blood glucose using the inference model based on ... one physical indicator
Step 2A Prong Two (Are there additional elements in the claim that imposes a meaningful limit on the abstract idea? NO). The following dependent claims recite mere instructions to implement an abstract idea on a computer, or merely use a computer as a tool to implement the abstract idea. (refer to MPEP 2106.05(f)). Accordingly, the claims as a whole do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims include:
Claim 22:
wherein the first responding signal is received by the measuring device after applying the specimen recognizing signal.
Claims 24: server.
Claims 27: terminal
Claims 29: measuring device
Claim 25:
Terminal;
transmitted from the terminal to the server
Claims 26, 28:
measuring device, and
transmitted from the measuring device to the server.
Claims 30, 33, 36: wherein the measuring device is configured to measure the glucose concentration in the saliva based on the second responding signal.
Claims 31: wherein the measuring device is configured to transmit information on the measured glucose concentration to the server.
Claims 34: wherein the measuring device is configured to transmit information on the measured glucose concentration to the terminal
Claims 32, 35: wherein the server is configured to predict the blood glucose using the inference model based on .. the second responding signal, and the transmitted information
Claim 37: wherein the measuring device is configured to predict the blood glucose using the inference model base on
Step 2B (Does the additional elements of the claim provide an inventive concept?: NO). As discussed previously with respect to Step 2A Prong Two, the following dependent claims recite mere instructions to implement an abstract idea on a computer, or merely use a computer as a tool to implement the abstract idea. (refer to MPEP 2106.05(f)). Accordingly, the claim does not provide an inventive concept (significantly more than the abstract idea) and hence the claim is ineligible. The claims include:
Claim 22:
wherein the first responding signal is received by the measuring device after applying the specimen recognizing signal.
Claims 24: server.
Claims 27: terminal
Claims 29: measuring device
Claim 25:
Terminal;
transmitted from the terminal to the server
Claims 26, 28:
measuring device, and
transmitted from the measuring device to the server.
Claims 30, 33, 36: wherein the measuring device is configured to measure the glucose concentration in the saliva based on the second responding signal.
Claims 31: wherein the measuring device is configured to transmit information on the measured glucose concentration to the server.
Claims 34: wherein the measuring device is configured to transmit information on the measured glucose concentration to the terminal
Claims 32, 35: wherein the server is configured to predict the blood glucose using the inference model based on .. the second responding signal, and the transmitted information
Claim 37: wherein the measuring device is configured to predict the blood glucose using the inference model base on
Claim Rejections - 35 USC § 103
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 set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied 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
non-obviousness.
Claims 19-22, 30-37 are rejected under 35 U.S.C. 103 as being un-patentable by Zhang et.al. (US 20140197042 A1) hereinafter “Zhang”, in view of Mondro et.al (EP 2345367 A1) hereinafter “Mondro”, in view of Chou et.al (WO 2021092506 A1) hereinafter “Chou”, in further view of De Laat et.al (WO 2019197486 A1) hereinafter “Laat”
Regarding claims 19, 20, 21 Zhang teaches:
a server (signal conditioning and/or analysis device/ data processing device) configured to process and analyze data; a terminal (remote receiver) configured to receive and display predicted blood glucose information on a user; (See at least [0016] via: “...The system includes the above-described glucose sensor and a signal conditioning and/or analysis device that processes an electrical signal from the sensor... The analysis system may also include a transmitter device for sending a radio signal to a remote receiver and/or to a data processing device.. the information is obtained from the signal conditioning and/or analysis device. The analysis system may also include a memory device for accumulating data related to the glucose concentration in the liquid sample; the data can be obtained at different times or from different liquid samples...”; in addition see at least [0036] via: “...The saliva glucose sensor of the present invention can be used as part of a real-time noninvasive saliva glucose monitoring system. The system contains a saliva sampling mechanism, an enzyme-based electrode biosensor, a glucose meter, signal processing components, and a display for outputting the results...”)
a collecting device for non-invasively collecting saliva from the user, the collecting device comprising: a specimen collecting unit for collecting saliva; a compression tube for storing and compressing the collected saliva; and a filter for removing interfering substances from the stored saliva; (See at least [0036] via: “...The saliva sampling mechanism optionally can include a collector for collecting saliva from the oral cavity as well as saliva filtration and/or saliva pretreatment modules, which may enhance reliability of sampling and accuracy of results...”; in addition see at least [0048] via: “...A sensor system according to the invention can use either treated or untreated saliva ... Saliva pretreatment can be achieved, for example, by passing a patient sample ... through a semi-permeable membrane that coats the sensor surface. ... In yet another embodiment, the sensor system includes a built-in saliva filtration mechanism, which can be, for example, a microfluidics-based system. ..”)
a biosensor configured to receive the saliva after interfering substances have been removed from the saliva and sense glucose within the received saliva; (See at least [0036] via: “...The saliva glucose sensor of the present invention can be used as part of a real-time noninvasive saliva glucose monitoring system. The system contains a saliva sampling mechanism, an enzyme-based electrode biosensor, a glucose meter, signal processing components, and a display for outputting the results. The saliva sampling mechanism .. can include a collector for collecting saliva from the oral cavity as well as saliva filtration and/or saliva pretreatment modules, which may enhance reliability of sampling and accuracy of results. ...The biosensor is an electrochemical system which can include a three- or four-electrode cell on a single chip...”)
a measuring device configured to: upon detecting insertion of the biosensor, apply a specimen recognizing signal to detect whether the saliva is in contact with the biosensor (See at least [0023] via: “...FIG. 1A shows a photograph of the sample application area of an embodiment of a saliva glucose sensor according to the invention. The rectangle indicates the sample area where a drop of saliva is deposited. The sample area includes three electrodes on the lower surface, each of which contacts the drop of saliva, and each connected to a lead providing signal to the signal conditioning electronic module shown in FIG. 1B. The conditioned signal is then passed to the microcontroller module shown in FIG. 1C, which can perform calculations, analyze the data, and store the data or transmit it to an external receiver (not shown).
upon determining that the saliva is in contact with the biosensor, apply a specimen measuring signal (conditioned signal) to the biosensor to measure a glucose concentration in the saliva, (See at least [0023] via: “...FIG. 1A shows a photograph of the sample application area of an embodiment of a saliva glucose sensor according to the invention. The rectangle indicates the sample area where a drop of saliva is deposited. The sample area includes three electrodes on the lower surface, each of which contacts the drop of saliva, and each connected to a lead providing signal to the signal conditioning electronic module shown in FIG. 1B. The conditioned signal is then passed to the microcontroller module shown in FIG. 1C, which can perform calculations, analyze the data, and store the data or transmit it to an external receiver (not shown) Examiner interprets the conditioned signal as taught by Zhang is one used to analyze the specimen and which corresponds to the specimen measuring signal.
transmit, a second responding signal (glucose concentration), received from the biosensor after applying the specimen measuring signal, to the server (data processing device), (See at least [0016] via: “...The analysis system may also include a transmitter device for sending a radio signal to a remote receiver and/or to a data processing device. The radio signal carries information related to a glucose concentration in the liquid sample..”)
transmit the (predicted) blood glucose information to the terminal (See at least [0016] via: “...The analysis system may also include a transmitter device for sending a radio signal to a remote receiver...”)
However, Zhang is silent the following limitations that are taught by Mondro
a measuring device configured to: receive the biosensor; detect insertion of the biosensor; upon detecting insertion of the biosensor, (See at least [Page 7, lines 6-7] via: “...injecting a lancet through the lancet hole at a first test site into a subject to obtain a ... sample contacting the strip..”; in addition see at least [Page 4, lines 3-6] via: “...The system ...comprises a lancet and lancet injector, a motor for advancing the strip, and a processor. The processor is adapted to process signals produced when the device contacts make electrical contact with the conductive pads on the strip at stop positions in the lancing/sensing process, and to communicate with the lancet injector, the test electrodes, and the motor...”)
determine whether the saliva is in contact with the biosensor based on a first responding signal; (See at least [Page 4, lines 14-15] via: “...contacting the .. sample with the electrodes for determining a .. sample volume so that a signal is produced when a .. sample volume is detected..”)
wherein the specimen measuring signal (sample characteristic signal) is distinct from the specimen recognizing signal (See at least [Page 4, lines 16-15] via: “... advancing the strip responsive to the signal produced when a ... sample is detected; contacting the .. sample with the test electrodes to obtain a ...sample characteristic signal..:) Examiner interprets the conditioned signal as taught by Zhang which is the one used to analyze and measure the specimen is distinct from the sample characteristic signal as taught by Mondro that detects that the saliva specimen is in contact with the biosensor
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the invention to have modified Zhang to incorporate the teachings of Mondro. Those in the art would have recognized that Zhang’s teaching regarding a glucose sensor suitable for measuring glucose levels in human saliva could be modified to include Mondro’s teaching regarding a sample with electrodes for determining a sample volume so that a signal is produced when a sample volume is detected. This combination of Zhang and Mondro would be beneficial in instructing the glucose sensor to start measuring glucose levels in the sample only after the sample to be measured has been placed on the glucose sensor in order to prevent extraneous measurements when the sample is not in contact with the glucose sensor .
However, Zhang and Mondro are silent the following limitations that are taught by Chou:
wherein the server (computing unit) comprises a pre-trained inference model utilizing a machine learning algorithm, the inference model being trained with experimental data to infer blood glucose based on glucose concentration) and at least one physical indicator associated with the user; (See at least [Page 7, lines 9-21-] via: “…A method for correlating the glucose concentration in a non-blood bodily fluid with the glucose in the blood of an individual, comprising: measuring, in a first period in time, the glucose in a non-blood bodily fluid and measuring the glucose in the blood of the same individual to establish a [GNBF1]/[GB1] ratio, where [GNBF1] is the glucose concentration in the non-blood bodily fluid in the first period in time, and [GB1] is the glucose concentration in the blood of the individual in the first period in time; storing the [GNBF1]/[GB1] ratio in a memory; measuring [GNBF2] in a second period in time, the glucose concentration in the non blood bodily fluid; and correlating the measured [GNBF2] with the [GNBF1]/[GB1] ratio to generate a correlated estimated [BB2] glucose concentration in blood of the individual in the second period in time…”; in addition see at least [Page 7, lines 4-7] via: “…The method ..further comprising applying machine learning (ML) to improve the accuracy of the method by human comparison of, for example, preliminary results, secondary results, or tertiary results, generated by the presently disclosed device..”; in addition see at least [Page 7, line 23] via: “…wherein the non-blood bodily fluid is saliva..”; in addition see at least [Page 34, lines 18-21] via: “…The training stage generates a model that will be used in the prediction stage. The model can be repeatedly used in the prediction stage for assaying the input. Thus, the computing unit only needs access to the generated model. It does not need access to the training data, nor requiring the training stage to be run again on the computing unit…”)
wherein the server (computing unit) is further configured to: predict blood glucose using the inference model based on glucose concentration) [and the physical indicator] (See at least [Page 7, lines 9-10] via: “…A method for correlating the glucose concentration in a non-blood bodily fluid with the glucose in the blood of an individual..”; in addition see at least [Page 7, line 23] via: “…wherein the non-blood bodily fluid is saliva..”; in addition see at least [Page 34, lines 18-21] via: “…The training stage generates a model that will be used in the prediction stage. The model can be repeatedly used in the prediction stage for assaying the input. Thus, the computing unit only needs access to the generated model. It does not need access to the training data, nor requiring the training stage to be run again on the computing unit…”)
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the invention to have modified Zhang and Mondro to incorporate the teachings of Chou. Those in the art would have recognized that Zhang’s teaching regarding a glucose sensor suitable for measuring glucose levels in human saliva could, could be modified to include Chou’s teaching regarding a method for correlating a biomarker such as glucose in a non-blood bodily fluid such as saliva with the same biomarker in the blood of an individual. This combination of Zhang and Chou would be beneficial in establishing an alternate method of deriving the glucose concentration in the blood by measuring glucose in the saliva without having to measure directly the concentration of glucose in the blood.
predicted blood glucose information (See at least [Page 7, lines 9-10] via: “…A method for correlating the glucose concentration in a non-blood bodily fluid with the glucose in the blood of an individual..”; in addition see at least [Page 7, line 23] via: “…wherein the non-blood bodily fluid is saliva..”; in addition see at least [Page 34, lines 18-21] via: “…The training stage generates a model that will be used in the prediction stage. The model can be repeatedly used in the prediction stage for assaying the input...”; in addition see at least [Page 34, lines 18-21] via: “…The training stage generates a model that will be used in the prediction stage. The model can be repeatedly used in the prediction stage for assaying the input...”)
However, Zhang, Mondro and Chou are silent the following limitations that are taught by Laat:
blood glucose based on at least one physical indicator associated with the user (See at least [Page 6, lines 33-34] via: “...CGM device ... to measure glucose values from interstitial fluid..”)
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the invention to have modified Zhang, Mondro and Chou to incorporate the teachings of Laat. Those in the art would have recognized that Zhang’s teaching regarding a glucose sensor suitable for measuring glucose levels in human saliva and Chou’s teaching correlating glucose in blood with glucose in saliva could, could be modified to include Laat’s teaching regarding measuring glucose values from interstitial fluid. The combination of Zhang and Laat would be beneficial in establishing the relationship between blood glucose in a patient and the patient’s skin interstitial fluid.
Regarding claim 22 Zhang, Mondro, Chou and Laat teach the invention as detailed above with respect to claims 19, 20 or 21. Zhang also teaches:
received by the measuring device (See at least [claim 16] via: “... the glucose sensor of claim 1; a signal conditioning and/or analysis device that processes an electrical signal from the sensor...”)
However Zhang and Chou are silent the following limitation that is taught by Mondro:
wherein the first responding signal is received ... after applying the specimen recognizing signal (See at least [Page 4, lines 16-17] via: “ ... sample is detected; contacting the .. sample with the test electrodes to obtain a ...sample characteristic signal..”) Examiner interprets the sample characteristic signal as taught by Mondro as one that detects that the saliva specimen is in contact with the biosensor.
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the invention to have modified Zhang and Mondro to incorporate the teachings of Chou. Those in the art would have recognized that Zhang’s teaching regarding a glucose sensor suitable for measuring glucose levels in human saliva could, could be modified to include Chou’s teaching regarding a method for correlating a biomarker such as glucose in a non-blood bodily fluid such as saliva with the same biomarker in the blood of an individual. This combination of Zhang and Chou would be beneficial in establishing an alternate method of deriving the glucose concentration in the blood by measuring glucose in the saliva without having to measure directly the concentration of glucose in the blood.
Regarding claims 30, 33, 36 Zhang, Mondro, Chou and Laat teach the invention as detailed above with respect to claims 19, 20 and 21 respectively. Zhang also teaches:
wherein the measuring device (glucose sensor) is configured to measure the glucose concentration in the saliva based on the second responding signal (See at least [0006] via: “...One aspect of the invention is a glucose sensor for determining a concentration of glucose in a liquid sample..”; in addition see at least [claim 12] via: “... The glucose sensor of claim 1 that is capable of detecting glucose at concentrations down to 5 ppm (0.5 mg/dL) or lower...’; in addition see at least [claim 14] via: “...The glucose sensor of claim 1 that is configured for determination of glucose concentration in saliva..”)
Regarding claims 31, 34 Zhang, Mondro, Chou and Laat teach the invention as detailed above with respect to claims 19&30 and 20&33 respectively. Zhang also teaches:
wherein the measuring device (signal conditioning and/or analysis device/ glucose sensor) is configured to transmit information on the measured glucose concentration to the server (data processing device) (See at least [0016] via: “...The analysis system may also include a transmitter device for sending a radio signal to a ... data processing device. The radio signal carries information related to a glucose concentration in the liquid sample; the information is obtained from the signal conditioning and/or analysis device. ..”; in addition see at least [claim 16] via: “... the glucose sensor of claim 1; a signal conditioning and/or analysis device that processes an electrical signal from the sensor...”; in addition see at least [claim 17] via: “...a transmitter device for sending a radio signal to a ... data processing device, wherein the radio signal carries information related to a glucose concentration in the liquid sample, the information obtained from the signal conditioning and/or analysis device...”)
wherein the measuring device (signal conditioning and/or analysis device/ glucose sensor) is configured to transmit information on the measured glucose concentration to the terminal (remote receiver) (See at least [0016] via: “...The analysis system may also include a transmitter device for sending a radio signal to a remote receiver .... The radio signal carries information related to a glucose concentration in the liquid sample; the information is obtained from the signal conditioning and/or analysis device. ..”; in addition see at least [claim 16] via: “... the glucose sensor of claim 1; a signal conditioning and/or analysis device that processes an electrical signal from the sensor...”; in addition see at least [claim 17] via: “...a transmitter device for sending a radio signal to a remote receiver ..., wherein the radio signal carries information related to a glucose concentration in the liquid sample, the information obtained from the signal conditioning and/or analysis device...”)
Regarding claim 32 Zhang, Mondro, Chou and Laat teach the invention as detailed above with respect to claims 19, 30, 31. Zhang also teaches:
wherein the server (a data processing device) is configured to (See at least [claim 16] via: “... a data processing device..”)
blood glucose ... based on (See at least [0016] via: “...The analysis system may also include a transmitter device for sending a radio signal to a remote receiver and/or to a data processing device. The radio signal carries information related to a glucose concentration in the liquid sample..”)
However Zhang and Mondro are silent the following limitation that is taught by Chou:
predict the blood glucose using the inference model based on the at least one physical indicator, and the transmitted information] (See at least [Page 7, lines 9-10] via: “…A method for correlating the glucose concentration in a non-blood bodily fluid with the glucose in the blood of an individual..”; in addition see at least [Page 7, line 23] via: “…wherein the non-blood bodily fluid is saliva..”; in addition see at least [Page 34, lines 18-21] via: “…The training stage generates a model that will be used in the prediction stage. The model can be repeatedly used in the prediction stage for assaying the input. Thus, the computing unit only needs access to the generated model. It does not need access to the training data, nor requiring the training stage to be run again on the computing unit…”)
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the invention to have modified Zhang and Mondro to incorporate the teachings of Chou. Those in the art would have recognized that Zhang’s teaching regarding a glucose sensor suitable for measuring glucose levels in human saliva could, could be modified to include Chou’s teaching regarding a method for correlating a biomarker such as glucose in a non-blood bodily fluid such as saliva with the same biomarker in the blood of an individual. This combination of Zhang and Chou would be beneficial in establishing an alternate method of deriving the glucose concentration in the blood by measuring glucose in the saliva without having to measure directly the concentration of glucose in the blood.
However, Zhang, Mondro and Chou are silent the following limitations that are taught by Laat:
blood glucose based on one physical indicator(See at least [Page 6, lines 33-34] via: “...CGM device ... to measure glucose values from interstitial fluid..”)
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the invention to have modified Zhang, Mondro and Chou to incorporate the teachings of Laat. Those in the art would have recognized that Zhang’s teaching regarding a glucose sensor suitable for measuring glucose levels in human saliva and Chou’s teaching correlating glucose in blood with glucose in saliva could, could be modified to include Laat’s teaching regarding measuring glucose values from interstitial fluid. The combination of Zhang and Laat would be beneficial in establishing the relationship between blood glucose in a patient and the patient’s skin interstitial fluid.
Regarding claim 35 Zhang, Mondro, Chou and Laat teach the invention as detailed above with respect to claims 20, 33, 34. Zhang also teaches:
wherein the terminal is configured to (remote receiver) is configured to (See at least [claim 16] via: “...a remote receiver..”)
blood glucose ... based on (See at least [0016] via: “...The analysis system may also include a transmitter device for sending a radio signal to a remote receiver and/or to a data processing device. The radio signal carries information related to a glucose concentration in the liquid sample..”)
However Zhang and Mondro are silent the following limitation that is taught by Chou:
predict the blood glucose using the inference model based on the at least one physical indicator, and the transmitted information] (See at least [Page 7, lines 9-10] via: “…A method for correlating the glucose concentration in a non-blood bodily fluid with the glucose in the blood of an individual..”; in addition see at least [Page 7, line 23] via: “…wherein the non-blood bodily fluid is saliva..”; in addition see at least [Page 34, lines 18-21] via: “…The training stage generates a model that will be used in the prediction stage. The model can be repeatedly used in the prediction stage for assaying the input. Thus, the computing unit only needs access to the generated model. It does not need access to the training data, nor requiring the training stage to be run again on the computing unit…”)
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the invention to have modified Zhang and Mondro to incorporate the teachings of Chou. Those in the art would have recognized that Zhang’s teaching regarding a glucose sensor suitable for measuring glucose levels in human saliva could, could be modified to include Chou’s teaching regarding a method for correlating a biomarker such as glucose in a non-blood bodily fluid such as saliva with the same biomarker in the blood of an individual. This combination of Zhang and Chou would be beneficial in establishing an alternate method of deriving the glucose concentration in the blood by measuring glucose in the saliva without having to measure directly the concentration of glucose in the blood.
However, Zhang, Mondro and Chou are silent the following limitations that are taught by Laat:
blood glucose based on one physical indicator(See at least [Page 6, lines 33-34] via: “...CGM device ... to measure glucose values from interstitial fluid..”)
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the invention to have modified Zhang, Mondro and Chou to incorporate the teachings of Laat. Those in the art would have recognized that Zhang’s teaching regarding a glucose sensor suitable for measuring glucose levels in human saliva and Chou’s teaching correlating glucose in blood with glucose in saliva could, could be modified to include Laat’s teaching regarding measuring glucose values from interstitial fluid. The combination of Zhang and Laat would be beneficial in establishing the relationship between blood glucose in a patient and the patient’s skin interstitial fluid.
Regarding claim 37 Zhang, Mondro, Chou and Laat teach the invention as detailed above with respect to claims 21 & 36. Zhang and Mondro are silent the following claim that is taught by Chou:
wherein the measuring device is configured to predict the blood glucose using the inference model based on the at least one physical indicator, and the measured glucose concentration (See at least [Page 7, lines 9-10] via: “…A method for correlating the glucose concentration in a non-blood bodily fluid with the glucose in the blood of an individual..”; in addition see at least [Page 7, line 23] via: “…wherein the non-blood bodily fluid is saliva..”; in addition see at least [Page 34, lines 18-21] via: “…The training stage generates a model that will be used in the prediction stage. The model can be repeatedly used in the prediction stage for assaying the input. Thus, the computing unit only needs access to the generated model. It does not need access to the training data, nor requiring the training stage to be run again on the computing unit…”)
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the invention to have modified Zhang and Mondro to incorporate the teachings of Chou. Those in the art would have recognized that Zhang’s teaching regarding a glucose sensor suitable for measuring glucose levels in human saliva could, could be modified to include Chou’s teaching regarding a method for correlating a biomarker such as glucose in a non-blood bodily fluid such as saliva with the same biomarker in the blood of an individual. This combination of Zhang and Chou would be beneficial in establishing an alternate method of deriving the glucose concentration in the blood by measuring glucose in the saliva without having to measure directly the concentration of glucose in the blood.
Claims 23-24, 27, 29 are rejected under 35 U.S.C. 103 as being un-patentable by Zhang, in view of Mondro, in view of Chou, in view of Laat, in view of Kim et.al (KR 102114746 B1) hereinafter “Kim”
Regarding claim 23 Zhang, Mondro, Chou and Laat teach the invention as detailed above with respect to claims 19, 20 or 21. Zhang. However, Zhang, Mondro, Chou and Laat are silent the following claim that is taught by Kim:
wherein the at least one physical indicator comprises at least one of a body mass index (BMI) and a waist circumference (See at least [Page 9, lines 21-23] via: “… the subjects' body weight (kg) and height (m) were measured and body mass index (BMI) was calculated. In addition, anthropometric data including waist circumference, … are collected..”)
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the invention to have modified Zhang, Mondro, Chou and Laat to incorporate the teachings of Kim. Those in the art would have recognized that Zhang’s teaching regarding a glucose sensor suitable for measuring glucose levels in human saliva and Chou’s teaching correlating glucose in blood with glucose in saliva could, could be modified to include Kim’s teaching regarding collecting the subjects' body mass index (BMI) and waist circumference. The combination of Zhang and Kim would be beneficial in establishing the relationship between blood glucose in a patient and the patient’s BMI and waist circumference.
Regarding claims 24 Zhang, Mondro, Chou and Laat teach the invention as detailed above with respect to claim 19. Zhang teaches:
input into the server (See at least [0016] via: “...The analysis system may also include a transmitter device for sending a radio signal to a data processing device...”)
However, Zhang, Mondro, Chou and Laat are silent the following claim that is taught by Kim:
wherein the at least one physical indicator is input .. by the user (See at least [Page 9, lines 21-23] via: “… the subjects' body weight (kg) and height (m) were measured and body mass index (BMI) was calculated. In addition, anthropometric data including waist circumference, … are collected..”)
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the invention to have modified Zhang, Mondro, Chou and Laat to incorporate the teachings of Kim. Those in the art would have recognized that Zhang’s teaching regarding a glucose sensor suitable for measuring glucose levels in human saliva and Chou’s teaching correlating glucose in blood with glucose in saliva could, could be modified to include Kim’s teaching regarding collecting the subjects' body mass index (BMI) and waist circumference. The combination of Zhang and Kim would be beneficial in establishing the relationship between blood glucose in a patient and the patient’s BMI and waist circumference.
Regarding claim 27 Zhang, Mondro, Chou and Laat teach the invention as detailed above with respect to claims 20. Zhang teaches:
input into the terminal (See at least [claim 16] via: “...a remote receiver..”)
However Zhang, Mondro, Chou and Laat are silent the following limitation taught by Kim
wherein the at least one physical indicator is input ... by the user (See at least [Page 9, lines 21-23] via: “… the subjects' body weight (kg) and height (m) were measured and body mass index (BMI) was calculated. In addition, anthropometric data including waist circumference, … are collected..”)
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the invention to have modified Zhang, Mondro, Chou, and Laat to incorporate the teachings of Kim. Those in the art would have recognized that Zhang’s teaching regarding a glucose sensor suitable for measuring glucose levels in human saliva and Chou’s teaching correlating glucose in blood with glucose in saliva could, could be modified to include Kim’s teaching regarding collecting the subjects' body mass index (BMI) and waist circumference. The combination of Zhang and Kim would be beneficial in establishing the relationship between blood glucose in a patient and the patient’s BMI and waist circumference.
Regarding claim 29 Zhang, Mondro, Chou, Laat, and Kim teach the invention as detailed above with respect to claims 21. Zhang teaches:
input to the measuring device (See at least [0016] via: “... a signal conditioning and/or analysis device...”)
However Zhang, Mondro, Chou and Laat are silent the following limitation taught by Kim
wherein the at least one physical indicator is input ... by the user (See at least [Page 9, lines 21-23] via: “… the subjects' body weight (kg) and height (m) were measured and body mass index (BMI) was calculated. In addition, anthropometric data including waist circumference, … are collected..”)
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the invention to have modified Zhang, Mondro, Chou, and Laat to incorporate the teachings of Kim. Those in the art would have recognized that Zhang’s teaching regarding a glucose sensor suitable for measuring glucose levels in human saliva and Chou’s teaching correlating glucose in blood with glucose in saliva could, could be modified to include Kim’s teaching regarding collecting the subjects' body mass index (BMI) and waist circumference. The combination of Zhang and Kim would be beneficial in establishing the relationship between blood glucose in a patient and the patient’s BMI and waist circumference.
Claims 25-26, 28 are rejected under 35 U.S.C. 103 as being un-patentable by Zhang, in view of Mondro, in view of Chou, in view of Laat, in view of Kim, in view of Ryu et.al (WO 2016111551 A1) hereinafter “Ryu”
Regarding claim 25 Zhang, Mondro, Chou and Laat teach the invention as detailed above with respect to claim 19. Zhang also teaches:
Input into the terminal (See at least [claim 16] via: “...a remote receiver..”)
However Zhang, Mondro, Chou and Laat are silent the following limitation taught by Kim:
wherein the at least one physical indicator is input ... by the user (See at least [Page 9, lines 21-23] via: “… the subjects' body weight (kg) and height (m) were measured and body mass index (BMI) was calculated. In addition, anthropometric data including waist circumference, … are collected..”)
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the invention to have modified Zhang, Mondro, Chou and Laat to incorporate the teachings of Kim. Those in the art would have recognized that Zhang’s teaching regarding a glucose sensor suitable for measuring glucose levels in human saliva and Chou’s teaching correlating glucose in blood with glucose in saliva could, could be modified to include Kim’s teaching regarding collecting the subjects' body mass index (BMI) and waist circumference. The combination of Zhang and Kim would be beneficial in establishing the relationship between blood glucose in a patient and the patient’s BMI and waist circumference.
However Zhang, Mondro, Chou, Laat, and Kim are silent the following limitation taught by Ryu:
and transmitted from the terminal to the server (See at least [Page 5, lines 40-42] via: “… the network 20 is a network in which the biometric information measuring device 10, the personal computer 31, the smart terminal 33, and the biometric information providing server 100 may transmit and receive information to each other..”)
Regarding claims 26 Zhang, Mondro, Chou, and Laat teach the invention as detailed above with respect to claim 19. Zhang also teaches:
input into the measuring device (See at least [0016] via: “... a signal conditioning and/or analysis device...”)
However Zhang, Mondro, Chou and Laat are silent the following limitation taught by Kim:
wherein the at least one physical indicator is input ... by the user (See at least [Page 9, lines 21-23] via: “… the subjects' body weight (kg) and height (m) were measured and body mass index (BMI) was calculated. In addition, anthropometric data including waist circumference, … are collected..”)
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the invention to have modified Zhang, Mondro, Chou and Laat to incorporate the teachings of Kim. Those in the art would have recognized that Zhang’s teaching regarding a glucose sensor suitable for measuring glucose levels in human saliva and Chou’s teaching correlating glucose in blood with glucose in saliva could, could be modified to include Kim’s teaching regarding collecting the subjects' body mass index (BMI) and waist circumference. The combination of Zhang and Kim would be beneficial in establishing the relationship between blood glucose in a patient and the patient’s BMI and waist circumference.
However Zhang, Mondro, Chou, Laat, and Kim are silent the following limitation taught by Ryu:
and transmitted from the measuring device to the server (See at least [Page 5, lines 40-42] via: “… the network 20 is a network in which the biometric information measuring device 10, the personal computer 31, the smart terminal 33, and the biometric information providing server 100 may transmit and receive information to each other..”)
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the invention to have modified Zhang, Mondro, Chou, Laat, and Kim to incorporate the teachings of Ryu. Those in the art would have recognized that Zhang’s teaching regarding a glucose sensor suitable for measuring glucose levels in human saliva and Chou’s teaching correlating glucose in blood with glucose in saliva could, could be modified to include Ryu’s teaching regarding a network that permits transmitting and receiving biometric information between and among a measuring device a computer, and a terminal. The combination of Zhang and Chou with Ryu is be beneficial in establishing two way communication between the measuring device, terminal and server which facilitates flow of data and ease of use of the glucose sensing system.
Regarding claims 28 Zhang, Mondro, Chou, and Laat teach the invention as detailed above with respect to claim 20. Zhang also teaches:
input into the measuring device (See at least [0016] via: “... a signal conditioning and/or analysis device...”)
However Zhang, Mondro, Chou and Laat are silent the following limitation taught by Kim:
wherein the at least one physical indicator is input ... by the user (See at least [Page 9, lines 21-23] via: “… the subjects' body weight (kg) and height (m) were measured and body mass index (BMI) was calculated. In addition, anthropometric data including waist circumference, … are collected..”)
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the invention to have modified Zhang, Mondro, Chou and Laat to incorporate the teachings of Kim. Those in the art would have recognized that Zhang’s teaching regarding a glucose sensor suitable for measuring glucose levels in human saliva and Chou’s teaching correlating glucose in blood with glucose in saliva could, could be modified to include Kim’s teaching regarding collecting the subjects' body mass index (BMI) and waist circumference. The combination of Zhang and Kim would be beneficial in establishing the relationship between blood glucose in a patient and the patient’s BMI and waist circumference.
However Zhang, Mondro, Chou, Laat, and Kim are silent the following limitation taught by Ryu:
and transmitted from the measuring device to the terminal (See at least [Page 5, lines 40-42] via: “… the network 20 is a network in which the biometric information measuring device 10, the personal computer 31, the smart terminal 33, and the biometric information providing server 100 may transmit and receive information to each other..”)
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the invention to have modified Zhang, Mondro, Chou, Laat, and Kim to incorporate the teachings of Ryu. Those in the art would have recognized that Zhang’s teaching regarding a glucose sensor suitable for measuring glucose levels in human saliva and Chou’s teaching correlating glucose in blood with glucose in saliva could, could be modified to include Ryu’s teaching regarding a network that permits transmitting and receiving biometric information between and among a measuring device a computer, and a terminal. The combination of Zhang and Chou with Ryu is be beneficial in establishing two way communication between the measuring device, terminal and server which facilitates flow of data and ease of use of the glucose sensing system.
Prior Art Made of Record
The prior art made of record and not relied upon is considered pertinent to Applicant's disclosure, and is listed in the attached form PTO-892 (Notice of References Cited). Unless expressly noted otherwise by the Examiner, all documents listed on form PTO-892 are cited in their entirety.
LABELLE (WO 2017132565 A1) - SALIVA GLUCOSE MEASUREMENT DEVICES AND METHODS - teaches: Devices and methods capable of detecting glucose in saliva (FIG. 12). The devices feature a sensor having a substrate containing electrodes and one or more reagents on the electrodes. A detection device is operably coupled with the sensor to detect glucose based on measurement of an electrical parameter when electricity is applied to the electrodes.
Jia (US 20190285656 A1) - DIABETES-RELATED BIOMARKERS AND TREATMENT OF DIABETES-RELATED CONDITIONS - teaches: provides biomarkers useful for evaluating the risk that a subject will develop diabetes, monitoring such risk, identifying members of a population at risk of developing diabetes, calculating risk of a subject developing diabetes, advising subjects of risk for developing diabetes, providing diagnostic tests for identifying subjects at risk for developing diabetes or kits there for, and providing diagnostic tests for determining risk of a subject developing diabetes and kits there for. The present invention also provides compounds and methods for treating subjects.
Response to Arguments
Applicant's arguments filed 1-26-2026, have been fully considered but not found
persuasive.
Applicant amended independent claims 19, 20, 21 and dependent claims 32, 35, 37 and cancelled claims 1-18 as posted in the above analysis with additions underlined and deletions as .
In response to applicant's arguments regarding claim rejection under 35 U.S.C § 101.
Several steps are taken in the analysis as to whether an invention is rejected under 101. The first step is to determine if the claim falls within a statutory category. In this case it does for claims 19, 20 and 21 since the claims recite a saliva-based blood glucose prediction system using artificial intelligence.
The second step under 2A prong one is to determine if the claims recite an abstract idea, which would be the case if the invention can be grouped as either: a) mathematical concepts; (b) mental processes; or (c) certain methods of organizing human activity (encompassing (i) fundamental economic principles, (ii) commercial or legal interactions or (iii) managing personal behavior or relationships or interactions between people). The current invention is classified as an abstract idea since it may be grouped as mental processes under concepts performed in the human mind (including an observation, evaluation, judgement, opinion) as it recites “predicting blood glucose levels based on a physical indicator and sugar content in saliva”. Alternatively it belongs to certain methods of organizing human activity under managing personal behavior or relationships or interactions between people as it recites “predicting blood glucose levels based on a physical indicator and sugar content in saliva”.
The third step under 2A Prong Two is to determine if additional elements in the claim imposes a meaningful limit on the abstract idea in order to integrate it into a practical idea. The current invention does not represent a practical idea since the additional elements amount to mere instructions to implement an abstract idea on a computer, or merely use a generic computer as a tool to implement the abstract idea.
the fourth step under 2B is to determine if additional elements of the claim provide an inventive concept. An invention may be classified as an inventive concept if a computer-implemented processes is determined to be significantly more than an abstract idea (and thus eligible), where generic computer components are able in combination to perform functions that are not merely generic, and non-conventional even if generic computer operations on a generic computing device is used to implement the abstract idea. The current invention does not represent an inventive concept since the additional elements amount to mere instructions to implement an abstract idea on a computer, or merely use a generic computer as a tool to implement the abstract idea.
Step 2A Prong ONE
The Applicant argues that Claims 19-21 are not directed to an abstract idea. Specifically claim 19 does not recite mental processes or certain methods of organizing human activity. Instead, claim 19 is directed to a system for specific configurations (collecting device, filter) for collecting saliva and removing interfering substances in the saliva in order to measure a glucose concentration in the saliva for predicting blood glucose information. In this way, physical manipulation of saliva is combined with machine-learning techniques to non-invasively determine blood glucose information. This technological innovation is impossible to perform in the human mind. Moreover, this innovation does not fall under the certain (i.e., enumerated) methods of organizing human activity, as it is not a method of managing personal behavior and relationships or interactions between people. The claimed invention is rather directed to a technological system for non-invasive inference of blood glucose based on saliva glucose measurement. While these claims may be tangentially related to interactions between people, as blood glucose levels relate to the human body and thus obliquely relate to human interactions, the claimed invention is in no way directed to these tangential human interactions.
The Examiner disagrees since the Applicant’s arguments are not persuasive. The method used to select the abstract idea, is to strip the additional elements from the claims. As seen below the recited boldened words constitute the abstract idea after stripping the un-boldened additional elements of amended limitation of claim 19
Claim 19:
a server configured to process and analyze data;
a terminal configured to receive and display predicted blood glucose information on a user;
a collecting device for non-invasively collecting saliva from the user, the collecting device comprising:
a specimen collecting unit for collecting saliva,
a compression tube for storing and compressing the collected saliva, and
a filter for removing interfering substances from the stored saliva;
a biosensor configured to receive the saliva after interfering substances have been removed from the saliva and sense glucose within the received saliva; and
a measuring device configured to:
receive the biosensor,
detect insertion of the biosensor,
upon detecting insertion of the biosensor, apply a specimen recognizing signal to detect whether the saliva is in contact with the biosensor
determine whether the saliva is in contact with the biosensor based on a first responding signal,
upon determining that the saliva is in contact with the biosensor, apply a specimen measuring signal to the biosensor to measure a glucose concentration in the saliva, wherein the specimen measuring signal is distinct from the specimen recognizing signal; and
transmit, a second responding signal, received from the biosensor after applying the specimen measuring signal, to the server, wherein the server comprises a pre-trained inference model utilizing a machine learning algorithm, the inference model being trained with experimental data to infer blood glucose based on:
the second responding signal; and
at least one physical indicator associated with the user, and wherein the server is further configured to:
predict blood glucose using the inference model based on the second responding signal and the physical indicator; and
transmit the predicted blood glucose information to the terminal.
The selected abstract idea (boldened limitations) of claim 19 can be implemented by pencil and paper and thus belong to the grouping of mental processes under concepts performed in the human mind (including an observation, evaluation, judgement, opinion) as it recites “predicting blood glucose levels based on a physical indicator and sugar content in saliva”. Alternatively, the selected abstract idea belongs to the grouping of certain methods of organizing human activity under managing personal behavior or relationships or interactions between people as it recites “predicting blood glucose levels based on a physical indicator and sugar content in saliva”. (refer to MPP 2106.04(a)(2)). Accordingly this claim recites an abstract idea.
Step 2A Prong TWO
The Applicant argues that the claims recite a practical application of any alleged abstract idea which may be found in Step 2A - Prong 1. The applicant further argues that the claimed systems and methods integrate a set of steps into an overall claimed process, which, when viewed as a whole, has the clear practical application of non- invasive inference of blood glucose based on saliva glucose measurement. The specification describes "a system for estimating blood glucose variability from a physical indicator by using a blood glucose variability inference model constructed by learning experiments for inferring a correlation between a physical indicator and blood glucose variability of a target based on artificial intelligence and a method thereof, and through this, may solve disadvantages of inconvenience and complexity of blood glucose variability measurement." Thus, the claims represent a practical application by providing a system for non-invasive, accurate measurement of blood glucose variability. Moreover, the claims represent a specify way of inferring blood glucose information from saliva glucose measurement. Specifically, the claims recite a collecting device, biosensor, measuring device, and an inference model trained to infer blood glucose based on a second responding signal and at least one physical indicator associated with a user. The claims include specific details regarding each of these features, such that the claims are directed to a specific way of inferring blood glucose information from saliva glucose measurement, not merely the idea of inferring blood glucose information from saliva glucose measurement.
The Examiner disagrees since the Applicant’s arguments are not persuasive. What is required for the invention to be directed to a practical application is a demonstration of improvement to the functioning of a computer, or to any other technology or technical field that the invention has recited. The Applicant’s arguments to demonstrate that the invention is a practical application is based on a colloquial interpretation of what may be deemed a practical application.
The Examiner restates that claims 19, 20 and 20 do not integrate the abstract idea into a practical application and do not recite additional elements that impose a meaningful limit on the abstract idea:
Claims 19, 20, 21 recite:
a collecting device;
a measuring device;
biosensor;
detect insertion of the biosensor;
upon detecting insertion of the biosensor, apply a specimen recognizing signal to detect whether the saliva is in contact with the biosensor;
determine whether the saliva is in contact with the biosensor based on a first responding signal;
upon determining that the saliva is in contact with the biosensor, apply a specimen measuring signal to the biosensor wherein the specimen measuring signal is distinct from the specimen recognizing signal;
second responding signal;
the server is further configured to predict blood glucose using the inference model based on.. the second responding signal, and transmit the predicted blood glucose information to the terminal.
Claim 19 recites:
a server configured to process and analyze data;
a terminal configured to receive and display predicted blood glucose information on a user
transmit, a second responding signal, received from the biosensor after applying the specimen measuring signal, to the server, wherein the server comprises a pre-trained inference model utilizing a machine learning algorithm.
Claim 20 recites:
transmit, a second responding signal, received from the biosensor after applying the specimen measuring signal, to the terminal, wherein the terminal comprises a pre-trained inference model utilizing a machine learning algorithm.
Claim 21 recites:
receive a second responding signal from the biosensor after applying the specimen measuring signal, wherein the measuring device comprises a pre-trained inference model utilizing a machine learning algorithm
The elements as recited above for claims 19, 20, 21 amount to additional elements that are recited at a high-level of generality such that it amounts to no more than mere instructions to implement an abstract idea on a computer, or merely use a computer as a tool to implement the abstract idea. (refer to MPEP 2106.05(f)). Accordingly, the claim as a whole does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
In order to integrate the abstract idea into a practical idea the Applicant could demonstrate at least one of the conditions enumerated below applies:
Improvements to the functioning of a computer, or to any other technology or technical field - see MPEP 2106.05(a)
Applying the judicial exception with, or by use of, a particular machine - see MPEP 2106.05(b)
Effecting a transformation or reduction of a particular article to a different state or thing - see MPEP 2106.05(c)
Applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception - see MPEP 2106.05(e) and Vanda Memo
The Applicant has not demonstrated any of the above listed conditions. As a result, the Examiner restates the rejection of the invention under 35 USC §101.
Step 2B
Similar to the analysis under Step 2A Prong Two, the additional elements amount to mere instructions to implement an abstract idea on a computer, or merely use a computer as a tool to implement the abstract idea. The use of generic computer components, in combination, do not perform functions that are not merely generic, and non-conventional even if the generic computer operations on a generic computing device is used to implement the abstract idea. Accordingly, the claim does not provide an inventive concept (significantly more than the abstract idea) and hence the claim is ineligible.
In order evaluate whether the claim recites additional elements that amount to an inventive concept what could be shown is:
Adding a specific limitation (unconventional other than what is well-understood, routine, conventional (WURC) activity in the field - see MPEP 2106.05(d)
The Applicant has not demonstrated the above listed condition.
In response to applicant's arguments regarding claim rejection under 35 U.S.C § 103.
The Applicant submits that the cited references, whether taken alone or in combination, do not teach or suggest the amended claimed invention. Accordingly, the Applicant requests that the rejections under 35 U.S.C. § 103 be withdrawn.
The applicant's arguments with respect to claims 19-37 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
For reasons of record and as set forth above, the examiner maintains the rejection of claims 19-37 as being directed to a judicial exception without significantly more, and thereby being directed to non-statutory subject matter under 35 USC §101 in addition to maintaining the rejection under 35 USC §103. In reaching this decision, the Examiner considered all evidence presented and all arguments actually made by Applicant.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to PIERRE L MACCAGNO whose telephone number is (571)270-5408. The examiner can normally be reached M-F 8:00 to 5:00.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Mamon Obeid can be reached at (571)270-1813. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/PIERRE L MACCAGNO/Examiner, Art Unit 3687
/STEVEN G.S. SANGHERA/Primary Examiner, Art Unit 3684
Prosecution Insights