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 .
Response to Arguments
Applicant’s arguments and amendments filed 11/19/2025 have been fully considered.
Regarding the 35 USC 112a Rejection, the amended claims have overcome the rejection.
Regarding the 35 USC 112b Rejection, the amended claims have overcome the rejection.
Regarding the 35 USC 101 Rejection:
The applicant is directed to the 35 U.S.C 101 rejection below, necessitated by amendments where the abstract ideas and additional elements are defined through underlining abstract ideas and bolding additional elements.
Claim 1 (and its dependent claims) recites gathering data, storing said data, processing said data, and analyzing said data which are grouped as a mental process under subtract ideas. The additional elements include one or more sensors, storage, processor, and display are not part of the abstract idea because those elements are generically recited within the claims. The abstract ideas within the 101 rejection fall within the mental process groupings of abstract ideas because they cover concepts performed in the human mind including observation, evaluation, judgement, and opinion. See MPEP 2106.04(a)(2), subsection III.
Claim 14 (and its dependent claims) recites gathering data, storing said data, processing said data, and analyzing said data which are grouped as a mental process under subtract ideas. The additional elements include storage and display are not part of the abstract idea because those elements are generically recited within the claims. The abstract ideas within the 101 rejection fall within the mental process groupings of abstract ideas because they cover concepts performed in the human mind including observation, evaluation, judgement, and opinion. See MPEP 2106.04(a)(2), subsection III.
Regarding Claim 1, “An apparatus configured to estimate an antioxidant component, the apparatus comprising:
one or more sensors configured to measure optical signals from body parts of a user (Observation);
a storage configured to store first antioxidant concentrations estimated at a first body part and second antioxidant concentrations estimated at a second body part (Judgement);
a processor configured to:
estimate the first antioxidant concentrations at the first body part (Judgement),
extract, as training data, data pairs of the first antioxidant concentrations and the second antioxidant concentrations from the storage based on predetermined learning conditions (Judgement),
generate a transformation model configured to transfer the second antioxidant concentrations into a reference index based on the training data (Judgement); and
a display configured to display the first antioxidant concentrations, the second antioxidant concentrations, and the reference index (Judgement),
wherein the processor is further configured to determine parameters by training a basic transformation model by using the training data and to generate the transformation model by using the determined parameters (Judgement),
wherein the transformation model is defined as a linear function, anon-linear function or a neural network-based model,
wherein the processor is further configured to extract one or more data pairs of the first antioxidant concentrations and the second antioxidant concentrations, corresponding to estimation times of the respective first antioxidant concentrations, as the training data from the storage (Observation), and
wherein based on a time point at which a change in absorbance of an optical signal measured at the second body part is greater than or equal to a threshold value, the processor is further configured to extract the data pairs of the first antioxidant concentrations and the second antioxidant concentrations from the storage at a time interval after the time point (Observation).”
Regarding Claim 14, “A method of estimating an antioxidant component, the method comprising:
estimating first antioxidant concentrations at a first body part (Observation);
extracting, as training data, data pairs of first antioxidant concentrations estimated at the first body part and second antioxidant concentrations estimated at a second body part from a storage based on predetermined learning conditions (Judgement); and
generating a transformation model configured to transform the second antioxidant concentrations into a reference index based on the training data (Judgement); and
by a display, displaying the first antioxidant concentrations, the second antioxidant concentrations, and the reference index (Judgement),
wherein the generating the transformation model further comprises determining parameters by training a basic transformation model by using the training data and generating the transformation model by using the determined parameters (Judgement),
wherein the transformation model is defined as a linear function, anon-linear function or a neural network-based model,
wherein extracting data pairs further comprises extracting one or more data pairs of the first antioxidant concentrations and the second antioxidant concentrations, corresponding to estimation times of the respective first antioxidant concentrations, as the training data from the storage (Judgement),
wherein extracting the data pairs further comprises, based on a time point at which a change in absorbance of an optical signal measured at the second body part is greater than or equal to a threshold value, extracting the data pairs of the first antioxidant concentrations and the second antioxidant concentrations from the storage at a time interval after the time point (Observation).”
Under MPEP 2106.05(a), it states in determining patent eligibility, examiners should consider whether the claim "purport(s) to improve the functioning of the computer itself" or "any other technology or technical field." Alice Corp. Pty. Ltd. v. CLS Bank Int’l, 573 U.S. 208, 225, 110 USPQ2d 1976, 1984 (2014). This consideration has also been referred to as the search for a technological solution to a technological problem. See e.g., DDR Holdings, LLC. v. Hotels.com, L.P., 773 F.3d 1245, 1257, 113 USPQ2d 1097, 1105 (Fed. Cir. 2014); Amdocs (Israel), Ltd. v. Openet Telecom, Inc., 841 F.3d 1288, 1300-01, 120 USPQ2d 1527, 1537 (Fed. Cir. 2016). It is further advised:
An important consideration in determining whether a claim improves technology is the extent to which the claim covers a particular solution to a problem or a particular way to achieve a desired outcome, as opposed to merely claiming the idea of a solution or outcome. McRO, 837 F.3d at 1314-15, 120 USPQ2d at 1102-03; DDR Holdings, 773 F.3d at 1259, 113 USPQ2d at 1107. In this respect, the improvement consideration overlaps with other considerations, specifically the particular machine consideration (see MPEP § 2106.05(b)), and the mere instructions to apply an exception consideration (see MPEP § 2106.05(f)). Thus, evaluation of those other considerations may assist examiners in making a determination of whether a claim satisfies the improvement consideration.
It is important to note, the judicial exception alone cannot provide the improvement. The improvement can be provided by one or more additional elements. See the discussion of Diamond v. Diehr, 450 U.S. 175, 187 and 191-92, 209 USPQ 1, 10 (1981)) in subsection II, below. In addition, the improvement can be provided by the additional element(s) in combination with the recited judicial exception. See MPEP §2106.04(d) (discussing Finjan, Inc. v. Blue Coat Sys., Inc., 879 F.3d 1299, 1303-04, 125 USPQ2d 1282, 1285-87 (Fed. Cir. 2018)). Thus, it is important for examiners to analyze the claim as a whole when determining whether the claim provides an improvement to the functioning of computers or an improvement to other technology or technical field.
Regarding the guidance from MPEP 2106.05(a), it is important to note, the judicial exception alone cannot provide the improvement. The claims are directed to generic analysis steps that are all within the capabilities of a human. The claimed invention is more analogous to Claim 1 of Example 46 provided by the USPTO October 2019 which was deemed ineligible under 101. Further from MPEP 2105.04(a)(2): “Examples of claims that recite mental processes include: a claim to “collecting information, analyzing it, and displaying certain results of the collection and analysis,” where the data analysis steps are recited at a high level of generality such that they could practically be performed in the human mind, Electric Power Group v. Alstom, S.A., 830 F.3d 1350, 1353-54, 119 USPQ2d 1739, 1741-42 (Fed. Cir. 2016);” This is clearly the same as the claimed invention. Nothing in the claim appears to reflect any improvement.
The evaluation of whether the claim as a whole integrates the recited judicial exception into a practical application of the exception or whether the claim is ‘directed to’ the judicial exception is performed by identifying additional elements recited in the claim beyond the judicial exception and evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application. See MPEP 2106.04(d). The claim recites the additional elements of: one or more sensors, storage, processor, and display. The claim recites that the processor executes the limitations using the other additional elements listed.
Regarding the guidance from MPEP 2106.05(b), it’s important to note that a general purpose computer that applies a judicial exception, such as an abstract idea, by use of conventional computer functions does not qualify as a particular machine. The amended claims contain the following additional elements: one or more sensors, storage, processor, and display, which are generic computer or generic computer components. The additional elements do not integrate the exception into a practical application or provide significantly more than the judicial exception. Merely adding a generic computer, generic computer components, or a programmed computer to perform generic computer functions does not automatically overcome an eligibility rejection.
Integral use of a machine to achieve performance of a method may integrate the recited judicial exception into a practical application or provide significantly more, in contrast to where the machine is merely an object on which the method operates, which does not integrate the exception into a practical application or provide significantly more. See CyberSource v. Retail Decisions, 654 F.3d 1366, 1370, 99 USPQ2d 1690, 1694 (Fed. Cir. 2011) ("We are not persuaded by the appellant's argument that the claimed method is tied to a particular machine because it ‘would not be necessary or possible without the Internet.’ . . . Regardless of whether "the Internet" can be viewed as a machine, it is clear that the Internet cannot perform the fraud detection steps of the claimed method"). For example, as described in MPEP § 2106.05(f), additional elements that invoke computers or other machinery merely as a tool to perform an existing process will generally not amount to significantly more than a judicial exception. See, e.g., Versata Development Group v. SAP America, 793 F.3d 1306, 1335, 115 USPQ2d 1681, 1702 (Fed. Cir. 2015) (explaining that in order for a machine to add significantly more, it must "play a significant part in permitting the claimed method to be performed, rather than function solely as an obvious mechanism for permitting a solution to be achieved more quickly").
Whether its involvement is extra-solution activity or a field-of-use, i.e., the extent to which (or how) the machine or apparatus imposes meaningful limits on the claim. Use of a machine that contributes only nominally or insignificantly to the execution of the claimed method (e.g., in a data gathering step or in a field-of-use limitation) would not integrate a judicial exception or provide significantly more. See Bilski, 561 U.S. at 610, 95 USPQ2d at 1009 (citing Parker v. Flook, 437 U.S. 584, 590, 198 USPQ 193, 197 (1978)), and CyberSource v. Retail Decisions, 654 F.3d 1366, 1370, 99 USPQ2d 1690 (Fed. Cir. 2011) (citations omitted) ("[N]othing in claim 3 requires an infringer to use the Internet to obtain that data. The Internet is merely described as the source of the data. We have held that mere ‘[data-gathering] step[s] cannot make an otherwise nonstatutory claim statutory.’" 654 F.3d at 1375, 99 USPQ2d at 1694 (citation omitted)). See MPEP § 2106.05(g) & (h) for more information on insignificant extra-solution activity and field of use, respectively.
Further, the limitations are executed on a processor and utilize one or more sensors, storage, and display. The one or more sensors, storage, processor, and display are recited at a high level of generality. The one or more sensors, storage, processor, and display are used to perform an abstract idea, such that it amounts to no more than mere instructions to apply the exception using a generic computer or conventional equipment. The support structure merely indicate filed of use which does not provide significantly more. See MPEP 2106.05(f) and MPEP 2106.05(h). There is no indication that the claim as a whole includes an improvement to a computer or to a technological field, any alleged improvement is not reflected in the claims. See MPEP 2106.04(d)(1).
Therefore, the applicant’s arguments are not persuasive.
Regarding 35 USC 103 rejection, applicant’s amendments respect to the rejected claims 1, 4, 5, 7-14, 16, 18, and 19 have overcome the 35 USC 103 rejection. However, upon further consideration, new grounds of rejection is made in view of Claims 1 and 14 because the amended claims incorporates predetermined learning conditions; a display configured to display the first antioxidant concentrations, the second antioxidant concentrations, and the reference index, wherein the processor is further configured to determine parameters by training a basic transformation model by using the training data and to generate the transformation model by using the determined parameters, wherein the transformation model is defined as a linear function, anon-linear function or a neural network-based model, wherein the processor is further configured to extract one or more data pairs of the first antioxidant concentrations and the second antioxidant concentrations, corresponding to estimation times of the respective first antioxidant concentrations, as the training data from the storage. The previous set of claims did not incorporate predetermined learning conditions; a display configured to display the first antioxidant concentrations, the second antioxidant concentrations, and the reference index, wherein the processor is further configured to determine parameters by training a basic transformation model by using the training data and to generate the transformation model by using the determined parameters, wherein the transformation model is defined as a linear function, anon-linear function or a neural network-based model, wherein the processor is further configured to extract one or more data pairs of the first antioxidant concentrations and the second antioxidant concentrations, corresponding to estimation times of the respective first antioxidant concentrations, as the training data from the storage.
Claim Objections
Claims 1 and 14 objected to because of the following informalities:
In claims 1 and 14, “anon-linear function” should read “a non-linear function.”
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.
Claims 1, 4, 5, 7-14, 16, 18, and 19 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.
In Claim 1 and 14, the claim limitation “predetermined learning condition” renders the claim indefinite because the limitation is unclear. It is unclear what characteristics or terms are defined as the predetermined learning condition. For purposes of examination, the claim limitation is interpreted as the color, thickness, structure of skin at a body part.
In Claims 1 and 14, the claim limitation “the processor is further configured to determine parameters by training a basic transformation model by using the training data and to generate the transformation model by using the determined parameters” renders the claim indefinite because the limitation is unclear. It is unclear how the basic transformation model is different from the transformation model, and how the basic transformation model generates the transformation model. For purposes of examination, the claim limitation is interpreted as the basic transformation model and the transformation model utilize the same linear function.
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, 4, 5, 7-14, 16, 18, and 19 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Each of Claims 1, 4, 5, 7-14, 16, 18, and 19 has been analyzed to determine whether it is directed to any judicial exceptions.
Step 2A, Prong 1
Each of Claims 1, 4, 5, 7-14, 16, 18, and 19 recites at least one step or instruction for estimating an antioxidant concentration, which is grouped as a mental process under the 2019 PEG or a certain method of organizing human activity under the 2019 PEG. Accordingly, each of Claims 1, 4, 5, 7-14, 16, 18, and 19 recites an abstract idea.
Specifically, Claims 1 and 14 recite:
Claim 1 | “An apparatus configured to estimate an antioxidant component, the apparatus comprising:
one or more sensors configured to measure optical signals from body parts of a user (Observation);
a storage configured to store first antioxidant concentrations estimated at a first body part and second antioxidant concentrations estimated at a second body part (Judgement);
a processor configured to:
estimate the first antioxidant concentrations at the first body part (Judgement),
extract, as training data, data pairs of the first antioxidant concentrations and the second antioxidant concentrations from the storage based on predetermined learning conditions (Judgement),
generate a transformation model configured to transfer the second antioxidant concentrations into a reference index based on the training data (Judgement); and
a display configured to display the first antioxidant concentrations, the second antioxidant concentrations, and the reference index (Judgement),
wherein the processor is further configured to determine parameters by training a basic transformation model by using the training data and to generate the transformation model by using the determined parameters (Judgement),
wherein the transformation model is defined as a linear function, anon-linear function or a neural network-based model,
wherein the processor is further configured to extract one or more data pairs of the first antioxidant concentrations and the second antioxidant concentrations, corresponding to estimation times of the respective first antioxidant concentrations, as the training data from the storage (Observation), and
wherein based on a time point at which a change in absorbance of an optical signal measured at the second body part is greater than or equal to a threshold value, the processor is further configured to extract the data pairs of the first antioxidant concentrations and the second antioxidant concentrations from the storage at a time interval after the time point (Observation).”
Claim 14 | “A method of estimating an antioxidant component, the method comprising:
estimating first antioxidant concentrations at a first body part (Observation);
extracting, as training data, data pairs of first antioxidant concentrations estimated at the first body part and second antioxidant concentrations estimated at a second body part from a storage based on predetermined learning conditions (Judgement); and
generating a transformation model configured to transform the second antioxidant concentrations into a reference index based on the training data (Judgement); and
by a display, displaying the first antioxidant concentrations, the second antioxidant concentrations, and the reference index (Judgement),
wherein the generating the transformation model further comprises determining parameters by training a basic transformation model by using the training data and generating the transformation model by using the determined parameters (Judgement),
wherein the transformation model is defined as a linear function, anon-linear function or a neural network-based model,
wherein extracting data pairs further comprises extracting one or more data pairs of the first antioxidant concentrations and the second antioxidant concentrations, corresponding to estimation times of the respective first antioxidant concentrations, as the training data from the storage (Judgement),
wherein extracting the data pairs further comprises, based on a time point at which a change in absorbance of an optical signal measured at the second body part is greater than or equal to a threshold value, extracting the data pairs of the first antioxidant concentrations and the second antioxidant concentrations from the storage at a time interval after the time point (Observation).”
Regarding the dependent claims, the following dependent claims are directed to steps that are also abstract or organizing human activity:
Claims 4, 5, 7, 12, 16, include steps that are also abstract as a mental process through additional data gathering or analysis.
Claims 8, 9, 10, 11, 13, 18, and 20 include steps that are also abstract because the transformation model is updated through a mental process.
Although the dependent claims are further limiting, they do not recite significantly more than the abstract idea. A narrowing idea is still an abstract idea and an abstract idea with additional well-known equipment/functions are not significantly more than the abstract idea.
Accordingly, as indicated above, each of the above-identified claims recites an abstract idea.
Step 2A, Prong 2
The above-identified abstract idea in each of independent Claims 1 and 14 (and their respective dependent Claims 4, 5, 7-13, 16, 18, and 19) is not integrated into a practical application under 2019 PEG because the additional elements (identified above in independent Claims 1 and 14), either alone or in combination, generally link the use of the above-identified abstract idea to a particular technological environment or field of use. More specifically, the additional elements of: one or more sensors, storage, processor, and display are generically recited computer elements in independent Claims 1 and 14 (and their respective dependent claims) which do not improve the functioning of a computer, or any other technology or technical field. Nor do these above-identified additional elements serve to apply the above-identified abstract idea with, or by use of, a particular machine, effect a transformation or apply or use the above-identified abstract idea in some other meaningful way beyond generally linking the use thereof to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception. Furthermore, the above-identified additional elements do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer. For at least these reasons, the abstract idea identified above in independent Claims 1 and 14 (and their respective dependent claims) is not integrated into a practical application under 2019 PEG.
Moreover, the above-identified abstract idea is not integrated into a practical application under 2019 PEG because the claimed method and system merely implements the above-identified abstract idea (e.g., mental process and certain method of organizing human activity) using rules (e.g., computer instructions) executed by a computer (e.g., storage and processor as claimed). In other words, these claims are merely directed to an abstract idea with additional generic computer elements which do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer. Additionally, Applicant’s specification does not include any discussion of how the claimed invention provides a technical improvement realized by these claims over the prior art or any explanation of a technical problem having an unconventional technical solution that is expressed in these claims. That is, like Affinity Labs of Tex. v. DirecTV, LLC, the specification fails to provide sufficient details regarding the manner in which the claimed invention accomplishes any technical improvement or solution. Thus, for these additional reasons, the abstract idea identified above in independent Claims 1 and 14 (and their respective dependent claims) is not integrated into a practical application under the 2019 PEG.
Accordingly, independent Claims 1 and 14 (and their respective dependent claims) are each directed to an abstract idea under 2019 PEG.
Step 2B
None of Claims 1, 4, 5, 7-14, 16, 18, and 19 include additional elements that are sufficient to amount to significantly more than the abstract idea for at least the following reasons.
These claims require the additional elements of one or more sensors, storage, processor, and display.
The above-identified additional elements are generically claimed computer components which enable the above-identified abstract idea(s) to be conducted by performing the basic functions of automating mental tasks. The courts have recognized such computer functions as well understood, routine, and conventional functions when claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity. See, Versata Dev. Group, Inc. v. SAP Am., Inc. , 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); and OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93.
Per Applicant’s specification, one or more sensors measure the optical signals from the body (Paragraph 0004); storage stores the measured optical signal and the estimated antioxidant concentration (Paragraph 0045); processor controls the sensors, generates an estimated antioxidant concentration from the optical signals collected, and generates a transformation model (Paragraphs 0045-0047); display outputs visual information to the user (Paragraphs 0094-0095).
Accordingly, in light of Applicant’s specification, the claimed processor and storage is reasonably construed as a generic computing device. Like SAP America vs Investpic, LLC (Federal Circuit 2018), it is clear, from the claims themselves and the specification, that these limitations require no improved computer resources, just already available computers, with their already available basic functions, to use as tools in executing the claimed process.
Furthermore, Applicant’s specification does not describe any special programming or algorithms required for the processor. This lack of disclosure is acceptable under 35 U.S.C. §112(a) since this hardware performs non-specialized functions known by those of ordinary skill in the computer arts. By omitting any specialized programming or algorithms, Applicant's specification essentially admits that this hardware is conventional and performs well understood, routine and conventional activities in the computer industry or arts. In other words, Applicant’s specification demonstrates the well-understood, routine, conventional nature of the above-identified additional elements because it describes these additional elements in a manner that indicates that the additional elements are sufficiently well-known that the specification does not need to describe the particulars of such additional elements to satisfy 35 U.S.C. § 112(a) (see Berkheimer memo from April 19, 2018, (III)(A)(1) on page 3). Adding hardware that performs “‘well understood, routine, conventional activit[ies]’ previously known to the industry” will not make claims patent-eligible (TLI Communications).
The recitation of the above-identified additional limitations in Claims 1, 4, 5, 7-14, 16, 18, and 19 amounts to mere instructions to implement the abstract idea on a computer. Simply using a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); and TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Moreover, implementing an abstract idea on a generic computer, does not add significantly more, similar to how the recitation of the computer in the claim in Alice amounted to mere instructions to apply the abstract idea of intermediated settlement on a generic computer.
A claim that purports to improve computer capabilities or to improve an existing technology may provide significantly more. McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314-15, 120 USPQ2d 1091, 1101-02 (Fed. Cir. 2016); and Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335-36, 118 USPQ2d 1684, 1688-89 (Fed. Cir. 2016). However, a technical explanation as to how to implement the invention should be present in the specification for any assertion that the invention improves upon conventional functioning of a computer, or upon conventional technology or technological processes. That is, the disclosure must provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. Here, Applicant’s specification does not include any discussion of how the claimed invention provides a technical improvement realized by these claims over the prior art or any explanation of a technical problem having an unconventional technical solution that is expressed in these claims. Instead, as in Affinity Labs of Tex. v. DirecTV, LLC 838 F.3d 1253, 1263-64, 120 USPQ2d 1201, 1207-08 (Fed. Cir. 2016), the specification fails to provide sufficient details regarding the manner in which the claimed invention accomplishes any technical improvement or solution.
For at least the above reasons, the apparatus and method of Claims 1, 4, 5, 7-14, 16, 18, and 19 are directed to applying an abstract idea as identified above on a general purpose computer without (i) improving the performance of the computer itself, or (ii) providing a technical solution to a problem in a technical field. None of Claims 1, 4, 5, 7-14, 16, 18, and 19 provides meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that these claims amount to significantly more than the abstract idea itself.
Taking the additional elements individually and in combination, the additional elements do not provide significantly more. Specifically, when viewed individually, the above-identified additional elements in independent Claims 1 and 14 (and their dependent claims) do not add significantly more because they are simply an attempt to limit the abstract idea to a particular technological environment. That is, neither the general computer elements nor any other additional element adds meaningful limitations to the abstract idea because these additional elements represent insignificant extra-solution activity. When viewed as a combination, these above-identified additional elements simply instruct the practitioner to implement the claimed functions with well-understood, routine and conventional activity specified at a high level of generality in a particular technological environment. As such, there is no inventive concept sufficient to transform the claimed subject matter into a patent-eligible application. When viewed as whole, the above-identified additional elements do not provide meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that the claims amount to significantly more than the abstract idea itself. Thus, Claims 1, 4, 5, 7-14, 16, 18, and 19 merely apply an abstract idea to a computer and do not (i) improve the performance of the computer itself (as in Bascom and Enfish), or (ii) provide a technical solution to a problem in a technical field (as in DDR).
Therefore, none of the Claims 1, 4, 5, 7-14, 16, 18, and 19 amounts to significantly more than the abstract idea itself. Accordingly, Claims 1, 4, 5, 7-14, 16, 18, and 19 are not patent eligible and rejected under 35 U.S.C. 101.
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 for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 4, 5, 7-14, 16, 18, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Diab et al. (US 20210113121 A1) in view of Jang et al (US 20210113087 A1).
Regarding Claim 1, Diab discloses an apparatus (patient monitor – elements 102 and 202) configured to estimate an analyte component (Paragraph 0097, The patient monitor 102 can, for example, determine physiological parameters corresponding to the patient, such as an amount of light absorbed, transmitted through, or reflected at a tissue site, path length (for example, distance that light travels through the material), concentration of an analyte; [Examiner’s note, both patient monitors preform the same function.]), the apparatus comprising:
one or more sensors configured to measure optical signals from body parts of a user (Diab | Paragraphs 0100, 0105);
a storage (memory device – element 228; Paragraph 0124) configured to store first analyte concentrations estimated at a first body part (tissue site – element 206A; Figure 2; Paragraph 0120) and second analyte concentrations estimated at a second body part (tissue site – element 206B; Figure 2; Paragraph 0120);
a processor (DSP – elements 212A-C; Figure 2; Paragraphs 0107, 0110, and 0118) configured to:
estimate the first analyte concentrations at the first body part (1308 of Figure 12A; Paragraph 0175; [Examiner’s note, the learning condition is the skin geometry information.]),
extract, as training data, data pairs of the first analyte concentrations and the second analyte concentrations from the storage based on predetermined learning conditions (instrument manager – element 210; Figure 2; Paragraph 0119-0120; 1308 of Figure 12A; Paragraph 0175; [Examiner’s note, the learning condition is the skin geometry information. The data extraction of a data pair are the data collected by the DSP 212A, DSP 212B, and DSP 212C from corresponding tissue sites 206A, 206B, and 206C.]),
generate a transformation model configured to transfer the second analyte concentrations into a reference index based on the training data (Equation 1; Paragraph 0176, based on the data received at block 1304 from the one or more second noninvasive sensors, the processor can determine an absorbance corresponding to a tissue site interrogated by the one or more second noninvasive sensors. Using one or more relationships derived from Beer's law (Equation 1), the concentration, c, of one or more analytes can be determined using the absorbance, A, determined from the pulse oximetry sensor data, and the path length, b, determined from the tissue geometry data; Paragraph 0201; [Examiner’s note, the transformation model is Beer’s Law, which is a linear regression model.]); and
a display (user interface – element 222) configured to display the first analyte concentrations, the second analyte concentrations, and the reference index (Paragraph 0101, 0121, 0181),
wherein the processor is further configured to determine parameters by training a basic transformation model by using the training data and to generate the transformation model by using the determined parameters (Equation 1; Paragraph 0176),
wherein the transformation model is defined as a linear function (Equation 1; Paragraph 0176; [Examiner’s note, the transformation model is Beer’s Law, which is a linear regression.], anon-linear function or a neural network-based model [Examiner’s note, the claim comprises multiple limitations; however, only one of the alternatives needs to be supported by the prior art.],
wherein the processor is further configured to extract one or more data pairs of the first analyte concentrations and the second analyte concentrations, corresponding to estimation times of the respective first analyte concentrations, as the training data from the storage (3305 of Figure 13; Paragraphs 0190, 0191, 0197, 0201, 0202 and 0244-0250; [Examiner’s note, The signal processing of 3305 harmonizes the data collected from the sensor system 100; harmonized physiological measures include Raman measurements (3307 of Figure 13), absorbance measurements (3309 of Figure 13), and OCT measurements (3311 of Figure 13). Additionally, the timing processor system 1800 works along with the sensor system 100 to synchronize the data from the various measurements. One skilled in the art can determine extracted data pairs corresponding to the first analyte concentration because the sensor system collects data from multiple tissue sites.]), and
wherein based on a time point at which a change in absorbance of an optical signal measured at the second body part (Figure 25A; Paragraph 0294; [Examiner’s note, the change in absorbance is measured by Beer’s Law Equation (equation 1), which is rewritten as
∆
A
=
ε
b
(
C
2
-
C
1
), where
C
1
and
C
2
are the first and second antioxidant concentrations.]) is greater than or equal to a threshold value (Paragraph 0287-0289, 0291; [Examiner’s note, the threshold is the temperature at different tissue depths to collect the desired physiological data. For example, different tissue sites, with varying tissue depths, may require differing temperatures by a laser to be reached in order to collect sufficient and accurate data.]), the processor is further configured to extract the data pairs of the first analyte concentrations and the second analyte concentrations from the storage at a time interval after the time point (Figure 25A; Paragraph 0291; [Examiner’s note, data is collected after the baseline period is over.]).
Diab is silent on explicitly teaching an antioxidant component/concentration; Jang teaches an optical sensor used to estimate an antioxidant component/concentration (Jang | Paragraphs 0007, 0055; [Examiner’s note, one skilled in the art can determine if an antioxidant value is determined from the optical sensor, then a component/concentration is determined.]). Diab teaches of an analyte concentration and Jang teaches an optical sensor used to estimate an antioxidant component/concentration. One having an ordinary skill in the art the time the invention was filed would have found it obvious to modify the apparatus of Diab to incorporate the teachings of determining an antioxidant component/concentration because the level of antioxidant component/concentration correlates to the prevention of oxygen toxicity within the user (Jang | Paragraph 0005).
Regarding Claim 4, Diab in view of Jang teaches the apparatus of claim 1, wherein the processor is further configured to extract data pairs of the first analyte concentrations and the second analyte concentrations from the storage included in a predetermined period (Diab | Paragraph 0135, a subsequent OCT measurement or set of measurements can occur minutes, hours, days, weeks, or some other period of time after the first measurement, and it can be unreasonable to require a patient to wear or interact with the OCT sensor for the duration of that period of time) based on at least one of a thickness (Diab | Paragraph 0116, 0300), and a structure of a user's skin (Diab | Paragraph 0115, The patient monitor 200 uses the detected signals obtained from the interference of the reflected sample arm light beams 250 and the reflected reference arm light beams 230 to calculate tissue geometry data, such as a skin geometry of one or more skin layers; Paragraph 0132) and physiological characteristics (Diab | Paragraph 0127).
Diab is silent on explicitly teaching an antioxidant component/concentration; Jang teaches an optical sensor used to estimate an antioxidant component/concentration (Jang | Paragraphs 0007, 0055; [Examiner’s note, one skilled in the art can determine if an antioxidant value is determined from the optical sensor, then a component/concentration is determined.]). Diab teaches of an analyte concentration and Jang teaches an optical sensor used to estimate an antioxidant component/concentration. One having an ordinary skill in the art the time the invention was filed would have found it obvious to modify the apparatus of Diab to incorporate the teachings of determining an antioxidant component/concentration because the level of antioxidant component/concentration correlates to the prevention of oxygen toxicity within the user (Jang | Paragraph 0005).
Regarding claim 5, Diab in view of Jang teaches the apparatus of claim 1, wherein based on second analyte concentration, corresponding to the time at which the first analyte concentration is estimated, not being included in the storage, the processor is further configured to extract data pair of a first analyte concentration and a second analyte concentration from the storage based on one or more adjacent second analyte concentrations estimated at times prior to or after the time at which the first analyte concentration is estimated (Diab | Paragraphs 0197, 0200, 0202, 0319, 0322; [Examiner’s note, the sensor system 100 works in conjunction with the signal processing system 3305 and timing processor system 1800, as shown in Claim 3. The Raman, absorbance, and OCT utilize interpolation with the data collected from those measurement. One skilled in the art can determine interpolation is a method used to estimate unknown values between known data. That known data can be times prior to or after the time at which the first analyte concentration is estimated.]).
Diab is silent on explicitly teaching an antioxidant component/concentration; Jang teaches an optical sensor used to estimate an antioxidant component/concentration (Jang | Paragraphs 0007, 0055; [Examiner’s note, one skilled in the art can determine if an antioxidant value is determined from the optical sensor, then a component/concentration is determined.]). Diab teaches of an analyte concentration and Jang teaches an optical sensor used to estimate an antioxidant component/concentration. One having an ordinary skill in the art the time the invention was filed would have found it obvious to modify the apparatus of Diab to incorporate the teachings of determining an antioxidant component/concentration because the level of antioxidant component/concentration correlates to the prevention of oxygen toxicity within the user (Jang | Paragraph 0005).
Regarding claim 7, Diab in view of Jang teaches the apparatus of claim 1, wherein the processor is further configured to extract the data pairs of the training data until a number of data pairs is greater than or equal to a predetermined number (Diab | 2508 of Figure 25A; Paragraph 0296; [Examiner’s note, the purpose of heating and cooling on a tissue site is based on the tissue depth for collecting the desired physiological parameter. One skilled in the art can determine that when a specific temperature is reached during the cooling period, based upon the tissue depth, the accuracy of data collected is not reliable, and will result in the end of the data collection from the various sensors at its corresponding tissue sites. Therefore the predetermined number is the cooling temperature.]).
Regarding claim 8, Diab in view of Jang teaches the apparatus of claim 1, wherein based on generating the transformation model, the processor is further configured to perform update by transforming the second analyte concentrations (Diab | Paragraph 0104), stored in the storage, into the reference index (Diab | Paragraph 0124; [Examiner’s note, the reference index is the memory device. According to ScienceDirect’s article on Indexing Method, the term "index" or "indexing" generally refers to methods of organizing and structuring data to facilitate efficient access and retrieval, especially in scenarios involving large datasets and tasks like similarity search or information retrieval]) based on the generated transformation model (Diab | Paragraph 0097, the patient monitor 102 can derive or use one or more relationships (for instance, a set of linear equations) from two or more of the determined parameters).
Diab is silent on explicitly teaching an antioxidant component/concentration; Jang teaches an optical sensor used to estimate an antioxidant component/concentration (Jang | Paragraphs 0007, 0055; [Examiner’s note, one skilled in the art can determine if an antioxidant value is determined from the optical sensor, then a component/concentration is determined.]). Diab teaches of an analyte concentration and Jang teaches an optical sensor used to estimate an antioxidant component/concentration. One having an ordinary skill in the art the time the invention was filed would have found it obvious to modify the apparatus of Diab to incorporate the teachings of determining an antioxidant component/concentration because the level of antioxidant component/concentration correlates to the prevention of oxygen toxicity within the user (Jang | Paragraph 0005).
Regarding claim 9, Diab in view of Jang teaches the apparatus of claim 8, wherein the processor is further configured to transform second analyte concentrations, included in first data pair to last data pair of the training data of the generated transformation model, into the reference index (Diab | Paragraph 0124).
Diab is silent on explicitly teaching an antioxidant component/concentration; Jang teaches an optical sensor used to estimate an antioxidant component/concentration (Jang | Paragraphs 0007, 0055; [Examiner’s note, one skilled in the art can determine if an antioxidant value is determined from the optical sensor, then a component/concentration is determined.]). Diab teaches of an analyte concentration and Jang teaches an optical sensor used to estimate an antioxidant component/concentration. One having an ordinary skill in the art the time the invention was filed would have found it obvious to modify the apparatus of Diab to incorporate the teachings of determining an antioxidant component/concentration because the level of antioxidant component/concentration correlates to the prevention of oxygen toxicity within the user (Jang | Paragraph 0005).
Regarding claim 10, Diab in view of Jang teaches the apparatus of claim 9, wherein based on a missing interval existing between the first data pair of the training data of the generated transformation model and the last data pair of the training data of a transformation model generated at a previous time, the processor is further configured to transform second analyte concentrations in the missing interval (Diab | Paragraphs 0197, 0200, 0202, 0319, 0322; [Examiner’s note, the sensor system 100 works in conjunction with the signal processing system 3305 and timing processor system 1800, as shown in Claim 3. The Raman, absorbance, and OCT utilize interpolation with the data collected from those measurement. One skilled in the art can determine interpolation is a method used to estimate unknown values between known data. That known data can be times prior to or after the time at which the first analyte concentration is estimated.]) based on at least one of the two transformation models (Diab | Paragraph 0097, the patient monitor 102 can derive or use one or more relationships (for instance, a set of linear equations) from two or more of the determined parameters).
Diab is silent on explicitly teaching an antioxidant component/concentration; Jang teaches an optical sensor used to estimate an antioxidant component/concentration (Jang | Paragraphs 0007, 0055; [Examiner’s note, one skilled in the art can determine if an antioxidant value is determined from the optical sensor, then a component/concentration is determined.]). Diab teaches of an analyte concentration and Jang teaches an optical sensor used to estimate an antioxidant component/concentration. One having an ordinary skill in the art the time the invention was filed would have found it obvious to modify the apparatus of Diab to incorporate the teachings of determining an antioxidant component/concentration because the level of antioxidant component/concentration correlates to the prevention of oxygen toxicity within the user (Jang | Paragraph 0005).
Regarding claim 11, Diab in view of Jang teaches the apparatus of claim 10, wherein the processor is further configured to: obtain, as the reference index, an arithmetic mean or a weighted average of values obtained by transforming the second analyte concentrations in the missing interval based on each of the two transformation models (Diab | Equation 5; Paragraph 0143).
Diab is silent on explicitly teaching an antioxidant component/concentration; Jang teaches an optical sensor used to estimate an antioxidant component/concentration (Jang | Paragraphs 0007, 0055; [Examiner’s note, one skilled in the art can determine if an antioxidant value is determined from the optical sensor, then a component/concentration is determined.]). Diab teaches of an analyte concentration and Jang teaches an optical sensor used to estimate an antioxidant component/concentration. One having an ordinary skill in the art the time the invention was filed would have found it obvious to modify the apparatus of Diab to incorporate the teachings of determining an antioxidant component/concentration because the level of antioxidant component/concentration correlates to the prevention of oxygen toxicity within the user (Jang | Paragraph 0005).
Regarding claim 12, Diab in view of Jang teaches the apparatus of claim 8, wherein the processor is further configured to transform the second analyte concentrations of the data pairs, included in the training data of the generated transformation model and in the training data of the transformation model generated at the previous time (Diab | Paragraph 0180), based on the two transformation models (Diab | Paragraph 0097, the patient monitor 102 can derive or use one or more relationships (for instance, a set of linear equations) from two or more of the determined parameters).
Diab is silent on explicitly teaching an antioxidant component/concentration; Jang teaches an optical sensor used to estimate an antioxidant component/concentration (Jang | Paragraphs 0007, 0055; [Examiner’s note, one skilled in the art can determine if an antioxidant value is determined from the optical sensor, then a component/concentration is determined.]). Diab teaches of an analyte concentration and Jang teaches an optical sensor used to estimate an antioxidant component/concentration. One having an ordinary skill in the art the time the invention was filed would have found it obvious to modify the apparatus of Diab to incorporate the teachings of determining an antioxidant component/concentration because the level of antioxidant component/concentration correlates to the prevention of oxygen toxicity within the user (Jang | Paragraph 0005).
Regarding claim 13, Diab in view of Jang teaches the apparatus of claim 12, wherein the processor is further configured to: obtain, as the reference index, an arithmetic mean or a weighted average of values obtained by transforming the second analyte concentrations of the data pairs, included in the training data of the generated transformation model and in the training data of the transformation model generated at the previous time, by using the two transformation models (Diab | Equation 5; Paragraph 0143).
Diab is silent on explicitly teaching an antioxidant component/concentration; Jang teaches an optical sensor used to estimate an antioxidant component/concentration (Jang | Paragraphs 0007, 0055; [Examiner’s note, one skilled in the art can determine if an antioxidant value is determined from the optical sensor, then a component/concentration is determined.]). Diab teaches of an analyte concentration and Jang teaches an optical sensor used to estimate an antioxidant component/concentration. One having an ordinary skill in the art the time the invention was filed would have found it obvious to modify the apparatus of Diab to incorporate the teachings of determining an antioxidant component/concentration because the level of antioxidant component/concentration correlates to the prevention of oxygen toxicity within the user (Jang | Paragraph 0005).
Regarding Claim 14, Diab discloses a method of estimating an antioxidant component (Abstract), the method comprising:
estimating first antioxidant concentrations at a first body part (tissue site – element 206A; Figure 2; Paragraph 0120);
extracting, as training data, data pairs of first analyte concentrations estimated at the first body part and second analyte concentrations estimated at a second body part from a storage based on predetermined learning conditions (instrument manager – element 210; Figure 2; Paragraph 0119-0120; 1308 of Figure 12A; Paragraph 0175; [Examiner’s note, the learning condition is the skin geometry information. The data extraction of a data pair are the data collected by the DSP 212A, DSP 212B, and DSP 212C from corresponding tissue sites 206A, 206B, and 206C.]);
generating a transformation model configured to transform the second analyte concentrations into a reference index based on the training data (Equation 1; Paragraph 0176, based on the data received at block 1304 from the one or more second noninvasive sensors, the processor can determine an absorbance corresponding to a tissue site interrogated by the one or more second noninvasive sensors. Using one or more relationships derived from Beer's law (Equation 1), the concentration, c, of one or more analytes can be determined using the absorbance, A, determined from the pulse oximetry sensor data, and the path length, b, determined from the tissue geometry data; Paragraph 0201; [Examiner’s note, the transformation model is Beer’s Law, which is a linear regression model.]); and
by a display (user interface – element 222), displaying the first analyte concentrations, the second analyte concentrations, and the reference index (Paragraph 0101, 0121, 0181),
wherein the generating the transformation model further comprises determining parameters by training a basic transformation model by using the training data and generating the transformation model by using the determined parameters (Equation 1; Paragraph 0176),
wherein the transformation model is defined as a linear function(Equation 1; Paragraph 0176; [Examiner’s note, the transformation model is Beer’s Law, which is a linear regression.], anon-linear function or a neural network-based model [Examiner’s note, the claim comprises multiple limitations; however, only one of the alternatives needs to be supported by the prior art.],
wherein extracting data pairs further comprises extracting one or more data pairs of the first analyte concentrations and the second analyte concentrations, corresponding to estimation times of the respective first analyte concentrations, as the training data from the storage (3305 of Figure 13; Paragraphs 0190, 0191, 0197, 0201, 0202 and 0244-0250; [Examiner’s note, The signal processing of 3305 harmonizes the data collected from the sensor system 100; harmonized physiological measures include Raman measurements (3307 of Figure 13), absorbance measurements (3309 of Figure 13), and OCT measurements (3311 of Figure 13). Additionally, the timing processor system 1800 works along with the sensor system 100 to synchronize the data from the various measurements. One skilled in the art can determine extracted data pairs corresponding to the first analyte concentration because the sensor system collects data from multiple tissue sites.]),
wherein extracting the data pairs further comprises, based on a time point at which a change in absorbance of an optical signal measured at the second body part (Figure 25A; Paragraph 0294; [Examiner’s note, the change in absorbance is measured by Beer’s Law Equation (equation 1), which is rewritten as
∆
A
=
ε
b
(
C
2
-
C
1
), where
C
1
and
C
2
are the first and second antioxidant concentrations.]) is greater than or equal to a threshold value (Paragraph 0287-0289, 0291; [Examiner’s note, the threshold is the temperature at different tissue depths to collect the desired physiological data. For example, different tissue sites, with varying tissue depths, may require differing temperatures by a laser to be reached in order to collect sufficient and accurate data.]), extracting the data pairs of the first analyte concentrations and the second analyte concentrations from the storage at a time interval after the time point (Figure 25A; Paragraph 0291; [Examiner’s note, data is collected after the baseline period is over.]).
Regarding Claim 16, Diab in view of Jang teaches the method of claim 14, wherein the extracting further comprises extracting data pairs of the first analyte concentrations estimated at the first body part and second analyte concentrations estimated at the second body part from the storage included in a predetermined period (Diab | Paragraph 0135, a subsequent OCT measurement or set of measurements can occur minutes, hours, days, weeks, or some other period of time after the first measurement, and it can be unreasonable to require a patient to wear or interact with the OCT sensor for the duration of that period of time) based on at least one a thickness (Diab | Paragraph 0116, 0300), and a structure of a user's skin (Diab | Paragraph 0115, The patient monitor 200 uses the detected signals obtained from the interference of the reflected sample arm light beams 250 and the reflected reference arm light beams 230 to calculate tissue geometry data, such as a skin geometry of one or more skin layers; Paragraph 0132) and physiological characteristics (Diab | Paragraph 0127).
Diab is silent on explicitly teaching an antioxidant component/concentration; Jang teaches an optical sensor used to estimate an antioxidant component/concentration (Jang | Paragraphs 0007, 0055; [Examiner’s note, one skilled in the art can determine if an antioxidant value is determined from the optical sensor, then a component/concentration is determined.]). Diab teaches of an analyte concentration and Jang teaches an optical sensor used to estimate an antioxidant component/concentration. One having an ordinary skill in the art the time the invention was filed would have found it obvious to modify the apparatus of Diab to incorporate the teachings of determining an antioxidant component/concentration because the level of antioxidant component/concentration correlates to the prevention of oxygen toxicity within the user (Jang | Paragraph 0005).
Regarding Claim 18, Diab in view of Jang teaches method of claim 14, wherein the extracting further comprises extracting the data pairs of the training data until a number of data pairs is greater than or equal to a predetermined number (Diab | 2508 of Figure 25A; Paragraph 0296; [Examiner’s note, the purpose of heating and cooling on a tissue site is based on the tissue depth for collecting the desired physiological parameter. One skilled in the art can determine that when a specific temperature is reached during the cooling period, based upon the tissue depth, the accuracy of data collected is not reliable, and will result in the end of the data collection from the various sensors at its corresponding tissue sites. Therefore the predetermined number is the cooling temperature.]).
Regarding Claim 19, Diab in view of Jang teaches method of claim 14, further comprising, based on generating the transformation model, performing updating by transforming the second analyte concentrations (Diab | Paragraph 0104) stored in the storage, into a reference index (Diab | Paragraph 0124; [Examiner’s note, the reference index is the memory device. According to ScienceDirect’s article on Indexing Method, the term "index" or "indexing" generally refers to methods of organizing and structuring data to facilitate efficient access and retrieval, especially in scenarios involving large datasets and tasks like similarity search or information retrieval]) based on the generated transformation model (Diab | Paragraph 0097, the patient monitor 102 can derive or use one or more relationships (for instance, a set of linear equations) from two or more of the determined parameters).
Diab is silent on explicitly teaching an antioxidant component/concentration; Jang teaches an optical sensor used to estimate an antioxidant component/concentration (Jang | Paragraphs 0007, 0055; [Examiner’s note, one skilled in the art can determine if an antioxidant value is determined from the optical sensor, then a component/concentration is determined.]). Diab teaches of an analyte concentration and Jang teaches an optical sensor used to estimate an antioxidant component/concentration. One having an ordinary skill in the art the time the invention was filed would have found it obvious to modify the apparatus of Diab to incorporate the teachings of determining an antioxidant component/concentration because the level of antioxidant component/concentration correlates to the prevention of oxygen toxicity within the user (Jang | Paragraph 0005).
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SRISTI DIVINA GOMES whose telephone number is (571)272-1356. The examiner can normally be reached Monday-Thursday: 7:30-4:30 & Friday 7:30-3:30.
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, Robert Chen can be reached at 571-272-3672. 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.
/SRISTI DIVINA GOMES/Examiner, Art Unit 3791 /TSE W CHEN/Supervisory Patent Examiner, Art Unit 3791
Prosecution Insights