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 .
Responses to Amendments and Arguments
The amendments filed 4/14/2026 have been entered. Claims 1-4, 6-11 and 13-14 are amended. Claims 1-14 remain pending in the application.
Applicant's argument and amendments filed 4/14/2026 with respect to
the rejection of claims 1-14 directed to a judicial exception under 35 U.S.C. 101 have been fully considered but are not persuasive.
On pages 10-11 of Applicant’s response, Applicant alleges that the amended independent claim 1 recites specific features of a method that cannot be performed in the human mind. … the amended independent claim 1 recites, obtaining a first type estimated urine volume value by using the one or more first feature data and a pre-trained urine volume determination model …. Sound data, as defined in the specification, cannot be recorded in the human mind. … A human mind cannot filter sound data to remove noise. Further, urine volume cannot be measured within a human mind. … Therefore, the amended independent claim 1 is not directed to an abstract idea. … Even if the claims were viewed as involving mental processes or mathematical concepts, the amendments make clear that the recited elements integrate any such activity into a practical application through technically constrained architecture and operations, satisfying multiple integration considerations.
The Examiner respectfully disagrees.
Note that the features related to the obtaining steps in claim 1 may encompass manually calculating or inferring the first and second type estimated urine volume determination values and the estimated urine flow rate determination value based on the collected data, using mathematical algorithm/model (i.e., the pre-trained urine volume determination model and the pre-trained urine flow rate determination model), where the features data and training data may be obtained by data processing itself performed by a generic computer functions of a generic computer component.
Note that the features related to the generating and refining steps in claim 1 may encompass manually calculating or inferring the refined urine flow rate value based on the result of the mathematical calculations and the collected data (see at least pages 14 and 27-30).
The claims do not present tangible or physical elements/components and/or integration of improvements to be indicative of specific features/structure/acts how and or with what to obtain first to third features data by using first to third sound data, and obtain/calculate the first type estimated urine volume value, the estimated urine flow rate value and the refined urine flow rate value. (See MPEP 2106.04(d)). The claims do not present a technical solution to a technical problem by providing an improvement to the functioning of computer, or to any other technology or technical field related to obtain first to third features data by using first to third sound data, and obtain/calculate the first type estimated urine volume value, the estimated urine flow rate value and the refined urine flow rate value. (See MPEP 2106.04(d)). (See the detailed response presented below).
Applicant's argument and amendments filed 4/14/2026 with respect to
the rejection of claims 1-14 directed to a judicial exception under 35 U.S.C. 103 have been fully considered and are persuasive. Therefore, the rejection under 35 U.S.C. 103 is withdrawn. Examiner notes that no prior art teaches the claimed feature related to calculating the ration between the second type estimated urine volume value derived from the estimated urine flow rate value and the first type estimated urine volume value derived from the pre-trained urine volume determination model, and refining the estimated urine flow rate value by reflecting the calculated ratio (i.e., “generating a refined urine flow rate value by refining the estimated urine flow rate value using the first type estimated urine volume value and the second type estimated urine volume value; wherein the refining the estimated urine flow rate value comprises: calculating a ratio between the second type estimated urine volume value derived from the estimated urine flow rate value and the first type estimated urine volume value derived from the pre-trained urine volume determination model, and refining the estimated urine flow rate value by reflecting the calculated ratio to the estimated urine flow rate value”).
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.
The current 35 USC 101 analysis is based on the current guidance (Federal Register vol. 79, No. 241. pp. 74618-74633). The analysis follows several steps. Step 1 determines whether the claim belongs to a valid statutory class. Step 2A prong 1 identifies whether an abstract idea is claimed. Step 2A prong 2 determines whether any abstract idea is integrated into a practical application. If the abstract idea is integrated into a practical application the claim is patent eligible under 35 USC 101. Last, step 2B determines whether the claims contain something significantly more than the abstract idea. In most cases the existence of a practical application predicates the existence of an additional element that is significantly more.
The 35 USC 101 analysis between each element of claims and its combination is presented in the table below
Claim number and elements
Judicial exception (Step 2A Prong one)
Practical application (Step 2A Prong two)/ Significantly more (Step 2B)
Claim 1
Step 1: Yes, statutory class
Step 2A Prong two: No / Step 2B: No
A method of obtaining urination information, comprising:
obtaining one or more first feature data by using first sound data, wherein the first sound data reflect a sound of a first urination process;
Step2A Prong one: Yes
abstract idea
mathematical concept or mental process
“obtaining one or more first feature data ~ ” is a math process or data processing itself to collect feature data related to sound data.
obtaining a first type estimated urine volume value by using the one or more first feature data and a pre-trained urine volume determination model, wherein the pre- trained urine volume determination model is trained with a urine volume training data set, wherein the urine volume training data set comprises one or more second feature data labeled with a measured urine volume, wherein the one or more second feature data are generated based on second sound data recorded during a second urination process and the measured urine volume corresponding to the second urination process;
abstract idea
mathematical concept or mental process
“obtaining a first type estimated urine volume value ~” is a math or mental process. (pages 27- 32).
The pre-trained urine volume determination model is indicative of a mathematical relationship/concept, which is related to data processing itself or mathematical algorithm.
obtaining an estimated urine flow rate value by using the one or more first feature data and a pre-trained urine flow rate determination model, wherein the pre-trained urine flow rate determination model is trained with a urine flow rate training data set, wherein the urine flow rate training data set comprises one or more third feature data labeled with a measured urine flow rate, wherein the one or more third feature data is generated based on third sound data recorded during a third urination process and the measured urine flow rate corresponding to the third urination process;
abstract idea
mathematical concept or mental process
“obtaining an estimated urine flow rate determination value ~” is a math process and/or data processing. (pages 17-18)
The pre-trained urine flow rate determination model is indicative of a mathematical relationship/concept, which is related to data processing itself or mathematical algorithm.
obtaining a second type estimated urine volume value by using the estimated urine flow rate value; and
abstract idea
mathematical concept
“obtaining a second type estimated urine volume value ~” is a math or mental process. (pages 27- 32).
generating a refined urine flow rate value by refining the estimated urine flow rate value using the first type estimated urine volume value and the second type estimated urine volume value;
abstract idea
mathematical concept
“generating a refined urine flow rate value …” is a math or mental process. (pages 14, 27-30).
wherein the refining the estimated urine flow rate value comprises:
calculating a ratio between the second type estimated urine volume value derived from the estimated urine flow rate value and the first type estimated urine volume value derived from the pre-trained urine volume determination model, and
abstract idea
mathematical concept
“calculating a ratio between …” is a math or mental process. (pages 14, 27-30).
refining the estimated urine flow rate value by reflecting the calculated ratio to the estimated urine flow rate value.
abstract idea
mathematical concept
“refining the estimated urine flow rate value …” is a math or mental process. (pages 14, 27-30).
Claims 1-14 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. Claims 1-14 are directed to an abstract idea. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception as addressed below and presented in the above table.
Step 2A: Prong One
Regarding Claim 1, the limitations recited in Claim 1, as drafted, are processes that, under its broadest reasonable interpretation, cover performance of the limitation in the mathematical calculations and/or the mind, as presented in the above table. Nothing in the claim elements precludes the step from practically being performed in the mind and/or the mathematical calculations. For example, “obtaining one or more first feature data by using first sound data, wherein the first sound data reflect a sound of a urination process”, “obtaining a first type estimated urine volume value by using the one or more first feature data and a pre-trained urine volume determination model, wherein the pre- trained urine volume determination model is trained with a urine volume training data set, wherein the urine volume training data set comprises one or more second feature data labeled with a measured urine volume, wherein the one or more second feature data are generated based on second sound data recorded during a second urination process and the measured urine volume corresponding to the second urination process” and “obtaining an estimated urine flow rate value by using the one or more first feature data and a pre-trained urine flow rate determination model, wherein the pre-trained urine flow rate determination model is trained with a urine flow rate training data set, wherein the urine flow rate training data set comprises one or more third feature data labeled with a measured urine flow rate, wherein the one or more third feature data is generated based on third sound data recorded during a third urination process and the measured urine flow rate corresponding to the third urination process” in the context of this claim may encompass manually calculating or inferring the first type estimated urine volume determination value and the estimated urine flow rate determination value based on the collected data, where the features data and training data may be obtained by data processing itself performed by a generic computer functions of a generic computer component. (See at least pages 17-18 and 27-32). (MPEP 2106.04(a)(2)). The pre-trained urine volume determination model and the pre-trained urine flow rate determination model are indicative of a mathematical relationship/concept, which may be executed by a computer program to perform data processing itself or mathematical algorithm. For example, “obtaining a second type estimated urine volume value by using the estimated urine flow rate value” may encompass manually calculating or inferring the second type estimated urine volume value based on the collected data (i.e., the estimated urine flow rate value) (see at least pages 14 and 27-30). For example, “generating a refined urine flow rate value by refining the estimated urine flow rate value using the first type estimated urine volume value and the second type estimated urine volume value” in the context of this claim may encompass manually calculating or inferring the refined urine flow rate value based on the result of the mathematical calculations and the collected data (see at least pages 14 and 27-30). (MPEP 2106.04(a)(2)). Similarly, “wherein the refining the estimated urine flow rate value comprises: calculating a ratio between the second type estimated urine volume value derived from the estimated urine flow rate value and the first type estimated urine volume value derived from the pre-trained urine volume determination model, and refining the estimated urine flow rate value by reflecting the calculated ratio to the estimated urine flow rate value” in the context of this claim may encompass manually calculating or inferring the ratio between the second type estimated urine volume value and the first type estimated urine volume value, and the estimated urine flow rate value, based on the result of the mathematical calculations and the collected data (see at least pages 14 and 27-30). (MPEP 2106.04(a)(2)).
Step 2A: Prong Two
This judicial exception is abstract ideal itself and not integrated into a practical application. In particular, the specification details use of a computer processor to perform mathematical calculations or mental processes of “obtaining one or more first feature data by using first sound data, wherein the first sound data reflect a sound of a urination process”, “obtaining a first type estimated urine volume value by using the one or more first feature data and a pre-trained urine volume determination model, wherein the pre- trained urine volume determination model is trained with a urine volume training data set, wherein the urine volume training data set comprises one or more second feature data labeled with a measured urine volume, wherein the one or more second feature data are generated based on second sound data recorded during a second urination process and the measured urine volume corresponding to the second urination process” and “obtaining an estimated urine flow rate value by using the one or more first feature data and a pre-trained urine flow rate determination model, wherein the pre-trained urine flow rate determination model is trained with a urine flow rate training data set, wherein the urine flow rate training data set comprises one or more third feature data labeled with a measured urine flow rate, wherein the one or more third feature data is generated based on third sound data recorded during a third urination process and the measured urine flow rate corresponding to the third urination process”, “obtaining a second type estimated urine volume value by using the estimated urine flow rate value”, “generating a refined urine flow rate value by refining the estimated urine flow rate value using the first type estimated urine volume value and the second type estimated urine volume value”, “wherein the refining the estimated urine flow rate value comprises: calculating a ratio between the second type estimated urine volume value derived from the estimated urine flow rate value and the first type estimated urine volume value derived from the pre-trained urine volume determination model, and refining the estimated urine flow rate value by reflecting the calculated ratio to the estimated urine flow rate value”. Claim 1 does not present tangible or physical elements/components and/or integration of improvements to be indicative of specific features/structure/acts how and or with what to obtain first to third features data by using first to third sound data, and obtain/calculate the first type estimated urine volume value, the estimated urine flow rate value and the refined urine flow rate value. (See MPEP 2106.04(d)). Claim 1 does not present a technical solution to a technical problem by providing an improvement to the functioning of computer, or to any other technology or technical field related to obtain first to third features data by using first to third sound data, and obtain/calculate the first type estimated urine volume value, the estimated urine flow rate value and the refined urine flow rate value. (See MPEP 2106.04(d)). Therefore, there is no showing of integration into a practical application such as an improvement to the functioning of a computer, or to any other technology or technical field, or use of a particular machine.
Step 2B:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above, with respect to integration of the abstract idea into a practical application, using a computer system to perform “obtaining one or more first feature data by using first sound data, wherein the first sound data reflect a sound of a urination process”, “obtaining a first type estimated urine volume value by using the one or more first feature data and a pre-trained urine volume determination model, wherein the pre- trained urine volume determination model is trained with a urine volume training data set, wherein the urine volume training data set comprises one or more second feature data labeled with a measured urine volume, wherein the one or more second feature data are generated based on second sound data recorded during a second urination process and the measured urine volume corresponding to the second urination process” and “obtaining an estimated urine flow rate value by using the one or more first feature data and a pre-trained urine flow rate determination model, wherein the pre-trained urine flow rate determination model is trained with a urine flow rate training data set, wherein the urine flow rate training data set comprises one or more third feature data labeled with a measured urine flow rate, wherein the one or more third feature data is generated based on third sound data recorded during a third urination process and the measured urine flow rate corresponding to the third urination process”, “obtaining a second type estimated urine volume value by using the estimated urine flow rate value”, “generating a refined urine flow rate value by refining the estimated urine flow rate value using the first type estimated urine volume value and the second type estimated urine volume value”, “wherein the refining the estimated urine flow rate value comprises: calculating a ratio between the second type estimated urine volume value derived from the estimated urine flow rate value and the first type estimated urine volume value derived from the pre-trained urine volume determination model, and refining the estimated urine flow rate value by reflecting the calculated ratio to the estimated urine flow rate value” amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept cannot provide statutory eligibility. Claim 1 is not patent eligible.
Regarding Claims 2-7 and 12, the limitations are further directed to an abstract idea, as described in claim 1. The limitations of “obtaining a urination presence/absence determination value ... obtaining one or more adjusted first feature data … obtaining the urine volume determination value …” in Claim 3 may encompass manually calculating or inferring the urination presence/absence determination value and the adjusted first feature data using a mathematical model (the urination presence/absence determination model and the urine volume determination model). (MPEP 2106.04(a)(2)).
The limitations of “obtaining a urination presence/absence classification value … obtaining an adjusted urine flow rate determination value …” in Claim 4 may encompass manually calculating or inferring the urination presence/absence determination value and the adjusted first feature data using a mathematical model. (MPEP 2106.04(a)(2)).
The limitations of “obtaining a plurality of segmented urine volume values … obtaining the urine volume determination value…” in Claim 6 may encompass manually calculating or inferring the segmented urine volume determination value and the urine volume determination value using a mathematical model. (MPEP 2106.04(a)(2)).
Regarding Claim 8, it is a method type claim having similar limitations as of claim 1 above. Therefore, it is rejected under the same rationale as of claim 1 above.
Regarding Claims 9-11, the limitations are further directed to an abstract idea, as described in claim 1. For the reasons described above with respect to Claims 1-7, the judicial exceptions are not meaningfully integrated into a practical application, or amount to significantly more than the abstract idea.
Regarding Claim 13, it is a system type claim having similar limitations as of claim 1 above. Therefore, it is rejected under the same rationale as of claim 1 above. The additional elements of the memory and the processor are merely recited at a high-level of generality to perform a generic computer function. Mere nominal recitation of a generic computer system or component does not take the claim out of the mathematical concepts and the mental process grouping. Thus, the claim recites an abstract idea.
Regarding Claim 14, it is a system type claim having similar limitations as of claim 8 above. Therefore, it is rejected under the same rationale as of claims 1 and 8 above. The additional elements of the memory and the processor are merely recited at a high-level of generality to perform a generic computer function. Mere nominal recitation of a generic computer system or component does not take the claim out of the mathematical concepts and the mental process grouping. Thus, the claim recites an abstract idea.
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 BYUNG RO LEE whose telephone number is (571)272-3707. The examiner can normally be reached on Monday-Friday 8:30am-4:00pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Lee Rodak can be reached on (571) 270-5628. The fax phone number for the organization where this application or proceeding is assigned is 571-273-2555.
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/BYUNG RO LEE/Examiner, Art Unit 2858
/LEE E RODAK/Supervisory Patent Examiner, Art Unit 2858
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