DETAILED ACTION
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 on 17 November 2025 has been entered.
Status
This Office Action is in response to the communication filed on 17 November 2025. Claims 1-9 have been canceled currently or previously, claims 10, 12-13, and 15-19 have been amended, and claims 20 and 22-27 have been added; therefore, claims 10-20 and 22-27 are pending and presented for examination.
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 Amendment
A summary of the Examiner’s Response to Applicant’s amendment:
Applicant’s amendment misnumbers the submitted claims – see the Claim Objections below regarding how this is being handled currently and for future submissions.
Applicant’s amendment overcomes the rejection(s) under 35 USC § 112; therefore, the Examiner withdraws the rejection(s).
Applicant’s amendment does not overcome the rejection(s) under 35 USC § 101; therefore, the Examiner maintains the rejection(s) while updating phrasing in keeping with current examination guidelines.
Applicant’s amendment overcomes the rejection(s) under 35 USC §§ 102 and/or 103; therefore, the Examiner places new grounds of rejection.
Applicant’s arguments are found to be not persuasive; please see the Response to Arguments below.
Claim Objections
The numbering of claims is not in accordance with 37 CFR 1.126 which requires the original numbering of the claims to be preserved throughout the prosecution. When claims are canceled, the remaining claims must not be renumbered. When new claims are presented, they must be numbered consecutively beginning with the number next following the highest numbered claims previously presented (whether entered or not).
Since 37 CFR 1.126 indicates the claims will be renumbered, if needed, at the time of allowance, the Examiner is not renumbering the claims currently. Since significant work was performed and/or in progress when the Examiner noticed the error and in an effort to promote prosecution speed, the Examiner is electing to not send a Notice of Non-compliant Amendment.
Since it appears that a claim 21 was intended to be submitted but was deleted from, or left off, the submission and there is no dependency to or from what would be (or would have been) claim 21, the Examiner is considering claim 21 to be canceled.
For clarity of the record, any future claim listing should therefore include claim 21 and be labeled as “canceled”. Further, any additional claims added in the future should be begin numbering with claim 28.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
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.
The following is a quotation of 35 U.S.C. 112(d):
(d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
The following is a quotation of pre-AIA 35 U.S.C. 112, fourth paragraph:
Subject to the following paragraph [i.e., the fifth paragraph of pre-AIA 35 U.S.C. 112], a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
Claims 10-20 and 22-27 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Independent claims 10 and 27 recite “a filtering process on the received pulse wave data to remove noise components outside a frequency band suitable for extracting pulse wave data so as to obtain velocity pulse wave data” (citing claim 1, claim 27 phrased similarly). Although filtering, such as using a band pass filter, for noise is discussed at Applicant ¶¶ 0037, 0059, and 0102 (as submitted, 0051, 0073, and 0116 as published) -which apparently would include removing noise components, the Examiner has searched for and does not find an indication that the noise would be “outside a frequency band suitable for extracting pulse wave data”. There is no apparent indication of finding or defining a frequency band that is “suitable” for extracting pulse wave data.
Claims 11-20 and 22-26 depend from claim 10, but do not resolve the above issues and inherit the deficiencies of the parent claim(s); therefore claims 11-20 and 22-26 are also lacking written support.
Claims 10-20 and 22-27 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.
Independent claims 10 and 27 recite “a filtering process on the received pulse wave data to remove noise components outside a frequency band suitable for extracting pulse wave data so as to obtain velocity pulse wave data” (citing claim 1, claim 27 phrased similarly). Although filtering, such as using a band pass filter, for noise is discussed at Applicant ¶¶ 0037, 0059, and 0102 (as submitted, 0051, 0073, and 0116 as published), the Examiner has looked to the light of the specification for an indication of what may be considered “a frequency band suitable for extracting pulse wave data” such that components outside that band can or could be removed. It would appear that the term “suitable” is a subjective term – what one person may consider suitable frequencies for pulse wave data that they are interested in would readily vary or be different than the frequencies that another person may be interested in for pulse wave data they (i.e., the “another person”) are interested in. The specification offers no indication of a definition regarding what is “suitable” – the specification merely says that “depending on the usage or the generation condition of the sensor data” (at Applicant ¶ 0037 as submitted, 0051 as published) data corresponding to an acceleration or velocity pulse wave can be obtained.
Therefore, the term “suitable” in claims 10 and 27 is a relative term which renders the claim indefinite since the term “suitable” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention.
Claims 11-20 and 22-26 depend from claim 10, but do not resolve the above issues and inherit the deficiencies of the parent claim(s); therefore claims 11-20 and 22-26 are also indefinite.
Claim 26 is rejected under 35 U.S.C. 112(d) or pre-AIA 35 U.S.C. 112, 4th paragraph, as being of improper dependent form for failing to further limit the subject matter of the claim upon which it depends, or for failing to include all the limitations of the claim upon which it depends.
Claim 26 recites “The biometric information computing system of claim 10, wherein the instructions, when executed, cause the system to perform operations comprising preprocessing algorithms including filtering, differentiation, pulse cycle segmentation, and normalization of pulse wave data, and to generate the evaluation result according to a trained model, the operations further comprising operations (a)-(f)”. However, the filtering, differentiation, pulse cycle segmentation, normalization, and generating the evaluation result are already apparently required at operations (a)-(f) of parent claim 10. Therefore, claim 26 does not appear to further limit the subject matter of the claim upon which it depends.
Applicant may cancel the claim(s), amend the claim(s) to place the claim(s) in proper dependent form, rewrite the claim(s) in independent form, or present a sufficient showing that the dependent claim(s) complies with the statutory requirements.
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 10-20 and 22-27 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Please see the following Subject Matter Eligibility (“SME”) analysis:
For analysis under SME Step 1, the claims herein are directed to systems, which would be classified under one of the listed statutory classifications (SME Step 1=Yes).
For analysis under revised SME Step 2A, Prong 1, independent claim 10 recites a sensor configured to collect pulse wave data from the user; a database, stored on a non-transitory storage medium that stores classification information generated using a plurality of training data, the training data being a pair of input data based on a preliminarily obtained training pulse wave and reference data including a blood lactate level associated with the input data; one or more processors coupled to a non-transitory storage medium storing instructions that, when executed, cause the system to perform operations comprising: (a) receiving the pulse wave data from the sensor; (b) performing a filtering process on the received pulse wave data to remove noise components outside a frequency band suitable for extracting pulse wave data so as to obtain velocity pulse wave data; (c) performing differentiation or equivalent signal processing of the velocity pulse wave data so as to obtain acceleration pulse wave data; (d) dividing one or both of the velocity pulse wave data and the acceleration pulse wave data into one or more pulse cycles; (e) normalizing amplitude values within each pulse cycle of the one or more pulse cycles to generate evaluation data; and (f) generating an evaluation result including the blood lactate level for the evaluation data, wherein the evaluation result is generated by referring to the classification information stored in the database and applying the classification information to generate the blood lactate level based on the evaluation data and the classification information; and an output device configured to display the evaluation result.
Independent claim 27 recites a biometric information computing system for generating a blood lactate level of a user, comprising: a biological signal sensor configured to obtain pulse wave or related physiological signal data of a user, and configured to perform filtering to remove components unrelated to physiological pulse signals; a database, stored on a non-transitory storage medium that stores a trained regression or calibration model generated from a plurality of training pulse waves and corresponding measured blood lactate levels obtained under consistent sensor and preprocessing conditions; one or more processors coupled to a non-transitory storage medium storing instructions that, when executed, cause the system to perform operations comprising preprocessing algorithms including filtering, differentiation, pulse cycle segmentation, and normalization of pulse wave data, and to generate an evaluation result according to the trained model, the operations further comprising: (a) obtaining sensor data from the sensor; (b) performing a filtering process on the obtained sensor data to remove noise components outside a frequency band suitable for extracting pulse wave data; (c) performing differentiation or equivalent signal processing to obtain waveform features; (d) dividing the signal into pulse cycles; (e) normalizing amplitude values within each pulse cycle to generate evaluation data; and (f) applying the trained model stored in the database to the evaluation data to generate a blood lactate level representing a quantitative correlation between waveform features and measured blood lactate concentration; and an output device configured to display the generated blood lactate level together with an indication of measurement reliability based on predetermined calculation accuracy or error range.
The Examiner notes that a database may reasonably encompass a hard-copy (e.g., printed, or manual) database and is therefore included in the abstract idea.
The dependent claims (claims 11-20 and 22-26) appear to be encompassed by the abstract idea of the independent claims since they merely indicate the stored classification information being a PLS regression model (claim 11), obtaining additional information and generating a result evaluating athletic ability (claim 12), obtaining additional data and generating additional information based on the additional data (claims 13 and 15-17) where the additional data is a stress level, a pulse rate, a respiratory rate, a blood glucose level, a blood pressure, a feature of blood carbon dioxide, or a quantity of exercise (claim 14), obtaining data corresponding to a velocity and acceleration pulse wave (claim 18), displaying the result (claim 19), outputting normalized acceleration and velocity pulse wave data, selecting one piece of classification information, and applying the selected classification information to generate the blood lactate level (at claim 20), the type of sensor used (claim 22, admitted in the specification as being “publicly known” – see below), the model being a trained regression or calibration model (claim 23), that the model used represents correlation of waveform features and blood lactate concentration (claim 24), displaying the lactate level with an indication of measurement reliability (claim 25), and/or the operations comprising the operations at steps (a)-(f) at the parent claim (claim 26).
The underlined portions of the claims are an indication of elements additional to the abstract idea (to be considered below).
The claim elements may be summarized as the idea of obtaining and storing model data to report an estimate of blood lactate level; however, the Examiner notes that although this summary of the claims is provided, the analysis regarding subject matter eligibility considers the entirety of the claim elements, both individually and as a whole (or ordered combination). This idea is within the mental processes grouping of subject matter (e.g., concepts performed in the human mind such as observation, evaluation, judgment, and/or opinion) since based on the observation and evaluation of pulse waves and blood lactate levels to generate an evaluation result of lactate level – a judgment or opinion regarding estimated lactate levels.
The Examiner also notes that mathematical concepts (e.g., relationships, formulas, equations, and/or calculations) are, or may be, implicated based at least on the normalizing (when considered as requiring a calculation), that the classification information may be based on model use indicated by some dependent claims as comprising regression (see at least claims 11 and 23), and quantitative correlation (see at least claim 24). The Examiner notes that the normalizing may apparently just be a relative estimation or approximation (rather than a specific or granular calculation of relative amplitude) and therefore could apparently also be considered as within the mental processes grouping. The Examiner further notes indicating mathematical concepts not as the claim being fully directed to the mathematical concepts, but potentially using some mathematical concepts as an additional grouping, where MPEP § 2106.04(II)(A)(2) indicates that
Because a judicial exception is not eligible subject matter, Bilski, 561 U.S. at 601, 95 USPQ2d at 1005-06 (quoting Chakrabarty, 447 U.S. at 309, 206 USPQ at 197 (1980)), if there are no additional claim elements besides the judicial exception, or if the additional claim elements merely recite another judicial exception, that is insufficient to integrate the judicial exception into a practical application. See, e.g., RecogniCorp, LLC v. Nintendo Co., 855 F.3d 1322, 1327, 122 USPQ2d 1377 (Fed. Cir. 2017) ("Adding one abstract idea (math) to another abstract idea (encoding and decoding) does not render the claim non-abstract"); Genetic Techs. Ltd. v. Merial LLC, 818 F.3d 1369, 1376, 118 USPQ2d 1541, 1546 (Fed. Cir. 2016) (eligibility "cannot be furnished by the unpatentable law of nature (or natural phenomenon or abstract idea) itself.").
Therefore, the claims are found to be directed to an abstract idea.
For analysis under revised SME Step 2A, Prong 2, the above judicial exception is not integrated into a practical application because the additional elements do not impose a meaningful limit on the judicial exception when evaluated individually and as a combination. The additional elements are a sensor configured to collect data; a database stored on a non-transitory storage medium that stores information; one or more processors coupled to a non-transitory storage medium storing instructions that, when executed, cause the system to perform operations comprising: receiving the pulse wave data from the sensor; performing a filtering process on the received pulse wave data to remove noise components outside a frequency band suitable for extracting pulse wave data so as to obtain velocity pulse wave data, and an output device configured to display (at claim 10), the one or more processors further execute instructions to perform activities (at various dependent claims), and a computing system, a biological signal sensor, a database stored on a non-transitory storage medium, receiving from the sensor; one or more processors coupled to a non-transitory storage medium storing instructions that, when executed, cause the system to perform operations; and an output device configured to display (at claim 27). These additional elements do not reflect an improvement in the functioning of a computer or an improvement to other technology or technical field, effect a particular treatment or prophylaxis for a disease or medical condition (there is no medical disease or condition, much less a treatment or prophylaxis for one), implement the judicial exception with, or by using in conjunction with, a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing (there is no transformation/reduction of a physical article), and/or apply or use the judicial exception in some other meaningful way beyond generically linking use of the judicial exception to a particular technological environment.
As noted above, the indication of a second or additional grouping – even if the claim is not directed primarily to that second or additional grouping – is generally regarded as insufficient to integrate the judicial exception into a practical application.
The filtering appears to be normal or standard ECG and/or MRI procedure – see at least Garcia, Langer, Righter, Thornander, Luo, and/or Mynard at the pertinent prior art below – and is therefore, considered to actually be part of, or included in, the receiving the sensor signal.
The claims appear to merely apply the judicial exception, include instructions to implement an abstract idea on a computer, or merely use a computer as a tool to perform the abstract idea. The additional elements appear to merely add insignificant extra-solution activity to the judicial exception and/or generally link the use of the judicial exception to a particular technological environment or field of use.
For analysis under SME Step 2B, the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements, as indicated above, are merely “[a]dding the words ‘apply it’ (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, e.g., a limitation indicating that a particular function such as creating and maintaining electronic records is performed by a computer, as discussed in Alice Corp.” that MPEP § 2106.05(I)(A) indicates to be insignificant activity.
There is no indication the Examiner can find in the record regarding any specialized computer hardware or other “inventive” components, but rather, the claims merely indicate computer components which appear to be generic components and therefore do not satisfy an inventive concept that would constitute “significantly more” with respect to eligibility. Applicant ¶ 0052 (as submitted, 0066 as published) indicates “The biometric information computing device 1 indicates, for example, an electronic device such as a personal computer (PC), a mobile phone, a smartphone, a tablet terminal, and a wearable device” – i.e., a generic or general-purpose computer. Applicant ¶ 0038 (as submitted, 0052 as published) indicates that “The sensor data can be generated with a publicly known sensor”, and at least Applicant ¶ 0076 (as submitted, 0090 as published) similarly indicates the claimed sensor and sensor types are “publicly known”. At least Applicant ¶ 0049 (as submitted, 0063 as published) indicates reference data measurement and oxygen saturation are measured using “a known measuring device” and “a known device”. At least Applicant ¶ 0072 (as submitted, 0087) indicates “The communications network 3 is a publicly known Internet network or the like”. At least Applicant ¶ 0056 (as submitted, 0070 as published) indicates the display as any display, and includes that it may be “a touch panel type”.
The consideration of the filtering with respect to it potentially being well-understood, routine, and/or conventional (WURC) activity, the pertinent prior art below (see at least Garcia, Langer, Righter, Thornander, Luo, and/or Mynard) also indicates that filtering of a pulse signal is WURC activity and therefore not considered to be significantly more than the performing of the abstract idea itself.
The individual elements therefore do not appear to offer any significance beyond the application of the abstract idea itself, and there does not appear to be any additional benefit or significance indicated by the ordered combination, i.e., there does not appear to be any synergy or special import to the claim as a whole other than the application of the idea itself.
The dependent claims, as indicated above, appear encompassed by the abstract idea since they merely limit the idea itself; therefore the dependent claims do not add significantly more than the idea.
Therefore, SME Step 2B=No, any additional elements, whether taken individually or as an ordered whole in combination, do not amount to significantly more than the abstract idea, including analysis of the dependent claims.
Please see the Subject Matter Eligibility (SME) guidance and instruction materials at https://www.uspto.gov/patent/laws-and-regulations/examination-policy/subject-matter-eligibility, which includes the latest guidance, memoranda, and update(s) for further information.
NOTICE
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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 of this title, 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.
Claims 10, 12-17, 19-20, 22, and 24-26 are rejected under 35 U.S.C. 103 as being unpatentable over Sasahara (U.S. Patent Application Publication No. 2016/0287938) in view of Ferber et al. (U.S. Patent Application Publication No. 2018/0085040, hereinafter Ferber) and in further view of Dietrich et al. (U.S. Patent Application Publication No. 2020/0315509, hereinafter Dietrich) .
Claim 10: Sasahara discloses a biometric information computing system for generating a blood lactate level of a user, comprising:
a sensor configured to collect pulse wave data from the user (see Sasahara at least at, e.g., ¶ 0042, “The pulse-wave-information acquirer 110 may acquire sensor information itself of the pulse wave sensor 210”, 0043, “The pulse wave sensor 210 is a sensor for detecting a pulse wave signal. For example, a photoelectric sensor including a light emitter and a light receiver can be used as the pulse wave sensor 210”; citation hereafter by number only);
a database, stored on a non-transitory storage medium that stores classification information generated using a plurality of training data, the training data being a pair of input data based on a preliminarily obtained training pulse wave and reference data including a blood lactate level associated with the input data (0041, “As shown in FIG. 1, the exercise-effect determining system 100 according to the first embodiment includes a pulse-wave-information acquirer 110, a body-motion-information acquirer 120, a pulse rate calculator 130, a storage 150 in which a lactate level information data table 250 and the like are stored, a determination mode setter 160, an exercise effect determiner 140, and an informing unit 230”, 0046, “a lactate level information data table 250 in which lactate level information representing a relation between a pulse rate and a blood lactate value of the user acquired in advance is stored”, 0047, “setting of a determination mode corresponding to a purpose of the user when exercise effect determination based on the pulse rate during exercise calculated by the pulse rate calculator 130 and the lactate level information stored in the lactate level information data table 250 is performed” – the stored data constituting training data);
Sasahara, however, does not appear to explicitly disclose that it is one or more processors coupled to a non-transitory storage medium storing instructions that, when executed, cause the system to perform operations comprising: (a) receiving the pulse wave data from the sensor; (b) performing a filtering process on the received pulse wave data to remove noise components outside a frequency band suitable for extracting pulse wave data so as to obtain velocity pulse wave data; (c) performing differentiation or equivalent signal processing of the velocity pulse wave data so as to obtain acceleration pulse wave data; (d) dividing one or both of the velocity pulse wave data and the acceleration pulse wave data into one or more pulse cycles; (e) normalizing amplitude values within each pulse cycle of the one or more pulse cycles to generate evaluation data; and (f) generating an evaluation result including the blood lactate level for the evaluation data, wherein the evaluation result is generated by referring to the classification information stored in the database and applying the classification information to generate the blood lactate level based on the evaluation data and the classification information; and an output device configured to display the evaluation result. Where Sasahara indicates “the exercise-effect determining system 100 according to the first embodiment includes a pulse-wave-information acquirer” (Sasahara at 0041), and “The pulse-wave-information acquirer 110 acquires pulse wave information (a pulse wave signal) detected by a pulse wave sensor 210 functioning as a pulse wave measurer” (Sasahara at 0042), this appears to necessarily be a processor executing instructions that would be stored on a medium (see, e.g., Sasahara at 0044, 0055-0058, and Figs. 1 and 2). However, the recitation may be considered to not be explicit regarding the processor executing instructions on the indicated medium.
Ferber, however, teaches “an … environment 100 utilizing a multispectral blood metrics measurement apparatus 102” (Ferber at 0076), where the “system comprises a processor; and memory storing instructions that, when executed by the processor, cause the processor to: receive a first signal and a second signal” (Ferber at 0035), “the multispectral blood metrics measurement apparatus 200 may measure, but is not limited to, skin conductivity, pulse, oxygen blood levels, blood pressure, blood glucose level, glycemic index, insulin index, Vvo2max, fat body composition, protein body composition, blood nutrient level (e.g., iron), body temperature, blood sodium levels, or naturally-produced chemical compound level (e.g., lactic acid)” (Ferber at 0106), “signals may be provided to a bandpass filter that separates AC components from DC components” (Ferber at 0114 and 0180), “The signals may be raw signals (e.g., as detected by the associated blood pressure measurement apparatus), filtered or pre-processed signals (e.g., to remove noise from the signals), and/or normalized signal values (e.g., between 0-1)” (Ferber at 0222), “the transit time may be measured as (1) the distance between the valleys in the corresponding waves in respective LED-PD systems at the start of the systolic cycle, and/or (2) the distance between the peaks in first derivatives between the two LED-PD systems” (Ferber at 0277) and “The time of occurrence of the systolic peak from the start of the systolic cycle (i.e., systolic peak time) may also be included as a feature. In some embodiments, a ratio between the second derivatives at the bottom and peak of the systolic cycle may be used as a feature” (Ferber at 0280) – the data being assessed according to cycle time indicating that the data is divided. Therefore, the Examiner understands and finds that to filter, differentiate and divide signals and cycles, and normalize evaluation data is applying a known technique to a known device, method, or product ready for improvement to yield predictable results so as to provide clean and comparable data to assess.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine or modify the pulse and blood analysis of Sasahara with the data analysis techniques of Ferber in order to to filter, differentiate and divide signals and cycles, and normalize evaluation data so as to provide clean and comparable data to assess.
The rationale for combining in this manner is that to filter, differentiate and divide signals and cycles, and normalize evaluation data is applying a known technique to a known device, method, or product ready for improvement to yield predictable results so as to provide clean and comparable data to assess as explained above.
Sasahara in view of Ferber, however, does not appear to explicitly disclose to generate and output an evaluation result including the blood lactate level for the evaluation data. Dietrich, though, teaches that “changes in the lactate level are also an indicator of further pathological changes as well as of physiological changes due to stress … [where] the measured data of a heart monitor worn by or connected to the athlete during training are used and, with the aid of numerous data and a neuronal network, an assessment of the lactate concentration in the body is carried out non-invasively via a mathematical model which models the lactate concentration in the body. Similar attempts at objectivising the training load of an athlete by using diagnostic methods from Asiatic medicine are known from EP 0 947 160 A1 and DE 698 33 656 T2. To that end, using a pulse wave diagnosing device which is worn like a wristwatch, the pulse waveform is detected, analysed and linked with numerous other physiological data of the athlete. By means of frequency analysis and filtering of the data, a correlation with physiological states of the athlete known in traditional Far Eastern medicine is made” (Dietrich at 0010). Therefore, the Examiner understands and finds that to display a lactate concentration result is applying a known technique to a known device, method, or product ready for improvement to yield predictable results so as to correlate and provide performance or training data to the user.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine or modify the pulse and blood analysis of Sasahara in view of Ferber with the lactate correlation of Dietrich in order to display a lactate concentration result so as to correlate and provide performance or training data to the user.
The rationale for combining in this manner is that to display a lactate concentration result is applying a known technique to a known device, method, or product ready for improvement to yield predictable results so as to correlate and provide performance or training data to the user as explained above.
Claim 12: Sasahara in view of Ferber in further view of Dietrich discloses the biometric information computing system according to claim 10, wherein the one or more processors further execute instructions to: obtain additional information indicating a feature of the user and generates a comprehensive evaluation result evaluating athletic ability of the user based on the evaluation result and the additional information (Sasahara at 0048, “In the determination mode set by the user with the determination mode setter 160, the exercise effect determiner 140 compares the pulse rate during exercise calculated by the pulse rate calculator 130 and the lactate level information stored in the lactate level information data table 250 to thereby determine an effect degree of the predetermined exercise performed by the user contributing to the physical strength of the user and obtain an exercise-effect determination result”).
Claim 13: Sasahara in view of Ferber in further view of Dietrich discloses the biometric information computing system according to claim 12, wherein the one or more processors further execute instructions to: obtain additional data indicating a feature different from the evaluation data, based on the pulse wave, and generate the additional information based on the additional data (Sasahara at 0079, “In the exercise-effect determining method in this modification, as the lactate level information, an aerobic threshold (AeT), an anaerobic threshold (AT), and a ventilation threshold (VT) representing a relation between oxygen concentration or carbon dioxide concentration in exhalation gas or an exhalation amount during exercise and a pulse rate measured by a publicly-known open circuit method during exercise of each user are used…. the lactate level information data table 250 in this modification represents a relation between a respiration quotient and a pulse rate during exercise of each user. The respiration quotient means a volume ratio of a carbon dioxide emission amount to an oxygen consumption amount until nutrients are decomposed in the body of the user and converted into energy in a certain time”).
Claim 14: Sasahara in view of Ferber in further view of Dietrich discloses the biometric information computing system according to claim 12; wherein the additional information indicates at least any one of a stress level, a pulse rate, a respiratory rate, a blood glucose level, a blood pressure, a feature of blood carbon dioxide, and a quantity of exercise (Sasahara at 0079, “In the exercise-effect determining method in this modification, as the lactate level information, an aerobic threshold (AeT), an anaerobic threshold (AT), and a ventilation threshold (VT) representing a relation between oxygen concentration or carbon dioxide concentration in exhalation gas or an exhalation amount during exercise and a pulse rate measured by a publicly-known open circuit method during exercise of each user are used…. the lactate level information data table 250 in this modification represents a relation between a respiration quotient and a pulse rate during exercise of each user. The respiration quotient means a volume ratio of a carbon dioxide emission amount to an oxygen consumption amount until nutrients are decomposed in the body of the user and converted into energy in a certain time”).
Claim 15: Sasahara in view of Ferber in further view of Dietrich discloses the biometric information computing system according to claim 10, wherein the one or more processors further execute instructions to: obtain additional data indicating a feature different from the evaluation data, based on the pulse wave, and the generating unit refers to the database and generates additional information indicating the feature of the user for the additional data (Sasahara at 0079, “In the exercise-effect determining method in this modification, as the lactate level information, an aerobic threshold (AeT), an anaerobic threshold (AT), and a ventilation threshold (VT) representing a relation between oxygen concentration or carbon dioxide concentration in exhalation gas or an exhalation amount during exercise and a pulse rate measured by a publicly-known open circuit method during exercise of each user are used…. the lactate level information data table 250 in this modification represents a relation between a respiration quotient and a pulse rate during exercise of each user. The respiration quotient means a volume ratio of a carbon dioxide emission amount to an oxygen consumption amount until nutrients are decomposed in the body of the user and converted into energy in a certain time”).
Claim 16: Sasahara in view of Ferber in further view of Dietrich discloses the biometric information computing system according to claim 10, wherein the one or more processors further execute instructions to: obtain additional information indicating a feature of the user; and generate the evaluation result based on a plurality of the evaluation data and the additional information (Sasahara at 0079, “In the exercise-effect determining method in this modification, as the lactate level information, an aerobic threshold (AeT), an anaerobic threshold (AT), and a ventilation threshold (VT) representing a relation between oxygen concentration or carbon dioxide concentration in exhalation gas or an exhalation amount during exercise and a pulse rate measured by a publicly-known open circuit method during exercise of each user are used…. the lactate level information data table 250 in this modification represents a relation between a respiration quotient and a pulse rate during exercise of each user. The respiration quotient means a volume ratio of a carbon dioxide emission amount to an oxygen consumption amount until nutrients are decomposed in the body of the user and converted into energy in a certain time”).
Claim 17: Sasahara in view of Ferber in further view of Dietrich discloses the biometric information computing system according to claim 10; wherein the one or more processors further execute instructions to obtain preliminary evaluation data different from the evaluation data, based on the pulse wave; the classification information includes a plurality of pieces of attribute-based classification information calculated using the training data different from one another, the one or more processors further execute instructions to refer to the preliminary evaluation data and selects first classification information among the plurality of pieces of attribute-based classification information; and the one or more processors further execute instructions to refer to the first classification information and generates the evaluation result for the evaluation data (Sasahara at Fig. 6 compared to Fig. 8; 0079, “In the exercise-effect determining method in this modification, as the lactate level information, an aerobic threshold (AeT), an anaerobic threshold (AT), and a ventilation threshold (VT) representing a relation between oxygen concentration or carbon dioxide concentration in exhalation gas or an exhalation amount during exercise and a pulse rate measured by a publicly-known open circuit method during exercise of each user are used…. the lactate level information data table 250 in this modification represents a relation between a respiration quotient and a pulse rate during exercise of each user. The respiration quotient means a volume ratio of a carbon dioxide emission amount to an oxygen consumption amount until nutrients are decomposed in the body of the user and converted into energy in a certain time”).
Claim 19: Sasahara in view of Ferber in further view of Dietrich discloses the biometric information computing system of claim 10, wherein the output device is a screen and the one or more processors further execute instructions to display the evaluation result on the screen (Sasahara at 0049, “The informing unit 230 informs the user of the exercise-effect determination result of the predetermined exercise of the user obtained by the exercise effect determiner 140. As the informing unit 230, it is possible to use, for example, a display section that informs the exercise-effect determination result with characters or a diagram, a sound output section that informs the exercise-effect determination result with sound, buzzer sound, or the like, a light emitting unit configured to inform the exercise-effect determination result with a color or flashing of light, and a vibrator that informs the exercise-effect determination result by transmitting vibration to a part of the body of the user, and the like”, as combined above).
Claim 20: Sasahara in view of Ferber in further view of Dietrich discloses the biometric information computing system of claim 10, wherein: operation (e) further comprises outputting normalized acceleration pulse wave data as preliminary evaluation data and normalized velocity pulse wave data as the evaluation data (Ferber at 0222, “The signals may be raw signals (e.g., as detected by the associated blood pressure measurement apparatus), filtered or pre-processed signals (e.g., to remove noise from the signals), and/or normalized signal values (e.g., between 0-1)”, as combined above and using the rationale as at the combination above); and operation (f) comprises: (f1) selecting, based on the preliminary evaluation data, one piece of classification information from a plurality of pieces of the classification information stored in the database; and (f2) generating an evaluation result including the blood lactate level for the evaluation data, wherein the evaluation result is generated by applying the selected piece of classification information to generate the blood lactate level based on the evaluation data and the selected piece of classification information (Sasahara at 0046, “a lactate level information data table 250 in which lactate level information representing a relation between a pulse rate and a blood lactate value of the user acquired in advance is stored”, 0047, “setting of a determination mode corresponding to a purpose of the user when exercise effect determination based on the pulse rate during exercise calculated by the pulse rate calculator 130 and the lactate level information stored in the lactate level information data table 250 is performed” – Sasahara not requiring more than one piece or pair of information that relates pulse to lactate level);.
Claim 22: Sasahara in view of Ferber in further view of Dietrich discloses the biometric information computing system of claim 10, wherein: the sensor is a biological signal sensor configured to obtain pulse wave or related physiological signal data of a user; the sensor is one or more of a photoplethysmography (PPG) sensor, strain sensor, fiber Bragg grating (FBG) sensor, gyroscopic sensor, electret condenser microphone (ECM), or pressure sensor (Sasahara at 0098, “the sensor 1012 may be a senor that measures one or more physiological parameters (e.g., a heart rate, a blood pressure, an exhalation amount, skin conductivity, and skin humidity)”; and the sensor is configured to perform filtering to remove components unrelated to physiological pulse signals (Ferber at 0016, “the blood pressure calculation system (or the blood pressure measurement apparatus) may filter the multi-channel signals (e.g., to remove noise from the signals”, as combined above and using the rationale as at the combination above).
Claim 24: Sasahara in view of Ferber in further view of Dietrich discloses the biometric information computing system of claim 10, wherein operation (e) further comprises applying a trained model stored in the database to the evaluation data to generate a blood lactate level representing a quantitative correlation between waveform features and measured blood lactate concentration (Sasahara at 0046, “a lactate level information data table 250 in which lactate level information representing a relation between a pulse rate and a blood lactate value of the user acquired in advance is stored”, 0047, “setting of a determination mode corresponding to a purpose of the user when exercise effect determination based on the pulse rate during exercise calculated by the pulse rate calculator 130 and the lactate level information stored in the lactate level information data table 250 is performed” – the stored data constituting a trained model).
Claim 25: Sasahara in view of Ferber in further view of Dietrich discloses the biometric information computing system of claim 10, wherein the output device is configured to display the generated blood lactate level together with an indication of measurement reliability based on predetermined calculation accuracy or error range (Ferber at 0366, “Error metrics between the ground truth and estimated blood pressure values in test dataset are averaged k-times. Those metrics may include, and are not limited to, mean square error (MSE, Example Equation 1, shown below), root mean square error (RMSE, Example Equation 2, shown below), median absolute deviation (MAD, Example Equation 3, shown below), and/or coefficient of determination (R.sup.2, Example Equation 4, shown below). In some embodiments, the model giving optimal (or, the lowest) error values may be selected and used by the blood pressure calculation system 1206 to calculate arterial blood pressure values” – therefore, the lactate level display as combined above is also an indication of reliability based on error range).
Claim 26: Sasahara in view of Ferber in further view of Dietrich discloses the biometric information computing system of claim 10, wherein the instructions, when executed, cause the system to perform operations comprising preprocessing algorithms including filtering, differentiation, pulse cycle segmentation, and normalization of pulse wave data, and to generate the evaluation result according to a trained model, the operations further comprising operations (a)-(f) (as cited to and combined above in relation to steps a-f at the parent claims above and using the rationale as at the combination above).
Claims 11, 23, and 27 are rejected under 35 U.S.C. 103 as being unpatentable over Sasahara in view of Ferber in further view of Dietrich and in still further view of Ajima (U.S. Patent Application Publication No. 2021/0030279).
Claims 11 and 23: Sasahara in view of Ferber in further view of Dietrich discloses the biometric information computing system according to claims 10 and 23; but does not appear to explicitly disclose wherein the classification information is a calibration model obtained using a PLS regression analysis with the input data as an explanatory variable and the reference data as an objective variable (at claim 11) and wherein the classification information includes a trained regression or calibration model generated from a plurality of training pulse waves and corresponding measured blood lactate levels obtained under consistent sensor and preprocessing conditions (at claim 23). Ajima, however, similarly teaches an “electronic device 100 measures the biological information of the subject while the subject wears the electronic device 100. The biological information measured by the electronic device 100 includes a pulse wave of the subject. In an embodiment, the electronic device 100 of Example 1 may acquire a pulse wave while being worn on a wrist of the subject” (Ajima at 0044) where “formulas for estimating the blood glucose level based on the above described estimation theory can be created by performing regression analysis … [where an] estimation formula may be created by the Partial Least Squares (PLS) regression analysis, for example. In the PLS regression analysis, the regression coefficient matrix is calculated using the covariance between the objective variable (feature quantity to be estimated) and the explanatory variable (feature quantity to be used for estimation), and by performing multiple regression analysis” (Ajima at 0095) so “that the health condition of the subject can be easily estimated” (Ajima at 0041). Although Ajima is primarily concerned with lipid and glucose levels (Ajima at 0005-0006), it is recognized that lactate levels are closely related to at least glucose levels – see at least the pertinent prior art cited below. Therefore, the base system and/or methods of pulse and blood analysis as in Sasahara in view of Ferber would be predictably improved or modified by the PLS regression techniques applied in a comparable method and system as indicated in Ajima so as to yield the predictable result of modeling blood pulse waves and lactate levels so as to easily estimate a user’s health condition. As such, the Examiner understands and finds that to obtain a model via PLS regression with explanatory and objective variables is the use of a known technique to improve similar devices, methods, or products in the same way so as to easily estimate a user’s health condition.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine or modify the pulse and blood analysis of Sasahara in view of Ferber in further view of Dietrich with the PLS regression of Ajima in order to obtain a model via PLS regression with explanatory and objective variables is the use of a known technique to improve similar devices, methods, or products in the same way so as to easily estimate a user’s health condition.
The rationale for combining in this manner is that to obtain a model via PLS regression with explanatory and objective variables is the use of a known technique to improve similar devices, methods, or products in the same way so as to easily estimate a user’s health condition as explained above.
Claim 27 is rejected on the same basis as claim 11 above since directed to the same or similar systems and operations as at claim 11 above.
Claim 18 is rejected under 35 U.S.C. 103 as being unpatentable over Sasahara in view of Ferber in further view of Dietrich and in still further view of Sato (U.S. Patent Application Publication No. 2010/0279820).
Claim 18: Sasahara in view of Ferber in further view of Dietrich discloses the biometric information computing system according to claim 17; but may not appear to explicitly disclose wherein the one or more processors further execute instructions to: obtain data corresponding to a velocity pulse wave based on the pulse wave as the evaluation data; and obtain data corresponding to an acceleration pulse wave based on the pulse wave as the preliminary evaluation data. The Examiner is not certain what data “corresponding to” velocity or acceleration pulse waves would encompass beyond any pulse wave data – pulse wave data appears to necessarily be “corresponding to” both velocity and acceleration pulse wave data. However, this appears to be a breadth issue, so the Examiner is not rejecting under 35 USC 112 at this time. Sato, though, teaches the effect of exercise in relation to lactic acid (Sato at 0004 and 0006-0007), remaining safe during exercising (Sato at 0040, “safe conditions when the user performs some exercises during the KAATSU training”), and “The reference pulse wave value herein is such pulse wave value that the user should not continue the KAATSU training when the pulse wave value of the user falls below it. The reference pulse wave value may have a fixed value. The pulse wave may be one of various types such as velocity pulse wave and acceleration pulse wave” (Sato at 0135). Therefore, the base system and/or methods of pulse and blood analysis as in Sasahara in view of Ferber would be predictably improved or modified by the velocity and acceleration pulse wave techniques indicated in Sato so as to yield the predictable result of obtaining data corresponding to velocity and acceleration pulse waves as preliminary evaluation data so as to remain safe during exercise. As such, the Examiner understands and finds that to obtain data corresponding to velocity and acceleration pulse waves is applying a known technique to a known device, method, or product ready for improvement to yield predictable results so as to remain safe during exercise.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine or modify the pulse and blood analysis of Sasahara in view of Ferber in further view of Dietrich with the velocity and acceleration pulse wave data of Sato in order to obtain data corresponding to velocity and acceleration pulse waves so as to remain safe during exercise.
The rationale for combining in this manner is that to obtain data corresponding to velocity and acceleration pulse waves is applying a known technique to a known device, method, or product ready for improvement to yield predictable results so as to remain safe during exercise as explained above.
Response to Arguments
Applicant's arguments filed 17 November 2025 have been fully considered but they are not persuasive.
Applicant first argues the 101 rejections (Remarks at 10-12), alleging “the claimed limitations, when viewed as a whole, are directed toward significantly more than the alleged abstract idea” (Id. at 10), since “the present invention is directed towards a specific technological improvement in physiological signal processing implemented by defined hardware and software elements” (Id. at 11). However, the claims collect pulse wave data and store pulse wave and lactate level data. The pulse wave data can be ANY pulse wave data apparently – the claims do not limit it, but that includes heart rate and/or ECG data. The filtering appears to be normal or standard ECG and/or MRI procedure (see above analysis at the rejection), the “differentiating” appears to merely be recognizing the portions of a heartbeat segment as different or differentiated from other heartbeat areas or portions – which people reading an ECG regularly perform. The dividing is apparently merely recognizing one heartbeat segment as a cycle, which people also regularly do when or while reading an ECG. The normalizing is apparently inclusive of recognizing the relative strength or amplitude of cycles/heartbeats, and as indicated at the rejection, even if this is considered an additional element as specifically requiring more precise, particular, or granular analysis by performing actual calculations of the normalized data, it is included with the abstract idea as part of performing mathematical calculations. The generating of an evaluation result (i.e., the lactate level) is literally merely comparing the database information to the test data so as to arrive at (including, e.g., an estimation or approximation of) the result and therefore a person can readily perform. The fact that the result is provided would be included with the abstract idea (what good or utility would analyzing data be/have if the result is never provided), but the indication that the result is provided by displaying it on a screen is merely the computer version of providing a result.
Applicant then argues the 112 rejections (Remarks at 12-13); however, the previous rejections are withdrawn and new, current rejections are indicated above based on the current claims.
Applicant then argues the 102 and 103 rejections based on the amending (Remarks at 9-10); however, the amendment necessitates new grounds of rejection. Therefore, the Examiner is not persuaded – please see the current rejections above.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Miller et al., Lactate and glucose interactions during rest and exercise in men: effect of exogenous lactate infusion. J Physiol. 2002 Nov 1;544(3):963-75. doi: 10.1113/jphysiol.2002.027128. PMID: 12411539; PMCID: PMC2290635. Downloaded 7 March 2025 from https://pmc.ncbi.nlm.nih.gov/articles/PMC2290635/, indicating a close relationship between blood lactate and blood glucose – “increased blood [lactate] during moderate intensity exercise increased lactate oxidation, spared blood glucose and decreased glucose production. Further, exogenous lactate infusion did not affect rating of perceived exertion (RPE) during exercise. These results demonstrate that lactate is a useful carbohydrate in times of increased energy demand” (at Abstract).
Buford et al., Kaatsu training to enhance physical function of older adults with knee osteoarthritis: Design of a randomized controlled trial. Contemp Clin Trials. 2015 Jul;43:217-22. doi: 10.1016/j.cct.2015.06.016. Epub 2015 Jun 23. PMID: 26111922; PMCID: PMC4522335. Downloaded 7 March 2025 from https://pmc.ncbi.nlm.nih.gov/articles/PMC4522335/, describing what Kaatsu training is, or entails.
Amano et al. (U.S. Patent Application Publication No. 2004/0147850, hereinafter Amano) discusses “An exercise load intensity evaluation device includes a pulse wave detection section which is attached to a subject during exercise and noninvasively detects a peripheral pulse wave. An ejection duration calculation section measures ejection duration from a feature of the pulse wave (dicrotic notch, for example) which reflects the cardiac ejection duration based on the detected pulse wave. The ejection duration measured at each measurement time by the ejection duration calculation section is input to an ejection duration change detection section, and the ejection duration change detection section detects a change in the ejection duration. Exercise load intensity of the subject during exercise is evaluated based on output from the ejection duration change detection section” (at Abstract) where “exercise at exercise load intensity near the lactate threshold may be defined as safe and effective exercise as an index in the same manner as in the case of the ejection duration, and this exercise load intensity range may be determined based on output from the diastolic time change detection section. The exercise load intensity evaluation device may notify the subject of this exercise load intensity by using the heart rate and power (watt)” (Amano at 0018, with similar information at 0036, and 0073-0077).
Hu et al., Pulse Wave Cycle Features Analysis of Different Blood Pressure Grades in the Elderly. Evid Based Complement Alternat Med. 2018 May 22;2018:1976041. doi: 10.1155/2018/1976041. PMID: 29951104; PMCID: PMC5987238. Downloaded from https://pmc.ncbi.nlm.nih.gov/articles/PMC5987238/ on 12 August 2025, indicating that “The same range of blood pressure values may reflect different vascular functions, especially in the elderly. Therefore, a single blood pressure value may not comprehensively reveal cardiovascular function. This study focused on identifying pulse wave features in the elderly that can be used to show functional differences when blood pressure values are in the same range…. First, pulse data were preprocessed and pulse cycles were segmented. Second, time domain, higher-order statistics, and energy features of wavelet packet decomposition coefficients were extracted. Finally, useful pulse wave features were evaluated using a feature selection and classifier design…. A total of 6,075 pulse wave cycles were grouped into 3 types according to different blood pressure levels and each group was divided into 2 categories according to a history of hypertension. The classification accuracy of feature selection in the 3 groups was 97.91%, 95.24%, and 92.28%, respectively…. Selected features could be appropriately used to analyze cardiovascular function in the elderly and can serve as the basis for research on a cardiovascular risk assessment model based on Traditional Chinese Medicine pulse diagnosis.” (at the first page).
García-et al., Technical mistakes during the acquisition of the electrocardiogram. Ann Noninvasive Electrocardiol. 2009 Oct;14(4):389-403. doi: 10.1111/j.1542-474X.2009.00328.x. PMID: 19804517; PMCID: PMC6932211. Downloaded from https://pmc.ncbi.nlm.nih.gov/articles/PMC6932211/pdf/ANEC-14-389.pdf on 12 February 2026. Discussing, in part, that “Improper filter application is relatively frequent in ECGs performed in daily clinical practice, as shown by Kligfield and Okin. In the great majority of the ECGs they studied, filters were applied that did not conform to the standards established by AHA in 1975” (at 398, continuing discussion to 400, FN reference omitted), where “The objective of filtering 12‐lead ECG recordings is to reduce unwanted signals, noise and interference, and thus provide an ECG of maximum quality” (at 399), and “To avoid potentially important distortion from the clinical point of view, it is necessary to use a linear phase filter or a low‐frequency filter set at 0.05 Hz” (at 400).
Langer et al. (U.S. Patent No. 4,184,493, hereinafter Langer) for a “Circuit For Monitoring A Heart And For Effecting Cardioversion Of A Needy Heart” (at Title) says that “A typical endocardial electrocardiogram which would appear at terminal 20 and the corresponding output of the ECG section 12 which would appear at terminal 30 are illustrated in FIGS. 8(a) and 8(b), respectively. It should be apparent that the bandpass elements, or filter 26 in the ECG section 12, concentrate the cardiac signal to a significant degree along the time axis” (Langer at column:lines 7:23-30; citations hereafter by number only) – i.e., that as far back as at least 1980, a typical ECG includes filtering such as using a bandpass .
Righter et al. (U.S. Patent No. 4,938,228, hereinafter Righter) for a “Wrist Worn Heart Rate Monitor” (at Title) indicates that at least by 1989, “prior devices use essentially analog systems and may be described with reference to FIG. 1. Referring to FIG. 1, a conventional heart rate monitor 10 includes a sensor 12, that senses the QRS complex and accompanying noise, and a filter 14 that produces a pulse each time the QRS signal is detected” (Righter at 1:20-25).
Thornander (U.S. Patent No. 5,010,887) for a “Noise Discrimination In Implantable Pacemakers” (at Title) indicates that “One common technique that can be used to reduce noise in a pacemaker, or other implantable medical device, is a filter that limits the frequency of the signals that are allowed to pass through it. Because noise signals, especially white noise, tend to occur randomly over the entire frequency spectrum, the use of a filter thus significantly reduces the amount of noise present” (Thornander at 2: 23-29).
Luo et al., A review of electrocardiogram filtering, Journal of Electrocardiology, Volume 43, Issue 6, 2010, Pages 486-496, ISSN 0022-0736, https://doi.org/10.1016/j.jelectrocard.2010.07.007, downloaded 17 February 2026 from https://www.sciencedirect.com/science/article/pii/S0022073610002852, indicating that “Except for some very special situations (such as an all-pass filter), a filter is generally designed to attenuate or remove some frequencies from the input data. We expect that a filter only removes the noise without changing the desired signal” (at 486).
Mynard et al., Measurement, Analysis and Interpretation of Pressure/Flow Waves in Blood Vessels. Front Physiol. 2020 Aug 27;11:1085. doi: 10.3389/fphys.2020.01085. PMID: 32973569; PMCID: PMC7481457. Downloaded 18 February 2026 from https://pmc.ncbi.nlm.nih.gov/articles/PMC7481457/, describing wave activity (at 2), “The gold-standard non-invasive method for measuring flow is phase contrast (PC-)MRI” and filtering for signal-to-noise ratio control to prevent aliasing or insufficient contrast (at 5), indicating in part “forward compression wave (FCW) or flow-decelerating backward compression wave (BCW)” (at 13), where “A helpful way to understand the generation of waves by the ventricle is to consider the degree of matching between myocardial contraction rate and outflow. During early systole, the rate of myocardial contraction exceeds outflow (which is initially zero) and therefore causes acceleration and imparts momentum to blood, generating the FCW” (at 14)”.
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/SCOTT D GARTLAND/
Primary Examiner, Art Unit 3685