DETAILED ACTION
Applicant’s arguments, filed on 07/31/2025, have been fully considered. The following rejections and/or objections are either reiterated or newly applied. They constitute the complete set presently being applied to the instant application.
Applicants have amended their claims, filed on 07/31/2025, and therefore rejections newly made in the instant office action have been necessitated by amendment.
Claims 1-20 are the current claims hereby under 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 .
Claim Objections
Claims 1, 6, 12, 16, and 20 are objected to because of the following informalities:
In claim 1, line 18, “estimate blood pressure” should read “estimate the blood pressure”
In claim 6, line 15, “based on blood pressure variations” should read “based on the blood pressure variations”
In claim 12, line 16, “estimating blood pressure” should read “estimating the blood pressure”
In claim 16, line 4, “based on blood pressure variations” should read “based on the blood pressure variations”
In claim 20, line 16, “estimating blood pressure” should read “estimating the blood pressure”
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 3, 7, 10, and 17 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.
Regarding claim 3, the claim recites the limitation “a respective blood pressure variation”. It is unclear if this limitation refers to the plurality of blood pressure variations introduced in claim 1, or a different blood pressure variation. If it is referring to the plurality of blood pressure variations from claim 1, it needs to refer back to it. If it is referring to a different blood pressure variation, it needs to be distinguished from the candidates from claim 1. For purposes of examination, it is being interpreted as referring to the plurality of blood pressure variations from claim 1.
Regarding claim 7, the claim recites the limitation “combining coefficients”. It is unclear if this is referring to the plurality of combining coefficients from claim 1, or different combining coefficients. If it is referring to the plurality of combining coefficients from claim 1, it needs to refer back to it. If it is referring to different combining coefficients, it needs to be distinguished from the candidates from claim 1. For purposes of examination, it is being interpreted as referring to the plurality of combining coefficients from claim 1.
Regarding claim 10, the claim recites the limitation “a blood pressure estimation model”. It is unclear if this is referring to the plurality of blood pressure estimation models from claim 1, or a different blood pressure estimation model. If it is referring to the blood pressure estimation model from claim 1, it needs to refer back to it. If it is referring to a different blood pressure estimation model, it needs to be distinguished from the candidates from claim 1. For purposes of examination, it is being interpreted as referring to the plurality of blood pressure estimation models from claim 1.
Further regarding claim 10, the claim recites the limitation “a blood pressure variation”. It is unclear if this is referring to the plurality of blood pressure variations from claim 1, or a different blood pressure variation. If it is referring to the plurality of blood pressure variations from claim 1, it needs to refer back to it. If it is referring to a different blood pressure variation, it needs to be distinguished from the candidates from claim 1. For purposes of examination, it is being interpreted as referring to the plurality of blood pressure variations from claim 1.
Further regarding claim 10, the claim recites the limitation “a high combining coefficient”. It is unclear if this is referring to the high combining coefficient introduced earlier in the claim, or a different high combining coefficient. If it is referring to the high combining coefficient introduced earlier in the claim, it needs to refer back to it. If it is referring to a different high combining coefficient, it needs to be distinguished from the candidates from earlier in the claim. For purposes of examination, it is being interpreted as referring to the high combining coefficient from earlier in the claim.
Regarding claim 17, the claim recites the limitation “combining coefficients”. It is unclear if this is referring to the plurality of combining coefficients from claim 12, or different combining coefficients. If it is referring to the plurality of combining coefficients from claim 12, it needs to refer back to it. If it is referring to different combining coefficients, it needs to be distinguished from the candidates from claim 12. For purposes of examination, it is being interpreted as referring to the plurality of combining coefficients from claim 12.
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 1-20 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. Under the two-step 101 analysis, the claims fail to satisfy the criteria for subject matter eligibility.
Regarding step 1, claims 1-20 are all within at least one of the four statutory categories.
Claim 1 and its dependent claims disclose an apparatus (machine).
Claim 12 and its dependent claims disclose a method (process).
Claim 20 discloses an electronic device (machine).
Regarding Step 2A, Prong One, the independent claims 1, 12, and 20 recite an abstract idea. In particulate, the claims generally recite the following:
inputting the PPG signal into each of a plurality of blood pressure estimation models;
obtaining a plurality of blood pressure variations respectively for each of the plurality of blood pressure estimation models based on the PPG signal input into each of the plurality of blood pressure estimation models;
obtaining a plurality of combining coefficients respectively for the plurality of blood pressure estimation models based on the obtained plurality of blood pressure variations;
estimating blood pressure by using the obtained plurality of combining coefficients.
These elements recited in claims 1, 12, and 20 are drawn to abstract ideas since they are a mental process that can be practically performed in the human mind including observation, evaluation, judgement, and opinion and using pen and paper.
Inputting the PPG signal into each of a plurality of blood pressure estimation models is drawn to an abstract idea since it is a mental process that can be practically performed in the human mind, or with the aid of pen and paper. A person of ordinary skill in the art could reasonably input the PPG signals obtained into a plurality of blood pressure estimation models, since the blood pressure estimation models are based in algorithms, calculations, evaluation, and judgement, which can be performed mentally or with the aid of pen and paper. There is nothing to suggest an undue level of complexity in inputting the PPG signal into each of a plurality of blood pressure estimation models.
Obtaining a plurality of blood pressure variations respectively for each of the plurality of blood pressure estimation models based on the PPG signal input into each of the plurality of blood pressure estimation models is drawn to an abstract idea since it is a mental process that can be practically performed in the human mind, or with the aid of pen and paper. A person of ordinary skill in the art could reasonably obtain the blood pressure variations for each blood pressure estimation model by performing the calculations and evaluations mentally or with the aid of pen and paper. These techniques are based on algorithms, calculations, evaluation, and judgement, which can be performed by hand. The mathematics of calculating blood pressure variations using PPG signal measurements are not overly complicated to perform using pen and paper given enough time, therefore these are defined as abstract ideas. There is nothing to suggest an undue level of complexity in obtaining a plurality of blood pressure variations respectively for each of the plurality of blood pressure estimation models based on the PPG signal input into each of the plurality of blood pressure estimation models.
Obtaining a plurality of combining coefficients respectively for the plurality of blood pressure estimation models based on the obtained plurality of blood pressure variations is drawn to an abstract idea since it is a mental process that can practically be performed in the human mind, or with the aid of pen and paper. A person of ordinary skill in the art could reasonably receive the blood pressure variations and perform calculations and evaluations to determine the combining coefficients mentally or with the aid of pen and paper. These techniques are based on algorithms, calculations, evaluation, and judgement, which can be performed by hand. The mathematics are not overly complicated to perform using pen and paper given enough time, therefore these are defined as abstract ideas. There is nothing to suggest an undue level of complexity in obtaining a plurality of combining coefficients respectively for the plurality of blood pressure estimation models based on the obtained plurality of blood pressure variations.
Estimating blood pressure by using the obtained plurality of combining coefficients is drawn to an abstract idea since it is a mental process that can be practically performed in the human mind, or with the aid of pen and paper. A person of ordinary skill in the art could reasonably receive the combining coefficients and estimate blood pressure mentally. These techniques are based on algorithms, calculations, evaluation, and judgement, which can be performed by hand. The mathematics of estimating blood pressure are not overly complicated to perform using pen and paper given enough time, therefore these are defined as abstract ideas. There is nothing to suggest an undue level of complexity in estimating blood pressure by using the obtained plurality of combining coefficients.
Regarding Step 2A, Prong Two, claims 1, 12, and 20 do not recite additional elements that integrate the exception into a practical application. Therefore, the claims are directed to the abstract idea. The additional elements merely:
Recite the words “apply it” or an equivalent with the judicial exception, or include instructions to implement the abstract idea on a computer, or merely use the computer as a tool to perform the abstract idea (e.g., “a processor” (claim 1), and “a processor disposed in the main body” (claim 20)), and
Add insignificant extra-solution activity (the pre-solution activity of: using generic data-gathering components (e.g., “a photoplethysmogram (PPG) sensor configured to measure a PPG signal from an object” (claims 1 and 20), and “measuring a photoplethysmogram (PPG) signal from an object” (claim 12))).
As a whole, the additional elements merely serve to gather information to be used by the abstract idea, while generically implementing it on a computer. There is no practical application because the abstract idea is not applied, relied on, or used in a meaningful way. The processing performed remains in the abstract realm, i.e., the result is not used for a treatment. No improvement to the technology is evident. Therefore, the additional elements, alone or in combination, do not integrate the abstract idea into a practical application.
Regarding Step 2B, claims 1, 12, and 20 do not include additional elements, alone or in combination, that are sufficient to amount to significantly more than the judicial exception (i.e., an inventive concept) for the same reasons as described above.
Claims 1, 12, and 20 do not recites additional elements that amount to significantly more than the judicial exception itself. In particular, “a photoplethysmogram (PPG) sensor configured to measure a PPG signal from an object” does not qualify as significantly more because this limitation merely describes a well-known and conventional data gathering step.
The data gathering step of “a photoplethysmogram (PPG) sensor configured to measure a PPG signal from an object” is nothing more than a conventional PPG sensor. Such sensors are evidenced by: US Patent Application Publication No. 20240412874 (Aman) discloses PPG sensors as conventional (Aman, [0029]);
US Patent Application Publication No. 20240324955 (Tan) discloses PPG sensors as conventional in sensing technology (Tan, [0029]);
US Patent Application Publication No. 20240277260 (Soldner) discloses using PPG sensors in conventional methods (Soldner, [0097]);
US Patent Application Publication No. 20230020039 (Shin) discloses PPG sensors as conventional (Shin, [0025]).
Further, the element of a processor in claims 1 and 20 does not qualify as significantly more because this limitation is simply appending well-understood, routine and conventional activities previously known in the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known in the industry (see Electric Power Group, 830 F.3d 1350 (Fed. Cir. 2016); Alice Corp. v. CLS Bank Int’l, 110 USPQ2d 1976 (2014)) and/or a claim to an abstract idea requiring no more than being stored on a computer readable medium which is a well-understood, routine and conventional activity previously known in the industry (see Electric Power Group, 830 F.3d 1350 (Fed. Cir. 2016); Alice Corp. v. CLS Bank Int’l, 110 USPQ2d 1976 (2014); SAP Am. v. InvestPic, 890 F.3d 1016 (Fed. Circ. 2018)).
In view of the above, the additional elements individually do not integrate the exception into a practical application and do not amount to significantly more than the above judicial exception. Looking at the limitations as an ordered combination (that is, as a whole) adds nothing that is not already present when looking at the elements individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation, i.e., the computer is simply a tool to perform the process.
Regarding the dependent claims, claims 2-11 depend on claim 1 and claims 13-19 depend on claim 12. The dependent claims merely further define the abstract idea or are additional data output that is well-understood, conventional, routine, and previously known in the industry.
For example, the following are dependent claims reciting abstract ideas and can be performed in the human mind:
(Claim 2): “obtain a plurality of differences between a reference value and a respective blood pressure variation of the plurality of blood pressure variations, and obtain the plurality of combining coefficients respectively for the plurality of blood pressure estimation models based on a respective obtained difference of the plurality of differences” is based in mathematical concept that can be performed mentally or with the aid of pen and paper. These techniques are based on algorithms and calculations and mathematical principles, which can be performed by hand. The analysis involved with these techniques are based in performing calculations with received values. The mathematics are not overly complicated to perform using pen and paper given enough time, therefore these are defined as abstract ideas;
(Claim 3): “wherein at least one of the plurality of differences comprises at least one of an absolute value of a value, obtained by subtracting the reference value from an absolute value of a respective blood pressure variation, or a Euclidean distance between the absolute value of the respective blood pressure variation and the reference value” is based in mathematical concept that can be performed mentally or with the aid of pen and paper. These techniques are based on algorithms and calculations and mathematical principles, which can be performed by hand. The analysis involved with these techniques are based in performing calculations with received values. The mathematics are not overly complicated to perform using pen and paper given enough time, therefore these are defined as abstract ideas;
(Claim 4): “obtain, as at least one of the plurality of combining coefficients, a value obtained by dividing a respective difference oft eh plurality of differences by a sum of the plurality of differences” is based in mathematical concept that can be performed mentally or with the aid of pen and paper. These techniques are based on algorithms and calculations and mathematical principles, which can be performed by hand. The analysis involved with these techniques are based in performing calculations with received values. The mathematics are not overly complicated to perform using pen and paper given enough time, therefore these are defined as abstract ideas;
(Claim 5): “obtain a final blood pressure variation by applying the plurality of combining coefficients to a respective blood pressure variation of the plurality of blood pressure variations and by linearly combining the plurality of blood pressure variations, and estimate the blood pressure by adding a reference blood pressure to the final blood pressure variation” is based in mathematical concept that can be performed mentally or with the aid of pen and paper. These techniques are based on algorithms and calculations and mathematical principles, which can be performed by hand. The analysis involved with these techniques are based in performing calculations with received values. The mathematics are not overly complicated to perform using pen and paper given enough time, therefore these are defined as abstract ideas;
(Claim 6): “select at least one of the plurality of blood pressure estimation models based on the plurality of combining coefficients, obtain a final blood pressure variation based on blood pressure variations of the selected at least one of the plurality of blood pressure estimation models, and estimate the blood pressure based on the final blood pressure estimation” is based in mathematical concept that can be performed mentally or with the aid of pen and paper. These techniques are based on algorithms and calculations and mathematical principles, which can be performed by hand. The analysis involved with these techniques are based in performing calculations with received values. The mathematics are not overly complicated to perform using pen and paper given enough time, therefore these are defined as abstract ideas;
(Claim 7): “select the at least one of the plurality of blood pressure estimation models having combining coefficients greater than or equal to a predetermined threshold value” further defines the abstract idea since it is further defining which blood pressure estimation model is being used;
(Claim 8): “obtain, as the final blood pressure variation, a statistical value including a mean value or a median value of the blood pressure variations of the selected at least one of the plurality of blood pressure estimation models” is based in mathematical concept that can be performed mentally or with the aid of pen and paper. These techniques are based on algorithms and calculations and mathematical principles, which can be performed by hand. The analysis involved with these techniques are based in performing calculations with received values. The mathematics are not overly complicated to perform using pen and paper given enough time, therefore these are defined as abstract ideas;
(Claim 9): “calculate a statistical value including a mean or standard deviation of the obtained plurality of blood pressure variations, and obtain the plurality of combining coefficients based on the calculated statistical value” is based in mathematical concept that can be performed mentally or with the aid of pen and paper. These techniques are based on algorithms and calculations and mathematical principles, which can be performed by hand. The analysis involved with these techniques are based in performing calculations with received values. The mathematics are not overly complicated to perform using pen and paper given enough time, therefore these are defined as abstract ideas;
(Claim 10): “based on the statistical value being greater than a first predetermined value, determine a high combining coefficient of the plurality of combining coefficients for a blood pressure estimation model having a blood pressure variation abode a second predetermined value, and based on the statistical value being less than the first predetermined value, determine a high combining coefficient of the plurality of combining coefficients for a blood pressure estimation model having a blood pressure variation below the second predetermined value” is based in mathematical concept that can be performed mentally or with the aid of pen and paper. These techniques are based on algorithms and calculations and mathematical principles, which can be performed by hand. The analysis involved with these techniques are based in performing calculations with received values. The mathematics are not overly complicated to perform using pen and paper given enough time, therefore these are defined as abstract ideas;
(Claim 11): “divide a plurality of training data into a plurality of training data groups according to the plurality of blood pressure variations, and generate the plurality of blood pressure estimation models for each of the divided training data groups” is based in mathematical concept that can be performed mentally or with the aid of pen and paper. These techniques are based on algorithms and calculations and mathematical principles, which can be performed by hand. The analysis involved with these techniques are based in performing calculations with received values. The mathematics are not overly complicated to perform using pen and paper given enough time, therefore these are defined as abstract ideas;
(Claim 13): “obtaining a plurality of differences between a reference value and a respective blood pressure variation of the plurality of blood pressure variations; and obtaining the plurality of combining coefficients respectively for the plurality of blood pressure estimation models based on a respective obtained difference of the plurality of differences” is based in mathematical concept that can be performed mentally or with the aid of pen and paper. These techniques are based on algorithms and calculations and mathematical principles, which can be performed by hand. The analysis involved with these techniques are based in performing calculations with received values. The mathematics are not overly complicated to perform using pen and paper given enough time, therefore these are defined as abstract ideas;
(Claim 14): “obtaining, as at least one of the plurality of combining coefficients, a value obtained by dividing a respective difference of the plurality of differences by a sum of the plurality of differences” is based in mathematical concept that can be performed mentally or with the aid of pen and paper. These techniques are based on algorithms and calculations and mathematical principles, which can be performed by hand. The analysis involved with these techniques are based in performing calculations with received values. The mathematics are not overly complicated to perform using pen and paper given enough time, therefore these are defined as abstract ideas;
(Claim 15): “obtaining a final blood pressure variation by applying the plurality of combining coefficients to a respective blood pressure variation of the plurality of blood pressure variations and by linearly combining the plurality of blood pressure variations; and adding a reference blood pressure to the final blood pressure variation” is based in mathematical concept that can be performed mentally or with the aid of pen and paper. These techniques are based on algorithms and calculations and mathematical principles, which can be performed by hand. The analysis involved with these techniques are based in performing calculations with received values. The mathematics are not overly complicated to perform using pen and paper given enough time, therefore these are defined as abstract ideas;
(Claim 16): “selecting at least one of the plurality of blood pressure estimation models based on the plurality of combining coefficients; obtaining a final blood pressure variations based on blood pressure variations of the selected at least one of the plurality of blood pressure estimation models; and estimating the blood pressure based on the final blood pressure variation” is based in mathematical concept that can be performed mentally or with the aid of pen and paper. These techniques are based on algorithms and calculations and mathematical principles, which can be performed by hand. The analysis involved with these techniques are based in performing calculations with received values. The mathematics are not overly complicated to perform using pen and paper given enough time, therefore these are defined as abstract ideas;
(Claim 17): “wherein the selecting the at least one of the plurality of blood pressure estimation models comprises selecting the at least one of the plurality of blood pressure estimation models having combining coefficients greater than or equal to a predetermined threshold value” further defines the abstract idea since it is further defining which blood pressure estimation model is being used;
(Claim 18): “wherein the estimating the blood pressure comprises obtaining, as the final blood pressure variation, a statistical value including a mean value or a median value of the blood pressure variations of the selected at least one of the plurality of blood pressure estimation models” is based in mathematical concept that can be performed mentally or with the aid of pen and paper. These techniques are based on algorithms and calculations and mathematical principles, which can be performed by hand. The analysis involved with these techniques are based in performing calculations with received values. The mathematics are not overly complicated to perform using pen and paper given enough time, therefore these are defined as abstract ideas;
(Claim 19): “calculating a statistical value including a mean or standard deviation of the obtained plurality of blood pressure variations, and obtaining the plurality of combining coefficients based on the calculated statistical value” is based in mathematical concept that can be performed mentally or with the aid of pen and paper. These techniques are based on algorithms and calculations and mathematical principles, which can be performed by hand. The analysis involved with these techniques are based in performing calculations with received values. The mathematics are not overly complicated to perform using pen and paper given enough time, therefore these are defined as abstract ideas.
The dependent claims do not recite significantly more than the abstract ideas. Therefore, claims 1-20 are rejected as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
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 1-3, 6, 8-9, 12-13, 16, and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over Wei (US 20220095938) in further view of Sekhar (US 20230218179) and Quan (CN 111000543). Citations to CN 111000543 will refer to the English Machine Translation that accompanies this Office Action.
Regarding independent claim 1, Wei teaches an apparatus for estimating blood pressure ([0002]: “The present disclosure relates to methods for determining a blood pressure value of a patient and to a corresponding blood pressure monitor”), the apparatus comprising:
a photoplethysmogram (PPG) sensor configured to measure a PPG signal from an object ([0056]: “The measuring unit may be configured to determine the pulse course on the basis of time- and volume-based blood flow values acquired on a living tissue section of the patient, i.e., by applying photoplethysmography. Thus, the measuring unit may be a photoplethysmographic measuring unit, e.g., a pulse oximeter.”); and
a processor ([0078]: “The control unit 20 is configured for processing the signal and data measured by the measuring unit 18” ) configured to:
input the PPG signal into a blood pressure estimation model ([0025]: “the method may be intended or used for determining a systolic blood pressure value as the blood pressure value to be determined”; [0026]: “Alternatively or additionally, the proposed method may be intended or used for determining a mean arterial pressure value as the blood pressure value to be determined”; [0027]: “Alternatively or additionally, the proposed method may be intended or used for determining a diastolic blood pressure value as the blood pressure value to be determined”; [0041]: “In the step of determining the blood pressure value, a mathematical model or a mathematical function may be used”; [0042]: “The mathematical model or function may be provided such that the blood pressure value as an output value is determined on the basis of at least one input variable”).
However, Wei does not teach inputting the PPG signal into a plurality of blood pressure estimation models.
Sekhar discloses a method of estimating blood pressure of a subject. Specifically, Sekhar teaches the step of input the PPG signal into each of a plurality of blood pressure estimation models (Abstract, “the method involves receiving a photoplethysmogram (PPG) signal from a light-based Pulse-Plethysmography sensor applied to the skin of a subject and reconstructing a pulse blood pressure waveform between systolic and diastolic blood pressure of the subject”; [0169]: “multiple models were used which are concatenated at the end of the process to estimate a single output”). Wei and Sekhar are analogous arts as they are both related to systems and methods used to estimate blood pressure.
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to include the PPG signal being input into multiple blood pressure estimation models from Sekhar into the apparatus from Wei as it allows the device to determine the blood pressure using multiple models, which can then be combined for a more accurate and comprehensive analysis and provide more information about the user’s health.
The Wei/Sekhar combination teaches the steps of obtain a plurality of blood pressure variations respectively for the plurality of blood pressure estimation models based on the PPG signal input into each of the plurality of blood pressure estimation models (Wei, [0025]: “the method may be intended or used for determining a systolic blood pressure value as the blood pressure value to be determined”; [0026]: “Alternatively or additionally, the proposed method may be intended or used for determining a mean arterial pressure value as the blood pressure value to be determined”; [0027]: “Alternatively or additionally, the proposed method may be intended or used for determining a diastolic blood pressure value as the blood pressure value to be determined”; [0041]: “In the step of determining the blood pressure value, a mathematical model or a mathematical function may be used”; [0042]: “The mathematical model or function may be provided such that the blood pressure value as an output value is determined on the basis of at least one input variable”).
However, the Wei/Sekhar combination does not teach obtain a plurality of combining coefficients respectively for the plurality of blood pressure estimation models based on the obtained plurality of blood pressure variations, and estimate blood pressure by using the obtained plurality of combining coefficients.
Quan discloses a device for estimating blood pressure. Specifically, Quan teaches obtain a plurality of combining coefficients respectively for the plurality of blood pressure estimation models based on the obtained plurality of blood pressure variations ([0014]: “The processor can also be configured to obtain adjustment values for adjusting the combination coefficients by inputting the reference values into a predefined adjustment value estimation equation”; [0019]: “The combination coefficient can be one of multiple combination coefficients”; [0021]: “adjusting a combination coefficient for combining the one or more feature values based on a reference value associated with vascular compliance”), and
estimate blood pressure by using the obtained plurality of combining coefficients ([0007]: “According to an aspect of an example embodiment, a device for estimating blood pressure is provided, the device comprising: a biosignal measuring device configured to measure a biosignal from a user; and a processor configured to: extract one or more feature values from the biosignal, adjust a combination coefficient for combining the one or more feature values based on a reference value associated with vascular compliance, and estimate blood pressure based on the adjusted combination coefficient and the one or more feature values extracted from the biosignal.”). Wei, Sekhar, and Quan are analogous arts as they are all related to systems and methods used to estimate blood pressure.
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to include the combining coefficients from Quan into the Wei/Sekhar combination as the combination is silent on how it combines the plurality of blood pressure models, and Quan discloses a suitable process for combining the data that will allow the device to estimate the blood pressure adequately.
Regarding claim 2, the Wei/Sekhar/Quan combination teaches the apparatus of claim 1, wherein the processor is further configured to: obtain a plurality of differences between a reference value and a respective blood pressure variation of the plurality of blood pressure variations, and obtain the plurality of combining coefficients respectively for the plurality of blood pressure estimation models based on a respective obtained difference of the plurality of differences (Wei, [0028]: “The blood pressure value to be determined may be an absolute value of the blood pressure. Alternatively, the blood pressure value to be determined may be a relative blood pressure value, e.g., with regard to a reference blood pressure value. In this way, a change of the blood pressure value, i.e., during a medical treatment, may be indicated. For example, the reference blood pressure value may correspond to a blood pressure value of a preceding cardiac cycle. More specifically, the reference blood pressure value may correspond to a blood pressure value at the beginning of a monitoring procedure or at the beginning of a medical treatment, e.g., of a dialysis treatment.”; Quan, [0007]: “adjust a combination coefficient for combining the one or more feature values based on a reference value associated with vascular compliance”).
Regarding claim 3, the Wei/Sekhar/Quan combination teaches the apparatus of claim 2, wherein at least one of the plurality of differences comprises at least one of an absolute value of a value, obtained by subtracting the reference value from an absolute value of a respective blood pressure variation, or a Euclidean distance between the absolute value of the respective blood pressure variation and the reference value (Wei, [0028]: “The blood pressure value to be determined may be an absolute value of the blood pressure. Alternatively, the blood pressure value to be determined may be a relative blood pressure value, e.g., with regard to a reference blood pressure value. In this way, a change of the blood pressure value, i.e., during a medical treatment, may be indicated. For example, the reference blood pressure value may correspond to a blood pressure value of a preceding cardiac cycle. More specifically, the reference blood pressure value may correspond to a blood pressure value at the beginning of a monitoring procedure or at the beginning of a medical treatment, e.g., of a dialysis treatment.”; Quan, [0007]: “adjust a combination coefficient for combining the one or more feature values based on a reference value associated with vascular compliance”).
Regarding claim 6, the Wei/Sekhar/Quan combination teaches the apparatus of claim 1, wherein the processor is further configured to: select at least one of the plurality of blood pressure estimation models based on the plurality of combining coefficients, obtain a final blood pressure variation based on blood pressure variations of the selected at least one of the plurality of blood pressure estimation models (Wei, [0060]: “the control unit of the blood pressure monitor, via the interface, may receive blood pressure values measured at the patient. Based on the measured blood pressure values, the control unit may be configured to assign to each measured blood pressure value a pulse course of a cardiac cycle and/or a reference point in the pulse course, respectively. In this way, the control unit may generate at least two data sets, i.e., in each of which a measured blood pressure value is assigned to a corresponding reference point. Based on the thus generated data sets, the control unit may be configured to determine the mathematical function, e.g., by applying an interpolation method and/or a regression analysis method, e.g., a linear regression analysis method.”; Quan, [0014]: “The processor can also be configured to obtain adjustment values for adjusting the combination coefficients by inputting the reference values into a predefined adjustment value estimation equation”; [0019]: “The combination coefficient can be one of multiple combination coefficients”; [0021]: “adjusting a combination coefficient for combining the one or more feature values based on a reference value associated with vascular compliance”; [0007]: “According to an aspect of an example embodiment, a device for estimating blood pressure is provided, the device comprising: a biosignal measuring device configured to measure a biosignal from a user; and a processor configured to: extract one or more feature values from the biosignal, adjust a combination coefficient for combining the one or more feature values based on a reference value associated with vascular compliance, and estimate blood pressure based on the adjusted combination coefficient and the one or more feature values extracted from the biosignal.”), and estimate the blood pressure based on the final blood pressure variation (Wei, [0042]: “The mathematical model or function may be provided such that the blood pressure value as an output value is determined on the basis of at least one input variable”; Quan, [0007]: “According to an aspect of an example embodiment, a device for estimating blood pressure is provided, the device comprising: a biosignal measuring device configured to measure a biosignal from a user; and a processor configured to: extract one or more feature values from the biosignal, adjust a combination coefficient for combining the one or more feature values based on a reference value associated with vascular compliance, and estimate blood pressure based on the adjusted combination coefficient and the one or more feature values extracted from the biosignal.”).
Regarding claim 8, the Wei/Sekhar/Quan combination teaches the apparatus of claim 6, wherein the processor is further configured to obtain, as the final blood pressure variation, a statistical value including a mean value or a median value of the blood pressure variations of the selected at least one of the plurality of blood pressure estimation models (Wei, [0026]: “the proposed method may be intended or used for determining a mean arterial pressure value as the blood pressure value to be determined”).
Regarding claim 9, the Wei/Sekhar/Quan combination teaches the apparatus of claim 1, wherein the processor is further configured to: calculate a statistical value including a mean or standard deviation of the obtained plurality of blood pressure variations (Wei, [0026]: “the proposed method may be intended or used for determining a mean arterial pressure value as the blood pressure value to be determined”), and obtain the plurality of combining coefficients based on the calculated statistical value (Quan, [0007]: “According to an aspect of an example embodiment, a device for estimating blood pressure is provided, the device comprising: a biosignal measuring device configured to measure a biosignal from a user; and a processor configured to: extract one or more feature values from the biosignal, adjust a combination coefficient for combining the one or more feature values based on a reference value associated with vascular compliance, and estimate blood pressure based on the adjusted combination coefficient and the one or more feature values extracted from the biosignal.”).
Regarding independent claim 12, Wei teaches a method of estimating blood pressure ([0002]: “The present disclosure relates to methods for determining a blood pressure value of a patient and to a corresponding blood pressure monitor”), the method comprising:
measuring a photoplethysmogram (PPG) signal from an object ([0056]: “The measuring unit may be configured to determine the pulse course on the basis of time- and volume-based blood flow values acquired on a living tissue section of the patient, i.e., by applying photoplethysmography. Thus, the measuring unit may be a photoplethysmographic measuring unit, e.g., a pulse oximeter.”);
inputting the PPG signal into a blood pressure estimation model ([0025]: “the method may be intended or used for determining a systolic blood pressure value as the blood pressure value to be determined”; [0026]: “Alternatively or additionally, the proposed method may be intended or used for determining a mean arterial pressure value as the blood pressure value to be determined”; [0027]: “Alternatively or additionally, the proposed method may be intended or used for determining a diastolic blood pressure value as the blood pressure value to be determined”; [0041]: “In the step of determining the blood pressure value, a mathematical model or a mathematical function may be used”; [0042]: “The mathematical model or function may be provided such that the blood pressure value as an output value is determined on the basis of at least one input variable”).
However, Wei does not teach inputting the PPG signal into a plurality of blood pressure estimation models.
Sekhar discloses a method of estimating blood pressure of a subject. Specifically, Sekhar teaches the step of inputting the PPG signal into each of a plurality of blood pressure estimation models (Abstract, “the method involves receiving a photoplethysmogram (PPG) signal from a light-based Pulse-Plethysmography sensor applied to the skin of a subject and reconstructing a pulse blood pressure waveform between systolic and diastolic blood pressure of the subject”; [0169]: “multiple models were used which are concatenated at the end of the process to estimate a single output”). Wei and Sekhar are analogous arts as they are both related to systems and methods used to estimate blood pressure.
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to include the PPG signal being input into multiple blood pressure estimation models from Sekhar into the method from Wei as it allows the device to determine the blood pressure using multiple models, which can then be combined for a more accurate and comprehensive analysis and provide more information about the user’s health.
The Wei/Sekhar combination teaches the steps of obtaining a plurality of blood pressure variations respectively for the plurality of blood pressure estimation models based on the PPG signal input into each of the plurality of blood pressure estimation models (Wei, [0025]: “the method may be intended or used for determining a systolic blood pressure value as the blood pressure value to be determined”; [0026]: “Alternatively or additionally, the proposed method may be intended or used for determining a mean arterial pressure value as the blood pressure value to be determined”; [0027]: “Alternatively or additionally, the proposed method may be intended or used for determining a diastolic blood pressure value as the blood pressure value to be determined”; [0041]: “In the step of determining the blood pressure value, a mathematical model or a mathematical function may be used”; [0042]: “The mathematical model or function may be provided such that the blood pressure value as an output value is determined on the basis of at least one input variable”).
However, the Wei/Sekhar combination does not teach obtain a plurality of combining coefficients respectively for the plurality of blood pressure estimation models based on the obtained plurality of blood pressure variations, and estimate blood pressure by using the obtained plurality of combining coefficients.
Quan discloses a device for estimating blood pressure. Specifically, Quan teaches obtaining a plurality of combining coefficients respectively for the plurality of blood pressure estimation models based on the obtained plurality of blood pressure variations ([0014]: “The processor can also be configured to obtain adjustment values for adjusting the combination coefficients by inputting the reference values into a predefined adjustment value estimation equation”; [0019]: “The combination coefficient can be one of multiple combination coefficients”; [0021]: “adjusting a combination coefficient for combining the one or more feature values based on a reference value associated with vascular compliance”), and
estimating blood pressure by using the obtained plurality of combining coefficients ([0007]: “According to an aspect of an example embodiment, a device for estimating blood pressure is provided, the device comprising: a biosignal measuring device configured to measure a biosignal from a user; and a processor configured to: extract one or more feature values from the biosignal, adjust a combination coefficient for combining the one or more feature values based on a reference value associated with vascular compliance, and estimate blood pressure based on the adjusted combination coefficient and the one or more feature values extracted from the biosignal.”). Wei, Sekhar, and Quan are analogous arts as they are all related to systems and methods used to estimate blood pressure.
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to include the combining coefficients from Quan into the Wei/Sekhar combination as the combination is silent on how it combines the plurality of blood pressure models, and Quan discloses a suitable process for combining the data that will allow the device to estimate the blood pressure adequately.
Regarding claim 13, the Wei/Sekhar/Quan combination teaches the method of claim 12, wherein the obtaining the plurality of combining coefficients comprises: obtaining a plurality of differences between a reference value and a respective blood pressure variation of the plurality of blood pressure variations, and obtaining the plurality of combining coefficients respectively for the plurality of blood pressure estimation models based on a respective obtained difference of the plurality of differences (Wei, [0028]: “The blood pressure value to be determined may be an absolute value of the blood pressure. Alternatively, the blood pressure value to be determined may be a relative blood pressure value, e.g., with regard to a reference blood pressure value. In this way, a change of the blood pressure value, i.e., during a medical treatment, may be indicated. For example, the reference blood pressure value may correspond to a blood pressure value of a preceding cardiac cycle. More specifically, the reference blood pressure value may correspond to a blood pressure value at the beginning of a monitoring procedure or at the beginning of a medical treatment, e.g., of a dialysis treatment.”; Quan, [0007]: “adjust a combination coefficient for combining the one or more feature values based on a reference value associated with vascular compliance”).
Regarding claim 16, the Wei/Sekhar/Quan combination teaches the method of claim 12, wherein the estimating the blood pressure comprises: selecting at least one of the plurality of blood pressure estimation models based on the plurality of combining coefficients, obtain a final blood pressure variation based on blood pressure variations of the selected at least one of the plurality of blood pressure estimation models (Wei, [0060]: “the control unit of the blood pressure monitor, via the interface, may receive blood pressure values measured at the patient. Based on the measured blood pressure values, the control unit may be configured to assign to each measured blood pressure value a pulse course of a cardiac cycle and/or a reference point in the pulse course, respectively. In this way, the control unit may generate at least two data sets, i.e., in each of which a measured blood pressure value is assigned to a corresponding reference point. Based on the thus generated data sets, the control unit may be configured to determine the mathematical function, e.g., by applying an interpolation method and/or a regression analysis method, e.g., a linear regression analysis method.”; Quan, [0014]: “The processor can also be configured to obtain adjustment values for adjusting the combination coefficients by inputting the reference values into a predefined adjustment value estimation equation”; [0019]: “The combination coefficient can be one of multiple combination coefficients”; [0021]: “adjusting a combination coefficient for combining the one or more feature values based on a reference value associated with vascular compliance”; [0007]: “According to an aspect of an example embodiment, a device for estimating blood pressure is provided, the device comprising: a biosignal measuring device configured to measure a biosignal from a user; and a processor configured to: extract one or more feature values from the biosignal, adjust a combination coefficient for combining the one or more feature values based on a reference value associated with vascular compliance, and estimate blood pressure based on the adjusted combination coefficient and the one or more feature values extracted from the biosignal.”), and estimate the blood pressure based on the final blood pressure variation (Wei, [0042]: “The mathematical model or function may be provided such that the blood pressure value as an output value is determined on the basis of at least one input variable”; Quan, [0007]: “According to an aspect of an example embodiment, a device for estimating blood pressure is provided, the device comprising: a biosignal measuring device configured to measure a biosignal from a user; and a processor configured to: extract one or more feature values from the biosignal, adjust a combination coefficient for combining the one or more feature values based on a reference value associated with vascular compliance, and estimate blood pressure based on the adjusted combination coefficient and the one or more feature values extracted from the biosignal.”).
Regarding claim 18, the Wei/Sekhar/Quan combination teaches the method of claim 16, wherein the estimating the blood pressure comprises obtaining, as the final blood pressure variation, a statistical value including a mean value or a median value of the blood pressure variations of the selected at least one of the plurality of blood pressure estimation models (Wei, [0026]: “the proposed method may be intended or used for determining a mean arterial pressure value as the blood pressure value to be determined”).
Regarding claim 19, the Wei/Sekhar/Quan combination teaches the method of claim 12, wherein the obtaining the plurality of combining coefficients comprises: calculating a statistical value including a mean or standard deviation of the obtained plurality of blood pressure variations (Wei, [0026]: “the proposed method may be intended or used for determining a mean arterial pressure value as the blood pressure value to be determined”), and obtaining the plurality of combining coefficients based on the calculated statistical value (Quan, [0007]: “According to an aspect of an example embodiment, a device for estimating blood pressure is provided, the device comprising: a biosignal measuring device configured to measure a biosignal from a user; and a processor configured to: extract one or more feature values from the biosignal, adjust a combination coefficient for combining the one or more feature values based on a reference value associated with vascular compliance, and estimate blood pressure based on the adjusted combination coefficient and the one or more feature values extracted from the biosignal.”).
Regarding independent claim 20, Wei teaches an electronic device ([0002]: “The present disclosure relates to methods for determining a blood pressure value of a patient and to a corresponding blood pressure monitor”) comprising:
a main body ([0002]: “The present disclosure relates to methods for determining a blood pressure value of a patient and to a corresponding blood pressure monitor”);
a photoplethysmogram (PPG) sensor configured to measure a PPG signal from an object ([0056]: “The measuring unit may be configured to determine the pulse course on the basis of time- and volume-based blood flow values acquired on a living tissue section of the patient, i.e., by applying photoplethysmography. Thus, the measuring unit may be a photoplethysmographic measuring unit, e.g., a pulse oximeter.”); and
a processor disposed in the main body ([0078]: “The control unit 20 is configured for processing the signal and data measured by the measuring unit 18”), the processor being configured to:
input the PPG signal into a blood pressure estimation model ([0025]: “the method may be intended or used for determining a systolic blood pressure value as the blood pressure value to be determined”; [0026]: “Alternatively or additionally, the proposed method may be intended or used for determining a mean arterial pressure value as the blood pressure value to be determined”; [0027]: “Alternatively or additionally, the proposed method may be intended or used for determining a diastolic blood pressure value as the blood pressure value to be determined”; [0041]: “In the step of determining the blood pressure value, a mathematical model or a mathematical function may be used”; [0042]: “The mathematical model or function may be provided such that the blood pressure value as an output value is determined on the basis of at least one input variable”).
However, Wei does not teach inputting the PPG signal into a plurality of blood pressure estimation models.
Sekhar discloses a method of estimating blood pressure of a subject. Specifically, Sekhar teaches the step of input the PPG signal into each of a plurality of blood pressure estimation models (Abstract, “the method involves receiving a photoplethysmogram (PPG) signal from a light-based Pulse-Plethysmography sensor applied to the skin of a subject and reconstructing a pulse blood pressure waveform between systolic and diastolic blood pressure of the subject”; [0169]: “multiple models were used which are concatenated at the end of the process to estimate a single output”). Wei and Sekhar are analogous arts as they are both related to systems and methods used to estimate blood pressure.
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to include the PPG signal being input into multiple blood pressure estimation models from Sekhar into the device from Wei as it allows the device to determine the blood pressure using multiple models, which can then be combined for a more accurate and comprehensive analysis and provide more information about the user’s health.
The Wei/Sekhar combination teaches the steps of obtain a plurality of blood pressure variations respectively for the plurality of blood pressure estimation models based on the PPG signal input into each of the plurality of blood pressure estimation models (Wei, [0025]: “the method may be intended or used for determining a systolic blood pressure value as the blood pressure value to be determined”; [0026]: “Alternatively or additionally, the proposed method may be intended or used for determining a mean arterial pressure value as the blood pressure value to be determined”; [0027]: “Alternatively or additionally, the proposed method may be intended or used for determining a diastolic blood pressure value as the blood pressure value to be determined”; [0041]: “In the step of determining the blood pressure value, a mathematical model or a mathematical function may be used”; [0042]: “The mathematical model or function may be provided such that the blood pressure value as an output value is determined on the basis of at least one input variable”).
However, the Wei/Sekhar combination does not teach obtain a plurality of combining coefficients respectively for the plurality of blood pressure estimation models based on the obtained plurality of blood pressure variations, and estimate blood pressure by using the obtained plurality of combining coefficients.
Quan discloses a device for estimating blood pressure. Specifically, Quan teaches obtain a plurality of combining coefficients respectively for the plurality of blood pressure estimation models based on the obtained plurality of blood pressure variations ([0014]: “The processor can also be configured to obtain adjustment values for adjusting the combination coefficients by inputting the reference values into a predefined adjustment value estimation equation”; [0019]: “The combination coefficient can be one of multiple combination coefficients”; [0021]: “adjusting a combination coefficient for combining the one or more feature values based on a reference value associated with vascular compliance”), and
estimate blood pressure by using the obtained plurality of combining coefficients ([0007]: “According to an aspect of an example embodiment, a device for estimating blood pressure is provided, the device comprising: a biosignal measuring device configured to measure a biosignal from a user; and a processor configured to: extract one or more feature values from the biosignal, adjust a combination coefficient for combining the one or more feature values based on a reference value associated with vascular compliance, and estimate blood pressure based on the adjusted combination coefficient and the one or more feature values extracted from the biosignal.”). Wei, Sekhar, and Quan are analogous arts as they are all related to systems and methods used to estimate blood pressure.
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to include the combining coefficients from Quan into the Wei/Sekhar combination as the combination is silent on how it combines the plurality of blood pressure models, and Quan discloses a suitable process for combining the data that will allow the device to estimate the blood pressure adequately.
Claims 4 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over the Wei/Sekhar/Quan combination as applied to claims 2 and 13 above, and further in view of Park (EP 3636145).
Regarding claim 4, the Wei/Sekhar/Quan combination teaches the apparatus of claim 2.
However, the Wei/Sekhar/Quan combination does not teach wherein the processor is further configured to: obtain, as at least one of the plurality of combining coefficients, a value obtained by dividing a respective difference of the plurality of differences by a sum of the plurality of differences.
Park discloses an apparatus and method for estimating blood pressure. Specifically, Park teaches wherein the processor is further configured to: obtain, as at least one of the plurality of combining coefficients, a value obtained by dividing a respective difference of the plurality of differences by a sum of the plurality of differences ([0061]: “the time values associated with the pulse waveform components may include a time of a position of the pulse waveform component, a time of a position of the DN, a time calculated by multiplying the times by a predetermined coefficient, a time of an internally dividing point obtained by applying a weighted value to the times, a start time and an end time of a bio-signal period, a time calculated by linearly combining at least some of the times, and the like. In this case, the weighted value to be applied to the times may be determined by using an amplitude of a differential signal of positions corresponding to the times, and/or an amplitude of the bio-signal. For example, the amplitude of the differential signal and/or the amplitude of the bio-signal, corresponding to each of the times, may be set as a weighted value to be applied to each time, so that a higher weighted value is applied to time values corresponding to a higher amplitude of a differential signal and/or a higher amplitude of the bio-signal, and an internally dividing point may be obtained by integrating the time values, to which weighted values are applied, and by dividing the added value by the sum of the weighed values. However, the weighted value is not limited thereto.”). Wei, Sekhar, Quan, and Park are analogous arts as they are all related to systems used to monitor a user’s health parameters.
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to include the calculation steps of Park into the apparatus from the Wei/Sekhar/Quan combination as it allows shows a specific way to calculate the combining coefficient in an analogous art.
Regarding claim 14, the Wei/Sekhar/Quan combination teaches the method of claim 13.
However, the Wei/Sekhar/Quan combination does not teach wherein the obtaining the plurality of combining coefficients comprises obtaining, as at least one of the plurality of combining coefficients, a value obtained by dividing a respective difference of the plurality of differences by a sum of the plurality of differences.
Park teaches wherein the obtaining the plurality of combining coefficients comprises obtaining, as at least one of the plurality of combining coefficients, a value obtained by dividing a respective difference of the plurality of differences by a sum of the plurality of differences ([0061]: “the time values associated with the pulse waveform components may include a time of a position of the pulse waveform component, a time of a position of the DN, a time calculated by multiplying the times by a predetermined coefficient, a time of an internally dividing point obtained by applying a weighted value to the times, a start time and an end time of a bio-signal period, a time calculated by linearly combining at least some of the times, and the like. In this case, the weighted value to be applied to the times may be determined by using an amplitude of a differential signal of positions corresponding to the times, and/or an amplitude of the bio-signal. For example, the amplitude of the differential signal and/or the amplitude of the bio-signal, corresponding to each of the times, may be set as a weighted value to be applied to each time, so that a higher weighted value is applied to time values corresponding to a higher amplitude of a differential signal and/or a higher amplitude of the bio-signal, and an internally dividing point may be obtained by integrating the time values, to which weighted values are applied, and by dividing the added value by the sum of the weighed values. However, the weighted value is not limited thereto.”).
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to include the calculation steps of Park into the method from the Wei/Sekhar/Quan combination as it allows shows a specific way to calculate the combining coefficient in an analogous art.
Claims 5 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over the Wei/Sekhar/Quan combination as applied to claims 1 and 12 above, and further in view of Jang (US 20200054290).
Regarding claim 5, the Wei/Sekhar/Quan combination teaches the apparatus of claim 1, wherein the processor is configured to: obtain a final blood pressure variation by applying the plurality of combining coefficients to a respective blood pressure variation of the plurality of blood pressure variations (Wei, [0042]: “The mathematical model or function may be provided such that the blood pressure value as an output value is determined on the basis of at least one input variable”).
However, the Wei/Sekhar/Quan combination does not teach linearly combining the blood pressure variations.
Jang discloses an apparatus and method for estimating blood pressure. Specifically, Jang teaches linearly combining the blood pressure variations ([0126]: “a final offset may be obtained by linearly combining the calculated third change value with an estimation result of the offset estimation model.”). Wei, Sekhar, Quan, and Jang are analogous arts as they are all related to systems used to monitor a user’s health parameters.
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to include the step of linearly combining the blood pressure variations, as the Wei/Sekhar/Quan combination allows the device to use multiple blood pressure variations to estimate the blood pressure of the user, providing a more accurate and informed result.
The Wei/Sekhar/Quan/Jang combination teaches the step of estimate the blood pressure by adding a reference blood pressure to the final blood pressure variation (Wei, [0028]: “The blood pressure value to be determined may be an absolute value of the blood pressure. Alternatively, the blood pressure value to be determined may be a relative blood pressure value, e.g., with regard to a reference blood pressure value. In this way, a change of the blood pressure value, i.e., during a medical treatment, may be indicated. For example, the reference blood pressure value may correspond to a blood pressure value of a preceding cardiac cycle. More specifically, the reference blood pressure value may correspond to a blood pressure value at the beginning of a monitoring procedure or at the beginning of a medical treatment, e.g., of a dialysis treatment.”).
Regarding claim 15, the Wei/Sekhar/Quan combination teaches the method of claim 12, wherein the estimating the blood pressure comprises: obtaining a final blood pressure variation by applying the plurality of combining coefficients to a respective blood pressure variation of the plurality of blood pressure variations (Wei, [0042]: “The mathematical model or function may be provided such that the blood pressure value as an output value is determined on the basis of at least one input variable”).
However, the Wei/Sekhar/Quan combination does not teach linearly combining the blood pressure variations.
Jang teaches linearly combining the blood pressure variations ([0126]: “a final offset may be obtained by linearly combining the calculated third change value with an estimation result of the offset estimation model.”).
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to include the step of linearly combining the blood pressure variations, as the Wei/Sekhar/Quan combination allows the device to use multiple blood pressure variations to estimate the blood pressure of the user, providing a more accurate and informed result.
The Wei/Sekhar/Quan/Jang combination teaches the step of adding a reference blood pressure to the final blood pressure variation (Wei, [0028]: “The blood pressure value to be determined may be an absolute value of the blood pressure. Alternatively, the blood pressure value to be determined may be a relative blood pressure value, e.g., with regard to a reference blood pressure value. In this way, a change of the blood pressure value, i.e., during a medical treatment, may be indicated. For example, the reference blood pressure value may correspond to a blood pressure value of a preceding cardiac cycle. More specifically, the reference blood pressure value may correspond to a blood pressure value at the beginning of a monitoring procedure or at the beginning of a medical treatment, e.g., of a dialysis treatment.”).
Claims 7, 10, 11, and 17 are rejected under 35 U.S.C. 103 as being unpatentable over the Wei/Sekhar/Quan combination as applied to claims 1, 6, 9 and 16 above, and further in view of Chang (US 20230293112).
Regarding claim 7, the Wei/Sekhar/Quan combination teaches the apparatus of claim 6.
However, the Wei/Sekhar/Quan combination does not teach wherein the processor is further configured to select the at least one of the plurality of blood pressure estimation models having combining coefficients greater than or equal to a predetermined threshold value.
Chang discloses a physiological signal feature extraction method and device. Specifically, Chang discloses wherein the processor is further configured to select the at least one of the plurality of models having values greater than or equal to a predetermined threshold value ([0035]: “since each of the pulses 110i3-110i5 (with respect to another pulse preceding or following the one of the pulses 110i3-110i5) has an abnormal waveform in its corresponding continuous waveform, the cross-correlation coefficient between the one of the pulses 110i3-110i5 and the template pulse 108v (or the waveform of another pulse preceding or following the one of the pulses 110i3-110i5) is lower than the match threshold. As a result, the pulses 110i3-110i5 may be filtered out and may not be used for feature extraction, while the waveforms of other pulses may be extracted to obtain pulse wave features. In other words, the signal feature extraction device 10 of the present invention may ignore/abandon abnormal pulse waveform(s) and extract pulse wave feature(s) from other well-shaped pulses in a signal.”). Wei, Sekhar, Quan, and Chang are analogous arts as they are all related to systems used to monitor a user’s health parameters.
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to include the predetermined threshold from Chang into the apparatus from the Wei/Sekhar/Quan combination as it allows the device to have a threshold to compare the combining coefficients to, which allows the device to make sure the values are at a specifically chosen value, ensuring the device provides accurate results.
Regarding claim 10, the Wei/Sekhar/Quan combination teaches the apparatus of claim 9.
However, the Wei/Sekhar/Quan combination does not teach wherein the processor is configured to: based on the statistical value being greater than a first predetermined value, determine a high combining coefficient of the plurality of combining coefficients for a blood pressure estimation model having a blood pressure variation above a second predetermined value, and based on the statistical value being less than the first predetermined value, determine a high combining coefficient of the plurality of combining coefficients for a blood pressure estimation model having a blood pressure variation below the second predetermined value.
Chang teaches wherein the processor is configured to: based on the statistical value being greater than a first predetermined value, determine a high combining coefficient of the plurality of combining coefficients for a blood pressure estimation model having a blood pressure variation above a second predetermined value, and based on the statistical value being less than the first predetermined value, determine a high combining coefficient of the plurality of combining coefficients for a blood pressure estimation model having a blood pressure variation below the second predetermined value ([0029]: “if the cross-correlation coefficient between the previous pulse (referred to as a first pulse) and the pulse under analysis (referred to as a second pulse) is greater than or equal to a similarity threshold (for example, 0.9, but not limited to), it is determined that the previous pulse (e.g., the pulse 107S2) is similar/correlated to the pulse under analysis (e.g., the pulse 107S3), and the pulse under analysis (e.g., the pulse 107S3) may be added to the reference waveform sequence”; [0034]: “If the cross-correlation coefficient is greater than or equal to a match threshold (for example, 0.9, but not limited thereto), the template matching module 110 may determine that the pulse being compared matches the template pulse 108v and extract feature(s) from the pulse being compared”; [0035]: “since each of the pulses 110i3-110i5 (with respect to another pulse preceding or following the one of the pulses 110i3-110i5) has an abnormal waveform in its corresponding continuous waveform, the cross-correlation coefficient between the one of the pulses 110i3-110i5 and the template pulse 108v (or the waveform of another pulse preceding or following the one of the pulses 110i3-110i5) is lower than the match threshold. As a result, the pulses 110i3-110i5 may be filtered out and may not be used for feature extraction, while the waveforms of other pulses may be extracted to obtain pulse wave features. In other words, the signal feature extraction device 10 of the present invention may ignore/abandon abnormal pulse waveform(s) and extract pulse wave feature(s) from other well-shaped pulses in a signal.”).
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to include the two thresholds from Chang into the apparatus from the Wei/Sekhar/Quan combination as it allows the device to have a threshold to compare the combining coefficients and blood pressure variations to, which allows the device to make sure the values are at a specifically chosen value, ensuring the device provides accurate results.
Regarding claim 11, the Wei/Sekhar/Quan combination teaches the apparatus of claim 1.
However, the Wei/Sekhar/Quan combination does not teach wherein the processor is further configured to: divide a plurality of training data into a plurality of training data groups according to the plurality of blood pressure variations, and generate the plurality of blood pressure estimation models for each of the dividing training data groups.
Chang teaches wherein the processor is further configured to: divide a plurality of training data into a plurality of training data groups according to the plurality of blood pressure variations, and generate the plurality of blood pressure estimation models for each of the dividing training data groups ([0043]: “the calculation unit 1124 may find potential correlations between feature(s) and blood pressure(s) by means of machine learning. For example, (known) first data (e.g., feature(s) corresponding to a (known) blood pressure, which is/are extracted by the feature extraction unit 1122) may be put through an (untrained) model by the calculation unit 1124 in the training (stage) of machine learning. The calculation unit 1124 may compare the output of the model with the (known) blood pressure of the (known) first data. As a result, parameter(s) of the model may be re-evaluated/update and optimized to train the model and to minimize (total) error(s). The calculation unit 1124 may apply/use knowledge from the (trained) model to infer a result in the inference or prediction (stage) of machine learning. Accordingly, when the (unknown) second data to be interpreted/recognized (e.g., feature(s) extracted by the feature extraction unit 1122 without corresponding to a (known) blood pressure) is input through the (trained) model, the (trained) model may perform inference on the second data according to the (optimized) parameter(s) to generate its output prediction(s).”).
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to include the training data from Chang into the apparatus from the Wei/Sekhar/Quan combination as it allows the models to use training data to create more advanced models that provide more accurate results.
Regarding claim 17, the Wei/Sekhar/Quan combination teaches the method of claim 16.
However, the Wei/Sekhar/Quan combination does not teach wherein the selecting the at least one of the plurality of blood pressure estimation models comprises selecting the at least one of the plurality of blood pressure estimation models having combining coefficients great than or equal to a predetermined threshold value.
Chang teaches wherein the selecting the at least one of the plurality of blood pressure estimation models comprises selecting the at least one of the plurality of blood pressure estimation models having combining coefficients great than or equal to a predetermined threshold value ([0035]: “since each of the pulses 110i3-110i5 (with respect to another pulse preceding or following the one of the pulses 110i3-110i5) has an abnormal waveform in its corresponding continuous waveform, the cross-correlation coefficient between the one of the pulses 110i3-110i5 and the template pulse 108v (or the waveform of another pulse preceding or following the one of the pulses 110i3-110i5) is lower than the match threshold. As a result, the pulses 110i3-110i5 may be filtered out and may not be used for feature extraction, while the waveforms of other pulses may be extracted to obtain pulse wave features. In other words, the signal feature extraction device 10 of the present invention may ignore/abandon abnormal pulse waveform(s) and extract pulse wave feature(s) from other well-shaped pulses in a signal.”).
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to include the predetermined threshold from Chang into the method from the Wei/Sekhar/Quan combination as it allows the device to have a threshold to compare the combining coefficients to, which allows the device to make sure the values are at a specifically chosen value, ensuring the device provides accurate results.
Response to Arguments
All of applicant’s argument regarding the rejections and objections previously set forth have been fully considered and are persuasive unless directly addressed subsequently.
Applicant’s arguments with respect to the 103 rejections of claims 1-20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Applicant's arguments in regards to the 101 rejection of claims 1-20 have been fully considered but they are not persuasive. Applicant argues that the human mind is not quipped to determine a blood pressure variation from a PPG signal without the use of additional equipment. However, as explained in the 101 rejection above, a person could reasonably receive the measured PPG signal waveform on a piece of paper and analyze it mentally through the aid of calculations, evaluation, and judgement to determine the blood pressure variations. These steps are a mental process since they can be performed in the human mind, or by hand on a piece of paper. Applicant states that the analysis of the waveform cannot be performed in the human mind, yet does not provide reasoning as to why this analysis cannot be performed in the human mind. A person of ordinary skill in the art could very reasonably extract information such as heart rate, amplitude, a time between different points, areas, and more from a PPG waveform provided to them on a piece of paper. All steps of the claims are either mental processes or generic data gathering steps, as described in the 101 rejection of the claims above. Additionally, Applicant states without evidence that the claim is a technical benefit for improved blood pressure estimation accuracy, yet only describes what the invention does, not the benefit or improvement.
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.
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/E.K.M./Examiner, Art Unit 3791
/MATTHEW KREMER/Primary Examiner, Art Unit 3791
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