DETAILED ACTION
This action is pursuant to claims filed on 01/14/2025. Claims 1-20 are pending. A first action on the merits is as follows.
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 .
Drawings
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(4) because multiple reference characters have both been used to designate the same component:
Reference characters "902" in paragraph [0113] of the specification and "906" in Figure 9 have both been used to designate “processor system” in relation to the hemodynamic monitoring system 900
Reference characters “908” in paragraph [0113] of the specification and “904” in Figure 9 have both been used to designate “I/O Interface” in relation to the hemodynamic monitoring system 900
Reference characters “910” in paragraph [0113] of the specification and “906” in Figure 9 have both been used to designate “memory system” in relation to the hemodynamic monitoring system 900
Reference characters “912” in paragraph [0113] of the specification and “908’ in Figure 9 have both been used to designate “real-time hemodynamic data applications” in relation to the hemodynamic monitoring system 900
Reference characters “914” in paragraph [0113] of the specification and “910” in Figure 9 have both been used to designate “calibration applications” in relation to the hemodynamic monitoring system 900
Reference characters “916” in paragraph [0113] of the specification and “812” in Figure 9 have both been used to designate “pressure regulation” in relation to the hemodynamic monitoring system 900
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(4) because reference characters have been used to designate different components:
Reference character “902” has been used to designate both “processor system” and “Cuff/PPG” in Figure 9
Reference character “904” has been used to designate both “I/O interface” and “pump system” in Figure 9
Reference character “906” has been used to designate both “memory system” in Figure 9 and “processor system” in paragraph [0113] in the specification
Reference character “908” has been used to designate both “real-time hemodynamic data applications in Figure 9 and “I/O Interface” in paragraph [0113] of the specification
Reference character “910” has been used to designate both “calibration applications” in Figure 9 and “memory system” in paragraph [0113] of the specification
Reference character “ 812” has been used to designate both “transformation function parameter prediction model” in Figure 8 and “pressure regulation” in Figure 9
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(5) because they do not include the following reference sign(s) mentioned in the description:
Reference character “912” in paragraph [0113] of the specification does not appear in the figures
Reference character “914” in paragraph [0113] of the specification does not appear in the figures
Reference character “916” in paragraph [0113] in specification does not appear in the figures
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(5) because they include the following reference character(s) not mentioned in the description:
Reference character “SBP” in Figures 7A and 7C does not appear in the specification
Reference character “1” in Figure 7B does not appear in the specification
Reference character “4” in Figure 7B does not appear in the specification
Reference character “5” in Figure 7B does not appear in the specification
Reference character “N” in Figure 7C does not appear in the specification
Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Claim Objections
Claims 4-10 and 14-20 are objected to under 37 CFR 1.75(c) as being in improper form because a multiple dependent claim cannot depend from any other multiple dependent claim. See MPEP § 608.01(n). Accordingly, the claims 4-10 and 14-20 have not been further treated on the merits.
Claims 1, 3, 11, and 13 are objected to because of the following informalities:
In claim 1, line 10, “physiological data” should read “the physiological data”
In claim 3, line 4, “physiological data” should read “the physiological data”
In claim 11, line 8, “mcmory” should read “memory” to correct the spelling error
In claim 11, line 14, “physiological data” should read “the physiological data”
In claim 11, line 15, “physiological data” should read “the physiological data”
In claim 13, “proccssor” should read “processor” to correct the spelling error
In claim 13, line 3, “physiological data” should read “the physiological data”
In claim 13, line 4, “physiological data” should read “the physiological data”
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-3 and 11-13 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 1, the claim recites the limitation “a hemodynamic monitoring system” in lines 3-4. It is unclear if this limitation is meant to refer to the hemodynamic monitoring system from line 1, or a different hemodynamic monitoring system. If it is meant to refer to the hemodynamic monitoring system from line 1, it needs to refer back to it. If it is meant to refer to a different hemodynamic monitoring system, it needs to be distinguished from the hemodynamic monitoring system from line 1. For purposes of examination, it is being interpreted as referring to the hemodynamic monitoring system from line 1. Claims 2-3 are also rejected due to their dependence on claim 1.
Further regarding claim 1, the claim recites the limitation “digit arterial pressure waveform data” in lines 4-5. It is unclear if this limitation is meant to refer to the digit arterial pressure data from lines 1-2, or different digit arterial pressure data. If it is meant to refer to the digit arterial pressure data from limes 1-2, it needs to refer back to it. If it is meant to refer to a different digit arterial pressure data, it needs to be distinguished from the digit arterial pressure data from lines 1-2. For purposes of examination, it is being interpreted as referring to the digit arterial pressure waveform data from lines 1-2. Claims 2-3 are also rejected due to their dependence on claim 1.
Further regarding claim 1, the claim recites the limitation “radial arterial pressure waveform data” in lines 14-15. It is unclear if this limitation is meant to refer to the radial arterial pressure data from line 2, or different radial arterial pressure data. If it is meant to refer to the radial arterial pressure data from line 2, it needs to refer back to it. If it is meant to refer to a different radial arterial pressure data, it needs to be distinguished from the radial arterial pressure data from line 2. For purposes of examination, it is being interpreted as referring to the radial arterial pressure data from line 2. Claims 2-3 are also rejected due to their dependence on claim 1.
Further regarding claim 1, the claim recites the limitation “radial arterial pressure waveform data” in line 17. It is unclear if this limitation is meant to refer to the radial arterial pressure data from line 2, the radial arterial pressure waveform data from lines 14-15, or different radial arterial pressure waveform data. If it is meant to refer to any of the previously introduced radial arterial pressure data, it needs to clearly refer back to it. If it is meant to refer to different radial arterial pressure waveform data, it needs to be distinguished from all of the previously introduced pressure data. For purposes of examination, it is being interpreted as referring to any of the previously introduced radial arterial pressure data. Claims 2-3 are also rejected due to their dependence on claim 1.
Regarding claim 3, the claim recites the limitation “a representative vector” in lines 4-5. It is unclear if this limitation is meant to refer the representative vector from claim 1, line 10, or a different representative vector. If it is meant to refer to the representative vector from claim 1, it needs to refer back to it. If it is meant to refer to a different representative vector, it needs to be distinguished from the representative vector from claim 1. For purposes of examination, it is being interpreted as referring to the representative vector from claim 1.
Regarding claim 11, the claim recites the limitation “digit arterial pressure waveform data” in line 12. It is unclear if this limitation is meant to refer to the digit arterial pressure in line 2, or different digit arterial pressure. If it is meant to refer to the digit arterial pressure from line 2, it needs to refer back to it. If it is meant to refer to different digit arterial pressure, it needs to be distinguished from the digit arterial pressure from line 2. For purposes of examination, it is being interpreted as referring to the digit arterial pressure from line 2. Claims 12-13 are also rejected due to their dependence on claim 11.
Further regarding claim 11, the claim recites the limitation “radial arterial pressure waveform data” in lines 18-19. It is unclear if this limitation is meant to refer to the radial arterial pressure from line 1, or a different radial arterial pressure. If it is meant to refer to the radial arterial pressure from line 1, it needs to refer back to it. If it is meant to refer to a different radial arterial pressure, it needs to be distinguished from the radial arterial pressure from line 1. For purposes of examination, it is being interpreted as referring to the radial arterial pressure from line 1. Claims 12-13 are also rejected due to their dependence on claim 11.
Regarding claim 13, the claim recites the limitation “a representative vector” in line 5. It is unclear if this limitation is meant to refer to the representative vector from claim 11, line 14, or a different representative vector. If it is meant to refer to the representative vector from claim 11, it needs to refer back to it. If it is meant to refer to a different representative vector, it needs to be distinguished from the representative vector from claim 11. For purposes of examination, it is being interpreted as referring to the representative vector from claim 11.
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 and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Lokare (WO 2022146881) in view of Zuckerman (US 20170135631).
Regarding independent claim 1, Lokare teaches a real-time method for a hemodynamic monitoring system to transform digit arterial pressure data into radial arterial pressure data (Abstract: “A method of generating a blood pressure estimation for a subject includes receiving real-time PPG data from a PPG sensor attached to the subject, and generating a blood pressure estimation for the subject via an adaptive predictive model using the real time PPG data”), comprising:
obtaining hemodynamic data of a digit via a pressurized digit cuff of a hemodynamic monitoring system (Page 3, lines 29-30: “the wearable device may include a cuff configured to be attached to a limb or digit of the subject”; Page 16, lines 19-21: “BP measurements from the cuff-based BP monitor … were received every 60-to-90 seconds” The BP measurements are the hemodynamic data), wherein the hemodynamic data comprise digit arterial pressure waveform data (Page 10, lines 24-27: “The term “blood pressure”, as used herein, refers to a measurement or estimate of the pressure associated with blood flow of a person, such as a diastolic blood pressure, a systolic blood pressure, a mean arterial pressure, pulse pressure, or the like.”; Page 17, line 30 – Page 18, line 1: “an estimated BP pulse wave trace (i.e., a complete “beat-to-beat” BP waveform having a resolution much less than 1 second) may be generated via this invention”. The blood pressure measurement includes arterial blood pressure, and since the device is applied to the user’s digit, it is digit arterial pressure waveform data.);
obtaining physiological data via a photoplethysmogram of the hemodynamic monitoring system (Page 39, line 5: “receiving real-time PPG data from a PPG sensor attached to the subject”. The PPG sensor is the photoplethysmogram, and the PPG data is the physiological data), wherein the physiological data comprise physiological information of the digit (Page 3, lines 24-29: “a wearable device includes a PPG sensor … The wearable device may be configured to be worn … on a digit of the subject”. Since the PPG sensor is in the wearable device that is on the digit, the physiological information is from the digit);
receiving, using a computational processing system of the hemodynamic monitoring system, the hemodynamic data and the physiological data (Page 4, lines 15-20: “a method of improving blood pressure estimation accuracy of an adaptive predictive model (e.g., a regression model, a machine learning model, a classifier model, etc.) includes the following steps performed by at least one processor: a) receiving, within a receiving period, real-time PPG data from a PPG sensor attached to a subject and a real-time blood pressure measurement from a blood pressure monitoring device attached to the subject”. The processor is the computational processing system which receives the blood pressure measurement and the PPG data.).
However, Lokare does not teach mapping, using the computational processing system, the hemodynamic data and physiological data to a representative vector that represents the hemodynamic data and physiological data.
Zuckerman discloses a method and system for monitoring pain and a state of a user with physiological signals. Specifically, Zuckerman teaches mapping, using the computational processing system, physiological data to a representative vector that represents the combined data (Claim 29: “generating a first vector, said first vector comprising at least three features extracted from said at least two physiological signals”. The vector includes features from physiological signals, which can include blood pressure measurements and PPG signals.). Lokare and Zuckerman are analogous art as they are directed to solving the same problem of combining data from multiple sources to be used for analysis of a state of a user.
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to use the vector from Zuckerman into the method from Lokare as Lokare is silent on how the data is combined for use in the analysis, and Zuckerman discloses a suitable combination method in an analogous device.
The Lokare/Zuckerman combination teaches selecting, using the computational processing system, a set of transformation function parameters based on the representative vector (Lokare, Page 25, line 29 – Page 26, line 5: “an adaptive predictive model 300 for generating a biometric estimation (BE) may take the form of BE = f(F, S), where F is a set of “n” generated characteristic features (e.g., normalized features) at a time t=ki, and where S is a set of statistic(s) for F. The function f(F,S) may comprise a transfer function connecting the biometric estimation with the aforementioned features and statistics. For each new BP measurement (or biometric measurement) received, the adaptive predictive model 300 may be updated (as shown in Fig. 7) at each new update time-point t=uj. Updating the model comprises updating one or more parameters of the adaptive predictive model 300”. The transfer function is the transformation function parameters, and the set of statistics can include the representative vector, as Lokare is silent on the specific type of statistics used in this equation, and it would be obvious to use the representative vector, as it is a suitable statistical representation of the data being used for analysis.), wherein the set of transformation parameters can be utilized to transform the digit arterial pressure waveform data into radial arterial pressure waveform data; and transforming, using the computational processing system, the digit arterial pressure waveform data into radial arterial pressure waveform data utilizing the selected set of transformation function parameters (Lokare, Page 27, lines 15-17: “the type of blood pressure that may be estimated may from virtually any location on the body, such as (but not limited to) brachial, thoracic, subclavian, femoral, tibial, radial, carotid, central (aortic), cerebral, or the like”; Page 10, lines 24-26: “The term “blood pressure”, as used herein, refers to a measurement or estimate of the pressure associated with blood flow of a person, such as a diastolic blood pressure, a systolic blood pressure, a mean arterial pressure, pulse pressure, or the like.”. This limitation includes estimating radial blood pressure, and blood pressure includes arterial blood pressure, therefore the estimated blood pressure includes radial arterial pressure waveform data. The estimated blood pressure is determined from the measured data, which includes the measured blood pressure and PPG data from the digit, therefore transforming the digit arterial waveform data into the radial arterial pressure waveform data (Lokare, Abstract: “A method of generating a blood pressure estimation for a subject includes receiving real-time PPG data from a PPG sensor attached to the subject, and generating a blood pressure estimation for the subject via an adaptive predictive model using the real time PPG data”).).
Regarding independent claim 11, Lokare teaches a hemodynamic monitoring system for monitoring radial arterial pressure via captured digit arterial pressure (Page 5, lines 26-27: “a system for improving
blood pressure estimation accuracy of an adaptive predictive model”), the system comprising:
a pressurized digit cuff (Page 3, lines 29-30: “the wearable device may include a cuff configured to be attached to a limb or digit of the subject”);
a photoplethysmogram (Page 39, line 5: “receiving real-time PPG data from a PPG sensor attached to the subject”. The PPG sensor is the photoplethysmogram); and
a computational processing system in digital connection with the digit cuff and the photoplethysmogram; the computational processing system comprising: a processor system (Page 4, lines 15-20: “a method of improving blood pressure estimation accuracy of an adaptive predictive model (e.g., a regression model, a machine learning model, a classifier model, etc.) includes the following steps performed by at least one processor: a) receiving, within a receiving period, real-time PPG data from a PPG sensor attached to a subject and a real-time blood pressure measurement from a blood pressure monitoring device attached to the subject”. The processor is the computational processing system which receives the blood pressure measurement and the PPG data.); and
a memory system comprising one or more applications that can direct the processor system to (Page 7, lines 22-23: “Fig. 15 is a block diagram that illustrates details of an exemplary processor and memory that may be used in accordance with various embodiments of the present invention”):
receive hemodynamic data derived from the pressurized digit cuff and physiological data derived from the photoplethysmogram (Page 4, lines 15-20: “a method of improving blood pressure estimation accuracy of an adaptive predictive model (e.g., a regression model, a machine learning model, a classifier model, etc.) includes the following steps performed by at least one processor: a) receiving, within a receiving period, real-time PPG data from a PPG sensor attached to a subject and a real-time blood pressure measurement from a blood pressure monitoring device attached to the subject”. The BP measurements are the hemodynamic data and the PPG data is the physiological data.), wherein the hemodynamic data comprise digit arterial pressure waveform data (Page 10, lines 24-27: “The term “blood pressure”, as used herein, refers to a measurement or estimate of the pressure associated with blood flow of a person, such as a diastolic blood pressure, a systolic blood pressure, a mean arterial pressure, pulse pressure, or the like.”; Page 17, line 30 – Page 18, line 1: “an estimated BP pulse wave trace (i.e., a complete “beat-to-beat” BP waveform having a resolution much less than 1 second) may be generated via this invention”. The blood pressure measurement includes arterial blood pressure, and since the device is applied to the user’s digit, it is digit arterial pressure waveform data.) and the physiological data comprise physiological information of the digit (Page 3, lines 24-29: “a wearable device includes a PPG sensor … The wearable device may be configured to be worn … on a digit of the subject”. Since the PPG sensor is in the wearable device that is on the digit, the physiological information is from the digit).
However, Lokare does not teach mapping, using the computational processing system, the hemodynamic data and physiological data to a representative vector that represents the hemodynamic data and physiological data.
Zuckerman discloses a method and system for monitoring pain and a state of a user with physiological signals. Specifically, Zuckerman teaches map the hemodynamic data and physiological data to a representative vector that represents the hemodynamic data and physiological data (Claim 29: “generating a first vector, said first vector comprising at least three features extracted from said at least two physiological signals”. The vector includes features from physiological signals, which can include blood pressure measurements and PPG signals.). Lokare and Zuckerman are analogous art as they are directed to solving the same problem of combining data from multiple sources to be used for analysis of a state of a user.
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to use the vector from Zuckerman into the system from Lokare as Lokare is silent on how the data is combined for use in the analysis, and Zuckerman discloses a suitable combination method in an analogous device.
The Lokare/Zuckerman combination teaches select a set of transformation function parameters based on the representative vector (Lokare, Page 25, line 29 – Page 26, line 5: “an adaptive predictive model 300 for generating a biometric estimation (BE) may take the form of BE = f(F, S), where F is a set of “n” generated characteristic features (e.g., normalized features) at a time t=ki, and where S is a set of statistic(s) for F. The function f(F,S) may comprise a transfer function connecting the biometric estimation with the aforementioned features and statistics. For each new BP measurement (or biometric measurement) received, the adaptive predictive model 300 may be updated (as shown in Fig. 7) at each new update time-point t=uj. Updating the model comprises updating one or more parameters of the adaptive predictive model 300”. The transfer function is the transformation function parameters, and the set of statistics can include the representative vector, as Lokare is silent on the specific type of statistics used in this equation, and it would be obvious to use the representative vector, as it is a suitable statistical representation of the data being used for analysis.); and
transform the digit arterial pressure waveform data into radial arterial pressure waveform data utilizing the selected set of transformation function parameters (Lokare, Page 27, lines 15-17: “the type of blood pressure that may be estimated may from virtually any location on the body, such as (but not limited to) brachial, thoracic, subclavian, femoral, tibial, radial, carotid, central (aortic), cerebral, or the like”; Page 10, lines 24-26: “The term “blood pressure”, as used herein, refers to a measurement or estimate of the pressure associated with blood flow of a person, such as a diastolic blood pressure, a systolic blood pressure, a mean arterial pressure, pulse pressure, or the like.”. This limitation includes estimating radial blood pressure, and blood pressure includes arterial blood pressure, therefore the estimated blood pressure includes radial arterial pressure waveform data. The estimated blood pressure is determined from the measured data, which includes the measured blood pressure and PPG data from the digit, therefore transforming the digit arterial waveform data into the radial arterial pressure waveform data (Lokare, Abstract: “A method of generating a blood pressure estimation for a subject includes receiving real-time PPG data from a PPG sensor attached to the subject, and generating a blood pressure estimation for the subject via an adaptive predictive model using the real time PPG data”).).
Claims 2 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over the Lokare/Zuckerman combination as applied to claims 1 and 11 above, and further in view of Dirkes (US 20210169425).
Regarding claim 2, the Lokare/Zuckerman combination teaches the method of claim 1.
However, the Lokare/Zuckerman combination does not teach wherein the hemodynamic data is determined via a volume clamp method using the pressurized digit cuff.
Dirkes discloses a method of assessing the reliability of a blood pressure measurement. Specifically, Dirkes teaches wherein the hemodynamic data is determined via a volume clamp method using the pressurized digit cuff ([0055]: “the device 8 can be a cuff-based device that uses the volume-clamp method to measure blood pressure”). Lokare and Dirkes are analogous art as they are directed to the same field of endeavor of blood pressure measurement devices.
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 cuff using a volume clamp method from Dirkes into the Lokare/Zuckerman combination as the combination is silent on the method the cuff uses, and Dirkes discloses a suitable method in an analogous device.
Regarding claim 12, the Lokare/Zuckerman combination teaches the hemodynamic monitoring system of claim 11.
However, the Lokare/Zuckerman combination does not teach wherein the hemodynamic data is determined via a volume clamp method using the pressurized digit cuff.
Dirkes discloses a method of assessing the reliability of a blood pressure measurement. Specifically, Dirkes teaches wherein the one or more applications can direct the processor system to determine the digit arterial pressure data via a volume clamp method ([0055]: “the device 8 can be a cuff-based device that uses the volume-clamp method to measure blood pressure”). Lokare and Dirkes are analogous art as they are directed to the same field of endeavor of blood pressure measurement devices.
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 cuff using a volume clamp method from Dirkes into the Lokare/Zuckerman combination as the combination is silent on the method the cuff uses, and Dirkes discloses a suitable method in an analogous device.
Claims 3 and 13 are rejected under 35 U.S.C. 103 as being unpatentable over the Lokare/Zuckerman combination as applied to claims 1 and 11 above, and further in view of Bhalla (“SAS Macro: Capping Outlier”).
Regarding claim 3, the Lokare/Zuckerman combination teaches the method of claim 1 or 2.
However, the Lokare/Zuckerman combination does not teach the method further comprising: determining, using the computational processing system, that a particular data point of the hemodynamic data or a particular data point of the physiological data is beyond a limit threshold; wherein the step of mapping the hemodynamic data and physiological data to a representative vector further comprises: utilizing a limit value instead of the particular data point.
Bhalla discloses a method for identifying outliers during calculations. Specifically, Bhalla teaches further comprising: determining, using the computational processing system, that a particular data point of the data point is beyond a limit threshold; wherein the step of mapping the hemodynamic data and physiological data to a representative vector further comprises: utilizing a limit value instead of the particular data point (Page 2: “You can replace all the values that exist outside the following limit with the limit value”). Lokare and Bhalla are analogous art as they are both related to solving the same issue of using the best data for a calculation method.
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 capping method from Bhalla into the Lokare/Zuckerman combination as it allows the combination to use a capping method to filter outliers, as this allows the method to remove extreme outliers to ensure the estimation is not skewed unnecessarily.
Regarding claim 13, the Lokare/Zuckerman combination teaches the hemodynamic monitoring system of claim 11 or 12.
However, the Lokare/Zuckerman combination does not teach the method further comprising: determining, using the computational processing system, that a particular data point of the hemodynamic data or a particular data point of the physiological data is beyond a limit threshold; wherein the step of mapping the hemodynamic data and physiological data to a representative vector further comprises: utilizing a limit value instead of the particular data point.
Bhalla discloses a method for identifying outliers during calculations. Specifically, Bhalla teaches wherein the one or more applications can further direct the processor system to: determine that a particular data point of the hemodynamic data and physiological data is beyond a limit threshold; wherein the step to map the hemodynamic data and physiological data to a representative vector utilizes a limit value instead of the particular data point (Page 2: “You can replace all the values that exist outside the following limit with the limit value”). Lokare and Bhalla are analogous art as they are both related to solving the same issue of using the best data for a calculation method.
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 capping method from Bhalla into the Lokare/Zuckerman combination as it allows the combination to use a capping method to filter outliers, as this allows the method to remove extreme outliers to ensure the estimation is not skewed unnecessarily.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ERIN K MCCORMACK whose telephone number is (703)756-1886. The examiner can normally be reached Mon-Fri 7:30-5.
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/E.K.M./Examiner, Art Unit 3791
/MATTHEW KREMER/Primary Examiner, Art Unit 3791
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