DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.
Status of Claims
The amendments and remarks filed on 24JULY2026 have been entered into and considered.
Claims 1-2, 7, 11, 19, 20, 28 have been amended.
Claims 4-6, 9-10, 13-16, 18, 22-25, & 27 have been canceled.
Claim 29 has been added.
Response to Arguments
Applicant's amendments filed 24JULY2026 regarding the rejections under 35 U.S.C 112(a) have been fully considered and are found to obviate the rejections. Therefore, the 112(a) rejections have been withdrawn. The amendments necessitate a new ground for rejection which can be found below.
Applicant's amendments filed 24JULY2026 regarding the rejections under 35 U.S.C 112(b) have been fully considered and are found to obviate the rejections. Therefore, the 112(b) rejections have been withdrawn.
Applicant's arguments filed 24JULY2026 regarding the rejections under 35 U.S.C 101 have been fully considered but are not persuasive. Parts deemed not persuasive discussed below:
Applicant argues (Pages 13-14 of the Remarks):
Applicant respectfully disagrees for reasons of record; and in particular, maintains that the claimed inventions recite improvements to the technical field of cardiovascular disease diagnosis technology. See Amendment Reply of Feb. 10, 2025 at 15-17 ("the claimed invention provides for taking a limb BCG signal and generating synthetic whole-body BCG data."). The Examiner maintained the rejection of claims in the Final Rejection, at least in part, by asserting that the claims presented in the 10FEB2025 Reply were "recited at high levels of generality" and "do not have any supporting structures or algorithms" and thus do not "integrate the abstract idca into a practical application because it does not impose any meaningful limits on practicing the invention." See Final Office Action at 8. With regard to the previously presented recitations of the "machine learning model," the Examiner asserts that "it remains an abstract unless further processing, structure, and algorithms related to the model are provided." Final at 3 (emphasis added); see also id. at 4.
Applicant submits that the claims as now amended herein recite features of a technology improvement to the field of estimating cardiovascular parameters (CV). In particular, each of the independent claims have been amended to recite that the claimed "unobtrusive" systems and methods estimate the following CV parameters: a diastolic BP (DP), a pulse BP (PP), a systolic BP (SP), a stroke volume (SV), a cardiac output (CO), and a total peripheral resistance (TPR), from features of a "pre-conditioned PPG signal" and a filtered "synthetic whole-body BCG signal" in which each of CV parameter is "estimated from as few as two features from the plurality of features" of the two signals. See Application As-Filed at paras [0049] & [0062]. Moreover, as suggested by the Examiner, the claims have been amended to recite the particular algorithm(s) for estimating the CV parameters using two features of the PPG and BCG signals in connection with a machine learning model. As reproduced wherein in-part, each of the independent claims recite: the DP being estimated based on a PTT(I) and an A(J) in which: the PP being estimated based on the PTT(I) and a T(JJ) the SP being estimated based on an A(JK) and an A(IJ)-PTT(I)² the SV being estimated based on the T(JJ) and the A(IJ)-PTT(I)² the CO being estimated based on the T(JJ) and a PTT(J) and the TPR being estimated based on the T(JJ) and an A(JK)-PTT(I)² in which wherein each of the K1,DP; K₂,DP; K3,DP K1,TPR; K2,TPR; and K3,TPR are determined using standard regression techniques on a machine leaning regression model the machine learning regression model being constructed from the estimated CV parameters with an input of measured CV parameters and measured limb BCG and PPG signals from a plurality of human subjects over a plurality of hemodynamic interventions with rest states between two interventions. See Application As-Filed at [0054]; Table 3(d), [0071] and [0082]. Applicant submits that the amended claims recite features which provide for unobtrusive CV estimation system and methods that improve over the known whole-body direct or invasive measurements by using as few as two features of a synthetic BCG and pre- conditioned PPG signal in particular estimate algorithms or equations. See Application As-Filed at [0053]. For at least these reasons, applicant maintains that the claims recite significantly more than the asserted abstract idea; and to the extent the amended claims are found to still recite a judicial exception of mental process and/or a mathematical process, applicant submits that the exception is integrated into a practical application.
However, the arguments are not persuasive. The applicant argues that the amended claim improves the technical field of cardiovascular disease diagnosis and is no longer reciting components with a high level of generality since the limitations include signal processing steps, features, equations, and machine learning regression model. Although the amended claim provides additional details regarding these aspects, providing the additional details does not immediately establish that the claimed mathematical limitations and processing improves a technology or otherwise integrates the claim into a patent eligible claim. The claim still used mathematical relationships and regression analysis to analyze the features of BCG/ECG/ and PPG data and calculated cardiovascular parameters including steps of filtering, using time intervals, using further processing equations, etc. The filtering steps, ECG waveform extraction, aligning of the BCG and PPG signals, and generating the synthetic whole body BCG signal relates to data analysis and manipulation of the physiological data for the claimed mathematical analysis steps but do not improve the operation of the sensors, processors or any other technology. Using as few as two features and training the regression model using measured CV parameter and signals from multiple subjects and hemodynamic interventions is only specifying the data and mathematical techniques used to perform the estimation. The use of a machine learning model is not a patentable feature as it relates to the automation of data processing steps when not shown to integrate the limitations into a practical application or shows an improvement to structural features or therapy applications. Although the applicant asserts that these techniques provide unobtrusive alternative to direct or invasive measurements, any such improvement results from the claimed analysis of the data rather than an improvement to the sensing or computing technology. Therefore, the claims are not patent eligible.
Applicant's amendments filed 24JULY2026 regarding the rejections under 35 U.S.C 102(a)(1) have been fully considered and are found to obviate the rejections. Therefore, the 112(b) rejections have been withdrawn.
Applicant's amendments filed 24JULY2026 regarding the rejections under 35 U.S.C 103(a) have been fully considered and are found to obviate the rejections. Therefore, the 112(b) rejections have been withdrawn.
Claim Objections
Claims 1, 11, 19, & 28-29 are objected to because of the following informalities:
Regarding Claims 1, 19, & 28:
The claims contain typo “machine leaning”. This should instead be “machine learning”.
Regarding Claims 11 & 29:
The claim is depending on claim 1 and should therefore be reciting “ the apparatus of claim 1” instead of the “system” of claim 1.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claim 29 is rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Regarding Claim 29:
Claim 29 recites “coefficient of r > 0.64.” Within the specification the coefficient r is described in paragraphs ¶0054 and ¶0061 where the Coefficient r is equal to 0.64. The Specification does not provide a disclosure for a coefficient of r which is greater than 0.64. The application has not shown possession of the claimed invention and therefore the claims are rejectable under 112a, written description for new matter.
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 1-2, 7, 11, 19-20, & 28-29 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 Claims 1, 19, & 28:
The claims recite gating “pre-conditioning instructions to cause the signal pre-conditioning circuitry to precondition the limb BCG signal and the PPG signal in a preconditioning procedure including: zero-phase filtering to smooth the limb BCG, PPG and ECG signals; extracting an R-wave from the ECG signal; and gating the limb BCG and PPG signals with a time instant of the ECG signal, “ in lines 41-46. It is unclear if the gating limitation is performing a gating process on new Limb BCG/PPG data or if this should be referencing the pre-conditioned BCG and PPG signals from the precondition limitation. Correction is required.
The term “unobtrusive” in Line 1 is a relative term which renders the claim indefinite. The term “unobtrusive” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. For examination, the examiner interprets that as describing a wearable device.
Claims 2, 7, 11, & 29 depend on claim 1 and therefore are additionally rejected.
Claim 20 depends on claim 19 and therefore are additionally rejected.
Regarding Claims 1 & 11:
Claim 1 recites “at least one sensor” in line 3 and then further claims “the at least one sensor including an accelerometer to acquire a limb ballistocardiogram (BCG) signal, an optical sensor to acquire a photoplethysmogram (PPG) signal, and at least one electrode lead to acquire an electrocardiogram (ECG) signal;” In lines 8-10. The claim needs to be corrected to state, “at least three sensors” to properly claim the required “accelerometer to acquire a limb ballistocardiogram (BCG) signal, an optical sensor to acquire a photoplethysmogram (PPG) signal, and at least one electrode lead to acquire an electrocardiogram (ECG) signal”. Claim 11 which depends on claim 1 contains the “at least one sensor” limitation as well and will need to be corrected in a similar manner.
Claims 2, 7, 11, & 29 depend on claim 1 and therefore are additionally rejected.
Regarding Claims 1 & 19:
The claims are directed to structural apparatus/system claims but lack the necessary “configured to” functional language to recite apparatus/system limitations. Therefore, the claims appear to be directed to both a product and process within the same claim. Correction is required to include the configured to language to necessary limitations.
Claims 2, 7, 11, & 29 depend on claim 1 and therefore are additionally rejected.
Claim 20 depends on claim 19 and therefore are additionally rejected.
Regarding Claim 1:
The claim recites a “computer readable medium” in line 12. In line 38 the claims then recite “a non-transitory computer readable medium”. The claim is indefinite for not reciting consistent terminology.
Claims 2, 7, 11, & 29 depend on claim 1 and therefore are additionally rejected.
Claims 1 & 28:
The claims each broadly recite pre-conditioning structure and steps then add more details regarding pre-conditioning further along with the claim. later, in the second page of the claim. The limitations regarding pre-conditioning should be grouped together to avoid having the limitations read as distinct and separate operation related to pre-conditioning.
Claims 2, 7, 11, & 29 depend on claim 1 and therefore are additionally rejected.
Regarding Claim 7:
The claim recites “wherein the zero-phase filtered synthetic whole-body BCG, the first trough is predominantly associated with…” In lines 1-2. This is a grammatically broken limitation that lacks a clear functional link between the two portions and appears to be missing language to form the complete limitation. It is therefore unclear what is required of the limitation. For examination, the examiner is interpreting this as “wherein the zero-phase filtered synthetic whole-body BCG includes, the first trough is predominantly associated with…”.
Claim 7 recites the limitation "the first trough and the first peak" in Lines 2-3. There is insufficient antecedent basis for this limitation in the claim. Claim 1, which claim 7 depends on, recites “the zero-phase filtered synthetic whole-body BCG signal being a second waveform including a second plurality of waves, each wave being defined by a first trough (I), second trough (K) with a peak (J) therebetween”. Claim 1 refers to the first trough as a processed signal, and a peak as a processed signal. There is no distinction between of a first peak in Claim 1. Therefore, Claim 7 lacks antecedent basis for reciting “the first peak”; and “the first trough” in relation to raw signal data rather than processed data.
Regarding Claim 29:
The claim recites “…wherein, the machine learning regression model showing that the plurality” In lines 1-2. This is a grammatically broken limitation that lacks a clear functional link between the two portions of the limitation and appears that the term “showing” should instead say “shows”. It is therefore unclear what is required of the limitation. For examination, the examiner is interpreting this as “…wherein, the machine learning regression model shows that the plurality”.
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 therefore, subject to the conditions and requirements of this title.
Claims 1-2, 7, 11, 19-20, & 28-29 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
The claims recite:
Claims 1 is an apparatus.
Claim 28 is a system.
Claim 19 is a method.
Therefore, claims are directed to a statutory category of invention.
Step 2A, Prong One
Regarding claims 1, 19, and 28, The limitation of “estimate by a processor cardiovascular parameters of the patient based on the synthetic whole- body BCG data, the CV parameters include: a diastolic BP (DP), a pulse BP (PP), a systolic BP (SP) a stroke volume (SV), a cardiac output (CO), and a total peripheral resistance (TPR);”, “transform the pre-conditioned limb BCG signal to a synthetic whole-body BCG signal including, wherein the signal integrator integrates the pre-conditioned limb BCG signal in time twice to yield the synthetic whole-body BCG signal and the at least one filter of the signal transformation circuit zero-phase filters the synthetic whole-body BCG signal to remove low-frequency drift in the synthetic whole-body BCG signal, the at least one filter having a cut-off frequency being 2.5 times a heart rate determined from the synthetic whole-body BCG signal, the zero-phase filtered synthetic whole-body BCG signal being a second waveform including a second plurality of waves, each wave being defined by a first trough (I), second trough (K) with a peak (J) therebetween”; “precondition the limb BCG signal and the PPG signal in a preconditioning procedure including: zero-phase filtering to smooth the limb BCG, PPG and ECG signals; extracting an R-wave from the ECG signal; and gating the limb BCG and PPG signals with a time instant of the ECG signal, the pre-conditioned PPG signal being a first waveform including a first plurality of waves defined by a plurality of foot/troughs;”; “transform the pre-conditioned limb BCG signal to a synthetic whole-body BCG signal including, wherein the signal integrator integrates the pre-conditioned limb BCG signal in time twice to yield the synthetic whole-body BCG signal and the at least one filter of the signal transformation circuit zero-phase filters the synthetic whole-body BCG signal to remove low-frequency drift in the synthetic whole-body BCG signal, the at least one filter having a cut-off frequency being 2.5 times a heart rate determined from the synthetic whole-body BCG signal, the zero-phase filtered synthetic whole-body BCG signal being a second waveform including a second plurality of waves, each wave being defined by a first trough (I), second trough (K) with a peak (J) therebetween;”; “estimate CV parameters from a plurality of features extracted from the first and second waveforms aligned in time series with one another, the plurality of features including: PTT(I) being a time interval between the first trough (I) of a first wave in the first waveform and a foot/trough of a next wave in the second waveform in time series; A(J) being an amplitude at the peak of the first wave in the first waveform; T(JJ) being a time interval between the peak of the first wave and the peak of a second wave next to the first wave in the first waveform; A(JK) being an amplitude difference between the peak of the first wave and the second trough of the first wave in the first waveform; A(IJ) being an amplitude difference between the first trough and the peak of the first wave in the first waveform; PTT(I)2 being a square of the PTT(I); and PTT(J) being a time interval between the peak of the first wave in the first waveform and the foot/trough of the second waveform, wherein each of the CV parameters being estimated from as few as two features from the plurality of features, the estimated CV parameters including:the DP being estimated based on a PTT(I) and an A(J) in which: DP=kl.DPPTT(I)+2.DPA(J)+k3.DP;the PP being estimated based on the PTT(I) and a T(JJ) in which PP=ki.PPPTT(I)+k2.PPT(B)+k3.PP;the SP being estimated based on an A(JK) and an A(IJ)-PTT(I)2 in which SP=kl.sPA(JK)+k2.sPA(IJ) PTT(I)2+k3s;_ the SV being estimated based on the T(JJ) and the A(IJ)-PTT(I)2 in which SV=ki.svT(JJ)+k2svA(IJ) -PTT(I)2+k3Sv;the CO being estimated based on the T(JJ) and a PTT(J) in which CO=ki.coT(JJ)+k2.coPTT(J)+k3.co, andthe TPR being estimated based on the T(JJ) and an A(JK)-PTT(I)2 in which TPR=kl.TPRT(JJ)+k2.TPRA(JK)-PTT(I)2+k3.TPR”. The recited limitations relate to mathematical concepts because they require mathematical calculations and relationships to estimate cardiovascular parameters from extracted features in the BCG and PPG signals. I particular, the limitations require calculating time intervals and amplitude differences between identified waveform features and using the calculated values to determine various features such as Blood pressure and stroke volume. The specification describes extracting the features from the BCG and PPG waveforms and using mathematical relationships such as linear regression (¶0041; ¶0044). Therefore, the identified limitations relate to mathematical concepts.
Step 2A, Prong Two
This judicial exception is not integrated into a practical application. In particular, the claims recite additional elements of “An apparatus for unobtrusive estimation of cardiovascular (CV)parameters”; “at least one sensor”, “the at least one sensor including an accelerometer to acquire a limb ballistocardiogram (BCG) signal”, “a memory”; “a computer-readable medium”; “a bus communicatively coupling the processor, memory and computer-readable medium to one another, the bus linking the processing system to the at least one sensor for acquiring the limb BCG signal and the PPG signal from the at least one sensor”; “Processor”, ”display”, “the at least one sensor including an accelerometer to acquire a limb ballistocardiogram (BCG) signal”, “machine learning regression model the machine learning regression model being constructed from the estimated CV parameters with an input of measured CV parameters and measured limb BCG and PPG signals from a plurality of human subjects over a plurality of hemodynamic interventions with rest states between two interventions.”, “an optical sensor to acquire a photoplethysmoaram (PPG) signal”, “at least one electrode lead to acquire an electrocardiogram (ECG) signal”; “a processing system coupled to the at least one sensor”; “the processing system including: a processor”; “the processor includes:a signal pre-conditioning circuitry including at least one filter to pre-condition the limb BCG signal and the PPG signal”; “a signal transformation circuit including a signal integrator and at least one filter to transform the pre-conditioned BCG signal to a synthetic whole-body BCG signal”, “and a CV parameters estimation circuit ixsn coordination with the memory to estimate
Step 2B
The independent claims 1, 19, and 28 do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of, a “Processor”, “display linked to the processing system to display the CV parameters”, “wherein the computer-readable medium is a non-transitory computer-readable medium having software stored thereon that is executed by the processor in coordination with the memory, the software” amounts to no more than mere pre-solution activity of data gathering with a specified data target, which does not amount of an inventive concept. Therefore, the claims are not patent eligible.
Regarding dependent claims 2, 7, & 29 the limitations describe data collected from generically recited High-resolution accelerometers and defining parameters for data analysis steps , however, do no more to further limit the physical means for acquiring data outside of the processor, sensors, and data filtering for waveform analysis.
Regarding dependent claim 11 the limitations describe data collected from generically recited High-resolution accelerometers, , however, do no more to further limit the physical means for acquiring data outside of the processor, sensors, and data filtering for waveform analysis.
Regarding dependent claim 20 the limitations describe data collected from generically recited High-resolution accelerometers, , however, do no more to further limit the physical means for acquiring data outside of the processor, sensors, and data filtering for waveform analysis.
Therefore, claims 1-2, 7, 11, 19-20, & 28-29 are directed to an abstract idea without significantly more.
Allowable Subject Matter
Claims 1-2, 7, 11, 19-20, & 28-29 do not currently have any prior art rejections applied. However, the claims do not stand in condition for allowance due to the pending 112(a) , (b) and 101 rejections.
The following is a statement of reasons for overcoming the art of record: In view of the persuasive arguments filed in the Remarks, none of the prior art of record explicitly discloses or teaches all of the claimed elements of Claims 1-2, 7, 11, 19-20, & 28-29 particularly as currently written. After further search and consideration, it has been determined that the prior art and possible combination of relevant references fails to arrive at the claimed invention, particularly the "pre-conditioning instructions to cause the signal pre-conditioning circuitry to precondition the limb BCG signal and the PPG signal in a preconditioning procedure including: zero-phase filtering to smooth the limb BCG, PPG and ECG signals; extracting an R-wave from the ECG signal; and gating the limb BCG and PPG signals with a time instant of the ECG signal, the pre-conditioned PPG signal being a first waveform including a first plurality of waves defined by a plurality of foot/troughs; signal transformation instructions to cause the signal transformation circuit to transform the pre-conditioned limb BCG signal to a synthetic whole-body BCG signal including, wherein the signal integrator integrates the pre-conditioned limb BCG signal in time twice to yield the synthetic whole-body BCG signal and the at least one filter of the signal transformation circuit zero-phase filters the synthetic whole-body BCG signal to remove low-frequency drift in the synthetic whole-body BCG signal, the at least one filter having a cut-off frequency being 2.5 times a heart rate determined from the synthetic whole-body BCG signal, the zero-phase filtered synthetic whole-body BCG signal being a second waveform including a second plurality of waves, each wave being defined by a first trough (I), second trough (K) with a peak (J) therebetween; andCV parameters estimation instructions to cause the CV parameters estimation circuit in coordination with the memory to estimate CV parameters from a plurality of features extracted from the first and second waveforms aligned in time series with one another, the plurality of features including: PTT(I) being a time interval between the first trough (I) of a first wave in the first waveform and a foot/trough of a next wave in the second waveform in time series; A(J) being an amplitude at the peak of the first wave in the first waveform; T(JJ) being a time interval between the peak of the first wave and the peak of a second wave next to the first wave in the first waveform; A(JK) being an amplitude difference between the peak of the first wave and the second trough of the first wave in the first waveform; A(IJ) being an amplitude difference between the first trough and the peak of the first wave in the first waveform; PTT(I)2 being a square of the PTT(I); and PTT(J) being a time interval between the peak of the first wave in the first waveform and the foot/trough of the second waveform, wherein each of the CV parameters being estimated from as few as two features from the plurality of features, the estimated CV parameters including: the DP being estimated based on a PTT(I) and an A(J) in which: DP=kl.DPPTT(I)+2.DPA(J)+k3.DP;the PP being estimated based on the PTT(I) and a T(JJ) in which PP=ki.PPPTT(I)+k2.PPT(B)+k3.PP;the SP being estimated based on an A(JK) and an A(IJ)-PTT(I)2 in which SP=kl.sPA(JK)+k2.sPA(IJ) PTT(I)2+k3s;_ the SV being estimated based on the T(JJ) and the A(IJ)-PTT(I)2 in which SV=ki.svT(JJ)+k2svA(IJ) -PTT(I)2+k3Sv;the CO being estimated based on the T(JJ) and a PTT(J) in which CO=ki.coT(JJ)+k2.coPTT(J)+k3.co, and the TPR being estimated based on the T(JJ) and an A(JK)-PTT(I)2 in which TPR=kl.TPRT(JJ)+k2.TPRA(JK)-PTT(I)2+k3.TPR, wherein each of the klDP; k2.DP; k3.DP; ki.PP; k2.DP; k3.DP; ki.PP; k2.PP; 3PP; ki.sP; k2; k3sP; ki.sv; k2.sv; k3.sv; ki.co; k2.co; k3.co; kl.TPR; k2.TP; and k3.TP are determined using standard regression techniques on a machine leaning regression model and stored in the memory, the machine learning regression model being constructed from the estimated CV parameters with an input of measured CV parameters and measured limb BCG and PPG signals from a plurality of human subjects over a plurality of hemodynamic interventions with rest states between two interventions. ". The prior art includes does not provide the specified algorithmic relationships as claimed by the instant application.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MEGAN FEDORKY whose telephone number is (571)272-2117. The examiner can normally be reached M-F 9:30-4:30.
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/MEGAN T FEDORKY/Examiner, Art Unit 3796
/ALLEN PORTER/Primary Examiner, Art Unit 3796
