DETAILED ACTION
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on May 12, 2026 has been entered.
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 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 1-6, specifically independent claims 1 and 5, are rejected under 35 U.S.C 101 because the invention is directed to a judicial exemption without significantly more. Please see the below 2 Prong Analysis:
Step One:
Claim 1 is directed to a system, which is a product. Therefore, the claim falls within a statutory category of invention.
Claim 5 is directed to a method. Therefore, the claim falls within a statutory category of invention.
Step 2A, Prong One:
Each of claims 1 and 5 recites the method steps of:
“…acquiring time-series biological information regarding pulsation of a heart…”
“…acquiring distribution candidate information…information indicating candidates for channel activity timing distribution…”
“…acquiring information indicating a state of an activity of an ion channel in the heart…by performing fitting processing of one of a plurality of cumulative distribution functions to the electrocardiograph waveform…”
Under the broadest reasonable interpretation, the claims recite a method comprising mental processes and/or method of organizing human activity (i.e. acquiring) and utilizing mathematical concepts (i.e. performing fitting processing), which is an act of evaluating information, i.e. biological information, that can be practically performed in the human mind. Thus, since claims 1 and 5 recite a limitation that falls within the mental processes and mathematical concept groupings of abstract idea.
Step 2A, Prong Two:Claim 1, as whole, fails to integrate the abstract idea into a practical application.
Claim 1 recites the following additional elements, which for the reasons set forth below, do not integrate the abstract idea into a practical application because they are insignificant extra-solution activity:
“a processor;” which is directed to data gathering, see MPEP 2106.05(g).
“a storage medium having computer program instructions stored thereon…” which is directed to data gathering, see MPEP 2106.05(g).
“…a display device…” which is directed to data output, see MPEP 2106.05(f).
Thus, the claims fail to integrate the abstract idea into a practical application. The examiner also notes that the additional elements recited in claims 1 & 5 do not apply or use the judicial exception to affect a particular treatment or prophylaxis for a disease or medical condition. The above claims are silent to providing any treatment at all to a patient.
Step 2B:
The claims as a whole fails to recite an inventive concept. The additional elements, when considered individually and in combination, do not recite significantly more than the abstract idea for the same reason as set forth above in Step 2A, Prong Two.
Upon re-evaluating the limitation that was previously identified as insignificant extra-solution activity in Step 2A, Prong 2, the following evidence to show that the limitation is well-understood, routine and conventional:
producing at said computer processor a human-readable output (i.e. processor) of the analysis of the gathered data, this is also WURC, as evidenced by Electric Power Group, LLC v. Alstom S.A., 830F.3d 1350, 119 USPQ2d 1739 (Fed.Cir. 2016), which discusses “conventional computer, network, and display technology” and states that “nothing in the patent contains any suggestion that the displays needed for that purpose are anything but readily available. We have repeatedly held that such invocations of computers and networks that are not even arguably inventive are “insufficient to pass the test of an inventive concept in the application” of an abstract idea”.” Similarly, there is nothing in Applicant’s specification that indicates that the device that is “producing at said computer processor a human-readable output indicating” the findings of the analysis is anything but readily available.
The examiner also notes that the limitations of the dependent claims, claims 2-4 & 6, define the distribution candidate information and the stored program that causes a computer to function etc. which further limit claim limitations already indicated above as being directed to an abstract idea. Therefore, the above dependent claims are directed to patient-ineligible subject matter.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, 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.
Claim(s) 1-7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Pak et al. (US 2018/0271453) in view of one having ordinary skill in the art, as evidenced by KSR.
Pak et al. teaches a signal analysis system comprising a processor and storage medium executing instructions for processing biological cardiac information, including:
acquiring cardiac action potential information of a patient using an action potential measurement unit, [0049];
recording cardiac action potential waveforms using a pacing protocol, [0049];
determining ion channel characteristics of the patient using the cardiac action potential information, [0049];
extracting ion-channel-related parameters associated with ion channel modeling, [0053];
generating pacing interval relation graphs using cardiac action potential data, [0055];
comparing generated waveform data with measured patient cardiac action potential information and calculating error values to determine ion channel characteristics, [0056]; and
determining ion channel characteristics corresponding to cardiac muscle cell activity, [0049]-[0056].
More specifically, Pak teaches:
1.
“…a processor; and a storage medium having computer program instructions stored thereon…”
E.G. via the disclosed ion channel characteristics determination unit including multiple processing units configured to execute signal analysis operations; [0050]-[0056], Fig. 7
“…acquiring a time-series of biological information regarding pulsation of a heart that is an analysis target, the time-series biological information including an electrocardiogram waveform…”
E.G. via the disclosed acquisition and recording of cardiac action potential waveforms of a patient over time using pacing protocols and cardiac measurement units, [0049]. Pak further teaches measured cardiac action potentials and waveform recordings representative of cardiac excitation behavior over time, [0049] & [0055]-[0056].
“…acquiring distribution candidate information including…candidates for channel activity timing distribution…”
E.G. via the disclosed extraction of ion channel parameters P1-Pn and generation of multiple parameter sets S1-Sk associated with ion channel activity distributions and timing behavior, [0053]-[0055];
acquiring information indicating a state of an activity distribution of timings of pulsation of cells in the heart…”
E.G. via the disclosed determination of ion channel characteristics associated with cardiac muscle cell excitation/de-excitation behavior using measured cardiac waveform information and simulated pacing interval relation graphs; [0049], [0055]-[0056].
“…by performing fitting processing of one or a plurality of cumulative distribution functions to the electrocardiogram waveform based on the distribution candidate information…”
E.G. via the disclosed repeated comparison, variance/error calculation, waveform graph generation, parameter extraction and iterative matching/fitting of waveform-derived cardiac activity information to extracted ion channel parameter sets, [0055]-[0056];
Although Pak does not explicitly use the phrase ‘cumulative distribution function,’ Pak does teach mathematical fitting and statistical comparison processes applied to cardiac waveform information in order to derive ion channel activity characteristics.
It would have been obvious to one of ordinary skill in the art at the time of the invention to utilize known statistical fitting techniques, including cumulative distribution fitting functions, as part of Pak’s waveform analysis and ion-channel characteristics determination processes in order to improve modeling accuracy, optimize matching reliability and enhance characterization of cardiac timing distributions, because applying known mathematical analysis techniques to known signal processing systems involves the predictable use of prior art elements according to their established functions. KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398, 417 (2007).
“…the fitting processing representing a distribution of activity timings of a plurality of ion channels corresponding to myocardial pulsation…”
E.G. via the disclosed determination of ion channel characteristics corresponding to cardiac muscle cell excitation activity and cardiac action potential timing behavior derived from waveform analysis and pacing simulations, [0049], [0055]-[0056].
“…displaying the information indicating the state of the activity of the ion channels…”
E.G. via the disclosed graph generation unit generating pacing interval relation graphs and displaying waveform comparison results and ion-channel characteristic-derived outputs.
2.
“…the distribution candidate information is expressed by a cumulative distribution function using a function representing candidates for channel activity timing distribution as a probability density function…”
E.G. via the disclosed generating multiple ion-channel-related parameter sets and statistically evaluating cardiac action potential waveform behavior using parameter distributions and repeated stimulation/graph generation processes, [0053]-[0056].
3.
“…wherein the information indicating a state of the activity of ion channels is acquired on the basis of a result of fitting one or a plurality of the cumulative distribution functions to the biological information…”
E.G. via the disclosed determined ion channel characteristics based on comparison/fitting of measured cardiac action potential information with generated waveform graphs and extracted parameter sets, [0055]-[0056]. Pak’s variance/error minimization process constitutes fitting biological waveform information to derived parameter distributions in order to determine ion-channel-related activity states, [0056];
It would have been obvious to one having ordinary skill in the art to use of cumulative distribution fitting functions constitutes an obvious implementation detail of known statistical fitting techniques, See KSR.
4.
“…wherein the fitting is fitting that minimizes a difference between the biological information and a linear sum of the plurality of cumulative distribution functions…”
E.G. via the disclosed calculating error values between measured cardiac action potential information and generated pacing interval relation graphs to identify parameter sets having minimized error ranges, [0056]; Pak et al. further teaches repeated parameter extraction and statistical comparison processes to identify optimal matching parameters sets, [0054]-[0056]
It would have been obvious to one having ordinary skill in the art to utilize linear combinations of cumulative distribution functions and weighted fitting constraints as predictable mathematical fitting implementations for Pak’s disclosed waveform matching and parameter optimization processes. KSR.
5.
Pak et al. view of KSR for substantially the same reasons set forth above with respect to claim 1, wherein Pak teaches the corresponding method limitations of:
Further, use of cumulative distribution fitting functions for waveform analysis and timing distribution characterization constitutes the predictable use of known statistical analysis techniques within Pak’s disclosed cardiac signal processing framework. KSR.
6.
“…a computer readable medium…which stores a program that causes a computer to function as the signal analysis device according to claim 1…”
E.G. via the disclosed computer-implemented signal analysis functionality executed using processing units and stored program instructions associated with the ion channel characteristics determination system, [0050]-[0056].
Pak teaches or at least renders obvious a non-transitory computer-readable medium storing instructions for performing the operations recited in claim 1.
7.
“…a processor, and a storage medium having program instructions stored thereon…”
E.G. via the disclosed ion channel characteristics determination unit and associated processing architecture, [0050]-[0056].
“…acquiring time-series biological information regarding pulsation of a heart…”
E.G. via the disclosed acquisition and recording of cardiac action potential waveforms of a patient over time, [0049].
“…acquiring distribution candidate information…indicating candidates for channel activity timing distribution…”
E.G. via the disclosed extraction and generation of ion-channel related parameter sets P1-Pn and S1-Sk associated with ion channel activity characteristics, [0053]-[0055].
“…acquiring information indicating a state of the activity of ion channels in the heart on the basis of the biological information and the distribution candidate information…”
E.G. via the disclosed determination of ion channel characteristics based on measured cardiac waveform information and extracted parameter sets using waveform comparison/error analysis, [0049], [0055]-[0056]
“…displaying the information indicating the state of the activity of the ion channels…”
E.G. via the disclosed graph generation unit and display of pacing interval relation graphs and waveform comparison outputs, [0055]-[0056].
Response to Arguments
Applicant's arguments filed May 12, 2026 have been fully considered but they are not persuasive. The applicant argues the following point(s) in which the examiner provides a reason(s) as to why the arguments are not persuasive:
The applicant argues that the claims are directed to improvements in signal processing technology and are similar to USPTO Eligibility Example 29. However, the examine does not agree.
The claims recite mathematical concepts including fitting processing using cumulative distribution functions, statistical analysis of biological waveform information and determining timing distributions associated with ion channel activity. Such limitations constitute an abstract idea under the 2019 Revised Patent Subject Matter Eligibility Guidance.
The additional claim elements, including acquiring electrogram waveform data, displaying results, and use of a processor and storage medium, merely amount to generic data gathering, output and computer implementation functions. The claims do not recite an improvement to computer functionality, signal processing hardware or another technological field. Rather, the claims use generic computing components as tools to analyze biological information and derive physiological conclusions.
Accordingly, the claims continue to recite a judicial exemption without significantly more than the exception itself. Therefore, the rejection under 35 U.S.C. § 101 is maintained.
II) The applicant argues that the primary reference, Pak, fails to teach:
acquiring a time-series of biological information including an electrocardiogram waveform;
performing fitting processing using cumulative distribution functions;
determining activity timing distributions corresponding to myocardial pulsation; and
acquiring information indicating a state of ion channel activity as presently claimed.
The applicant further argues that Pak is limited to molecular-level analysis of a single ion channel and does not concern collective excitation behavior represented through electrocardiogram waveform analysis. The examiner does not agree.
Pak expressly teaches acquiring and recording cardiac action potential waveforms of a patient over time using pacing protocols and cardiac measurement systems, [0049]. Pak further teaches generating pacing interval relation graphs, extracting ion-channel-related parameter sets, comparing generated waveform information with measured patient cardiac action potential information and calculating error values to determine ion channel characteristics, [0053]-[0056].
The applicant’s arguments improperly attempt to narrowly limit Pak to analysis of only a single ion channel at a molecular scale. However, Pak expressly teaches determining ion channel characteristics associated with cardiac muscle cell activity using measured cardiac action potential waveform information and repeated parameter extraction/comparison processes, [0049]-[0056]. Pak therefore teaches analysis of collective cardiac excitation behavior represented through cardiac waveform information.
Further, Applicant’s arguments improperly import limitations from the specification into the claims. For example, the applicant characterizes the claims as requiring Gaussian-function decomposition of collective cardiac excitation behavior. However, the claims do not expressly recite Gaussian-functions, molecular scale exclusions or any requirement excluding Pak’s disclosed ion-channel characteristics determination techinques. During examination, limitations appearing only in the specification are not read into the claims. See MPEP § 2111.
The applicant additionally argues that Pak is silent in regards to “fitting processing of one or a plurality of cumulative distribution functions.” However, Pak teaches repeated waveform comparison operations, variance/error calculations, parameter extraction, statistical evaluation and matching of generated waveform data to measured cardiac action potential information in order to determine ion channel characteristics, [0053]-[0056]. The use of cumulative distribution functions and probability density functions as statistical fitting tools for biological waveform analysis represents no more than the predictable use of known mathematical analysis techniques to improve modeling and matching accuracy within Pak’s disclosed system. KSR Int’l Co. v Teleflex Inc., 550 U.S. 398, 417 (2007).
Accordingly, the combination of Pak and the general knowledge in the art, as evidenced by KSR, teach or at least renders obvious the claimed subject matter.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to NICOLE F JOHNSON whose telephone number is (571)270-5040. The examiner can normally be reached Monday-Friday 8:00am-5:00pm EST.
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/NICOLE F JOHNSON/ Primary Examiner, Art Unit 3796
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