DETAILED ACTION
Applicant's request for reconsideration of the finality of the rejection of the last Office action is persuasive and, therefore, the finality of that action is withdrawn.
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 .
Election/Restriction - Maintained and Withdrawn
In view of the Petition Decision mailed on 11/03/2025, regarding the lack of unity restriction requirement between Species Election 1, Species A-H and Species Election 2, Species I-V, claims 39, 41, 42, 43, 46, 48, 50, 51, 54, and 58 are hereby rejoined.
For clarity, the restriction requirement between Group I (claims 1, 3, and 5-9), Group II (claims 15, 17-18, 20, 22-23, and 25), and Group III (claims 27-30 and 32-33) was made Final in the Non-Final Rejection mailed on 07/16/2024. The following is substantially reiterated from the Final Rejection mailed on 06/06/2025 and the Advisory Action mailed on 09/17/2025 in regards to Applicants arguments filed on 08/28/2025.
Groups I, II, and III do not fall within one of the combination of categories as provided in 37 CFR 1.475 (b). Groups I, II, and III are drawn to three distinct products, which is not one of the combinations of categories outlined. That is, because all groupings of the claims are not drawn to only one of the combination of categories, the claims will not be considered to have unity of invention. Further, no technical feature is shared across all inventions. Therefore, unity of invention is lacking a priori between Groups I, II, and III. See MPEP 1850 regarding Unity of Invention.
Status of Claims
Applicant's arguments, filed 08/28/2025 and 10/06/2025, 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 08/28/2025.
Applicants have amended claims 40, 44, 49, and 53.
Applicants have left claims 1, 3, 5-9, 38-39, 41-43, 45-48, 50-52, and 54-58 as originally filed/previously presented.
Applicants have canceled/previously canceled claims 2, 4, 10-14, 16-17, 19-26, 28-29, and 31-37.
Claims 15, 18, 27, and 30 remain withdrawn from further consideration as being drawn to nonelected inventions.
Claims 1, 3, 5-9, and 38-58 are the current claims hereby under examination.
Claim Objections - Withdrawn and Newly Applied
Claims 43, 46, and 50 are objected to because of the following informalities:
Regarding claim 43, line 4 recites “obtaining an artefact model”, however it appears it should read --obtaining the artefact model-- (emphasis added) to maintain proper antecedent basis.
Regarding claim 46, line 1 recites “the model”, however it appears it should read --the artefact model-- (emphasis added) to maintain consistent claim language.
Regarding claim 50, line 2 recites “using one or more of the iterations individually or and/or collectively”, however it appears it should read along the lines of --using one or more of the iterations individually and/or collectively-- (emphasis added).
Response to Arguments
Applicant’s arguments, see page 14 of Remarks, filed 08/28/2025, with respect to claims 40, 44, 49, and 53 have been fully considered and are persuasive. Applicants have amended the claims rendering the objections moot. The objection of claims 40, 44, 49, and 53 have been withdrawn. However, there are new claim objections.
Claim Rejections - 35 USC § 101 - Newly Applied
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, 3, 5-9, 38-58 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.
Step 1 of the subject matter eligibility test (see MPEP 2106.03).
Claim 1 is directed to a method, which describes one of the four statutory categories of patentable subject matter, i.e., a process. Therefore, further consideration is necessary.
Step 2A of the subject matter eligibility test (see MPEP 2106.04).
Prong One: Claim 1 recites an abstract idea. In particular, the claim recites the following:
Obtaining an artefact model based at least in part on the read data; and
Obtaining neural response data by comparing the read data to the artefact model.
The elements of claim 1 are drawn to an abstract idea since (1) they involve mathematical concepts in the form of mathematical relationships, mathematical formulas or equations, and/or mathematical calculations; and/or (2) they involve a mental process that can be practically performed in the human mind including observation, evaluation, judgment, and opinion and using pen and paper.
“Obtaining an artefact model based at least in part on the read data” is drawn to a mental process that can practically be performed in the human mind, with the aid of pen and paper. A person with ordinary skill in the art could reasonably obtain, or construct, an artefact model based on obtained read data on a piece of paper. There is nothing to suggest an undue level of complexity in the obtaining an artefact model step. Further, “obtaining an artefact model based at least in part on the read data” is a mathematical concept of manipulating mathematical formulas and equations. Obtaining the artefact model involves adjusting a mathematical formula in view of the obtained read data.
“Obtaining neural response data by comparing the read data to the artefact model” is drawn to a mental process that can be practically performed in the human mind, with the aid of pen and paper. A person of ordinary skill in the art could reasonably obtain a neural response by comparing a set of data and an artefact model on a piece of paper. There is nothing to suggest an undue level of complexity in the “comparing” step. Further, “obtaining neural response data by comparing the read data to the artefact model” is a mathematical concept in the form of mathematical formulas or equations. “Comparing the read data to the artefact model” involves subtracting an artefact model from the read data (para. [0110] of the instant disclosure filed 06/21/2021). A mathematical concept need not be expressed in mathematical symbols to be considered a mathematical concept (see MPEP 2106.04(a)(2), I).
Prong Two: Claim 1 does 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:
Add insignificant extra-solution activity (the pre-solution activity of: using generic data-gathering components (e.g. “applying electrical stimulation to a recipient” (with no structure recited), “obtaining from read electrodes read data resulting from the applied stimulation”).
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.
Per the Berkheimer requirement, the additional elements are well-understood, routine, and conventional.
For example, “applying electrical stimulation” and “obtaining from read electrodes read data” is well-understood, routine and convention, as disclosed by Stefan Strahl (US 20100069996 A1) - para. [0009-0010].
Step 2B of the subject matter eligibility test (see MPEP 2106.05).
Claim 1 does 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. E.g., all elements are directed to pre-solution activities of necessary data gathering, which merely facilitate the abstract idea.
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 (the abstract idea). 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 taking individually. There is no indication that the combination of elements improves the functioning of a computer, for example, or improves any other technology. There is no indication that the combination of elements permits automation of specific tasks that previously could not be automated. There is no indication that the combination of elements includes a particular solution to a computer-based problem or a particular way to achieve a desired computer-based outcome. Rather, the collective functions of the claimed invention merely are directed towards pre-solution activities to be used by the abstract idea, where the result of the abstract idea remains within a “black box”.
Analysis of the dependent claims:
Claims 3, 5-9, and 38-58 depend from the independent claim. The dependent claims merely further define the abstract idea and are, therefore, directed to an abstract idea for similar reasons: they merely
Further describe the abstract idea (“the artefact model is based on a constant phase model” (claim 5), “the artefact model is based on a true constant phase model” (claim 6), “the artefact model does not rely on the results of a double exponential” (claim 7), “the action of obtaining neural response data is executed by subtracting the artefact model from the read data” (claim 8), “accounting for, at least in part, noise that influenced the results of the obtained artefact model” (claim 9), “accounting for, at least in part, noise that influenced data that formed a basis for the obtained artefact model” (claim 38), “the obtained artefact model is based on the certain parameters and based on the read data” (claim 39), “the action of obtaining neural response data includes developing the neural response data without introducing additional thermal and/or quantization noise” (claim 40), “the artefact model is based on one or more of: stimulation parameters of an implant used for the applying action and the obtaining from read electrode actions; configuration of the implant used for the applying action and the obtaining from read electrode actions; behavioral characteristics of the implant used for the applying action and the obtaining from read electrode actions; or electrode interface properties” (claim 41), “the action of obtaining an artefact model is executed by repeatedly developing embryonic models, at least some of which are based on respective separate data sets of the read data” (claim 43), “the artefact model is a model that was developed by using predetermined constants and by using data from in-situ electrodes relative to the recipient” (claim 45), “the action of obtaining the model includes: obtaining one or more temporally and/or frequency based dataset(s) from sensors attached to the recipient; developing various iterations of embryonic models, all of which are intended to be different from the temporally and/or frequency based dataset(s); and using one of the iterations as a basis for the obtained artefact model” (claim 46), “the action of obtaining the artefact model includes: developing various iterations of embryonic models based on the dataset(s);comparing at least some of the respective various iterations of the embryonic models to the dataset(s) in an iterative manner, while making adjustments to the respective iteration to further drive the next embryonic model towards the dataset(s);selecting an iteration of the embryonic model from a subset of one or more of the iterations of the embryonic models where further adjustments of the subset will result in a statistically insignificant difference between the embryonic model and the dataset” (claim 47), “developing the artefact model at least in part based thereon” (claim 48), “using one or more of the iterations individually or and/or collectively as the model to compare to the temporally and/or frequency based dataset(s) to determine neural response based on the comparison (claim 50), “the comparison to the temporally and/or frequency based dataset(s) yields a difference between the temporally and/or frequency based dataset(s) and the artefact model, the difference being the neural response” (claim 51), “the artefact model excludes neural response data” (claim 54), “the neural response data is based on a phenomenon that decays faster than decay of a phenomenon upon which the artefact model is based” (claim 55), “the obtained neural response data is data corresponding to the neural response in the recipient” (claim 56), “the action of obtaining the neural response data includes removing the non-neural response data from the neural response data” (claim 57), “the action of obtaining the artefact model includes constructing the artefact model based on the non-neural response data” (claim 58)),
Further describe the pre-solution activity (or the structure used for such activity) (“the application of electrical stimulation and the obtaining of the read data occurs at a cochlea of a person” (claim 3), “the electrical stimulation is applied internally to the recipient” (claim 38), “the stimulation applied to the recipient meets certain parameters” (claim 39), “the actions of applying and obtaining are part of an EcaP measurement method” (claim 42), “the action of obtaining from read electrodes read data is executed in a plurality of temporally spaced obtaining actions” (claim 43), “the read electrodes are platinum electrodes” (claim 44), “obtaining one or more temporally and/or frequency based dataset(s) from sensors attached to the recipient” (claim 47), “obtaining one or more temporally and/or frequency based dataset(s) from sensors attached to the recipient” (claim 48), “the one or more temporally and/or frequency based dataset(s) is/are dataset(s) where the obtained neural response is overwhelmed by an artefact”, (claim 49), “the obtained read data includes residual artefacts of the electrical stimulation which are at least 0.1 orders of magnitude larger than a signal of interest in the read data, wherein the signal of interest in the read data corresponds to data resulting from a neural response created by the action of applying the electrical stimulation to the recipient” (claim 53), “the electrical stimulation evokes a neural response in the recipient” (claim 56), “the obtained read data includes neural response data and non-neural response data” (claim 57), “the obtained read data includes neural response data and non-neural response data” (claim 58)); and
Further describe the post-solution activity (“adjusting a medical device based on the obtained neural response data so that the medical device operates differently” (claim 52) (recited at a high level of generality)).
Per the Berkheimer requirement, the additional elements are well-understood, routine, and conventional.
For example, “platinum electrodes” are well-understood, routine, and conventional as disclosed by Patrick et al. (US 20140350640 A1) - para. [0103-0104].
Taken alone or in combination, the additional elements do not integrate the judicial exception into a practical application at least because the abstract idea is not applied, relied on, or used in a meaningful way. The additional elements do not add anything significantly more than the abstract idea. The collective functions of the additional elements merely provide means for collecting data to be used by the abstract idea, and no additional elements beyond those of the abstract idea. There is no indication that the combination of elements permits automation of specific tasks that previously could not be automated. There is no indication that the combination of elements improves the functioning of a computer, output device, improves technology other than the technical field of the claimed invention, etc. Therefore, the claims are rejected as being directed to non-statutory subjection matter. Claims 1, 3, 5-9, 38-58 are rejected.
Response to Arguments
Applicant's arguments filed 08/28/2025 and 10/06/2025 have been fully considered but they are not persuasive.
First, the 101 rejection above has been modified/newly applied
Applicants have argued on page 14 of Remarks, filed 08/28/2025, that the rejection does not follow the current rules on rejecting claims under section 101.
The Examiner respectfully disagrees. As reiterated above, the claims are rejected under 101 in accordance with the current guidelines outlined in 2106 of the MPEP. The Examiner cannot find a reason to withdraw the rejection. Substantially the same applies to the arguments filed on 10/06/2025.
Applicants have argued on pages 14-28 of Remarks, filed 08/28/2025, that because the claims are exactly and/or similar to multiple different PGPUBs and Patents, this serves as proof the claims meet section 101.
The Examiner respectfully disagrees. Applicants have not shown how the instant claims are similar to those of the cited references. The Examiner cannot find a reason to withdraw the rejection. Further, applicant's arguments fail to comply with 37 CFR 1.111(b) because they amount to a general allegation that the claims define a patentable invention without specifically pointing out how the language of the claims patentably distinguishes them from the references. Further, in regards to the patentability of the cited references by the Applicant, every patent is presumed valid and Examiners do not express any opinion as to the patentability or unpatentability of any US patent. (see MPEP 1701). Substantially the same applies to the arguments filed on 10/06/2025.
Claim Rejections - 35 USC § 102 - Withdrawn and Newly Applied
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1, 3, 7-9, 38-39, 41-42, 45, 48, 52, and 54-58 rejected under 35 U.S.C. 102(a)(1) as being anticipated by Stefan Strahl (US 20100069996 A1), hereinafter referred to as Strahl.
The claims are generally directed towards a method, comprising: applying electrical stimulation to a recipient; obtaining from read electrodes read data resulting from the applied stimulation; obtaining an artefact model based at least in part on the read data; and obtaining neural response data by comparing the read data to the artefact model.
Regarding claim 1, Strahl discloses a method (Abstract, “method … for processing a waveform signal containing a stimulus artifact …”), comprising:
applying electrical stimulation to a recipient (para. [0009-0010], “cochlear implant … applying the electrical stimulation signal to target neural tissue”);
obtaining from read electrodes read data resulting from the applied stimulation (Fig. 2, “recorded data”, para. [0009-0010], “neuronal action potentials may be an electrically evoked compound action potential, for example, as determined for a cochlear implant … measuring the waveform signal at the target tissue …”, para. [0013], - the cochlear implant inherently includes electrodes in order to obtain and measure the recorded data);
obtaining an artefact model based at least in part on the read data (para. [0018], “patient dependent waveform is derived dynamically … measurement starts with the a priori derived waveform … standard optimization algorithms, the stimulus artifact waveform can be changed to be optimized for the actual measure waveform …”); and
obtaining neural response data by comparing the read data to the artefact model (para. [0010], “removing the stimulus artifact from the waveform signal using a source separation algorithm that leaves the neuronal action potential signal remaining”, para. [0018], “stimulus artifact waveform can be changed to be optimized for the actual measurement waveform signal …”).
Regarding claim 3, Strahl discloses the method of claim 1, wherein: the application of the electrical stimulation and the obtaining of the read data occurs at a cochlea of the recipient, wherein the recipient is a person (para. [0009-0010], “neuronal action potentials may be an electrically evoked compound action potential, for example, as determined for a cochlear implant …”, para. [0013]).
Regarding claim 7, Strahl discloses the method of claim 1, wherein the artefact model does not rely on results of a double exponential (para. [0017-0018], “patient dependent waveform is derived dynamically … measurement starts with the a priori derived waveform … standard optimization algorithms, the stimulus artifact waveform can be changed to be optimized for the actual measure waveform …”).
Regarding claim 8, Strahl discloses the method of claim 1, wherein the action of obtaining the neural response data is executed by subtracting the artefact model from the read data (Fig. 2, para. [0010], “removing the stimulus artifact from the waveform signal using a source separation algorithm that leaves the neuronal action potential signal remaining”, para. [0018], “stimulus artifact waveform can be change to be optimized for the actual measurement waveform signal …”).
Regarding claim 9, Strahl discloses the method of claim 1, further comprising accounting for, at least in part, noise that influenced the results of the obtained artefact model (para. [0010], “removing the stimulus artifact from the waveform signal using a source separation algorithm that leaves the neuronal action potential signal remaining” - noise being the stimulus artifact that is accounted for and removed).
Regarding claim 38, Strahl discloses the method of claim 1, further comprising accounting for, at least in part, noise that influenced data that formed a basis for the obtained artefact mode (para. [0010], “removing the stimulus artifact from the waveform signal using a source separation algorithm that leaves the neuronal action potential signal remaining” - noise being the stimulus artifact that is accounted for and removed)l, wherein the electrical stimulation is applied internally to the recipient (para. [0009], “cochlear implant”, para. [0013]).
Regarding claim 39, Strahl discloses the method of claim 1, wherein: the stimulation applied to the recipient meets certain parameters (Fig. 2, para. [0009], “cochlear implant”, para. [0013] - the stimulation meets certain parameters to evoke a neuronal action potential); and the obtained artefact model is based on the certain parameters and based on the read data (para. [0018], “patient dependent waveform is derived dynamically … measurement starts with the a priori derived waveform … standard optimization algorithms, the stimulus artifact waveform can be changed to be optimized for the actual measure waveform …”).
Regarding claim 41, Strahl discloses the method of claim 1, wherein the artefact model is based on one or more of: stimulation parameters of an implant used for the applying action and the obtaining from read electrode actions; configuration of the implant used for the applying action and the obtaining from read electrode actions (para. [0009-0010], para. [0013], “processing electrically evoked compound action potentials (ECAPs) signals in neuroprosethtic devices such as cochlear implants, which contain a stimulus artifact component …”); behavioral characteristics of the implant used for the applying action and the obtaining from read electrode actions (para. [0009-0010], para. [0013], “processing electrically evoked compound action potentials (ECAPs) signals in neuroprosethtic devices such as cochlear implants, which contain a stimulus artifact component …”); or electrode interface properties.
Regarding claim 42, Strahl discloses the method of claim 1, wherein: the actions of applying and obtaining are part of an EcaP measurement method (para. [0013], “processing electrically evoked compound action potentials (ECAPs) signals in neuroprosthetic devices …”).
Regarding claim 45, Strahl discloses the method of claim 1, wherein: the artefact model is a model that was developed by using predetermined constants and by using data from in-situ electrodes relative to the recipient (para. [0018], “patient dependent waveform is derived dynamically … measurement starts with the a priori derived waveform … standard optimization algorithms, the stimulus artifact waveform can be changed to be optimized for the actual measure waveform …”).
Regarding claim 48, Strahl discloses the method of claim 1, wherein: the action of obtaining the artefact model includes obtaining one or more temporally and/or frequency based dataset(s) from sensors attached to the recipient and developing the artefact model at least in part based thereon (Fig. 2, “recorded data”, para. [0009-0010], “neuronal action potentials may be an electrically evoked compound action potential, for example, as determined for a cochlear implant … measuring the waveform signal at the target tissue …”, para. [0013], para. [0018], “patient dependent waveform is derived dynamically … measurement starts with the a priori derived waveform … standard optimization algorithms, the stimulus artifact waveform can be changed to be optimized for the actual measure waveform …”).
Regarding claim 52, Strahl discloses the method of claim 1, further comprising: adjusting a medical device based on the obtained neural response data so that the medical device operates differently (para. [0013], “cochlear implants … electrical stimulation signal is derived based on satisfying a cost function … improved removal of the stimulus artifact …”).
Regarding claim 54, Strahl discloses the method of claim 1, wherein: the artefact model excludes neural response data (Fig. 2, “stimulus artifact”, para. [0010], “removing the stimulus artifact from the waveform signal …”, para. [0018], “stimulus artifact waveform …” - the stimulus artifact waveform excludes the neural response data, the NAP).
Regarding claim 55, Strahl discloses the method of claim 1, wherein: the neural response data is based on a phenomenon that decays faster than decay of a phenomenon upon which the artefact model is based (Fig. 2, the NAP decays faster than the stimulus artifact, para. [0013], para. [0015]; Further, para. [0068] of the instant specification recites the decay response is due to ECAP).
Regarding claim 56, Strahl discloses the method of claim 1, wherein: the electrical stimulation evokes a neural response in the recipient (Fig. 2, para. [0009-0010], “cochlear implant … applying the electrical stimulation signal to target neural tissue”, para. [0013], “processing electrically evoked compound action potentials (ECAP) … which contain … a neuronal action potential (NAPs) component”); and the obtained neural response data is data corresponding to the neural response in the recipient (para. [0010], “removing the stimulus artifact from the waveform signal using a source separation algorithm that leaves the neuronal action potential signal remaining”).
Regarding claim 57, Strahl discloses the method of claim 1, wherein: the obtained read data includes neural response data and non-neural response data (Fig. 2, para. [0009-0010], “cochlear implant … applying the electrical stimulation signal to target neural tissue”, para. [0013], “processing electrically evoked compound action potentials (ECAP) … which contain a stimulus artifact component and a neuronal action potential (NAPs) component”); and the action of obtaining the neural response data includes removing the non-neural response data from the neural response data (para. [0010], “removing the stimulus artifact from the waveform signal using a source separation algorithm that leaves the neuronal action potential signal remaining”).
Regarding claim 58, Strahl discloses the method of claim 1, wherein: the obtained read data includes neural response data and non-neural response data (Fig. 2, para. [0009-0010], “cochlear implant … applying the electrical stimulation signal to target neural tissue”, para. [0013], “processing electrically evoked compound action potentials (ECAP) … which contain a stimulus artifact component and a neuronal action potential (NAPs) component”; and the action of obtaining the artefact model includes constructing the artefact model based on the non-neural response data (para. [0018], “patient dependent waveform is derived dynamically … measurement starts with the a priori derived waveform … standard optimization algorithms, the stimulus artifact waveform can be changed to be optimized for the actual measure waveform …”).
Response to Arguments
Applicant’s arguments with respect to claims 1, 3, 7-9, 38, 44, 45, 52, 56, and 57 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.
Claim Rejections - 35 USC § 103 - Withdrawn and Newly Applied
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 5 and 6 are rejected under 35 U.S.C. 103 as being unpatentable over Stefan Strahl (US 20100069996 A1), hereinafter referred to as Strahl as applied to claim 1 above, and further in view of Peter Single (US 20170049345 A1) (previously cited), hereinafter referred to as Single.
Regarding claim 5 and claim 6, Strahl discloses the method of claim 1.
However, Strahl does not explicitly disclose wherein the artefact model is based on a constant phase model (claim 5), or wherein the artefact model is based on a true constant phase model (claim 6).
Single teaches of an analogous method (Abstract), specifically of measuring a neural response to a stimulus (para. [0010]). Single teaches applying an electrical stimulus to a patient (para. [0011]) and obtaining a neural response data by comparing read data with an artefact model (para. [0069-0070]). Single further teaches the artefact model is based on a constant phase or a true constant phase (para. [0019], para. [0045-0047], para. [0053], para. [0059]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the artefact model disclosed by Strahl to explicitly be a constant phase model or a true constant phase model, as taught by Single. This is because Single teaches by using a constant phase model or a true constant phase model it allows for sources of artefacts to be reduced, specifically from the electrode-electrolyte interface capacitance and tissue capacitance (para. [0019], para. [0070]).
Claim 40 is rejected under 35 U.S.C. 103 as being unpatentable over Stefan Strahl (US 20100069996 A1), hereinafter referred to as Strahl as applied to claim 1 above, and further in view of Paul Holmberg (US 20130114835 A1) (previously cited), hereinafter referred to as Holmberg.
Regarding claim 40, Strahl discloses the method of claim 1.
However, Strahl does not explicitly disclose wherein the action of obtaining the neural response data includes developing the neural response data without introducing additional thermal and/or quantization noise.
Holmberg teaches of an analogous method (Abstract, Fig. 4, para. [0006]). Holmberg further teaches obtaining the neural response data includes developing the neural response data without introducing additional thermal noise (Fig. 4, para. [0032], para. [0038]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method disclosed by Strahl to additionally develop the neural response data without introducing additional thermal and/or quantization noise, as taught by Holmberg. This is because Holmberg teaches the presence of thermal noise may make hearing difficult or unpleasant for a user of a hearing prosthesis, and eliminating thermal noise improves the experience for the user (para. [0005]).
Claims 43, 46-47, 49-51, and 53 are rejected under 35 U.S.C. 103 as being unpatentable over Stefan Strahl (US 20100069996 A1), hereinafter referred to as Strahl as applied to claim 1 above, and further in view of Long et al. (US 20150258337 A1) (previously cited), hereinafter referred to as Long.
Regarding claim 43, Strahl discloses the method of claim 1.
However, Strahl does not explicitly disclose wherein: the action of obtaining from read electrodes read data is executed in a plurality of temporally spaced obtaining actions; and the action of obtaining an artefact model is executed by repeatedly developing embryonic models, at least some of which are based on respective separate data sets of the read data.
Long teaches an analogous method, specifically for reducing a stimulation artefact of an implantable stimulator (Abstract, para. [0006]). Long teaches obtaining from read electrodes read data resulting from an applied stimulation (para. [0059-0060]), and obtaining an artefact model based at least in part on the read data (para. [0061]). Long further teaches the action of obtaining from read electrodes read data is executed in a plurality of temporally spaced obtaining actions (para. [0059]), and the action of obtaining an artefact model is executed by repeatedly developing embryonic models, at least some of which are based on respective separate data sets of the read data (para. [0049-0051], para. [0085-0086]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method disclosed by Strahl to additionally obtain from read electrodes read data in a plurality of temporally spaced obtaining actions; and obtain an artefact model by repeatedly developing embryonic models, at least some of which are based on respective separate data sets of the read data, as taught by Long. This is because Long teaches a plurality of temporally spaced data allows for artefacts at different locations to be mitigated (para. [0049]), and developing embryonic models, which are based on separate data sets, allows for the artefact model to be repeatedly adjusted until the model reaches an acceptable level (para. [0085]).
Regarding claim 46, Strahl discloses the method of claim 1.
However, Strahl does not explicitly disclose wherein the action of obtaining the model includes: obtaining one or more temporally and/or frequency based dataset(s) from sensors attached to the recipient; developing various iterations of embryonic models, all of which are intended to be different from the temporally and/or frequency based dataset(s); and using one of the iterations as a basis for the obtained artefact model.
Long teaches an analogous method, specifically for reducing a stimulation artefact of an implantable stimulator (Abstract, para. [0006]), including obtaining an artefact model based at least in part on read data (para. [0061]). Long further teaches wherein the action of obtaining the model includes: obtaining one or more temporally and/or frequency based dataset(s) from sensors attached to the recipient (para. [0058-0059]); developing various iterations of embryonic models, all of which are intended to be different from the temporally and/or frequency based dataset(s) (para. [0049-0051], para. [0085-0087]); and using one of the iterations as a basis for the obtained artefact model (para. [0086]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method disclosed by Strahl to additionally include obtaining one or more temporally and/or frequency based dataset(s) from sensors attached to the recipient; developing various iterations of embryonic models, all of which are intended to be different from the temporally and/or frequency based dataset(s); and using one of the iterations as a basis for the obtained artefact model, as taught by Long. This is because Long teaches obtaining temporally based data sets, developing various iterations of embryonic models that are different, and using one of the iterations as a basis for the obtain artefact model, allows for the artefact model to be repeatedly adjusted until the model reaches an acceptable level (para. [0085]).
Regarding claim 47, Strahl discloses the method of claim 1.
However, Strahl does not explicitly disclose wherein the action of obtaining the artefact model includes: obtaining one or more temporally and/or frequency based dataset(s) from sensors attached to the recipient; developing various iterations of embryonic models based on the dataset(s); comparing at least some of the respective various iterations of the embryonic models to the dataset(s) in an iterative manner, while making adjustments to the respective iteration to further drive the next embryonic model towards the dataset(s); selecting an iteration of the embryonic model from a subset of one or more of the iterations of the embryonic models where further adjustments of the subset will result in a statistically insignificant difference between the embryonic model and the dataset.
Long teaches an analogous method, specifically for reducing a stimulation artefact of an implantable stimulator (Abstract, para. [0006]), including obtaining an artefact model based at least in part on read data (para. [0061]). Long further teaches wherein the action of obtaining the model includes: obtaining one or more temporally and/or frequency based dataset(s) from sensors attached to the recipient (para. [0058-0059]); developing various iterations of embryonic models based on the dataset(s) (para. [0049-0051], para. [0085-0087]); comparing at least some of the respective various iterations of the embryonic models to the dataset(s) in an iterative manner, while making adjustments to the respective iteration to further drive the next embryonic model towards the dataset(s) (para. [0085-0087]); selecting an iteration of the embryonic model from a subset of one or more of the iterations of the embryonic models where further adjustments of the subset will result in a statistically insignificant difference between the embryonic model and the dataset (para. [0085-0087]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method disclosed by Strahl to additionally include obtaining one or more temporally and/or frequency based dataset(s) from sensors attached to the recipient; developing various iterations of embryonic models based on the dataset(s); comparing at least some of the respective various iterations of the embryonic models to the dataset(s) in an iterative manner, while making adjustments to the respective iteration to further drive the next embryonic model towards the dataset(s); selecting an iteration of the embryonic model from a subset of one or more of the iterations of the embryonic models where further adjustments of the subset will result in a statistically insignificant difference between the embryonic model and the dataset, as taught by Long. This is because Long teaches obtaining temporally based data sets, developing various iterations of embryonic models, comparing at least some of the respective various iterations to the datasets, and selecting an iteration that results in a statistically insignificant difference, allows for the artefact model to be repeatedly adjusted until the model reaches an acceptable level (para. [0085]).
Regarding claim 49, modified Strahl discloses the method of claim 47.
However, modified Strahl does not explicitly disclose the one or more temporally and/or frequency based dataset(s) is/are dataset(s) where the obtained neural response is overwhelmed by an artefact.
Long further teaches the one or more temporally and/or frequency based dataset(s) is/are dataset(s) where the obtained neural response is overwhelmed by an artefact (para. [0038-0039]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the datasets taught by modified Strahl to explicitly be overwhelmed by an artefact, as taught by Long. This is because Long teaches in an ECAP measurement, artefacts overwhelm the actual ECAP response (para. [0039]), and datasets that include the artefacts allow for the model to more accurately obtained to obtain the neural response data, as taught by Long.
Regarding claim 50, modified Strahl discloses the method of claim 46, further comprising: using one or more of the iterations individually or and/or collectively as the model to compare to the temporally and/or frequency based dataset(s) to determine neural response based on the comparison (para. [0010], “removing the stimulus artifact from the waveform signal using a source separation algorithm that leaves the neuronal action potential signal remaining”).
Regarding claim 51, modified Strahl discloses the method of claim 50, wherein: the comparison to the temporally and/or frequency based dataset(s) yields a difference between the temporally and/or frequency based dataset(s) and the artefact model, the difference being the neural response (Fig. 2, para. [0010], “removing the stimulus artifact from the waveform signal using a source separation algorithm that leaves the neuronal action potential signal remaining”).
Regarding claim 53, Strahl discloses the method of claim 1.
However, Strahl does not explicitly disclose wherein: the obtained read data includes residual artefacts of the electrical stimulation which are at least 0.1 orders of magnitude larger than a signal of interest in the read data, wherein the signal of interest in the read data corresponds to data resulting from a neural response created by the action of applying the electrical stimulation to the recipient.
Long teaches an analogous method, specifically for reducing a stimulation artefact of an implantable stimulator (Abstract, para. [0006]). Long further teaches wherein: the obtained read data includes residual artefacts of the electrical stimulation which are at least 0.1 orders of magnitude larger than a signal of interest in the read data, wherein the signal of interest in the read data corresponds to data resulting from a neural response created by the action of applying electrical stimulation to the recipient (para. [0038-0039]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method disclosed by Strahl to additionally include obtained read data with residual artefacts of the electrical stimulation which are at least 0.1 orders of magnitude larger than a signal of interest in the read data, wherein the signal of interest in the read data corresponds to data resulting from a neural response created by the action of applying electrical stimulation to the recipient, as taught by Long. This is because Long teaches ECAP measurement methods allow for information pertaining to the response of the nerves to electrical stimulus to be measured (para. [0038-0041]), and allow for stimulus artifacts to be removed to accurately obtain the neural response data.
Claim 44 is rejected under 35 U.S.C. 103 as being unpatentable over Stefan Strahl (US 20100069996 A1), hereinafter referred to as Strahl as applied to claim 1 above, and further in view of Patrick et al. (US 20140350640 A1), hereinafter referred to as Patrick.
Regarding claim 44, Strahl discloses the method of claim 1.
However, Strahl does not explicitly disclose wherein: the read electrodes are platinum electrodes.
Patrick teaches an analogous method, comprising obtaining from read electrodes read data (Abstract, para. [0008], para. [0103-0104]). Patrick further teaches the read electrodes are platinum electrodes (para. [0103-0104]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the read electrodes disclosed by Strahl to explicitly be platinum electrodes, as taught by Patrick. This is because Patrick teaches platinum is a suitable conductive material for electrodes, specifically for cochlear implants (para. [0103-0104]).
Response to Arguments
Applicant’s arguments with respect to claims 5-6, 40, 48-49, 53, and 55 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.
Conclusion
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/K.W.K./Examiner, Art Unit 3791
/JASON M SIMS/Supervisory Patent Examiner, Art Unit 3791