DETAILED ACTION
1. This communication is in response to the Application No. 18/412,935 filed on January 15, 2024 in which Claims 1-11 are presented for examination.
Notice of Pre-AIA or AIA Status
2. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
3. The information disclosure statements submitted on 01/15/2024 and 11/29/2024 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
Claim Interpretation
4. The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
5. The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
6. This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier.
Such claim limitation(s) is/are:
“data management unit” in Claims 7-11
“training management unit” in Claims 7-11
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 101
7. 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.
8. Claims 1-11 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding Claim 1:
Step 1: Claim 1 is a method type claim. Therefore, Claims 1-6 are directed to either a process, machine, manufacture, or composition of matter.
2A Prong 1: If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation by mathematical calculation but for the recitation of generic computer components, then it falls within the “Mathematical Concepts” grouping of abstract ideas.
a method for managing training data of a biosignal analysis model […] (mental process – methods for managing training data of a biosignal analysis model may be performed manually by a user observing/analyzing the training data of a biosignal analysis model and accordingly using judgement/evaluation to manage the training data (by augmenting the data with the aid of pen and paper, adding/removing training data, etc.))
converting data on at least one of a plurality of leads into augmented data associated with a specific lead among the plurality of leads (mathematical process – converting data on at least one of a plurality of leads into augmented data associated with a specific lead among the plurality may be performed by mathematical process by calculating and correcting the phase of the data on other leads with respect to the phase of the data on the specific lead, utilizing a magnitude difference and/or phase difference – as described by Applicant’s specification Par. [0043-0044])
determining arrhythmia on the basis of data on the specific lead […] (mental process – determining arrhythmia on the basis of data on the specific lead may be performed manually by a user observing/analyzing the augmented data and the data on the specific lead and accordingly using judgement/evaluation to identify and determine potential anomalies/outliers which may indicate an arrhythmia on the basis of data on the specific lead)
2A Prong 2: This judicial exception is not integrated into a practical application.
Additional elements:
training an analysis model for […] using the augmented data and the data on the specific lead as training data (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f) – Examiner’s note: high level recitation of training a machine learning model with previously determined data without significantly more)
2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Additional elements:
training an analysis model for […] using the augmented data and the data on the specific lead as training data (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f) – Examiner’s note: high level recitation of training a machine learning model with previously determined data without significantly more. This cannot provide an inventive concept)
For the reasons above, Claim 1 is rejected as being directed to an abstract idea without significantly more. This rejection applies equally to dependent claims 1-6. The additional limitations of the dependent claims are addressed below.
Regarding Claim 2:
Step 2A Prong 1:
See the rejection of Claim 1 above, which Claim 2 depends on.
Step 2A Prong 2 & Step 2B:
wherein in the converting step, the data on the at least one lead and the data on the specific lead are vectorized (Field of Use – limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception does not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application; in this case specifying that the data on the at least one lead and the data on the specific lead are vectorized does not integrate the exception into a practical application nor amount to significantly more – See MPEP 2106.05(h))
Accordingly, under Step 2A Prong 2 and Step 2B, these additional elements do not integrate the abstract idea into practical application because they do not impose any meaningful limits on practicing the abstract idea, as discussed above in the rejection of claim 1.
Regarding Claim 3:
Step 2A Prong 1: See the rejection of Claim 2 above, which Claim 3 depends on.
wherein in the converting step, information on a difference between the vectorized data on the at least one lead and the vectorized data on the specific lead is calculated (mathematical process – calculating a difference between the vectorized data on the at least one lead and the vectorized data on the specific lead may be performed by mathematical process/calculation utilizing a phase difference or magnitude difference as described by Applicant’s specification Par. [0043-0044])
Step 2A Prong 2 & Step 2B:
Accordingly, under Step 2A Prong 2 and Step 2B, these additional elements do not integrate the abstract idea into practical application because they do not impose any meaningful limits on practicing the abstract idea, as discussed above in the rejection of claim 1.
Regarding Claim 4:
Step 2A Prong 1: See the rejection of Claim 3 above, which Claim 4 depends on.
wherein in the converting step, the data on the at least one lead is converted into the augmented data by correcting the data on the at least one lead with respect to the data on the specific lead with reference to the calculated information on the difference (mathematical process – correcting data on the at least one lead with respect to the data on the specific lead with reference to the calculated information on the difference may be performed by mathematical process, as described by Applicant’s specification Par. [0042-0046])
Step 2A Prong 2 & Step 2B:
Accordingly, under Step 2A Prong 2 and Step 2B, these additional elements do not integrate the abstract idea into practical application because they do not impose any meaningful limits on practicing the abstract idea, as discussed above in the rejection of claim 1.
Regarding Claim 5:
Step 2A Prong 1:
See the rejection of Claim 4 above, which Claim 5 depends on.
Step 2A Prong 2 & Step 2B:
wherein the calculated information on the difference includes at least one of information on a phase difference and information on a magnitude difference (Field of Use – limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception does not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application; in this case specifying that the calculated information includes at least one of information on a phase difference and information on a magnitude difference does not integrate the exception into a practical application nor amount to significantly more – See MPEP 2106.05(h))
Accordingly, under Step 2A Prong 2 and Step 2B, these additional elements do not integrate the abstract idea into practical application because they do not impose any meaningful limits on practicing the abstract idea, as discussed above in the rejection of claim 1.
Regarding Claim 6:
Step 2A Prong 1:
See the rejection of Claim 1 above, which Claim 6 depends on.
Step 2A Prong 2 & Step 2B:
a non-transitory computer-readable recording medium having stored thereon a computer program for executing the method of Claim 1 (mere instructions to apply the exception using generic computer components cannot provide an inventive concept)
Accordingly, under Step 2A Prong 2 and Step 2B, these additional elements do not integrate the abstract idea into practical application because they do not impose any meaningful limits on practicing the abstract idea, as discussed above in the rejection of claim 1.
Independent Claim 7 recites substantially the same limitations as Claim 1, in the form of a system, including generic computer components. The claim is also directed to performing mental processes/mathematical calculations without significantly more, therefore it is rejected under the same rationale.
For the reasons above, Claim 7 is rejected as being directed to an abstract idea without significantly more. This rejection applies equally to dependent claims 8-11. The additional limitations of the dependent claims are addressed below.
Claim 8 recites substantially the same limitations as Claim 2, in the form of a system, including generic computer components. The claim is also directed to performing mental processes/mathematical calculations without significantly more, therefore it is rejected under the same rationale.
Claim 9 recites substantially the same limitations as Claim 3, in the form of a system, including generic computer components. The claim is also directed to performing mental processes/mathematical calculations without significantly more, therefore it is rejected under the same rationale.
Claim 10 recites substantially the same limitations as Claim 4, in the form of a system, including generic computer components. The claim is also directed to performing mental processes/mathematical calculations without significantly more, therefore it is rejected under the same rationale.
Claim 11 recites substantially the same limitations as Claim 5, in the form of a system, including generic computer components. The claim is also directed to performing mental processes/mathematical calculations without significantly more, therefore it is rejected under the same rationale.
Claim Rejections - 35 USC § 102
9. 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.
10. Claims 1-2 and 7-8 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Zhang et al. (hereinafter Zhang) (“MLBF-Net: A Multi-Lead-Branch Fusion Network for Multi-Class Arrhythmia Classification Using 12-Lead ECG”).
Regarding Claim 1, Zhang teaches a method for managing training data of a biosignal analysis model (Zhang, Pg. 1, Abstract, “To maximize the information learning of multi-lead ECG, the information fusion of comprehensive features with integrity and lead-specific features with diversity should be taken into account. In this paper, we propose a novel Multi-Lead-Branch Fusion Network (MLBF-Net) architecture for arrhythmia classification by integrating multi-loss optimization to jointly learning diversity and integrity of multi-lead ECG.”, thus, methods for managing training data (lead-specific features) of a biosignal analysis model (multi-lead-branch fusion network) are disclosed), the method comprising steps of:
converting data on at least one of a plurality of leads into augmented data associated with a specific lead among the plurality of leads (Zhang, Pg. 5, Section C. Multi-Lead Feature Fusion Learning, “For learning complementary cross-lead information and pro viding more robust diagnosis, we fuse the features extracted from each lead by concatenating the lead-specific feature maps fBiGRUj of all branches in channel axis: F = Cat(fBiGRU1 ,fBiGRU2 ,...,fBiGRU12 ) (8) Then the concatenated feature map F is fed through the same attention module used in BranchNet to build the concatenated network. The concatenated network shares the feature maps from the input Xj to the output fBiGRUj of BiGRU layer with each branch for obtaining the comprehensive prediction based on 12-leadECG.Similartosinglelead-branchtraining, a cross-entropy loss is also employed to train the concatenated network, calculated as: […]”, therefore, data on at least one of a plurality of leads may be converted into augmented data associated with a specific lead among the plurality of leads, as the features of each lead (lead-specific feature maps) are extracted and fused using concatenation. Section D. Joint Optimization with Multiple Losses similarly describes how lead-specific branches are interrelated and used to jointly learn the diversity and integrity of a multi-lead ECG); and
training an analysis model for determining arrhythmia on the basis of data on the specific lead, using the augmented data and the data on the specific lead as training data (Zhang, Pg. 5, Section D. Joint Optimization with Multiple Losses, “The loss for each branch is designed to optimize lead-specific features for maximizing the discriminative capability of single-lead ECG, and the loss for the concatenated network aims to optimize multi-lead comprehensive features simultaneously. For the training of the whole model, the final loss function is defined as: L =Lc+λ(L1 +...+L12) (10) where λ is a balance parameter used for determining the importance ratio between diversity and integrity, which is set to 1 in our experiments. Lc and Lj are the cross-entropy losses of the concatenated network and the jth branch, respectively.” & Pg. 1, Abstract, “. In this paper, we propose a novel Multi-Lead-Branch Fusion Network (MLBF-Net) architecture for arrhythmia classification by integrating multi-loss optimization to jointly learning diversity and integrity of multi-lead ECG”, therefore, an analysis model is trained for determining arrhythmia on the basis of data on the specific lead, using the augmented data (concatenated data) and the data on the specific lead – this is similarly supported by Pgs. 6-7 Section 2) Training Setting which further details the training data/specifications used to train the model).
Regarding Claim 2, Zhang teaches the method of Claim 1, wherein in the converting step, the data on the at least one lead and the data on the specific lead are vectorized (Zhang, Pg. 5, Section C. Multi-Lead Feature Fusion Learning, “For learning complementary cross-lead information and pro viding more robust diagnosis, we fuse the features extracted from each lead by concatenating the lead-specific feature maps fBiGRUj of all branches in channel axis: F = Cat(fBiGRU1 ,fBiGRU2 ,...,fBiGRU12 ) (8)”, thus, the data on the at least one lead and the data on the specific lead are vectorized to provide a concatenated feature map).
Regarding Claim 7, Zhang teaches a system for managing training data of a biosignal analysis model (Zhang, Pg. 1, Abstract, “To maximize the information learning of multi-lead ECG, the information fusion of comprehensive features with integrity and lead-specific features with diversity should be taken into account. In this paper, we propose a novel Multi-Lead-Branch Fusion Network (MLBF-Net) architecture for arrhythmia classification by integrating multi-loss optimization to jointly learning diversity and integrity of multi-lead ECG.”, thus, a system for managing training data (lead-specific features) of a biosignal analysis model (multi-lead-branch fusion network) is disclosed), the system comprising: a data management unit […] and a training management unit (Zhang, Pg. 3, Section A. Model Overview, “The proposed Multi-Lead-Branch Fusion Network (MLBF Net) is illustrated in Fig. 1. It is mainly composed of three components: 1) multiple lead-specific branches for learning the diversity of multi-lead ECG; 2) cross-lead features fusion by concatenating the output feature maps of all branches for learning the integrity of multi-lead ECG; 3) multi-loss co-optimization for all the individual branches and the concatenated network. These three components are described in detail below.”, therefore, the system is comprised of multiple units/components, including a data management unit for cross-lead feature fusion and a training management unit for multi-loss co-optimization for all individual branches and the network as a whole) […]
The rest of the claim language in Claim 7 recites substantially the same limitations as Claim 1, in the form of a system, therefore it is rejected under the same rationale.
Claim 8 recites substantially the same limitations as Claim 2, in the form of a system, therefore it is rejected under the same rationale.
Claim Rejections - 35 USC § 103
11. 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.
12. Claims 3-6 and 9-11 are rejected under 35 U.S.C. 103 as being unpatentable over Zhang et al. (hereinafter Zhang) (“MLBF-Net: A Multi-Lead-Branch Fusion Network for Multi-Class Arrhythmia Classification Using 12-Lead ECG”), in view of Xue et al. (hereinafter Xue) (US PG-PUB 20080132799).
Regarding Claim 3, Zhang teaches the method of Claim 2.
Zhang does not explicitly disclose wherein in the converting step, information on a difference between the vectorized data on the at least one lead and the vectorized data on the specific lead is calculated.
However, Xue teaches wherein in the converting step, information on a difference between the vectorized data on the at least one lead and the vectorized data on the specific lead is calculated (Xue, Par. [0023], “FIG. 1 b depicts a generalized ECG signal 40 and a plurality of new T wave morphological features. The new morphological features are more sensitive to changes in the ion channels of the cardiac cells caused by either congenital factors or by drug induced factors. The ECG signal 40 can be from an individual lead, a composite lead formed from all of the leads, such as the vector magnitude of a 12 lead ECG, or the ECG signal 40 can be from the eigenvectors obtained by principal component analysis.”, thus, information on a difference between the vectorized data on the at least one lead and the vectorized data on the specific lead is calculated (vector magnitude)).
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of claim 2, as disclosed by Zhang to include wherein in the converting step, information on a difference between the vectorized data on the at least one lead and the vectorized data on the specific lead is calculated, as disclosed by Xue. One of ordinary skill in the art would have been motivated to make this modification to improve data mining capabilities for the detection of correlated lead features, hence enhancing system accuracy and efficiency (Xue, Par. [0023], “FIG. 1 b depicts a generalized ECG signal 40 and a plurality of new T wave morphological features. The new morphological features are more sensitive to changes in the ion channels of the cardiac cells caused by either congenital factors or by drug induced factors. The ECG signal 40 can be from an individual lead, a composite lead formed from all of the leads, such as the vector magnitude of a 12 lead ECG, or the ECG signal 40 can be from the eigenvectors obtained by principal component analysis.” & Par. [0050], “The method of the present invention provides the advantage of improved data mining capability for the detection of correlated ECG morphological features by analyzing the data in such a way as to reduce the significant data load thus enabling the processing of the collected ECG data to look for correlations among many morphological features with greater efficiency.”)
Regarding Claim 4, Zhang in view of Xue teaches the method of Claim 3, wherein in the converting step, the data on the at least one lead is converted into the augmented data by correcting the data on the at least one lead with respect to the data on the specific lead with reference to the calculated information on the difference (Zhang, Par. [0041], “Signals from ECG signal data database 22 are used to create a model ECG principal component analysis in step 24. The creation of the model principal component analysis in step 24 allows a clinician to select specific ECG signal data or groups of ECG signal data from the ECG signal data database 22 in order to create a specifically tailored ECG model principal component analysis to aid in analyzing specific portions, components, or features of the collected patient ECG signal data.”, therefore, the data may be converted by correcting the data (using the principal component analysis) on the at least one lead with respect to the data on the specific lead with reference to the calculated information on the difference (vector magnitude disclosed by Par. [0023])).
Regarding Claim 5, Zhang in view of Xue teaches the method of Claim 4, wherein the calculated information on the difference includes at least one of information on a phase difference and information on a magnitude difference (Xue, Par. [0023], “FIG. 1 b depicts a generalized ECG signal 40 and a plurality of new T wave morphological features. The new morphological features are more sensitive to changes in the ion channels of the cardiac cells caused by either congenital factors or by drug induced factors. The ECG signal 40 can be from an individual lead, a composite lead formed from all of the leads, such as the vector magnitude of a 12 lead ECG, or the ECG signal 40 can be from the eigenvectors obtained by principal component analysis.”, thus, information on the difference includes at least one of information on a magnitude difference (vector magnitude)).
The reasons of obviousness have been noted in the rejection of Claim 3 above and applicable herein.
Regarding Claim 6, Zhang in view of Xue teaches a non-transitory computer-readable recording medium having stored thereon a computer program for executing the method (Xue, Claim 20, “A computer program embodied on a computer readable medium having computer logic for enabling at least one processor in a computer system to facilitate analyzing an ECG signal collected as part of a pharmacological drug trial, the computer readable medium comprising: […]”, therefore, a computer-readable recording medium having stored thereon a computer program/instructions for executing methods is disclosed) of Claim 1 (See the rejection of Claim 1 above).
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method for managing training data of a biosignal analysis model of claim 1, as disclosed by Zhang to include a non-transitory computer-readable recording medium having stored thereon a computer program for executing the method of claim 1, as disclosed by Xue. One of ordinary skill in the art would have been motivated to make this modification to enable the use of a non-transitory computer readable medium which may store programs and/or logic for enabling the efficient management of training data of the biosignal analysis model (Xue, Claim 20, “A computer program embodied on a computer readable medium having computer logic for enabling at least one processor in a computer system to facilitate analyzing an ECG signal collected as part of a pharmacological drug trial, the computer readable medium comprising: […]”).
Claim 9 recites substantially the same limitations as Claim 3, in the form of a system, therefore it is rejected under the same rationale.
Claim 10 recites substantially the same limitations as Claim 4, in the form of a system, therefore it is rejected under the same rationale.
Claim 11 recites substantially the same limitations as Claim 5, in the form of a system, therefore it is rejected under the same rationale.
Conclusion
13. The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure:
Tripathy et al. (“Detection of Life Threatening Ventricular Arrhythmia Using Digital Taylor Fourier Transform”) disclosed methods for detecting and classifying life-threatening ventricular arrhythmia episodes by decomposing the ECG signal into various oscillatory modes using digital Taylor-Fourier transform, including evaluating magnitude and phase difference.
14. Any inquiry concerning this communication or earlier communications from the examiner should be directed to Devika S Maharaj whose telephone number is (571)272-0829. The examiner can normally be reached Monday - Thursday 8:30am - 5:30pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Alexey Shmatov can be reached at (571)270-3428. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/DEVIKA S MAHARAJ/Examiner, Art Unit 2123
Prosecution Insights