Patent Application 18227480 - METHOD AND SYSTEM FOR GENERATING 2D - Rejection

Patent Application 18227480 - METHOD AND SYSTEM FOR GENERATING 2D

Title: METHOD AND SYSTEM FOR GENERATING 2D REPRESENTATION OF ELECTROCARDIOGRAM (ECG) SIGNALS

Application Information

• Invention Title: METHOD AND SYSTEM FOR GENERATING 2D REPRESENTATION OF ELECTROCARDIOGRAM (ECG) SIGNALS
• Application Number: 18227480
• Submission Date: 2025-05-15T00:00:00.000Z
• Effective Filing Date: 2023-07-28T00:00:00.000Z
• Filing Date: 2023-07-28T00:00:00.000Z
• National Class: 705
• National Sub-Class: 002000
• Examiner Employee Number: 85229
• Art Unit: 3685
• Tech Center: 3600

Rejection Summary

• 102 Rejections: 0
• 103 Rejections: 1

Cited Patents

The following patents were cited in the rejection:

• US 0061797🔗
• US 0230105🔗

Office Action Text

    DETAILED ACTION
Status
This communication is in response to the application filed on 28 July 2023. Claims 1-15 are pending and presented for examination.

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 . 

Priority
Applicant’s claim for Foreign Priority to Indian Application No. IN202221050616, filed on 5 September 2022, is acknowledged.

Information Disclosure Statement
The information disclosure statement (IDS) submitted on 28 July 2023 was filed after the mailing date of the application on 28 July 2023. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.

Examiner’s Note
The Examiner notes that the terms “left R-peak” and “right R-peak” are merely referring to, in the light of the specification, the R-peak (i.e., heartbeat) on the left and right peaks of a 2-beat segment of the ECG. In reference to Figs. 4A-4C, the heartbeats of Fig. 4A are “segmented” into peaks or beats 1 and 2 at Fig. 4B, and peaks or beats 3 and 4 are “segmented” at Fig. 4C. Therefore, the generating element of claim 1 necessarily is merely showing (i.e., “generating”) the normally displayed peaks of a traditionally or usual ECG.

 The Examiner further notes that the terms “ECG” and “EKG” are understood to be synonymous.

The Examiner notes that claims 5, 10, and 15 recite “the 2D representation establishes a temporal dependency between different R- peaks”; however, as best understood by light of the specification, any “temporal dependency” is a fact of, or is established by, the time information of the ECG signal – the 2D representation apparently merely illustrates that there may be some variation or variance between different segments, i.e., heart beats.

Claim Objections
Claims 2, 7, and 12 are objected to because of the following informalities: 
Claims 2, 7, and 12 each recite “1-Dinmnsional”, which it is understood should be “1-Dimensional”. Appropriate correction is required.
Claims 2 and 12 each recite “transforming … segments that are 1-Dinmnsional format are into a fixed dimension 2D format” where the second “are” should apparently be deleted – i.e., this should be “transforming … segments that are 1-Dinmnsional format into a fixed dimension 2D format” (as at claim 7).

Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b)  CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.

The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.


Claims 2, 7, and 12 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, or for pre-AIA  the applicant regards as the invention.

Each of claims 2, 7, and 12 indicate “transforming … segments that are 1-Dimensional format into a fixed dimension 2D format” (omitting the spelling and grammar issues as at the objection). However, there is no explanation regarding what a 1-Dimensional format is, nor what constitutes a 2-Dimensional format. The only indication of “1-Dimensional” (or similar terms such as “1D”) is Applicant ¶ 029 (as submitted, 0030 as published), which provides no explanation. The Examiner assumes Fig. 4A is somehow an indication of a “1-Dimensional” format; however, that has height and width dimensions – it is, by definition, 2-Dimensional. There is also no indication of what “fixed” means in “fixed dimension 2D format” – the only mention of this is the same Applicant paragraph, again without explanation.
Each of claims 2, 7, and 12 also continues by indicating “each of a plurality of rows of the 2D format comprises of one left R-peak and one right R-peak and a corresponding morphological information”; however, as above, the only apparent mention of this is the same paragraph, but without any explanation of this. It appears that the “left” and “right” R-peaks are merely the R-peaks to the left and right of each other, but there is no indication of “rows” and what “morphological information” means or encompasses, nor how it could possibly be “corresponding” to anything.
Each of claims 2, 7, and 12 then also continues by indicating “further wherein the 2D format comprises of a plurality of distinct and co-located R-peaks, and a plurality of P-waves representing the morphological information, where the plurality of R-peaks and the plurality of P-waves are separated in time axis based on the R-R intervals”. There is no indication of what is meant by “co-located” R-peaks, there is no indication of how or why P-waves could possibly be “representing … morphological information” (in part because there is no indication of what the morphological information could possibly be.
The Examiner is completely guessing that Applicant is essentially trying to claim Figs. 4B and 4C, or possibly Fig. 4D. However, there is no description of P-waves except a mention at the same paragraph (Applicant ¶ 029 as submitted, 0030 as published) and then the R-peaks and P-waves are, by definition for any ECG or EKG signal, separated in (on) the time axis as the R-R interval represents the time interval between heart beats.
Therefore, as best the Examiner can tell, claims 2, 7, and 12 is best interpreted as merely essentially cutting a typical or usual ECG/EKG strip into individual heart beat segments and aligning the timing of the left-most R-peak for each segment so as to illustrate the variance in R-R interval for each segment.

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 1-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Please see the following Subject Matter Eligibility (“SME”) analysis:

For analysis under SME Step 1, the claims herein are directed to a method (claims 1-5), system (claims 6-10), and non-transitory machine-readable medium (claims 11-15), which would be classified under one of the listed statutory classifications (SME Step 1=Yes).

For analysis under revised SME Step 2A, Prong 1, independent claim 1 recites a processor implemented method, comprising: obtaining, via one or more hardware processors, a raw Electrocardiogram (ECG) signal as input; removing, via a bandpass filter implemented by the one or more hardware processors, noise data from the raw ECG signal to obtain a clean signal; segmenting, via the one or more hardware processors, the clean signal to obtain a plurality of segments, wherein each of the plurality of segments comprises a left R-peak and a right R-peak; arranging, via the one or more hardware processors, the plurality of segments by aligning the left R-peak of the plurality of segments; determining, via the one or more hardware processors, variability between the plurality of segments, in terms of position of the left R-peak and the right R-peak of consecutive segments; and generating (212), via the one or more hardware processors, 2- Dimensional (2D) representation of the segments, wherein in the 2D representation comprises information on relative position of the left R-peak and the right R-peak of each of the segments are captured.
Independent claims 6 and 11 are analyzed in the same manner since claim 6 is directed to a system, comprising: one or more hardware processors; a communication interface; and a memory comprising a plurality of instructions, wherein the plurality of instructions cause the one or more hardware processors to perform the same or similar activities as at claim 1 above, and claim 11 is directed to one or more non-transitory machine-readable information storage mediums comprising one or more instructions which when executed by one or more hardware processors cause the same or similar activities as at claim 1 above.
The dependent claims (claims 2-5, 7-10, and 12-15) appear to be encompassed by the abstract idea of the independent claims since they merely indicate generating a comparison of ECG segments (apparently) (claims 2, 7, and 12), extracting important regions of the ECG signal using an attention mechanism (a form of deep learning in artificial intelligence or machine learning) and training a data model (claims 3, 8, and 13), segmenting based on R-R intervals (claims 4, 9, and 14), and/or what the 2D representation illustrates – a temporal or timing difference between R-peaks of different segments (i.e., heart beats).

The underlined portions of the claims are an indication of elements additional to the abstract idea (to be considered below).
The claim elements may be summarized as the idea of representing ECG/EKG timing differences or variations (such as an R-R interval) from one segment (i.e., heart beat) to another; however, the Examiner notes that although this summary of the claims is provided, the analysis regarding subject matter eligibility considers the entirety of the claim elements, both individually and as a whole (or ordered combination). This idea is within the following grouping(s) of subject matter:
Mathematical concepts (e.g., relationships, formulas, equations, and/or calculations) based on the determining variability of segments, using an attention mechanism (a form of artificial intelligence or machine learning) and training a data model (at some dependent claims);
Certain methods of organizing human activity (e.g. … managing personal behavior or relationships between people such as social activities, teaching, and following rules or instructions) based on using a bandpass filter to remove noise, segmenting ECG/EKG signal data, arranging segments by aligning the initial R-peaks, and generating a 2D representation of segments; and
Mental processes (e.g., concepts performed in the human mind such as observation, evaluation, judgment, and/or opinion) based on the evaluation or judgments to segment ECG/EKG signal data, determine variability between segments, and observe the relative positions of R-peaks.
Therefore, the claims are found to be directed to an abstract idea.

For analysis under revised SME Step 2A, Prong 2, the above judicial exception is not integrated into a practical application because the additional elements do not impose a meaningful limit on the judicial exception when evaluated individually and as a combination. The additional elements are that the method is a processor implemented method, implemented by … one or more hardware processors (at claim 1) a system, comprising: one or more hardware processors; and a memory comprising a plurality of instructions, wherein the plurality of instructions cause the one or more hardware processors to perform activities (at claim 6), and one or more non-transitory machine-readable information storage mediums comprising one or more instructions which when executed by one or more hardware processors cause the activities (at claim 11). These additional elements do not reflect an improvement in the functioning of a computer or an improvement to other technology or technical field, effect a particular treatment or prophylaxis for a disease or medical condition (there is no medical disease or condition, much less a treatment or prophylaxis for one), implement the judicial exception with, or by using in conjunction with, a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing (there is no transformation/reduction of a physical article), and/or apply or use the judicial exception in some other meaningful way beyond generically linking use of the judicial exception to a particular technological environment.
The claims appear to merely apply the judicial exception, include instructions to implement an abstract idea on a computer, or merely use a computer as a tool to perform the abstract idea. The additional elements appear to merely add insignificant extra-solution activity to the judicial exception and/or generally link the use of the judicial exception to a particular technological environment or field of use.

For analysis under SME Step 2B, the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements, as indicated above, are merely “[a]dding the words ‘apply it’ (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, e.g., a limitation indicating that a particular function such as creating and maintaining electronic records is performed by a computer, as discussed in Alice Corp.” that MPEP § 2106.05(I)(A) indicates to be insignificant activity.
There is no indication the Examiner can find in the record regarding any specialized computer hardware or other “inventive” components, but rather, the claims merely indicate computer components which appear to be generic components and therefore do not satisfy an inventive concept that would constitute “significantly more” with respect to eligibility. Applicant ¶ 020 as submitted, 0021 as published, indicates that the processor(s) may be any of a general list indicating a general-purpose computer.
The individual elements therefore do not appear to offer any significance beyond the application of the abstract idea itself, and there does not appear to be any additional benefit or significance indicated by the ordered combination, i.e., there does not appear to be any synergy or special import to the claim as a whole other than the application of the idea itself.
The dependent claims, as indicated above, appear encompassed by the abstract idea since they merely limit the idea itself; therefore the dependent claims do not add significantly more than the idea.
Therefore, SME Step 2B=No, any additional elements, whether taken individually or as an ordered whole in combination, do not amount to significantly more than the abstract idea, including analysis of the dependent claims.  

Please see the Subject Matter Eligibility (SME) guidance and instruction materials at https://www.uspto.gov/patent/laws-and-regulations/examination-policy/subject-matter-eligibility, which includes the latest guidance, memoranda, and update(s) for further information.

NOTICE
In the event the determination of the status of the application as subject to AIA  35 U.S.C. 102 and 103 (or as subject to pre-AIA  35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.  

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 of this title, 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.


Claims 1-15 rejected under 35 U.S.C. 103 as being unpatentable over Geva et al. (U.S. Patent Application Publication No. 2004/0230105, hereinafter Geva) in view of Vernalis et al. (U.S. Patent Application Publication No. 2022/0061797, hereinafter Vernalis).

Claim 1: Geva discloses a processor implemented method, comprising:
obtaining, via one or more hardware processors, a raw Electrocardiogram (ECG) signal as input (see Geva at least at, e.g., ¶ 0203, “"Adaptive Feature Extraction" (AFE) process, which is described immediately herein below. Immediately after obtaining the time series, first features are extracted in step 12 (herein referred to as the "initial features"), which are directly related to the sampled signals. For example, such features may be the morphology of heartbeats and/or shape of portions of heartbeats, and/or heartbeat rate, all of which are derived, in this example, from ECG signals”; citation hereafter by number only) ;
removing, via a … filter implemented by the one or more hardware processors, noise data from the raw ECG signal to obtain a clean signal (0258, “An integral and essential part of the features extraction stage is d[e]riving, from features obtained from raw biomedical signals (being herein referred to as the "initial" features), various new features signals of medical importance (being herein referred to as the "secondary features signals")…. Accordingly, after filtering out noises and environmental artifacts, in step 24 (FIG. 2), essentially noiseless and artifact-free features are obtained, which could be utilized for generation of new features (i.e., secondary features) there from (reference numeral 25)”);
segmenting, via the one or more hardware processors, the clean signal to obtain a plurality of segments, wherein each of the plurality of segments comprises a left R-peak and a right R-peak (0214, “an ECG signal is relatively easily segmented, in a first segmentation process, into heartbeats, which are not necessarily quasi-stationary segments, and each heartbeat is further segmented, in a second segmentation process, into physiological/pathologically significant segments, such as PR, QRS, QT, ST, etc. The first segmentation process (i.e., into heartbeats) is based on detection of "R-waves" of the heartbeats and is carried out by employing the known "Wavelet Transform Algorithm" on the ECG signal”);
determining, via the one or more hardware processors, variability between the plurality of segments, in terms of position of the left R-peak and the right R-peak of consecutive segments (0032, “Referring to an ECG signal, an exemplary initial feature could be the Heart Rate (HR) or the shape of a heartbeat, or of portions thereof, while an exemplary secondary feature could be the Heart Rate complexity index, variance, duration, etc.”, 0077 and 0081, “Temporal Analysis Features… Mean, variance and skewness amplitude”, 0164, “FIG. 11 depicts extraction of Mean, Variance and Duration from the exemplary heart rate (HR) signal shown in FIG. 10”); and
generating (212), via the one or more hardware processors, 2-Dimensional (2D) representation of the segments, wherein in the 2D representation comprises information on relative position of the left R-peak and the right R-peak of each of the segments are captured (Figs. 12a and 12b, 0331, 0334).
Geva, however, does not appear to explicitly disclose that the filter is a bandpass filter, and arranging, via the one or more hardware processors, the plurality of segments by aligning the left R-peak of the plurality of segments. Where Geva does align R-peaks of signal data (Geva at 0413 and Figs. 23a, 23b, and 23c), this is apparently not a stacking of an individual segment or heartbeat. Vernalis, however, indicates displaying a stacked plot of individual segment heart beat signals (Vernalis at 0256 and Fig. 49) and “the data acquisition process 800 commences with step (802) by pre-filtering the electronic signal from the associated auscultatory sound sensor 12, 121′, 122′, 123′, 121″, 122″, 123″ with an analog anti-aliasing filter, for example, an analog second-order band-pass filter having a pass band in the range of 3 Hz to 2.5 KHz, for which the upper-cutoff frequency is sufficiently below the sampling frequency (i.e. no more than half) so as to prevent high frequency components in the signal being sampled from appearing as low frequency components of the sampled signal, i.e. so as to prevent aliasing” (Vernalis at 0123). Therefore, the Examiner understands and finds that to use a band-pass filter and to display a stacked set of left R-peak aligned signals is applying a known technique to a known device, method, or product ready for improvement to yield predictable results so as to display the variance of the R-R interval.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine or modify the ECG analysis and display of Geva with the filtering and display of Vernalis in order to use a band-pass filter and to display a stacked set of left R-peak aligned signals so as to display the variance of the R-R interval.
The rationale for combining in this manner is that to use a band-pass filter and to display a stacked set of left R-peak aligned signals is applying a known technique to a known device, method, or product ready for improvement to yield predictable results so as to display the variance of the R-R interval as explained above.

Claim 2: Geva in view of Vernalis discloses the processor implemented method of claim 1, wherein generating the 2D representation comprises transforming the plurality of segments that are 1-Dinmnsional format are into a fixed dimension 2D format, where each of a plurality of rows of the 2D format comprises of one left R-peak and one right R-peak and a corresponding morphological information, further wherein the 2D format comprises of a plurality of distinct and co- located R-peaks, and a plurality of P-waves representing the morphological information, where the plurality of R-peaks and the plurality of P-waves are separated in time axis based on the R-R intervals (Geva at 0413 and Figs. 23a, 23b, and 23c; Vernalis at 0256, Fig. 49, and 0123, as combined above and using the rationale as at the combination above).

Claim 3: Geva in view of Vernalis discloses the processor implemented method of claim 1 further comprising:
extracting a structural information from the 2D representation, by processing the 2D representation using an attention mechanism, wherein the structural information comprises information on a plurality of important regions of the ECG signal that contribute to classification of the ECG signal as being associated with one or more of a plurality of cardiovascular diseases (CVDs) (Geva at 0004, “life-threatening cardiac arrhythmias (LTCA)”, 0008, “Recent research demonstrated that changes in RR-interval (RRI) series might be a more accurate predictor of imminent LTCA”, 0030, “The present invention is directed to a method for predicting changes of physiological/pathological states in a patient, based on sampling, processing and analyzing a plurality of aggregated noisy biomedical signals”, 0031, “the present invention is characterized by allowing identifying physiological/pathological information that precedes physiological and pathological states, such as heart attacks and epilepsy”, 0099-0102, “employing local maxima detection method, for identifying the R-peaks, P-peaks and T-peaks in the filtered resulting summation, the R, P and T peaks being utilized for characterizing the corresponding heartBeats Under Test (BUTs), the P and T peaks being utilized also for further segmentation of heartbeats. Preferably, obtaining features from ECG signals comprises the steps: a) detecting `R-R` time-intervals between each two consecutive R-peaks; and b) identifying characterizing points `P`, `Q`, `S` and `T` of the corresponding BUTs, by utilizing the `R-R` time-intervals, at least some of the points being utilized for obtaining features related thereto”, 0258, “An integral and essential part of the features extraction stage is d[e]riving, from features obtained from raw biomedical signals (being herein referred to as the ‘initial’ features), various new features signals of medical importance (being herein referred to as the ‘secondary features signals’)”);
transforming the structural information into an ECG domain knowledge, wherein the ECG domain knowledge represents a determined classification of the ECG signal as being associated with one or more of the plurality of CVDs (Geva at 0030-0031, 0099-0102, 0258, as above); and
training a data model by using a) the ECG signal, b) the extracted structural information, and c) information on the domain knowledge the structural information has been transformed to, as a training data (0127, “Different HMM models may be trained to characterize different global physiological/pathological behavior, which may be associated with, e.g., specific group of population, sleep stage or any health condition”, 0239, “the system keeps on updating (i.e., training) itself by referring to additional clinically significant changes that would be used for predicting future events”, 0270, “Two main algorithms are utilized for the training stage: the Baum-Welch algorithm, which is an Expectation Maximization (EM) based algorithm, which is utilized for Maximum Likelhood Estimation (MLE)”).

Claim 4: Geva in view of Vernalis discloses the processor implemented method of claim 1, wherein the clean signal is segmented based on R-R intervals (Geva at 0413 and Figs. 23a, 23b, and 23c; Vernalis at 0256, Fig. 49, and 0123, as combined above and using the rationale as at the combination above).

Claim 5: Geva in view of Vernalis discloses the processor implemented method of claim 1, wherein the 2D representation establishes a temporal dependency between different R-peaks comprising the left R-peaks and right R-peaks of the plurality of segments, and represents relative positions between the R-peaks in different segments (Geva at 0099-0102, “employing local maxima detection method, for identifying the R-peaks, P-peaks and T-peaks in the filtered resulting summation, the R, P and T peaks being utilized for characterizing the corresponding heartBeats Under Test (BUTs), the P and T peaks being utilized also for further segmentation of heartbeats. Preferably, obtaining features from ECG signals comprises the steps: a) detecting `R-R` time-intervals between each two consecutive R-peaks; and b) identifying characterizing points `P`, `Q`, `S` and `T` of the corresponding BUTs, by utilizing the `R-R` time-intervals, at least some of the points being utilized for obtaining features related thereto”).

Claims 6-15 are rejected on the same basis as claims 1-5 above since Geva in view of Vernalis discloses a system, comprising: one or more hardware processors; a communication interface; and a memory comprising a plurality of instructions, wherein the plurality of instructions cause the one or more hardware processors to perform the activities indicated at claims 1-5 above (for claims 6-10), and one or more non-transitory machine-readable information storage mediums comprising one or more instructions which when executed by one or more hardware processors cause the activities indicated at claims 1-5 above (for claims 11-15) (see Geva at 0143-0152, the acquisition and processing means indicating a computer as performing the operations described; Vernalis at 0109, 0111, the system in communication indicating computer activities).

Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.

Electrocardiogram (ECG/EKG), Cleveland Clinic, downloaded 25 April 2025 from https://my.clevelandclinic.org/health/diagnostics/16953-electrocardiogram-ekg indicates that “You may hear the terms EKG and ECG. Both terms mean the same thing: an electrocardiogram. EKG comes from the German word, which uses ‘k’ instead of ‘c.’” (at p. 3)
Ganesh, Prakhar, Attention Mechanism in Deep Learning : Simplified, dated 29 February 2020, downloaded from https://medium.com/@prakhargannu/attention-mechanism-in-deep-learning-simplified-d6a5830a079d, explaining what is meant by “attention mechanism”.


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/SCOTT D GARTLAND/
Primary Examiner, Art Unit 3685