DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
Applicant’s arguments filed 4/19/2026 with respect to the rejections of Claims 2 and 7-14, and Claims 3-6 and 15-16 by dependency, under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor regards as the invention have been fully considered and are persuasive. The Examiner agrees that Applicant’s amendments have resolved the cited indefiniteness issues. Therefore, the rejection has been withdrawn.
Applicant’s arguments with respect to the rejection of Claim 1 under 35 U.S.C. 103 as being unpatentable over US 6507753 B1 to Xue et al. (“Xue”) in view of S. Ansari et al., "A Review of Automated Methods for Detection of Myocardial Ischemia and Infarction Using Electrocardiogram and Electronic Health Records," in IEEE Reviews in Biomedical Engineering, vol. 10, pp. 264-298, 2017 (“Ansari”) and A. Adeli et al., "A Fuzzy Expert System for Heart Disease Diagnosis," Proceedings of the International MultiConference of Engineers and Computer Scientists 2010, Vol I, IMECS 2010, March 17-19, 2010, Hong Kong (“Adeli”) have been fully considered and are persuasive. The Examiner agrees that the combination of Xue, Ansari and Adeli does not disclose “acquiring a raw single-lead electrocardiography (ECG) signal” as recited by amended Claim 1. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of US 10,463,302 B1.
Applicant's arguments regarding the rejection of Claims 1-16 under 35 USC 101 have been fully considered but they are not persuasive. Applicant makes two arguments: (1) that the recited abstract ideas are integrated into a practical application because the claimed invention constitutes an improvement in the functioning of a computer or other technology; and (2) the claimed invention constitutes a particular treatment of prophylaxis which renders the claim patent eligible. The Examiner respectfully disagrees.
With regard to Applicant’s argument that the recited abstract ideas are integrated into a practical application because the claimed invention constitutes an improvement in the functioning of a computer or other technology, Applicant’s argument has been fully considered but is not persuasive. Applicant argues that the provided improvement is “a fast and cost-efficient means for diagnosis of ECG and clinical symptoms,” citing Paras. [0007] through [0008] of the Present Specification. The Examiner does not disagree that such an improvement is provided, but disagrees that the improvement constitutes such an improvement in the functioning of a computer or other technology as would render the claim patent eligible pursuant to MPEP 2106.05(a).
The improvement Applicant highlights is provided by the abstract ideas themselves rather than by an additional element (that is, the particular methodology of diagnosis embodied in those elements explained below and in the previous rejection to be abstract idea provide the improvement). MPEP 2106.05(a) states “[i]t is important to note, the judicial exception alone cannot provide the improvement. The improvement can be provided by one or more additional elements.” As the purported improvement is provided by the judicial exception (i.e., the abstract ideas) rather than any additional element, Applicant’s arguments are not persuasive.
With regard to Applicant’s argument that the claimed invention constitutes a particular treatment of prophylaxis which renders the claim patent eligible, Applicant’s arguments have been fully considered but are not persuasive. Applicant argues on Pg. 13 of Applicant’s Remarks that “‘early detection of a heart attack in a subject’ to prevent ‘losing the golden time for MI patients’” constitutes such a particular prophylaxis as contemplated by MPEP 2106.04(d)(2). The Examiner respectfully disagrees. MPEP 2106.04(d)(2) states “in order to qualify as a ‘treatment’ or ‘prophylaxis’ limitation for purposes of this consideration, the claim limitation in question must affirmatively recite an action that effects a particular treatment or prophylaxis for a disease or medical condition. … If the limitation does not actually provide a treatment or prophylaxis, … then it cannot integrate a judicial exception under the ‘treatment or prophylaxis’ consideration.” Such early detection of a heart attack as Applicant highlights “does not actually provide a treatment or prophylaxis,” and thus “cannot integrate a judicial exception under the ‘treatment or prophylaxis’ consideration.” Applicant’s arguments are thus not persuasive.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., an abstract idea) without significantly more. The rejection is maintained.
Eligibility Step 1 – The Four Categories of Statutory Subject Matter
Claims 1-20 each fall within one of the four categories of statutory subject matter.
Eligibility Step 2A, Prong One
Claims 1-20 recite abstract ideas:
Regarding Independent Claim 1:
“generating, utilizing one or more processors, a denoised ECG signal by applying a first wavelet transform on the raw ECG signal” recites a mathematical concept, and more particularly a mathematical calculation when afforded its broadest reasonable interpretation. See MPEP 2106.04(a)(2)(I). “A mathematical calculation is a mathematical operation (such as multiplication) or an act of calculating using mathematical methods to determine a variable or number, e.g., performing an arithmetic operation such as exponentiation.” MPEP 2106.04(a)(2)(I)(C). A wavelet transform is such a mathematical operation.
“generating, utilizing the one or more processors, an artifact-free ECG signal by applying a second wavelet transform on the denoised ECG signal” recites a mathematical concept, and more particularly a mathematical calculation when afforded its broadest reasonable interpretation. See MPEP 2106.04(a)(2)(I). “A mathematical calculation is a mathematical operation (such as multiplication) or an act of calculating using mathematical methods to determine a variable or number, e.g., performing an arithmetic operation such as exponentiation.” MPEP 2106.04(a)(2)(I)(C). A wavelet transform is such a mathematical operation.
“generating, utilizing the one or more processors, a filtered ECG signal by applying a finite impulse response (FIR) filter on the artifact-free ECG signal” recites a mathematical concept, and more particularly a mathematical calculation when afforded its broadest reasonable interpretation. See MPEP 2106.04(a)(2)(I). “A mathematical calculation is a mathematical operation (such as multiplication) or an act of calculating using mathematical methods to determine a variable or number, e.g., performing an arithmetic operation such as exponentiation.” MPEP 2106.04(a)(2)(I)(C). A finite impulse response filter is such a mathematical operation.
“extracting, utilizing the one or more processors, an averaged ECG signal from the filtered ECG signal, the averaged ECG signal comprising a QRS complex, an ST segment, and a T wave” recites a mathematical concept, and more particularly a mathematical calculation when afforded its broadest reasonable interpretation. See MPEP 2106.04(a)(2)(I). “A mathematical calculation is a mathematical operation (such as multiplication) or an act of calculating using mathematical methods to determine a variable or number, e.g., performing an arithmetic operation such as exponentiation.” MPEP 2106.04(a)(2)(I)(C). The claimed “extracting” is being interpreted as a feature extraction step, with the extracted features subsequently being acquired. Such feature extraction is a mathematical operation.
“acquiring a plurality of ECG features from the averaged ECG signal and the filtered ECG signal” recites a mental process when afforded its broadest reasonable interpretation. The claimed acquiring could practically be performed in the human mind. See MPEP 2106.04(a)(2)(III). For example, a human could observe data reflective of the averaged ECG signal (e.g., a graph or spreadsheet) and exercise judgment to acquire ECG features therefrom.
It is noted that the limitation “extracting, utilizing the one or more processors, an averaged ECG signal…” is being interpreted as a feature extraction step, and the limitation “acquiring a plurality of ECG features from the averaged ECG signal…” is being interpreted as manipulation of the extracted features.
“generating, utilizing the one or more processors, a plurality of clinical symptoms fuzzy sets associated with the plurality of clinical symptoms” recites a mental process when afforded its broadest reasonable interpretation. The claimed generating could practically be performed in the human mind. See MPEP 2106.04(a)(2)(III). For example, a human could observe medical literature describing pertinent clinical symptoms and exercise judgment to design a plurality of fuzzy sets associated therewith.
“generating, utilizing the one or more processors, a plurality of gender-age fuzzy sets associated with the gender and the age” recites a mental process when afforded its broadest reasonable interpretation. The claimed generating could practically be performed in the human mind. See MPEP 2106.04(a)(2)(III). For example, a human could observe medical literature describing pertinent age-gender considerations relative to heart attack risk and exercise judgment to design a plurality of fuzzy sets associated therewith.
“generating, utilizing the one or more processors, a plurality of ECG fuzzy sets associated with the plurality of ECG features” recites a mental process when afforded its broadest reasonable interpretation. The claimed generating could practically be performed in the human mind. See MPEP 2106.04(a)(2)(III). For example, a human could observe medical literature describing pertinent ECG features relative to heart attack risk and exercise judgment to design a plurality of fuzzy sets associated therewith.
“generating, utilizing the one or more processors, a myocardial infarction (MI) class corresponding to occurrence of an MI in the subject and a non-MI class corresponding to an absence of MI in the subject” recites a mental process when afforded its broadest reasonable interpretation. The claimed generating could practically be performed in the human mind. See MPEP 2106.04(a)(2)(III). For example, a human could exercise judgment to create such a myocardial infarction (MI) class and a non-MI class.
“designing, utilizing the one or more processors, a fuzzy inference system based on a set of rules, each rule of the set of rules comprising mapping a respective combination of a respective clinical symptoms fuzzy set of the plurality of clinical symptoms fuzzy sets, a respective gender-age fuzzy set of the plurality of gender-age fuzzy sets, and a respective ECG fuzzy set of the plurality of ECG fuzzy sets to one of the MI class or the non-MI class” recites a mental process when afforded its broadest reasonable interpretation. The claimed designing could practically be performed in the human mind. See MPEP 2106.04(a)(2)(III). For example, a human could observe data and literature descriptive of typical associations characterized by the fuzzy sets, exercise judgment to create a set of rules based thereupon, and again exercise judgment to design a fuzzy inference system based on those rules.
“mapping each of the plurality of clinical symptoms, the gender, the age, and the plurality of ECG features to a respective fuzzy input of a plurality of fuzzy inputs” recites a mental process when afforded its broadest reasonable interpretation. The claimed mapping could practically be performed in the human mind. See MPEP 2106.04(a)(2)(III). For example, a human could exercise judgment to assign respective clinical symptoms, gender, age, and ECG features to a respective fuzzy inputs, thereby “mapping” such symptoms, gender, age, and ECG features as claimed.
“determining, utilizing the fuzzy inference system, an occurrence of the heart attack in the subject by applying the plurality of fuzzy inputs to the fuzzy inference system” recites a mathematical concept, and more particularly a mathematical calculation when afforded its broadest reasonable interpretation. See MPEP 2106.04(a)(2)(I). “A mathematical calculation is a mathematical operation (such as multiplication) or an act of calculating using mathematical methods to determine a variable or number, e.g., performing an arithmetic operation such as exponentiation.” MPEP 2106.04(a)(2)(I)(C). Such determining using a fuzzy inference system as claimed is a mathematical operation.
Regarding Claims 2-20, Claims 2-20 depend from and further limit Claim 1, and recite abstract ideas for the same reasons as does Claim 1.
Eligibility Step 2A, Prong Two
Claims 1-20 do not recite additional elements that integrate the judicial exception into a practical application:
Regarding Independent Claim 1:
“utilizing the one or more processors” (i.e., that the above-indicated abstract ideas are done “utilizing the one or more processors”) is a generic computer structure for performing a generic computer function, and thus simply amounts to using a computer as a tool to implement the abstract idea. See MPEP 2106.05(f).
“acquiring a plurality of clinical symptoms from the subject” is insignificant extra-solution activity insufficient to integrate the judicial exception into a practical application because it amounts to mere data gathering.
“acquiring a gender of the subject, the gender comprising one of a male or a female” is insignificant extra-solution activity insufficient to integrate the judicial exception into a practical application because it amounts to mere data gathering.
“acquiring an age of the subject” is insignificant extra-solution activity insufficient to integrate the judicial exception into a practical application because it amounts to mere data gathering.
“acquiring a raw single-lead electrocardiography (ECG) signal from the subject at a diagnosis time period” is insignificant extra-solution activity insufficient to integrate the judicial exception into a practical application because it amounts to mere data gathering.
Regarding Claims 2-16, Claims 2-16 do not recite any additional elements.
Regarding Claim 17:
“recording the raw ECG signal from the ECG electrode” is insignificant extra-solution activity insufficient to integrate the judicial exception into a practical application because it amounts to mere data gathering.
Regarding Claim 18, Claim 18 does not recite any additional elements.
Regarding Claim 19:
“wherein the electronic gadget comprises a smartwatch” does not integrate the judicial exception into a practical application because it is a generic computer structure for performing a generic computer function, and thus simply amounts to using a computer as a tool to implement the abstract idea. See MPEP 2106.05(f).
Regarding Claim 20, Claim 20 does not recite any additional elements.
Eligibility Step 2B
Claims 1-20 do not amount to significantly more than the abstract ideas recited therein:
Regarding Independent Claim 1
“utilizing the one or more processors” does not contribute an inventive concept. The claimed “one or more processors” are generic computer structures for performing generic computer functions, and are simply appended to the claimed abstract ideas. See MPEP 2106.05(I)(A).
“acquiring a plurality of clinical symptoms from the subject” does not contribute an inventive concept. Such acquiring clinical symptoms is well-understood, routine and conventional in the art. See, e.g., Goff DC, Sellers DE, McGovern PG, et al. Knowledge of Heart Attack Symptoms in a Population Survey in the United States: The REACT Trial. Arch Intern Med. 1998;158(21):2329–2338 at Pg. 2330, Left Column, Second Paragraph (“Our purpose herein is to describe knowledge regarding heart attack symptoms reported by participants…”); Pg. 2335, Table 3 (Table 3 depicts clinical symptoms reported by patients and characterized as existing “knowledge” at Pg. 2330, Left Column, Second Paragraph); S. ARSLANKAYA et al., "Prediction of Heart Attack Using Fuzzy Logic Method and Determination of Factors Affecting Heart Attacks," International Journal of Computational and Experimental Science and ENgineering (IJCESEN), Vol. 7-No.1 (2021)pp. 1-8, March 2021 at Pg. 2, Left Column, Second Paragraph.
“acquiring a gender of the subject, the gender comprising one of a male or a female” does not contribute an inventive concept. Such acquiring gender is well-understood, routine and conventional in the art. See, e.g., Goff DC, Sellers DE, McGovern PG, et al. Knowledge of Heart Attack Symptoms in a Population Survey in the United States: The REACT Trial. Arch Intern Med. 1998;158(21):2329–2338 at Pg. 2330, Left Column, Second Paragraph (“Our purpose herein is to describe knowledge regarding heart attack symptoms reported by participants…”); Pg. 2335, Table 3 (Table 3 depicts clinical symptoms reported by patients and characterized as existing “knowledge” at Pg. 2330, Left Column, Second Paragraph, and includes breakdown by gender); S. ARSLANKAYA et al., "Prediction of Heart Attack Using Fuzzy Logic Method and Determination of Factors Affecting Heart Attacks," International Journal of Computational and Experimental Science and ENgineering (IJCESEN), Vol. 7-No.1 (2021)pp. 1-8, March 2021 at Pg. 2, Left Column, Second Paragraph.
“acquiring an age of the subject” does not contribute an inventive concept. Such acquiring subject age is well-understood, routine and conventional in the art. See, e.g., Goff DC, Sellers DE, McGovern PG, et al. Knowledge of Heart Attack Symptoms in a Population Survey in the United States: The REACT Trial. Arch Intern Med. 1998;158(21):2329–2338 at Pg. 2330, Left Column, Second Paragraph (“Our purpose herein is to describe knowledge regarding heart attack symptoms reported by participants…”); Pg. 2335, Table 3 (Table 3 depicts clinical symptoms reported by patients and characterized as existing “knowledge” at Pg. 2330, Left Column, Second Paragraph, and includes breakdown by age); S. ARSLANKAYA et al., "Prediction of Heart Attack Using Fuzzy Logic Method and Determination of Factors Affecting Heart Attacks," International Journal of Computational and Experimental Science and ENgineering (IJCESEN), Vol. 7-No.1 (2021)pp. 1-8, March 2021 at Pg. 2, Left Column, Second Paragraph.
“acquiring a raw single-lead electrocardiography (ECG) signal from the subject at a diagnosis time period” does not contribute an inventive concept. Such acquiring a raw ECG signal is well-understood, routine and conventional in the art. See, e.g., S. Ansari et al., "A Review of Automated Methods for Detection of Myocardial Ischemia and Infarction Using Electrocardiogram and Electronic Health Records," in IEEE Reviews in Biomedical Engineering, vol. 10, pp. 264-298, 2017 at Pg. 264, Right Column, Second Paragraph.
Regarding Claims 2-16, Claims 2-16 do not recite any additional elements.
Regarding Claim 17:
“recording the raw ECG signal from the ECG electrode” does not contribute an inventive concept. Such recording is well-understood, routine and conventional in the art. See, e.g., S. Ansari et al., "A Review of Automated Methods for Detection of Myocardial Ischemia and Infarction Using Electrocardiogram and Electronic Health Records," in IEEE Reviews in Biomedical Engineering, vol. 10, pp. 264-298, 2017 at Pg. 264, Right Column, Second Paragraph.
Regarding Claim 18, Claim 18 does not recite any additional elements.
Regarding Claim 19:
“wherein the electronic gadget comprises a smartwatch” does not contribute an inventive concept. The claimed “one or more processors” are generic computer structures for performing generic computer functions, and are simply appended to the claimed abstract ideas. See MPEP 2106.05(I)(A).
Regarding Claim 20, Claim 20 does not recite any additional elements.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1 and 17-20 are rejected under 35 U.S.C. 103 as being unpatentable over previously cited US 6507753 B1 to Xue et al. (“Xue”) in view of previously cited S. Ansari et al., "A Review of Automated Methods for Detection of Myocardial Ischemia and Infarction Using Electrocardiogram and Electronic Health Records," in IEEE Reviews in Biomedical Engineering, vol. 10, pp. 264-298, 20171 (“Ansari”), previously cited A. Adeli et al., "A Fuzzy Expert System for Heart Disease Diagnosis," Proceedings of the International MultiConference of Engineers and Computer Scientists 2010, Vol I, IMECS 2010, March 17-19, 2010, Hong Kong (“Adeli”) and US 10,463,302 B1 to Ahmad et al. (“Ahmad”) as evidenced by J. Presedo et al., "Fuzzy modelling of the expert's knowledge in ECG-based ischaemia detection," Fuzzy Sets and Systems Volume 77, Issue 1, 15 January 1996, Pages 63-75 (“Presedo”).
Regarding Independent Claim 1, Xue teaches:
A method for early detection of a heart attack in a subject, the method comprising: (Title, “Method and apparatus to detect acute cardiac syndromes in specified groups of patients using ECG”);
acquiring a plurality of clinical symptoms from the subject; (Abstract, “…ECG data are acquired from a patient experiencing ACS symptoms.”);
acquiring a gender of the subject, the gender comprising one of a male or a female; (Col. 5, Ln. 50-52, “After the standard ECG analysis is implemented 100, the patient's gender and age are checked at 102.”);
acquiring an age of the subject; (Col. 5, Ln. 50-52, “After the standard ECG analysis is implemented 100, the patient's gender and age are checked at 102.”);
acquiring a raw … electrocardiography (ECG) signal from the subject at a diagnosis time period; (Col. 5, Ln. 50-52, “After the standard ECG analysis is implemented 100, the patient's gender and age are checked at 102;” see Col. 1, Ln. 52 through Col. 2, Ln. 26 elaborating on Xue’s “standard ECG analysis”);
It is noted that Xue acquires a 12 lead ECG signal rather than a “single-lead” ECG signal as claimed. This deficiency is addressed below.
generating … a denoised ECG signal… (Col. 4, Ln. 12-18, “The ECG device 10 has a signal conditioner 34 that receives the ECG signals and filters noise, sets thresholds, segregating signals, and provides the appropriate number of ECG signals for the number of leads 28 to an A/D converter 36 which converts the analog signals to digital signals for processing by a microcontroller 38, or any other type of processing unit.”);
generating, utilizing the one or more processors, a myocardial infarction (MI) class corresponding to occurrence of an MI in the subject and a non-MI class corresponding to an absence of MI in the subject; (Fig. 4, “Acute Inferior MI 118” and “No Acutre Inferior MI 142;” Col. 5, Ln. 49 through Col. 6, Ln 17).
determining, utilizing the fuzzy inference system, an occurrence of the heart attack in the subject by applying the plurality of fuzzy inputs to the fuzzy inference system (Abstract, “…the present invention provides a method and apparatus to improve diagnosis of acute cardiac syndromes (ACS), such as acute myocardial infarction…;” Claim 21, “The method of claim 17 further comprising identifying whether the patient has an ACS and whether the ACS is acute anterior myocardial infarction or acute inferior myocardial infarction;” Col. 2, Ln. 38-42, “Either a fuzzy logic or a neural network can be used for pattern recognition in addition to classical pattern recognition methods such as linear discriminant function analysis and thresholding.”)
Xue differs from the invention of Claim 1 in two main ways. First, Xue uses a simpler method of denoising, filtering and feature extraction than claimed. Second, Xue uses clinical symptoms, gender and age to reduce its threshold for determining myocardial infarction via fuzzy logic rather than as a fuzzy set used in such determination, with Xue’s fuzzy logic being described in less detail.
Accordingly, Xue does not disclose:
acquiring a raw single-lead electrocardiography (ECG) signal
That is, as explained above, Xue acquires a 12 lead ECG signal rather than a “single-lead” ECG signal as claimed.
generating, utilizing one or more processors, a denoised ECG signal by applying a first wavelet transform on the raw ECG signal;
That is, Xue teaches generating a denoised ECG signal, but does not teach doing so by “utilizing one or more processors” or “by applying a first wavelet transform on the raw ECG signal,” opting instead to denoise via a signal conditioner.
generating, utilizing the one or more processors, an artifact-free ECG signal by applying a second wavelet transform on the denoised ECG signal;
generating, utilizing the one or more processors, a filtered ECG signal by applying a finite impulse response (FIR) filter on the artifact-free ECG signal;
extracting, utilizing the one or more processors, an averaged ECG signal from the filtered ECG signal, the averaged ECG signal comprising a QRS complex, an ST segment, and a T wave;
acquiring a plurality of ECG features from the averaged ECG signal and the filtered ECG signal;
generating, utilizing the one or more processors, a plurality of clinical symptoms fuzzy sets associated with the plurality of clinical symptoms;
generating, utilizing the one or more processors, a plurality of gender-age fuzzy sets associated with the gender and the age;
generating, utilizing the one or more processors, a plurality of ECG fuzzy sets associated with the plurality of ECG features;
designing, utilizing the one or more processors, a fuzzy inference system based on a set of rules, each rule of the set of rules comprising mapping a respective combination of a respective clinical symptoms fuzzy set of the plurality of clinical symptoms fuzzy sets, a respective gender-age fuzzy set of the plurality of gender-age fuzzy sets, and a respective ECG fuzzy set of the plurality of ECG fuzzy sets to one of the MI class or the non-MI class;
mapping each of the plurality of clinical symptoms, the gender, the age, and the plurality of ECG features to a respective fuzzy input of a plurality of fuzzy inputs;
Ansari describes “…Automated Methods for Detection of Myocardial Ischemia and Infarction Using Electrocardiogram and Electronic Health Records” (Title). Ansari is analogous art.
Ansari teaches:
generating, utilizing one or more processors, a denoised ECG signal by applying a first wavelet transform on the raw ECG signal; (Pg. 270, Right Column, Second Paragraph, “Another popular method for denoising the ECG signal uses wavelet transform.”);
generating, utilizing the one or more processors, an artifact-free ECG signal by applying a second wavelet transform on the denoised ECG signal; (Pg. 269, Left Column, Fourth Paragraph, “Discrete wavelet transform (DWT) [81] has also been used for BW removal.”);
Ansari teaches both baseline wander (“BW”) removal and noise removal via wavelet transform as part of such “pre-processing” as described at Ansari’s Pg. 268, Right Column, First Paragraph (“There has been a growing number of studies that use the ECG waveform to automatically detect these conditions. These methods are generally composed of four steps, preprocessing, ECG wave quantification, feature extraction, and classification.”).
generating, utilizing the one or more processors, a filtered ECG signal by applying a finite impulse response (FIR) filter on the artifact-free ECG signal; (Pg. 269, Right Col., Third Paragraph, “A variety of methods have been used in the literature to reduce the effect of noise in the ECG signal. The simplest and most common approach is low-pass filtering. For example, Minchole et al. [71] and Garcıa et al. [36] used a linear-phase finite impulse response (FIR) filter with a cutoff frequency of 25 Hz.”);
extracting, utilizing the one or more processors, an averaged ECG signal from the filtered ECG signal, the averaged ECG signal comprising a QRS complex, an ST segment, and a T wave; (Pg. 270, Left Column, Second Paragraph, “Beat averaging is another approach for reducing the effect of noise and interference in the ECG signal, i.e., a sequence of consecutive beats are averaged together to create an aggregate beat that is a better representative of heart’s electrical activity;” Pg. 273, Fig. 3, “Depiction of different morphological features that different studies have extracted from the ECG waveform,” shows QRS complex, an ST segment, and a T wave as commonly extracted features);
acquiring a plurality of ECG features from the averaged ECG signal and the filtered ECG signal; (Pg. 272, Right Column, Third Paragraph, “Once the ECG signal has been preprocessed and segmented, various methodologies are used to extract informative features that will allow for downstream detection of MI or ischemia;” Pg. 273, Fig. 3);
designing, utilizing the one or more processors, a fuzzy inference system based on a set of rules, (Pg. 279, Right Column, Last Paragraph through Pg. 280, Right Column First Paragraph, “Classification algorithms can formalize clinical guidelines for MI and ischemia diagnosis using ECG signal. … Expert knowledge has also been modeled with fuzzy logic in [34], where the authors constructed a linguistic filter with persistence and separation criterions to detect ST and T episodes.”);
each rule of the set of rules comprising mapping a respective combination of … a respective ECG fuzzy set of the plurality of ECG fuzzy sets to one of the MI class or the non-MI class (Pg. 279, Right Column, Last Paragraph through Pg. 280, Right Column First Paragraph, “Classification algorithms can formalize clinical guidelines for MI and ischemia diagnosis using ECG signal. … Expert knowledge has also been modeled with fuzzy logic in [34], where the authors constructed a linguistic filter with persistence and separation criterions to detect ST and T episodes.”);
Ansari’s reference “[34]” is Presedo. Presedo elaborates beyond Ansari’s summary to describe such a set of rules as claimed at Pg. 68, Right Column, Third Paragraph through Pg. 70, Left Column, Second Paragraph under the heading “4. Fuzzy detection of ischaemie episodes”).
Ansari’s summary of Presedo and Presedo itself both allude to use of such a “clinical symptoms fuzzy sets” and “gender-age fuzzy sets” as claimed, but do not provide sufficient detail to on their own fairly disclose either. This deficiency is addressed below.
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Xue with the teachings of Ansari (i.e., to denoise Xue’s raw ECG signal by applying a first wavelet transform on the raw ECG signal using a processor in the manner of Ansari) in order to balance smoothness and efficiency in the denoising (Ansari at Pg. 270, Right Column, Second Paragraph).
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Xue with the teachings of Ansari (i.e., to modify Xue so as to additionally generate an artifact-free ECG signal by applying a second wavelet transform on the denoised ECG signal in the manner of Ansari) in order to mitigate artifact from baseline wander (Ansari at Pg. 269, Left Column, Fourth Paragraph).
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Xue with the teachings of Ansari (i.e., to modify Xue so as to additionally generate a filtered ECG signal by applying a finite impulse response (FIR) filter on the artifact-free ECG signal in the manner of Ansari) in order to further reduce the impact of noise in the signal (Ansari at Pg. 269, Right Col., Third Paragraph).
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Xue with the teachings of Ansari (i.e., to use beat averaging prior to extraction in the manner of Ansari) in order to reduce the influence of noise (Ansari at Pg. 270, Left Column, Second Paragraph).
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Xue with the teachings of Ansari (i.e., to extract an averaged ECG signal from the filtered ECG signal comprising a QRS complex, an ST segment, and a T wave in the manner of Ansari and to subsequently acquire such features as taught by Ansari) in order to extract informative features that will allow for downstream detection of MI or ischemia (Ansari at Pg. 272, Right Column, Third Paragraph).
It would have been obvious for a person of ordinary skill in the art before the effective filing date of claimed invention to modify the method of Xue with the collective teachings of Ansari (i.e., to modify Xue such that its simple denoising and filtering process is replaced with a more comprehensive process such as those of Ansari) in order to facilitate automatic initial diagnosis of patients with symptoms associated with ischemia or MI in accordance with modern techniques (Ansari at Pg. 268, Right Column, First Paragraph).
It would have been obvious for a person of ordinary skill in the art before the effective filing date of claimed invention to modify the method of Xue with the teachings of Ansari (i.e., to configure Xue’s fuzzy logic in the manner of Ansari) in order to facilitate MI and ischemia diagnosis using ECG signal (Ansari at Pg. 279, Right Column, Last Paragraph through Pg. 280, Right Column First Paragraph).
Adeli describes “A Fuzzy Expert System for Heart Disease Diagnosis” (Title). Adeli is analogous art.
Adeli teaches:
generating, utilizing the one or more processors, a plurality of clinical symptoms fuzzy sets associated with the plurality of clinical symptoms; (Pg. 2 of 6, Left Column, Second Paragraph, “Input fields (attributes) are chest pain type, blood pressure, cholesterol, resting blood sugar, resting maximum heart rate, sex, electrocardiography (ECG), exercise, old peak (ST depression induced by exercise relative to rest), thallium scan and age. The output field refers to the presence of heart disease in the patient. It is integer value from 0 (no presence) to 4 (distinguish presence (values 1, 2, 3 and 4)); increasing value shows increasing heart disease risk.”);
Adeli’s chest pain type, blood pressure, cholesterol, resting blood sugar are such “clinical symptoms” as claimed per Para. [0114] of the Present Specification (Present Specification at Para. [0114], “For each individual, a vector containing only zero or one value was generated describing the feeling or not feeling of the clinical sign and symptoms of upper chest pain, middle chest pain, upper abdomen pain, pain in the neck, pain in the jaw, pain in the right shoulder, pain in the left shoulder, pain inside the right arm, pain inside the left arm, pain between shoulders in back, fainting, sweating, shortness of breath, light headedness, vomiting, nausea, history of diabetes, history of hypertension, and history of hyperlipidemia.” (emphasis added)).
generating, utilizing the one or more processors, a plurality of gender-age fuzzy sets associated with the gender and the age; (Pg. 2 of 6, Left Column, Second Paragraph, “Input fields (attributes) are chest pain type, blood pressure, cholesterol, resting blood sugar, resting maximum heart rate, sex, electrocardiography (ECG), exercise, old peak (ST depression induced by exercise relative to rest), thallium scan and age. The output field refers to the presence of heart disease in the patient. It is integer value from 0 (no presence) to 4 (distinguish presence (values 1, 2, 3 and 4)); increasing value shows increasing heart disease risk.”);
generating, utilizing the one or more processors, a plurality of ECG fuzzy sets associated with the plurality of ECG features; (Pg. 2 of 6, Left Column, Second Paragraph, “Input fields (attributes) are chest pain type, blood pressure, cholesterol, resting blood sugar, resting maximum heart rate, sex, electrocardiography (ECG), exercise, old peak (ST depression induced by exercise relative to rest), thallium scan and age. The output field refers to the presence of heart disease in the patient. It is integer value from 0 (no presence) to 4 (distinguish presence (values 1, 2, 3 and 4)); increasing value shows increasing heart disease risk.”);
each rule of the set of rules comprising mapping a respective combination of a respective clinical symptoms fuzzy set of the plurality of clinical symptoms fuzzy sets, a respective gender-age fuzzy set of the plurality of gender-age fuzzy sets, (Pg. 5 of 6, Left Column, First Paragraph, “Rule base is the main part in fuzzy inference system and quality of results in a fuzzy system depends on the fuzzy rules. This system includes 44 rules. Antecedent part of all rules has one section. This system designed with another rule bases (64 rules, 15 rules, 10 rules and 5 rules) and results showed in 44 rules system are best in comparison with results of the other rule bases. In the other hand, results with 44 rules tend to the expert’s idea and laboratory results. The rules have been shown in FIG.9;” Pg. 5 of 6, Fig. 9 shows Adeli’s rules);
mapping each of the plurality of clinical symptoms, the gender, the age, and the plurality of ECG features to a respective fuzzy input of a plurality of fuzzy inputs; (Pg. 2 of 6, Left Column, Second Paragraph).
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of combined Xue and Ansari with the teachings of Adeli (i.e., to configure the fuzzy logic system of combined Xue and Ansari in the manner of Adeli wherein clinical symptoms, gender and age are used in the manner of Adeli) in order to increase classification accuracy (Adeli at Pg. 1 of 6, Right Column, Third Paragraph).
Ahmad describes “a wearable device related to electrocardiogram (ECG) monitoring technology” (Abstract). Ahmad is analogous art.
Ahmad teaches:
acquiring a raw single-lead electrocardiography (ECG) signal (Col. 4, Ln. 28-35, “This invention fulfills the theoretical underpinnings of electrocardiography and Einthoven's law such that biopotential is measured on the left and right sides of the body with the heart in-between utilizing a pair of wirelessly synced wearables (for example, smart bands, smartwatches, and/or any combination thereof) that process all information to acquire high-fidelity single-lead ECG waveform data.”).
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the device of combined Xue, Ansari and Adeli with the teachings of Ahmad (i.e., to acquire a single lead signal in the manner of Ahmad) in order to facilitate obtaining high-fidelity ECG signals in a wrist-worn device (Ahmad at Col. 8, Ln. 45-63).
Regarding Claim 17, the combination of Xue, Ansari, Adeli and Ahmad renders obvious the entirety of Claim 1 as explained above.
Ahmad additionally teaches:
wherein acquiring the raw single-lead ECG signal from the subject comprises: placing an ECG electrode on a wrist of the subject; and recording the raw ECG signal from the ECG electrode. (Col. 5, Ln. 57 through Col. 6, Ln. 19 (quotation omitted for brevity; see also Fig. 1)
Regarding Claim 18, the combination of Xue, Ansari, Adeli and Ahmad renders obvious the entirety of Claim 17 as explained above.
Ahmad additionally teaches:
wherein placing the ECG electrode on the wrist of the subject comprises: embedding the ECG electrode in an electronic gadget; (Col. 3, Ln. 14-22, “In one embodiment, both primary and secondary smart bands are provided with three ECG strip electrodes on their underside to maximize the electrode surface area and enhance connectivity around the wrist to obtain high-quality ECG signal. Each of the three strip electrodes can be arranged to have a rigid section on the smart band backplate and a flexible section along the underside of the smart band straps;” see also Figs. 4-5);
and wearing the electronic gadget on the wrist of the subject. (Col. 5, Ln. 57 through Col. 6, Ln. 19 (quotation omitted for brevity; see also Fig. 1).
Regarding Claim 19, the combination of Xue, Ansari, Adeli and Ahmad renders obvious the entirety of Claim 18 as explained above.
Ahmad additionally teaches:
wherein the electronic gadget comprises a smartwatch (Col. 4, Ln. 27-28, “It will be appreciated that the smart band could be a smartwatch or any other similar wearable.”).
Regarding Claim 20, the combination of Xue, Ansari, Adeli and Ahmad renders obvious the entirety of Claim 19 as explained above.
Ahmad additionally teaches:
wherein the one or more processors are embedded in the smartwatch (Col. 3, Ln. 5-10, “Both the primary and secondary smart bands preferably comprise electrodes, ECG amplification/conditioning circuitry, a microcontroller, a wireless transceiver, and a rechargeable battery.”)
Allowable Subject Matter
Claims 2-16 are rejected under 35 USC 101, and are dependent upon a base claim rejected under both 35 USC 101 and 35 USC 103, but are otherwise potentially allowable over prior art.
The following is a statement of reasons for the indication of potential allowability over prior art:
Claim 2 recites “wherein acquiring the plurality of clinical symptoms comprises assessment of: a first clinical symptom comprising: on/off pain with a continuous duration of at least five minutes during a one hour period before the diagnosis time in at least one of a first plurality of regions having a total size larger than three times of a size of a fingertip of the subject, the first plurality of regions comprising upper chest, middle chest (sternum), upper abdomen, neck, jaw, right shoulder, left shoulder, inside right arm, inside left arm, and between shoulders in back.” The prior art does not fairly teach, suggest or disclose acquiring as a first symptom such “on/off pain” having the duration claimed and in the regions claimed. Further, the prior art does not fairly teach, suggest or disclose acquiring as a first symptom such “on/off pain” having the duration claimed and in the regions claimed for use as part of a fuzzy set in a fuzzy logic system.
The closest prior art is Goff DC, Sellers DE, McGovern PG, et al. Knowledge of Heart Attack Symptoms in a Population Survey in the United States: The REACT Trial. Arch Intern Med. 1998;158(21):2329–2338. At Pg. 2333, Table 3, Goff lists “Chest pain or discomfort,” “Arm pain or numbness,” and “Jaw or neck pain” as “Reported Signs or Symptoms of Heart Attack,” with the intent that they be assessed as symptoms. However, Goff does not reasonably teach, disclose or suggest “on/off pain” having the duration claimed and in the regions claimed, and makes no mention of fuzzy logic.
A. Adeli et al., "A Fuzzy Expert System for Heart Disease Diagnosis," Proceedings of the International MultiConference of Engineers and Computer Scientists 2010, Vol I, IMECS 2010, March 17-19, 2010, Hong Kong (“Adeli”) and S. ARSLANKAYA et al., "Prediction of Heart Attack Using Fuzzy Logic Method and Determination of Factors Affecting Heart Attacks," International Journal of Computational and Experimental Science and ENgineering (IJCESEN), Vol. 7-No.1 (2021)pp. 1-8, March 2021 at Pg. 2, Left Column, Second Paragraph teach fuzzy logic systems which assess various symptoms in making their respective determinations, but neither remedies the deficiencies of Goff. It would not have been obvious to modify the prior art to acquire as a first symptom such “on/off pain” having the duration claimed and in the regions claimed for use as part of a fuzzy set in a fuzzy logic system, because the prior art simply does not contain these details. Given the nature of fuzzy logic, including such details would require substantial rework of prior art systems.
Claims 3-16 depend from and further limit Claim 2, and are potentially allowable over prior art for the same reasons as explained above with respect to Claim 2.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/C.J.M./Examiner, Art Unit 3796
/Jennifer Pitrak McDonald/Supervisory Patent Examiner, Art Unit 3796
1 The Examiner notes that S. Ansari et al., “A Review of Automated Methods for Detection of Myocardial Ischemia and Infarction Using Electrocardiogram and Electronic Health Records,” in IEEE Reviews in Biomedical Engineering, vol. 10, pp. 264-298, 2017 was cited by the International Searching Authority in the Written Opinion dated January 6, 2023.
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