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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 06/15/2023 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1, 3, 5-8, 10-17, and 34-39 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Similarly, original claims may lack written description when the claims define the invention in functional language specifying a desired result but the specification does not sufficiently describe how the function is performed or the result is achieved. For software, this can occur when the algorithm or steps/procedure for performing the computer function are not explained at all or are not explained in sufficient detail (simply restating the function recited in the claim is not necessarily sufficient). In other words, the algorithm or steps/procedure taken to perform the function must be described with sufficient detail so that one of ordinary skill in the art would understand how the inventor intended the function to be performed. See MPEP §§ 2163.02 and 2181, subsection IV.
When examining computer-implemented functional claims, examiners should determine whether the specification discloses the computer and the algorithm (e.g., the necessary steps and/or flowcharts) that perform the claimed function in sufficient detail such that one of ordinary skill in the art can reasonably conclude that the inventor possessed the claimed subject matter at the time of filing. An algorithm is defined, for example, as "a finite sequence of steps for solving a logical or mathematical problem or performing a task." Microsoft Computer Dictionary (5th ed., 2002). Applicant may “express that algorithm in any understandable terms including as a mathematical formula, in prose, or as a flow chart, or in any other manner that provides sufficient structure." Finisar Corp. v. DirecTV Grp., Inc., 523 F.3d 1323, 1340 (Fed. Cir. 2008) (internal citation omitted).It is not enough that one skilled in the art could write a program to achieve the claimed function because the specification must explain how the inventor intends to achieve the claimed function to satisfy the written description requirement. See, e.g., Vasudevan Software, Inc. v. MicroStrategy, Inc., 782 F.3d 671, 681-683, 114 USPQ2d 1349, 1356, 1357 (Fed. Cir. 2015).
Applicant’s computer-implemented algorithm for generating an Atrial Fibrillation diagnosis (claims 1 and 15) lacks written description support. The mere statement and recitation of the usage of models such as Neural Networks/CNN (for step d of claim 1, see pg. 16 and claims 8 and 10), autocorrelation, sliding Fourier transform, wavelet transform, self-similarity, and algorithms (for step c of claim 1, see pg. 16 and claim 6) provides insufficient disclosure of the details of the algorithm for determining Afib. Specifically, the instant specification fails to the type of data that is used to train the model and the inputs and outputs of the models to achieve the characteristic/atrial fibrillation determination. The specification fails to detail the features within a trained data set to of BCG features that allows one to observe abnormalities to characterize Afib. Applicant has not disclosed any particular process or algorithm that uses the BCG data for the self-similarity scoring or how the scoring is calculated. Ultimately, the specification is written generically such that it only defines the invention in functional language specifying a desired result but does not sufficiently identify how the function is performed or the result is achieved (see MPEP §2161.01).
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 1, 3, 5-8, 10-17, and 34-39 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 applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 is missing step b from the independent claim. Although claim 12 contains step b, claim 1’s steps are not in chronological order and therefore, appropriate action is required.
Claim 1 recites the limitation "the representative signal" in line 6. There is insufficient antecedent basis for this limitation in the claim.
Regarding claim 1, it is unclear if the phrase “a portion of the representative signal” of line 6 is the same or different than the phrase “at least part of the at least one obtained signal” in line 5.
Claim 1 recites the limitation "the at least one processed signal " in line 10. There is insufficient antecedent basis for this limitation in the claim.
Claim 1 recites the limitation "the signal " in line 11. There is insufficient antecedent basis for this limitation in the claim.
Regarding claim 3, it is unclear how a BCG is determined in step c as it is indefinite in its relationship to step c’s calculating of the similarity score.
Claim 5 recites the limitation "the portion" in lines 2 and 3. There is insufficient antecedent basis for this limitation in the claim.
Claim 6 recites the limitation "the representative signal" in lines 4 and 5. There is insufficient antecedent basis for this limitation in the claim.
Claim 11 recites the limitation "the feature" in line 3. There is insufficient antecedent basis for this limitation in the claim.
Claim 12 recites the limitation "the obtained signal" in lines 3 and 4. There is insufficient antecedent basis for this limitation in the claim.
Claim 13 recites the limitation "the signal obtained representative" in line 3. There is insufficient antecedent basis for this limitation in the claim.
Claim 14 recites the limitation "the representative signal" in line 2. There is insufficient antecedent basis for this limitation in the claim.
Regarding claim 34, it is unclear if the phrase “at least one signal representative of cardiac activity” of line 3 is the same or different than “at least one signal representative of cardiac activity” of claim 1 line 3.
Claim 36 recites the limitation "the at least one measured signal " in line 4. There is insufficient antecedent basis for this limitation in the claim.
Claim 36 recites the limitation "the at least one processed signal " in line 5. There is insufficient antecedent basis for this limitation in the claim.
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, 3, 5-8, 10-17, and 34-39 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Each of independent claims 1 recites a step calculating, for a portion of the representative signal, a set of similarity scores, said set of similarity scores associating similarity score values with respective time shifts…analyzing a temporal evolution of at least part of the at least one processed signal, which is a mental process. This judicial exception is not integrated into a practical application because the generically recited computer elements (ie. a storage device, a processing circuitry, implantable medical device), determining values, and identifying health events do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional limitations are to receiving data, processing data, and determine a health event, which are all well-understood, routine, and conventional computer functions. See MPEP § 2106.05(d).
MPEP 2106(III) outlines steps for determining whether a claim is directed to statutory subject
matter. The stepwise analysis for the instant claim is provided here.
Step 1 – Statutory categories
Claim 34 is directed to a system (i.e. machine) and thus meets the step 1 requirements.
Claim 1 is directed to a method and thus meets the step 1 requirements.
Claim 38 is directed to a tangible non-transitory computer-readable medium (i.e. a product), and
thus, meets the step 1 requirements.
Step 2A – Prong 1 – Judicial exception (j.e.)
Regarding claim 1, the following step is an abstract idea:
“calculating, for a portion of the representative signal, a set of similarity scores, said set of similarity scores associating similarity score values with respective time shifts…analyzing a temporal evolution of at least part of the at least one processed signal”, which is a mental process when given its broadest reasonable interpretation. As discussed in MPEP 2106.04(a)(2)(II), the mental process grouping includes observations, evaluations, judgements, and opinions. In this case, a human could calculate similarity scores respective to the shifts and analyze a temporal evolution by looking at the image and determining Afib.
Step 2A – Prong 2 – additional elements to integrate j.e. into a practical application
Regarding claim 1, the abstract idea is not integrated into a practical application.
The following claim elements do not add any meaningful limitation to the abstract idea:
- “processor” are recited at a high level of generality amounting to generic computer components for implementing abstract idea [MPEP 2106.05(b)];
It is noted that the similarity score, which requires the use of self-similarity/autocorrection, STFT, or wavelet, and the produced temporal evolution by using a CNN, are by definition automating the human thinking process with a computer.
- “signal/cardiac activity”, “cardiac condition/characteristic”, “representative signal”, “similarity scores”, “time shifts”, “similarity score values”, and “temporal evolution”, are data (gathering, selecting, and displaying) that is necessary to implement the abstract idea on a computer amounting to insignificant extra-solution activity [MPEP 2106.05(g)].
Step 2B – significantly more/inventive concept
The following claim elements do not add any meaningful limitation to the abstract idea:
- “processor” are recited at a high level of generality amounting to generic computer components for implementing abstract idea [MPEP 2106.05(b)];
It is noted that the similarity score, which requires the use of self-similarity/autocorrection, STFT, or wavelet, and the produced temporal evolution by using a CNN, are by definition automating the human thinking process with a computer.
- “signal/cardiac activity”, “cardiac condition/characteristic”, “representative signal”, “similarity scores”, “time shifts”, “similarity score values”, and “temporal evolution”, are data (gathering, selecting, and displaying) that is necessary to implement the abstract idea on a computer amounting to insignificant extra-solution activity [MPEP 2106.05(g)].
The additional elements of claim 1, when considered separately and in combination, do not add significantly more (ie. an inventive concept) to the abstract idea. As discussed above with respect to the integration of the abstract idea into a practical application, the processor, along with their associated functions, are recited at a high level of generality and simply amount to implementing the abstract idea on a computer.
Dependent claims 3, 5-8, 10-17, and 34-39 do not integrate the abstract idea into a practical application and do not add significantly more to the abstract idea of claim 1 and 10. The dependent claim limitations are directed to data for implementing the abstract idea amounting to extra-solution activity (claims 3, 5-8, 10-16, and 39) and to generic computer and data gathering structure (claims 17, and 34-38), which are insignificant extra-solution activity and do not amount to more than what is well-understood, routine, and conventional.
In summary, claims 1, 3, 5-8, 10-17, and 34-39 are directed to an abstract idea without significantly more and, therefore, are patent ineligible.
Claim Rejections - 35 USC § 102
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.
Claim(s) 1, 3, 5-8, 10, 12-17, 34-35, and 38-39 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Li et al. (US 20200138306)(Hereinafter Li).
Regarding claim 1, Li teaches A method of determining a characteristic of a cardiac condition of an individual (Abstract “A method of measuring biological signals of a person including obtaining physiological signals” Title “FEATURE SELECTION FOR CARDIAC ARRHYTHMIA CLASSIFICATION AND SCREENING”), said method comprising the following steps: a) obtaining at least one signal representative of a cardiac activity of the individual repeatedly ([0050] “The disclosure uses ballistocardiogram (BCG) signals as an example of physiological signals that may be used for the inventive concept.” [0052] “FIG. 1 depicts a flowchart of a feature selection method 100 in accordance with an embodiment of the inventive concept. As shown, raw signals (raw BCG signals, for example) are collected from a person (102), and the collected raw signals are subjected to preprocessing and segmentation (104) to generate envelope signals.”);
c) processing at least part of the at least one obtained signal, wherein said processing comprises calculating, for a portion of the representative signal, a set of similarity scores, said set of similarity scores associating similarity score values with respective time shifts ([0057] “FIG. 2 depicts a flowchart for preprocessing by reconstructing decomposed BCG signals according to a method that is disclosed in U.S. Patent Application Publication No. 2017/0273635, as a way of example. Referring to FIG. 2, various sensors detect motion (including acceleration) in different directions (202). The raw motion data may be decomposed using N-level wavelet decomposition.” [0062] “use the entropy S to calculate the Boltzmann entropy S.sub.B to reconstruct a reconstructed signal from the decomposed signals 206a-206h [set of similarity scores]…By adjusting the Boltzmann constant k.sub.B, various embodiments of the present disclosure may develop an adaptive weight for each sliding window [different time shifts].” By nature, wavelet decomposition uses time shifting to align different parts of the signal for a time frequency analysis. Examiner notes that each );
d) analyzing a temporal evolution of at least part of the at least one processed signal ([0080] “Time-Frequency Domain Features are Features 12, 13, and 14 in Table 1.To represent the short duration behaviors of the BCG signal, time-frequency distributions are widely used and can offer insights into the properties of signals. A spectrogram [temporal evolution], which is a time-varying spectral representation, is obtained by means of the short-time Fourier transform (STFT).”), and e) providing a characteristic of the signal representative of the cardiac activity based on steps a) to d) ([0081] “FIG. 16 depicts the spectrogram (shown as the square plot) in a “normal” state, FIG. 17 depicts the spectrogram in an Afib state, and FIG. 18 depicts the spectrogram for the “noise.” The spectrograms during Afib appear smeared as the lines representing the base frequency varies along time.”).
Regarding claim 3, Li teaches wherein the at least one signal representative of cardiac activity is a pressure signal ([0103] “The signals being monitored may be, for example, heart rate/pulse, pulse morphology, pulse spacing (IBIs), respiration rate, and blood pressure.”) and step c) comprises determining a ballistocardiogram ([0063] “The energy entropy calculations may then be used at 216 to reconstruct the BCG signal from the decomposed BCG signal in order to generate an envelope signal.”).
Regarding claim 5, Li teaches wherein the set of similarity scores is calculated by comparing the portion with a plurality of recopies of the portion to which a respective time offset has been applied, a similarity score value being assigned for each time offset (Fig. 2(210)[0058] “a moving average energy entropy may be used for the reconstruction process. A sliding window may be used to calculate moving average energy. In each window instance, energy-entropy is described in Equations 1-3 below. A sliding window with a desired window size based on specific use may be used.” Examiner notes that wavelet transforms require the time offset by scoring the recopies.).
Regarding claim 6, Li teaches processing step c) comprises stacking a plurality of sets of similarity scores calculated for a plurality of respective portions, to form a stack of self-similarity (Fig. 2(214’) [0062] “use the entropy S to calculate the Boltzmann entropy S.sub.B to reconstruct a reconstructed signal from the decomposed signals 206a-206h:”).
Regarding claim 7, Li teaches wherein step c) comprises calculating a self-similarity (Fig. 2(214) [0063] “At 214, one or more frequency bands corresponding to, for example, 206a to 206h may be selected. Equations 3 and 4 may be used to make energy entropy calculations of the selected frequency bands.”).
Regarding claim 8, Li teaches wherein step d) is implemented at least in part by artificial intelligence, wherein the artificial intelligence comprises an artificial neural network ([0093] “Convolutional Neural Network (CNN)+Deep Neural Network. Arrhythmia classification may be converted into image classification task by extending features into two dimensions.”).
Regarding claim 10, Li teaches wherein the artificial neural network comprises a two-dimensional convolutional neural network ([0093]] “Convolutional Neural Network (CNN)+Deep Neural Network. Arrhythmia classification may be converted into image classification task by extending features into two dimensions.”).
Regarding claim 12, Li teaches further comprising: b) determining a relevance of at least part of the at least one obtained signal, and wherein a step of notifying the characteristic of the obtained signal is implemented only if step b) determines that the obtained signal is relevant ([0055] “the raw BCG signals are complex because they contain multiple peak events during one heartbeat. The peaks may be categorized into three major groups: pre-systolic, systolic, and diastolic. Due to the complexity of the BCG signal and the harmonic pattern of the BCG signal, it may be challenging to determine a heartrate and a respiration rate directly from a raw BCG signal. Accordingly, the BCG signal is processed to determine the heart rate and respiration rate [relevant because BCG provides heart rate and RR.] .” The notification does not occur because of the conditional language that says “only if step b) determines that the obtained signal is relevant”. See MPEP 2111.04.).
Regarding claim 13, Li teaches wherein step b) comprises analyzing the at least one signal obtained representative of cardiac activity of the individual; and/or measure and analyze at least one additional signal representative of a movement performed by the individual, a breath taken by the individual or a pressure exerted by the individual ([0053] “Raw data recordings of physiological signals (e.g., taken from a monitoring device such as ECG, BCG, or PPG) is preprocessed… During preprocessing, features such as beat locations and signal transform may be calculated.”).
Regarding claim 14, Li teaches wherein the characteristic of the representative signal relates to the regularity or irregularity of the signal over time ([0083] “During motions, the heart beat extraction may become inaccurate. To evaluate the randomness of IBI changes, Feature 4 and Feature 5 were calculated.”).
Regarding claim 15, Li teaches wherein step e) comprises identifying an atrial fibrillation or identifying an absence of a characteristic ([0081] “FIG. 16 depicts the spectrogram (shown as the square plot) in a “normal” state, FIG. 17 depicts the spectrogram in an Afib state, and FIG. 18 depicts the spectrogram for the “noise.” The spectrograms during Afib appear smeared as the lines representing the base frequency varies along time.”).
Regarding claim 16, Li teaches wherein at least part of the process is carried out while the individual is asleep ([0065] “Information from the envelope signal may be further extracted for downstream methods to determine heart rate variability (HRV), sleeping quality, and stress.” Examiner notes that since sleep quality can be collected, the process is also carried out while sleeping.).
Regarding claim 17, Li teaches A processing unit for determining a characteristic of a cardiac condition of an individual, the processing unit being configured to implement a method of determining a characteristic of a cardiac condition of an individual according to claim 1 ([0096] “The processor 1110 may include a CPU 1200, memory 1210, an input/output (I/O) interface 1220, a communication interface 1230, a power management unit (PMU) 1240, a preprocessing module 1250 that handles signal decomposition and reconstruction, feature extraction module 1260, and feature selection module 1270.”).
Regarding claim 34, Li teaches a device for determining a characteristic of a cardiac condition of an individual, the device comprising at least one sensor configured to measure at least one signal representative of cardiac activity of the individual repeatedly, and the processing unit according to claim 17 ([0102] “The sensor module 1120 may include sensors 1122 and 1124 on the side of the strap that contacts the user. Although the particular embodiment of the electronic device 1000 shown in FIG. 21 is designed to be worn around a wrist, this is not a limitation of the inventive concept and the electronic device 1000 may be implemented in various other ways” [0104] “The sensors 1122 and 1124 may be, for example, an accelerometer or motion sensor used to continuously or periodically [repeatedly] monitor pulse related information as well as temperature.”).
Regarding claim 35, Li teaches configured to determine the individual's cardiac status without being in physical contact with the individual ([0104] “For example, the processor 1112 may preprocess the signals monitored by the sensors 1122 and/or 1124, and extract and select features from the preprocessed signals.” Examiner notes that the claim does not specify why is in physical contact with the user, and the processor is not in physical contact with the individual.).
Regarding claim 38, Li teaches a non-transitory computer readable medium comprising instructions for implementing the method according to claim 1 when the is instructions are executed by a processor ([0107] “disclosure may also cover an article of manufacture that includes a non-transitory computer readable medium on which computer-readable instructions for carrying out embodiments of the method are stored.”).
Regarding claim 39, Li teaches the method according to claim 12, wherein step b) comprises an automatic learning step, implemented by artificial intelligence ([0091] “At the first training stage, autoencoder inputs are raw feature inputs with noise corruption or missing components; the training targets are original features. The noise terms would help the autoencoder to learn inherent feature combination and prevent over-fitting. At the second stage of training, the trained encoder is connected to a supervised classifier (e.g., a fully connected neural network), and the combined network is further trained with labeled data.”).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Li et al. (US 20200138306)(Hereinafter Li).
Regarding claim 11, although Li teaches repeatedly doing steps a-e, Li does not teach the feature is provided every 1 minute to 5 minutes. Since the model can be optimized for rapid detection, the neural network can be altered to provide features every 1-5 minutes to optimize for efficient rapid detection. It would have been obvious to one having ordinary skill in the art at the time the invention was made to have the feature is provided every 1 minute to 5 minutes, since it has been held that discovering an optimum value of a result effective variable involves only routine skill in the art. In re Boesch, 617 F.2d 272, 205 USPQ 215 (CCPA 1980).
while Li does not specifically disclose, one of ordinary skill would have arrived by routine experimentation for optimizing the self-similarity and CNN of Li to sensitivity to detect a suitable range for each parameter and sizes of the model for optimizing diagnosis efficiently ([0090]).
Claim(s) 36-37 is/are rejected under 35 U.S.C. 103 as being unpatentable over Li et al. (US 20200138306)(Hereinafter Li) in view of Bhushan et al. (US 20170347894)(Hereinafter Bhushan).
Regarding claims 36-37, Li teaches the invention of claim 1. Although Li teaches sending data to an external display ([0095]), Li does not teach the second processing device receiving a measure signal from the first processing device. Bhushan, in the same field of endeavor, teaches a wearable device for continuous measurement of physiological parameters including ECG, PPG, and accelerometers (Abstract and [0010]), and further teaches comprising a second processing unit remote from the device and configured to receive from the first processing unit, after implementation of the process by the first processing unit, data representative of at least part of the at least one measured signal and/or the at least one processed signal and/or the characteristic, wherein the second processing unit comprises a smartphone or tablet ([0044] “The Biostrip contains a microprocessor or other processor to collect data from the multiple sensors, which implements a series of algorithms on the wearable device itself. The Biostrip also contains an integrated circuit for wireless data communication that enables it to connect and communicate, and send to and receive data from, a smartphone/smartwatch or another gateway device such as a wifi router.”) to alert a user of an abnormality ([0042]). It would have been obvious to one skilled in the art, prior to the effective filing date of the invention, to modify the method of Li, with the second processing device receiving a measure signal from the first processing device of Lee, because such a modification would allow to alert a user of an abnormality.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MOUSSA M HADDAD whose telephone number is (571)272-6341. The examiner can normally be reached M-TH 8:00-6:00.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jennifer McDonald can be reached at (571) 270-3061. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MOUSSA HADDAD/ Examiner, Art Unit 3796
/Jennifer Pitrak McDonald/ Supervisory Patent Examiner, Art Unit 3796