DETAILED ACTION
Notice of 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 Amendment
Applicant’s Amendment and remarks dated 10/16/2025 have been considered. Claims 5-6, 9, and 17-20 are cancelled. Claims 1-4, 7-8, and 10-16 are pending.
Drawing Objections. Except for the objections to Figs. 19 and 20 for including grayscale, the remaining objections to the drawings are withdrawn in view of Applicant’s specification amendments. As set forth below, Figs. 19 and 20 remain objected to as including grayscale portions.
Claim Objections. The objection to claim 10 is withdrawn in view of Applicant’s amendments to claim 10. The objection to claim 17 is moot in view of Applicant’s cancellation of such claim.
35 U.S.C. 112(b) Rejections. The rejection to claim 13 is withdrawn in view of Applicant’s amendments to such claim 13.
Response to Arguments
On page 6 of Applicant’s 10/16/2025 Amendment and remarks, Applicant asserts that the claim amendments are supported by at least paras. 0005, 0187, 0190, and 0191 and original Figs. 19 and 20.
The examiner agrees that such portions of the disclosure provide sufficient written description support for the claim amendments.
On page 7 of Applicant’s 10/16/2025 Amendment and remarks, with respect to the rejection of claim 1 under 35 U.S.C. 101, with respect to Step 2B, Applicant argues:
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The examiner respectfully disagrees. Applicant’s arguments highlight the use of 2 separate LSTM networks within the recited RNN, but no improvements are made to the RNN or any of the LSTM elements. The claims merely recite that the RNN is trained using certain types of data, which merely applies the RNN (and LSTM layers) to a particular field-of-use. The amendments to the claims do not sufficiently show that the claim incorporates “substantially more” than the identified mental processes.
On page 8 of Applicant’s 10/16/2025 Amendment and remarks, with respect to the rejection of claim 1 under 35 U.S.C. 101, with respect to Step 2B, Applicant argues that the instant specification identifies a particular technical problem.
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The examiner respectfully disagrees. First, the examiner respectfully disagrees that there is a “technical problem” relating to “creating respiratory-disease classifiers.” Generating such a classifier using data is merely a mental step as explained in the detailed rejections below. Moreover, simply “downsampling” signals from a BCG stream to solve issues with “accuracy” does not solve a “technical problem”, as the claim is not directed to improvements for BCG capture.
Second, the examiner respectfully disagrees that there is any “technical problem” relating to the “uses of RNNs.” The claims merely recite having prospective and historic LSTM networks, without providing any disclosure about the structure of such LSTM networks and how such networks achieve the “prospective” or “historic” purposes. There are no improvements to RNN or LSTM technologies.
On pages 8-9 of Applicant’s 10/16/2025 Amendment and remarks, with respect to the rejection of claim 1 under 35 U.S.C. 101, with respect to Step 2B, Applicant argues that claim 1 discloses an improvement in the claim itself.
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The examiner respectfully disagrees. As explained above, the examiner respectfully disagrees that any “technical” problem is at issue. Regardless, MPEP 2106.04(d)(1) explains that “if the specification explicitly sets forth an improvement but in a conclusory manner (i.e., a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art), the examiner should not determine the claim improves technology.” Here, Applicant’s arguments are merely conclusory statements. One of ordinary skill would not understand claim 1, as amended, to provide any technical improvement to any technology or other technical field. As explained above, there are no improvements to BCG capture technology, or to the RNNs or LSTMs. At most, these elements are used to more efficiently generate a classifier for disease classification, but that concept is a mental process as explained above.
On page 9 of Applicant’s 10/16/2025 Amendment and remarks, with respect to the rejection of claim 1 under 35 U.S.C. 101, with respect to Step 2B, Applicant argues that claim 1 discloses a particular solution.
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The examiner respectfully disagrees. MPEP 2106.04(d)(1) explains that “if the specification explicitly sets forth an improvement but in a conclusory manner (i.e., a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art), the examiner should not determine the claim improves technology.” Here, Applicant’s arguments are merely conclusory statements. One of ordinary skill would not understand claim 1, as amended, to provide a particular solution to a technical problem. The “downsampling the BCG stream” is merely a field-of-use limitation, where the generic concept of downsampling data is applied to a particular type of stream, to “retain” certain data, without providing any explanation about how such downsampling is carried out to “retain” data. Moreover, simply training RNNs and LSTMs and CNNs using particular types of data, without any improvements to the RNNs, CNNs, and/or LSTMs, merely applies such generic RNNs, CNN,s and LSTMs to the judicial exception using generic computer components. Finally, the claims do not recite any particular architecture for implementing the recited “prospective LSTM network” and “historic LSTM network.”
On page 10 of Applicant’s 10/16/2025 Amendment and remarks, with respect to the rejection of claim 1 under 35 U.S.C. 103, Applicant requests withdrawal of the rejection because claim 1 has been amended to include the subject matter of claim 9 (and intervening claims) that was previously indicated as including allowable subject matter.
The examiner agrees. All rejections under 35 U.S.C. 103 are hereby withdrawn.
Drawings
The drawings are objected to because Figs. 19 and 20 include grayscale and should be replaced with drawings using black ink and without the grayscale. 37 C.F.R. 1.84(a)(1) states: “Black and white drawings are normally required. India ink, or its equivalent that secures solid black lines, must be used for drawings.”
Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Claim Rejections - 35 USC § 101
Claims 1-4, 7-8, and 10-16 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding Step 1 of the Alice/Mayo framework, Claims 1-4, 7-8, and 10-16 are directed to a system (a machine) which falls within one of the four statutory categories of inventions.
Regarding Claim 1
Step 2A, prong 1 (Is the claim directed to a law of nature, a natural phenomenon or an abstract idea).
Claim 1 recites the following mental processes, that in each case under the broadest reasonable interpretation, covers performance of the limitation in the mind (including an observation, evaluation, judgment, opinion) or with the aid of pencil and paper but for the recitation of generic computer components (e.g., “processors”, “memory storing instructions”, “CNN”, “RNN”, “LSTM”).
generating a respiratory-disease classifier using respiratory cardiac data and the tagging data (under the broadest reasonable interpretation, a human can mentally (or using pencil and paper), generate a classifier using respiratory cardiac data and tagging data to classify a respiratory disease, for example, a human can listen to audio respiratory cardiac data and review associated tagging data, and determine criteria for whether to classify the data as pertaining to a particular disease, such as sleep apnea)
Step 2A, prong 2 (Does the claim recite additional elements that integrate the judicial exception into a practical application?).
The judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements (e.g., “processors”, “memory storing instructions”, “CNN”, “RNN”, “LSTM”) which are recited at a high-level of generality such that they amount to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
Regarding the “A system for generating respiratory-disease classifiers, the system comprising: one or more processors; and memory storing instructions, that when executed by the one or more processors, cause the one or more processors to perform operations comprising” limitation, such limitations are recited at a high-level of generality and amount to no more than adding the words “apply it” (or an equivalent) with the judicial exception. In particular, the claim only recites the additional elements of processors and memory. These additional elements are recited at a high-level of generality and amount to no more than mere instructions to apply the exception using generic computer components (generic processors and memory). Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f)).
Regarding the “receiving respiratory data recording breathing action of a person on a bed” limitation, such additional element of a data gathering step is recited at a high level of generality and amounts to extra-solution activity of receiving data, i.e. pre-solution activity of gathering data for use in the claimed process (see MPEP 2106.05(g)).
Regarding the “receiving tagging data that defines tags of disease state and severity thereof for the respiratory data” limitation, such additional element of a data gathering step is recited at a high level of generality and amounts to extra-solution activity of receiving data, i.e. pre-solution activity of gathering data for use in the claimed process (see MPEP 2106.05(g)).
Regarding the “... the generating comprising: training a convolutional neural network (CNN) configured to use as input i) the respiratory data and ii) the tagging data, the CNN configured to generate intermediate data; and training a recurrent neural network (RNN) configured to use as input the intermediate data, the RNN configured to generate a disease classification, the RNN comprising i) a prospective long short-term memory (LSTM) network using as input later disease classifications and ii) a historic LSTM network using as input previous disease classifications. ” limitation, such limitations are recited at a high-level of generality and amount to no more than adding the words “apply it” (or an equivalent) with the judicial exception. In particular, the claim only recites the additional elements of different types of neural network configurations (CNN, RNN, LSTM). These additional elements are recited at a high-level of generality and amount to no more than mere instructions to apply the exception using generic computer components (neural network configurations). Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f)). In particular, the examiner notes that the claim merely recites generic CNN, RNN, and LSTM networks, without claiming any technical improvements to such components.
Regarding the “wherein the respiratory data is created with a ballistocardiogram (BCG) stream” limitation, such limitation amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (BCG streams as a data source). As explained by the Supreme Court, a claim directed to a judicial exception cannot be made eligible "simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use." Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not integrate a judicial exception into a practical application.
Regarding the “wherein creation of the respiratory data comprises downsampling the BCG stream to a lower frequency” limitation, this limitation merely describes aspects of the collected data, and such limitation amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (downsampled BCG streams as a data source). As explained by the Supreme Court, a claim directed to a judicial exception cannot be made eligible "simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use." Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not integrate a judicial exception into a practical application.
Regarding the “wherein the downsampling retains i) signal of cardiac activity and ii) signal of gross motor activity” limitation, this limitation merely describes aspects of the collected data, and such limitation amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (downsampled BCG streams as a data source). As explained by the Supreme Court, a claim directed to a judicial exception cannot be made eligible "simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use." Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not integrate a judicial exception into a practical application.
Regarding the “wherein the training of the CNN and the training of the RNN use the i) signal of cardiac activity and ii) signal of gross motor activity” limitation, such limitations are recited at a high-level of generality and amount to no more than adding the words “apply it” (or an equivalent) with the judicial exception. In particular, the claim only recites the additional elements of different types of neural networks and specific types of training data. These additional elements are recited at a high-level of generality and amount to no more than mere instructions to apply the exception using generic computer components (neural networks). Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f)).
Step 2B (Does the claim recite additional elements that amount to significantly more than the judicial exception?)
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception. As discussed above, the additional elements (e.g., “processors”, “memory storing instructions”, “CNN”, “RNN”, “LSTM”) are recited at a high-level of generality such that they amount to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
Regarding the “A system for generating respiratory-disease classifiers, the system comprising: one or more processors; and memory storing instructions, that when executed by the one or more processors, cause the one or more processors to perform operations comprising” limitation, such limitation is recited at a high-level of generality and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception, because the limitation merely provides instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not add significantly more than the judicial exception. (See MPEP 2106.05(f)).
Regarding the “receiving respiratory data recording breathing action of a person on a bed” limitation, as discussed above, the additional element of a data gathering step is recited at a high level of generality and amounts to extra-solution activity of receiving data, i.e. pre-solution activity of gathering data for use in the claimed process. The courts have found limitations directed to obtaining information electronically, recited at a high level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II), “receiving or transmitting data over a network”, "electronic record keeping," and "storing and retrieving information in memory").
Regarding the “receiving tagging data that defines tags of disease state and severity thereof for the respiratory data” limitation, as discussed above, the additional element of a data gathering step is recited at a high level of generality and amounts to extra-solution activity of receiving data, i.e. pre-solution activity of gathering data for use in the claimed process. The courts have found limitations directed to obtaining information electronically, recited at a high level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II), “receiving or transmitting data over a network”, "electronic record keeping," and "storing and retrieving information in memory").
Regarding the “... the generating comprising: training a convolutional neural network (CNN) configured to use as input i) the respiratory data and ii) the tagging data, the CNN configured to generate intermediate data; and training a recurrent neural network (RNN) configured to use as input the intermediate data, the RNN configured to generate a disease classification, the RNN comprising i) a prospective long short-term memory (LSTM) network using as input later disease classifications and ii) a historic LSTM network using as input previous disease classifications. ” limitation, such limitation is recited at a high-level of generality and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception, because the limitation merely provides instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not add significantly more than the judicial exception. (See MPEP 2106.05(f)).
Regarding the “wherein the respiratory data is created with a ballistocardiogram (BCG) stream” limitation, such limitation amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use as explained above, which does not amount to significantly more than the judicial exception. MPEP 2106.05(h).
Regarding the “wherein creation of the respiratory data comprises downsampling the BCG stream to a lower frequency” limitation, such limitation amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use as explained above, which does not amount to significantly more than the judicial exception. MPEP 2106.05(h).
Regarding the “wherein the downsampling retains i) signal of cardiac activity and ii) signal of gross motor activity” limitation, such limitation amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use as explained above, which does not amount to significantly more than the judicial exception. MPEP 2106.05(h).
Regarding the “wherein the training of the CNN and the training of the RNN use the i) signal of cardiac activity and ii) signal of gross motor activity” limitation, such limitation is recited at a high-level of generality and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception, because the limitation merely provides instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not add significantly more than the judicial exception. (See MPEP 2106.05(f)).
Regarding Claim 2
Step 2A, Prong 1
wherein generating the respiratory-disease classifier comprises extracting an epoch of data from the respiratory data for use in the training of the CNN and in the training of the RNN. (under the broadest reasonable interpretation, a human can mentally (or using pencil and paper) perform this limitation, for example, a human can mentally determine an epoch (or portion) of respiratory data to use when training the CNN and RNN)
Regarding Step 2A, Prong 2, the claim does not include any additional elements that integrate the judicial exception into a practical application and regarding Step 2B, there are no additional elements recited that amount to significantly more than the judicial exception.
Regarding Claim 3
Step 2A, Prong 1
wherein generating the respiratory-disease classifier comprises extracting overlapping epochs of data from the respiratory data for use in the training of the CNN and in the training of the RNN such that the training of the CNN and the training of the RNN is performed for overlapping epochs of data. (under the broadest reasonable interpretation, a human can mentally (or using pencil and paper) perform this limitation, for example, a human can mentally determine overlapping epochs (or portions) of respiratory data to use when training the CNN and RNN)
Regarding Step 2A, Prong 2, the claim does not include any additional elements that integrate the judicial exception into a practical application and regarding Step 2B, there are no additional elements recited that amount to significantly more than the judicial exception.
Regarding Claim 4
Step 2A, Prong 1
wherein the epoch is 10 seconds. (under the broadest reasonable interpretation, a human can mentally (or using pencil and paper) perform this limitation, for example, a human can mentally determine 10 second epochs (or portions) of respiratory data to use when training the CNN and RNN)
Regarding Step 2A, Prong 2, the claim does not include any additional elements that integrate the judicial exception into a practical application and regarding Step 2B, there are no additional elements recited that amount to significantly more than the judicial exception.
Regarding Claim 7
Step 2A, Prong 2
Regarding the “where the downsampling is to 40 Hz” limitation, this limitation merely describes aspects of the collected data, and such limitation amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (downsampled BCG streams as a data source). As explained by the Supreme Court, a claim directed to a judicial exception cannot be made eligible "simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use." Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not integrate a judicial exception into a practical application.
Step 2B
Regarding the “where the downsampling is to 40 Hz” limitation, such limitation amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use as explained above, which does not amount to significantly more than the judicial exception. MPEP 2106.05(h).
Regarding Claim 8
Step 2A, Prong 2
Regarding the “wherein the downsampling of the BCG stream removes signal of acoustic phenomena recorded in the BCG stream” limitation, this limitation merely describes aspects of the collected data, and such limitation amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (downsampled BCG streams as a data source). As explained by the Supreme Court, a claim directed to a judicial exception cannot be made eligible "simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use." Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not integrate a judicial exception into a practical application.
Step 2B
Regarding the “wherein the downsampling of the BCG stream removes signal of acoustic phenomena recorded in the BCG stream” limitation, such limitation amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use as explained above, which does not amount to significantly more than the judicial exception. MPEP 2106.05(h).
Regarding Claim 10
Step 2A, Prong 2
Regarding the “CNN is configured to perform feature extraction on the respiratory data” limitation, such limitation is recited at a high-level of generality and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception. In particular, the claim only recites the additional element of a CNN. This additional element is recited at a high-level of generality and amounts to no more than mere instructions to apply the exception using a generic computer component (a CNN). Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f)).
Regarding the “intermediate data comprises extracted features of the respiratory data” limitation, such limitation amounts to extra solution activity because it is a mere nominal or tangential addition to the claim, amounting to mere data output (see MPEP 2106.05(g)). Moreover, this limitation merely describes the type of data output by the CNN, and therefore such limitation amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (use of a CNN to generate features from a particular data set). As explained by the Supreme Court, a claim directed to a judicial exception cannot be made eligible "simply by having the applicant acquiesce to limiting the reach of the patent for the formula to a particular technological use." Diamond v. Diehr, 450 U.S. 175, 192 n.14, 209 USPQ 1, 10 n. 14 (1981). Thus, limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not integrate a judicial exception into a practical application.
Regarding the “the RNN is configured to use as input the extracted features” limitation, such limitation is recited at a high-level of generality and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception. In particular, the claim only recites the additional element of a RNN. This additional element is recited at a high-level of generality and amounts to no more than mere instructions to apply the exception using a generic computer component (a RNN). Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f)).
Step 2B
Regarding the “CNN is configured to perform feature extraction on the respiratory data” limitation, such limitation is recited at a high-level of generality and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception, because the limitation merely provides instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not add significantly more than the judicial exception. (See MPEP 2106.05(f)).
Regarding the “intermediate data comprises extracted features of the respiratory data” limitation, this limitation amounts to extra solution activity because it is a mere nominal or tangential addition to the claim, amounting to mere data output (see MPEP 2106.05(g)). The courts have similarly found limitations directed to displaying a result, recited at a high level of generality, to be well-understood, routine, and conventional. See (MPEP 2106.05(d)(II), "presenting offers and gathering statistics.", “determining an estimated outcome and setting a price”). Moreover, such limitation amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use as explained above, which does not amount to significantly more than the judicial exception. MPEP 2106.05(h).
Regarding the “the RNN is configured to use as input the extracted features” limitation, such limitation is recited at a high-level of generality and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception, because the limitation merely provides instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not add significantly more than the judicial exception. (See MPEP 2106.05(f)).
Regarding Claim 11
Step 2A, Prong 2
Regarding the “wherein the RNN is a gated recurrent network (GRU) / long short-term memory (LSTM) RNN” limitation, such limitation is recited at a high-level of generality and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception. In particular, the claim only recites the additional element of a GRU/LSTM RNN. This additional element is recited at a high-level of generality and amounts to no more than mere instructions to apply the exception using a generic computer component (a processor). Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f)).
Step 2B
Regarding the “wherein the RNN is a gated recurrent network (GRU) / long short-term memory (LSTM) RNN” limitation, such limitation is recited at a high-level of generality and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception, because the limitation merely provides instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not add significantly more than the judicial exception. (See MPEP 2106.05(f)).
Regarding Claim 12
Step 2A, Prong 2
Regarding the “wherein the RNN is configured to use post processing functions to generate the disease classification” limitation, such limitation is recited at a high-level of generality and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception. In particular, the claim only recites the additional element of a RNN + generic post-processing functions. This additional element is recited at a high-level of generality and amounts to no more than mere instructions to apply the exception using a generic computer component (a processor). Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f)).
Step 2B
Regarding the “wherein the RNN is configured to use post processing functions to generate the disease classification” limitation, such limitation is recited at a high-level of generality and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception, because the limitation merely provides instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not add significantly more than the judicial exception. (See MPEP 2106.05(f)).
Regarding Claim 13
Step 2A, Prong 2
Regarding the “wherein the post processing functions comprise concatenating output from a plurality of output nodes of the RNN” limitation, such limitation is recited at a high-level of generality and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception. In particular, the claim only recites the additional element of a concatenation operation with respect to RNN output. This additional element is recited at a high-level of generality and amounts to no more than mere instructions to apply the exception using a generic computer component (a processor). Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f)).
Step 2B
Regarding the “wherein the post processing functions comprise concatenating output from a plurality of output nodes of the RNN” limitation, such limitation is recited at a high-level of generality and amounts to no more than adding the words “apply it” (or an equivalent) with the judicial exception, because the limitation merely provides instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not add significantly more than the judicial exception. (See MPEP 2106.05(f)).
Regarding Claim 14
Step 2A, Prong 1
wherein the disease classification comprises an apnea-hypoxia index (AHI) value. (under the broadest reasonable interpretation, a human can mentally (or using pencil and paper), perform this limitation, for example, a human can mentally calculate the AHI and use the AHI as a criteria for classifying sleep apnea data samples)
Regarding Step 2A, Prong 2, the claim does not include any additional elements that integrate the judicial exception into a practical application and regarding Step 2B, there are no additional elements recited that amount to significantly more than the judicial exception.
Regarding Claim 15
Step 2A, Prong 1
wherein the operations further comprise generating an aggregated AHI value for a night's sleep from a plurality of disease classifications for a particular sleep session. (under the broadest reasonable interpretation, a human can mentally (or using pencil and paper), perform this limitation, for example, a human can mentally calculate the aggregated AHI according to this claim and use the aggregated AHI as a criteria for classifying sleep apnea data samples)
Regarding Step 2A, Prong 2, the claim does not include any additional elements that integrate the judicial exception into a practical application and regarding Step 2B, there are no additional elements recited that amount to significantly more than the judicial exception.
Regarding Claim 16
Step 2A, Prong 1
wherein the operations further comprise generating an aggregated AHI value for a user from a plurality of disease classifications from a plurality of sleep sessions that are one of the group comprising: contiguous or non-contiguous. (under the broadest reasonable interpretation, a human can mentally (or using pencil and paper), perform this limitation, for example, a human can mentally calculate the aggregated AHI from contiguous or non-contiguous sleep sessions and use the aggregated AHI as a criteria for classifying sleep apnea data samples)
Regarding Step 2A, Prong 2, the claim does not include any additional elements that integrate the judicial exception into a practical application and regarding Step 2B, there are no additional elements recited that amount to significantly more than the judicial exception.
Allowable Subject Matter
Claims 1-4, 7-8, and 10-16 have no prior art rejections and would be allowable if the rejections under 35 U.S.C. 101 are overcome.
The following is a statement of reasons for the indication of allowable subject matter:
Claim 1 would be considered allowable since none of the references of record either alone or in combination fairly disclose or suggest the combination of limitations specified in claim 1, including at least:
training a convolutional neural network (CNN) configured to use as input i) the respiratory data and ii) the tagging data, the CNN configured to generate intermediate data; and
training a recurrent neural network (RNN) configured to use as input the intermediate data, the RNN configured to generate a disease classification, the RNN comprising i) a prospective long short-term memory (LSTM) network using as input later disease classifications and ii) a historic LSTM network using as input previous disease classifications;
wherein the respiratory data is created with a ballistocardiogram (BCG) stream
wherein creation of the respiratory data comprises downsampling the BCG stream to a lower frequency; and
wherein the downsampling retains i) signal of cardiac activity and ii) signal of gross motor activity, and
wherein the training of the CNN and the training of the RNN use the i) signal of cardiac activity and ii) signal of gross motor activity.
The closest prior art of record discloses:
Liao, Jun, et al. "Recognizing diseases with multivariate physiological signals by a DeepCNN-LSTM network." Applied Intelligence 51.11 (March 20, 2021): pp. 7933-7945, hereinafter referenced as LIAO, discloses a CNN-LSTM system for disease recognition, which uses physiological signals to determine respiratory signals for patients resting on their back. (LIAO, p. 7934, section 1, p. 7935, sections 3-3.1).
US 20210365775 A1, hereinafter referenced as NAYAR, discloses a 2-layer bidirectional LSTM, including a forward and backwards layer for considering both past and future information. (para. 0068).
US 20200337566 A1, hereinafter referenced as PETERSON, discloses a data set that includes severity scores with respect to physiological data (para. 0117).
US 20200163627 A1, hereinafter referenced as SAYADI, discloses capturing respiratory data using a ballistocardiogram, and downsampling such received sensor data. (paras. 0068, 0092).
US 20170238847 A1, hereinafter referenced as INAN, discloses that “Ballistocardiography (BCG), the measurement of the mechanical forces of the body in reaction to cardiac ejection of blood” and more generally discloses that BCG data detects cardiac activity.
However, the examiner has found that the distinct feature of the applicant's claimed invention over the prior art is the explicit claiming of the aforementioned limitations in combination with all the other limitations as specified in claim 1. The examiner further finds that one of ordinary skill would not have been motivated to combine the prior art of record in the manner specifically recited in claim 1 without the hindsight aid of Applicant’s disclosure. In particular, the prior art of record does not teach using ballistocardiography to determine a “signal of gross motor activity”, does not teach downsampling BGC in a manner to retain such “signal of gross motor activity”, and does not teach training both a CNN and RNN using the “signal of gross motor activity” detected using BCG, including training a RNN having both a prospective and historic LSTM network for the purpose of classifying a respiratory disease.
Therefore, to the extent that these features are not found in the prior art cited by the examiner, claim 1 would be held allowable over the prior art, provided that the rejection under 35 U.S.C. 101 is overcome.
Claims 2-4, 7-8, and 10-16 depend from claim 1, and would be allowed for the same reasons explained with respect to claim 1, provided that the rejections under 35 U.S.C. 101 are overcome.
Conclusion
THIS ACTION IS MADE FINAL. 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.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 20120220835 A1 (Chung). “Digital signal processing can be used to reduce the noise from the physiological data. For example, respiration causes periodic movement of the chest, which can interfere with BCG measurements, which rely on minute movements of the patient's torso. ... If such activities cause too much noise for the BCG measurement, then the BCG measurements can be temporarily halted until these activities cease and normal BCG measurements can again be taken. The most accurate data collection generally occurs, with respect to at least BCG measurements, when the patient is still, like for example, when the patient is sleeping.” (para. 0042). In other words, patient movement interferes with BCG measurements.
US 20180296163 A1 (DeBusschere). “By way of example, consider an integrated floormat capable of sensing data to create an electrocardiograph (ECG) and ballistocardiogram (BCG). The floormat offers the advantage of an inconspicuous measurement device that is much less disruptive to the patient than standard ECG electrodes or blood-pressure cuffs. Beyond the standard vitals of heart rate, heart rate variability, and respiration rate, the ECG and BCG can nominally be combined to monitor the timing of important cardiac events, such as contraction and aortic valve opening. They can also be combined with a photo-plethysmogram (PPG) to measure pulse transit time, allowing for an estimation of pulse wave velocity, which correlates with arterial blood pressures. This type of monitor, however, often has low signal quality and susceptibility to artifacts, such as a muscle's EMG corrupting the ECG or physical body motion corrupting BCG.” (para. 0020).
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/MICHAEL C. LEE/Examiner, Art Unit 2128
/OMAR F FERNANDEZ RIVAS/Supervisory Patent Examiner, Art Unit 2128