DETAILED ACTION
This Office Action is in response to the amendments filed on 03/03/2026.
Claims 1, 5, 7, 21-22, 25-27, 29, and 35-37, 41-42, and 45 are currently amended.
Claims 1-2, 5, 7, 9, 16, 18-19, 21-22, 25-27, 29, 35-37, 41-42, and 45 are currently pending in this application and have been examined.
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
In reference to Applicant’s arguments on page(s) 13 regarding claim objections:
The Examiner has objected to claims 22, 26-27, 29, and 35-37 because of defects in their preamble. Applicant has amended claims 22, 27, 29, and 35-37 to depend on claim 21 which is a method claim and claim 26 to depend on claim 25 which is not cancelled. Reconsideration and withdrawal of the rejection are respectfully requested.
Examiner’s response:
Applicant’s arguments and amendments have been fully considered and the objections on the above mentioned claims are withdrawn.
In reference to Applicant’s arguments on page(s) 13-14 regarding rejections made under 35 U.S.C. 101:
The Examiner has rejected claims 1, 2, 5, 7, 9, 16, 18, 19, 21, 22, 25-27, 29, 35-37, 41-42, and 45 under 35 U.S.C. 101 because they are allegedly directed toward an abstract idea without significantly more.
Without conceding to the merit of the Examiner's rejection and solely to advance prosecution on this point, Applicant has amended claims 1, 21, 41, 42, and 45.
Applicant has clarified that at least one set is a non-matching set with an anchor window and a negative sample window from the same subject. The inclusion of such non-matching sets can enable the trained embedder neural network to better extract relevant features from the windows to better classify states within the same patient. As described in paragraph [0288] the pending subject matter can be used to train neural networks to label EEG data related to sleep staging where the subject passes through different stages of sleep in a given session. Accordingly, training the embedder neural network on data that may be of a different stage within the same session and from the same user can improve the resulting neural network.
Applicant submits that the claims recite no judicial exceptions.
The claims recite systems and methods for training neural networks (claims 1, 21, 41) and an apparatus for classifying data with a neural network (claim 45). The computer components of these claims are inextricably tied to the claimed subject matter. Accordingly, the claims recite no mental processes as the claimed processes are carried out with computing components.
More specifically, "label the unlabeled training bio-signal data" does not recite a judicial exception because the limitation specifies that this labeling is done "using a classifier, the labeled training bio-signal data, and the embedder neural network". These include neural network models and accordingly cannot be carried out in the mind.
Applicant submits that any judicial exceptions (of which Applicant does not concede there are any) are integrated into practical application.
An improvement in the functioning of a computer, or an improvement to other technology or technical field integrate judicial exceptions into practical applications (MPEP, s. 2106.04(d). I. RELEVANT CONSIDERATIONS FOR EVALUATING WHETHER ADDITIONAL ELEMENTS INTEGRATE A JUDICIAL EXCEPTION INTO A PRACTICAL APPLICATION).
As described above, "label the unlabeled training bio-signal data using a classifier, the labeled training bio-signal data, and the embedder neural network" is an addition element that cannot be carried out in the human mind. Applicant submits that the information provided by any of the judicial exceptions is employed to update the embedder neural network and subsequently label the unlabelled training bio-signal data with the classifier and the embedder neural network. This limitation along with the other limitations that update the neural network provide the specific details that render the embedder neural network more specific than a generic computer component.
Examiner’s response:
Applicant’s arguments have been fully considered but are found to be not persuasive.
Applicant argues that the limitations reciting the action(s) of labeling unlabeled training data cannot be performed in the human mind since the labeling is performed via a classifier and an embedder neural network. Examiner disagrees, the action of labeling unlabeled data can be reasonably performed in the human mind and does not require the use of a neural network to do so. Even if the claim limitations are performed with the use of a neural network, the use of said network does not preclude the action from being able to be performed in the human mind and the use of the neural network, without any information about how that network is unique in its own right, simply directs the claim limitation to being performed by a generic computer component.
Applicant argues that the use of the embedder neural network provides the specific details that render the embedder neural network more specific than a generic computer component. Examiner disagrees. As mentioned above, the use of the embedder neural network does not preclude the action(s) of labeling unlabeled data from being performed in the human mind. The claims do not provide any information as to what makes this embedder neural network novel in its use, aside from the limitations that mention the extraction of features from the anchor windows using the embedder network. Feature extraction via a neural network is not a novel invention, and even if it was, data can still be labeled without the use of the neural network.
In reference to Applicant’s arguments on page(s) 14-15 regarding rejections made under 35 U.S.C. 103:
Without conceding to the merit of the Examiner's rejection and solely to advance prosecution on this point, Applicant has amended claims 1, 21, 41, 42, and 45.
The pending subject matter can be used to determine and label data that may change over the course of a single session for a subject. For example, as described in paragraph [0288] the pending subject matter can be used to label EEG data related to sleep staging where the subject passes through different stages of sleep in a given session. Applicant has amended the claims to clarify that at least one non-matching set includes and anchor window and a negative sample window from the same subject. This can enable the subject matter to properly train the models to label subject states that may evolve within the same subject over time (e.g., sleep staging).
Kiyasseh redefines shared context to refer to representations that belong to the same patient (s. 4.1, p. 3) and goes on to define the negative examples as instances from different patients. This works within the context of Kiyasseh because the ultimate labels relate to conditions which the patients exhibit rather than transient states the patients may pass though.
Furthermore, the Examiner asserts that as the embedding dimension increases, the distance between representations increases (as described in section E, page 32) discloses update trainable parameters of the embedder neural network to minimize a difference between the determined set representation and the predicted set representation. Applicant respectfully disagrees. The embedding dimension is not treated as a trainable parameter in Kiyasseh. Furthermore, the distance between the representations are compared on an inter-patient v an intra-patient basis. As described above, the pending claims can be used to determine states that may change within a subject. Attempting to increase the distance between the intra-patient distance and the inter-patient distance provides no way to discriminate between data arising from the same patient but having a different state.
Accordingly, Kiyasseh fails to disclose "wherein at least one set is a non-matching set comprising an anchor window and a negative sample window each from one subject of the one or more subjects" and "updating trainable parameters of the embedder neural network to minimize a difference between the determined set representation of the each and the predicted set representation of the each set” as now claimed.
None of Guvenc, Kushnir, and Jeong remedy this deficiency.
Applicant submits substantially the same arguments for claims 21, 41, 42, and 45. Applicant submits that the claims, as amended, are inventive over Kiyasseh, Guvenc, Kushnir, and Jeong. Reconsideration and withdrawal of the rejection are respectfully requested.
Examiner’s response:
Applicant’s arguments have been fully considered and are found to be persuasive.
Applicant argues that the prior art reference of Kiyasseh is mischaracterized in regards to the teaching of positive and negative anchor windows. Examiner agrees. Upon further consideration of Kiyasseh, and the other applied prior art references, the limitation regarding negative anchor windows about the same patient(s) is not disclosed. Furthermore, the amended limitation of “a non-matching set comprising an anchor window and a negative sample window…” is also not taught by any applied reference; in order to remedy this deficiency a new search was conducted and relevant art was identified as being closely related to, but not directly teaching that limitation, and as such the rejections are withdrawn.
In light of the amendments made on the claims, the rejections made under 35 U.S.C. 103 are withdrawn.
Claim Rejections - 35 USC § 101
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claims 1, 2, 5, 7, 9, 16, 18, 19, 21, 22, 25-27, 29, 35-37, 41, 42, and 45 are rejected under 35 U.S.C. 101 because they are directed toward an abstract idea without significantly more.
Step 1 Analysis:
Independent Claims 1, 41, and 42 recite, in part, a system for classifying bio-signal data consisting of a memory and computing apparatus, therefore falling into the statutory category of manufacture. Independent Claim 21 recites, in part, a method for training a neural network, therefore falling into the statutory category of process. Independent Claim 45 recites, in part, an apparatus for classifying bio-signal data, therefore falling into the statutory category of machine.
Regarding Claim 1:
Step 2A: Prong 1 analysis:Claim 1 recites in part:
“define one or more sets of time windows within the training bio-signal data, each set comprising a first anchor window and a sampled window”. As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgement, or opinion) or with the aid of pencil and paper. For example, this limitation encompasses defining windows of observation of the provided data.
“determine a determined set representation based in part on the relative position of the first anchor window and the sampled window”. As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgement, or opinion) or with the aid of pencil and paper. For example, this limitation encompasses determining a representation of the data based on the defined windows of observation.
“predict a predicted set representation using the aggregated feature representations”. As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgement, or opinion) or with the aid of pencil and paper. For example, this limitation encompasses making a prediction based on aggregated data.
“aggregate the feature representations”. As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgement, or opinion) or with the aid of pencil and paper. For example, this limitation encompasses grouping data together.
“update trainable parameters of the embedder neural network to minimize a difference between the determined set representation of the at least one set and the predicted set representation of the at least one set”. As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgement, or opinion) or with the aid of pencil and paper. For example, this limitation encompasses changing parameters/settings of a model.
“label the unlabeled training bio-signal data”. As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgement, or opinion) or with the aid of pencil and paper. For example, this limitation encompasses adding labels to unlabeled data.
Accordingly, at Step 2A: Prong 1, the claim is directed to an abstract idea.
Step 2A: Prong 2 analysis:
The judicial exception is not integrated into practical application. In particular, the claim recites the additional elements of:
“a memory configured to store training bio-signal data from one or more subjects”. This additional element is recited at a high level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component (memory) (See MPEP 2106.05(f)).
“wherein the training bio- signal data comprises labeled training bio-signal data and unlabeled training bio-signal data”. This limitation merely indicates a field of use or technological environment in which the judicial exception is performed (bio-signals) and thus fails to add an inventive concept to the claims. See MPEP 2106.05(h).
“receive the training bio-signal data from the memory”. This additional elements is recited at a high level of generality and amounts to extra-solution activity of gathering data i.e. pre-solution activity of gathering data for use in the claimed process.
“extract a feature representation of the first anchor window and a feature representation of the sampled window using an embedder neural network”. This additional elements is recited at a high level of generality and amounts to extra-solution activity of gathering data i.e. pre-solution activity of gathering data for use in the claimed process.
“using a contrastive module”. This additional element is recited at a high level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component (contrastive model) (See MPEP 2106.05(f)).
“wherein the set representation denotes likely label correspondence between the first anchor window and the sampled window”. This limitation merely indicates a field of use or technological environment in which the judicial exception is performed (data labels) and thus fails to add an inventive concept to the claims. See MPEP 2106.05(h).
“wherein at least one set is a non-matching set comprising an anchor window and a negative sample window each from one subject of the one or more subjects”. This limitation merely indicates a field of use or technological environment in which the judicial exception is performed (bi0-signals) and thus fails to add an inventive concept to the claims. See MPEP 2106.05(h).
“using a classifier, the labeled training bio-signal data, and the embedder neural network”. This additional element is recited at a high level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component (neural network) (See MPEP 2106.05(f)).
Accordingly at Step 2A: Prong 2, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B analysis:
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 element(s) of “a memory configured to store training bio-signal data from one or more subjects”, “using a contrastive module” and “using a classifier, the labeled training bio-signal data, and the embedder neural network” is/are recited at a high-level of generality such that it/they amount(s) to no more than mere instructions to apply the exception using generic computer components (See MPEP 2106.05(f)).
The additional element(s) of “wherein the training bio- signal data comprises labeled training bio-signal data and unlabeled training bio-signal data” and “wherein the set representation denotes likely label correspondence between the first anchor window and the sampled window”, and “wherein at least one set is a non-matching set comprising an anchor window and a negative sample window each from one subject of the one or more subjects” is/are directed to particular field(s) of use (bio-signals and data labels) (MPEP 2106.05(h)) and therefore do not provide significantly more than the abstract idea, and thus the claim is subject-matter ineligible.
The additional element(s) of “receive the training bio-signal data from the memory” and “extract a feature representation of the first anchor window and a feature representation of the sampled window using an embedder neural network” is/are recited at a high level of generality and amount(s) 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").
Accordingly, at Step 2B, the additional elements individually or in combination do not amount to significantly more than the judicial exception.
Regarding Claim 2:
Step 2A: Prong 1 analysis:
Claim 2 recites in part:
“label the user bio-signal data”. As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgement, or opinion) or with the aid of pencil and paper. For example, this limitation encompasses adding labels to unlabeled data.
Accordingly, at Step 2A: Prong 1, the claim is directed to an abstract idea.
Step 2A: Prong 2 analysis:
The judicial exception is not integrated into practical application. In particular, the claim recites the additional elements of:
“a bio-signal sensor configured to receive user bio-signal data from a user”. This additional elements is recited at a high level of generality and amounts to extra-solution activity of gathering data i.e. pre-solution activity of gathering data for use in the claimed process.
“receive the embedder neural network from the training computing apparatus”. This additional elements is recited at a high level of generality and amounts to extra-solution activity of gathering data i.e. pre-solution activity of gathering data for use in the claimed process.
“receive the user bio-signal data from the bio-signal sensor”. This additional elements is recited at a high level of generality and amounts to extra-solution activity of gathering data i.e. pre-solution activity of gathering data for use in the claimed process.
“using the embedder neural network”. This additional element is recited at a high level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component (neural network) (See MPEP 2106.05(f)).
Accordingly at Step 2A: Prong 2, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B analysis:
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 element(s) of “using the embedder neural network” is/are recited at a high-level of generality such that it/they amount(s) to no more than mere instructions to apply the exception using generic computer components (See MPEP 2106.05(f)).
The additional element(s) of “a bio-signal sensor configured to receive user bio-signal data from a user”, “receive the embedder neural network from the training computing apparatus”, and “receive the user bio-signal data from the bio-signal sensor” is/are recited at a high level of generality and amount(s) 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").
Accordingly, at Step 2B, the additional elements individually or in combination do not amount to significantly more than the judicial exception.
Regarding Claim 5:
Step 2A: Prong 1 analysis:
Claim 5 recites in part:
“defining a positive context region and a negative context region surrounding the first anchor window”. As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgement, or opinion) or with the aid of pencil and paper. For example, this limitation encompasses defining data in an observation window.
“determining if the sampled window is within the positive context region or the negative context region”. As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgement, or opinion) or with the aid of pencil and paper. For example, this limitation encompasses determining if data is within a previously defined window.
Accordingly, at Step 2A: Prong 1, the claim is directed to an abstract idea.
Step 2A: Prong 2 analysis:
The judicial exception is not integrated into practical application. In particular, the claim recites the additional elements of:
“the one or more sets of time windows comprise one or more pairs of time windows”. This limitation merely indicates a field of use or technological environment in which the judicial exception is performed (timing windows) and thus fails to add an inventive concept to the claims. See MPEP 2106.05(h).
“the at least one set of the one or more sets comprises at least one pair of the one or more pairs”. This limitation merely indicates a field of use or technological environment in which the judicial exception is performed (timing windows) and thus fails to add an inventive concept to the claims. See MPEP 2106.05(h).
Accordingly at Step 2A: Prong 2, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B analysis:
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception.
The additional element(s) of “the one or more sets of time windows comprise one or more pairs of time windows” and “the at least one set of the one or more sets comprises at least one pair of the one or more pairs” is/are directed to particular field(s) of use (timing windows) (MPEP 2106.05(h)) and therefore do not provide significantly more than the abstract idea, and thus the claim is subject-matter ineligible.
Accordingly, at Step 2B, the additional elements individually or in combination do not amount to significantly more than the judicial exception.
Regarding Claim 7:
Step 2A: Prong 1 analysis:
Claim 7 recites in part:
“determining a temporal order of the first anchor window, the sampled window, and the second anchor window”. As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgement, or opinion) or with the aid of pencil and paper. For example, this limitation encompasses determining the order of observation windows based on the timing of the windows.
Accordingly, at Step 2A: Prong 1, the claim is directed to an abstract idea.
Step 2A: Prong 2 analysis:
The judicial exception is not integrated into practical application. In particular, the claim recites the additional elements of:
“the one or more sets of time windows comprise one or more triplets of time windows, each triplet further comprising a second anchor window, wherein the second anchor window is within a positive context region surrounding the first anchor window”. This limitation merely indicates a field of use or technological environment in which the judicial exception is performed (timing windows) and thus fails to add an inventive concept to the claims. See MPEP 2106.05(h).
“the at least one set of the one or more sets comprises at least one triplet of the one or more triplets”. This limitation merely indicates a field of use or technological environment in which the judicial exception is performed (timing windows) and thus fails to add an inventive concept to the claims. See MPEP 2106.05(h).
“the extract the feature representation of the first anchor window and a feature representation of the sampled window using an embedder neural network”. This additional element is recited at a high level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component (neural network) (See MPEP 2106.05(f)).
“further comprises extracting a feature representation of the second anchor window”. This additional elements is recited at a high level of generality and amounts to extra-solution activity of gathering data i.e. pre-solution activity of gathering data for use in the claimed process.
Accordingly at Step 2A: Prong 2, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B analysis:
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception.
The additional element(s) of “the one or more sets of time windows comprise one or more triplets of time windows, each triplet further comprising a second anchor window, wherein the second anchor window is within a positive context region surrounding the first anchor window” and “the at least one set of the one or more sets comprises at least one triplet of the one or more triplets” is/are directed to particular field(s) of use (timing windows) (MPEP 2106.05(h)) and therefore do not provide significantly more than the abstract idea, and thus the claim is subject-matter ineligible.
As discussed above, the additional element(s) of “the extract the feature representation of the first anchor window and a feature representation of the sampled window using an embedder neural network” is/are recited at a high-level of generality such that it/they amount(s) to no more than mere instructions to apply the exception using generic computer components (See MPEP 2106.05(f)).
The additional element(s) of “further comprises extracting a feature representation of the second anchor window” is/are recited at a high level of generality and amount(s) 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").
Accordingly, at Step 2B, the additional elements individually or in combination do not amount to significantly more than the judicial exception.
Regarding Claim 9:
Step 2A: Prong 1 analysis:
Claim 9 recites in part:
“the training computing apparatus determines the determined set representation based in part on the relative position of the first anchor window and the sampled window by determining that a given sampled window is in the series of sampled windows”. As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgement, or opinion) or with the aid of pencil and paper. For example, this limitation encompasses determining that a timing window comes from a given series of sample timing windows.
“aggregating the embedded anchor series, a given feature representation of a given sampled window of the series of sampled windows, and one or more given feature representations of one or more given negative sample windows of the set of negative sample windows”. As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgement, or opinion) or with the aid of pencil and paper. For example, this limitation encompasses grouping data together.
“the predict the predicted set representation comprises predicting which of the given feature representations corresponds to the given feature representation of the sampled window of the series of sampled windows”. As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgement, or opinion) or with the aid of pencil and paper. For example, this limitation encompasses predicting which feature representation corresponds to a given timing window.
Accordingly, at Step 2A: Prong 1, the claim is directed to an abstract idea.
Step 2A: Prong 2 analysis:
The judicial exception is not integrated into practical application. In particular, the claim recites the additional elements of:
“the first anchor window comprises a series of consecutive anchor windows”. This limitation merely indicates a field of use or technological environment in which the judicial exception is performed (timing windows) and thus fails to add an inventive concept to the claims. See MPEP 2106.05(h).
“the sampled window comprises a series of consecutive sampled windows, wherein the series of consecutive sampled windows is adjacent to the series of consecutive anchor windows”. This limitation merely indicates a field of use or technological environment in which the judicial exception is performed (timing windows) and thus fails to add an inventive concept to the claims. See MPEP 2106.05(h).
“the set further comprises a set of negative sample windows”. This limitation merely indicates a field of use or technological environment in which the judicial exception is performed (timing windows) and thus fails to add an inventive concept to the claims. See MPEP 2106.05(h).
“extracting a feature representation of each anchor window of the series of consecutive anchor windows”. This additional elements is recited at a high level of generality and amounts to extra-solution activity of gathering data i.e. pre-solution activity of gathering data for use in the claimed process.
“extracting a feature representation of each sampled window of the series of consecutive sampled windows”. This additional elements is recited at a high level of generality and amounts to extra-solution activity of gathering data i.e. pre-solution activity of gathering data for use in the claimed process.
“extracting a feature representation of each negative sample window of the set of negative sample windows”. This additional elements is recited at a high level of generality and amounts to extra-solution activity of gathering data i.e. pre-solution activity of gathering data for use in the claimed process.
“embedding the feature representation of each anchor window of the series of anchor windows using an autoregressive embedder”. This additional element is recited at a high level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component (autoregressive embedder) (See MPEP 2106.05(f)).
Accordingly at Step 2A: Prong 2, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B analysis:
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception.
The additional element(s) of “the first anchor window comprises a series of consecutive anchor windows”, “the sampled window comprises a series of consecutive sampled windows, wherein the series of consecutive sampled windows is adjacent to the series of consecutive anchor windows”, and “the set further comprises a set of negative sample windows” is/are directed to particular field(s) of use (timing windows) (MPEP 2106.05(h)) and therefore do not provide significantly more than the abstract idea, and thus the claim is subject-matter ineligible.
The additional element(s) of “extracting a feature representation of each anchor window of the series of consecutive anchor windows”, “extracting a feature representation of each sampled window of the series of consecutive sampled windows”, and “extracting a feature representation of each negative sample window of the set of negative sample windows” is/are recited at a high level of generality and amount(s) 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").
As discussed above, the additional element(s) of “embedding the feature representation of each anchor window of the series of anchor windows using an autoregressive embedder” is/are recited at a high-level of generality such that it/they amount(s) to no more than mere instructions to apply the exception using generic computer components (See MPEP 2106.05(f)).
Accordingly, at Step 2B, the additional elements individually or in combination do not amount to significantly more than the judicial exception.
Regarding Claim 16:
Step 2A: Prong 2 analysis:
The judicial exception is not integrated into practical application. In particular, the claim recites the additional elements of:
“the training computing apparatus comprises a server configured to upload the embedder neural network and the classifier to the classifier computing apparatus”. This additional element is recited at a high level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component (server) (See MPEP 2106.05(f)).
Accordingly at Step 2A: Prong 2, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B analysis:
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 element(s) of “the training computing apparatus comprises a server configured to upload the embedder neural network and the classifier to the classifier computing apparatus” is/are recited at a high-level of generality such that it/they amount(s) to no more than mere instructions to apply the exception using generic computer components (See MPEP 2106.05(f)).
Accordingly, at Step 2B, the additional elements individually or in combination do not amount to significantly more than the judicial exception.
Regarding Claim 18:
Step 2A: Prong 1 analysis:
Claim 18 recites in part:
“the update trainable parameters comprises updating trainable parameters of the classifier neural network”. As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgement, or opinion) or with the aid of pencil and paper. For example, this limitation encompasses updating variables.
Accordingly, at Step 2A: Prong 1, the claim is directed to an abstract idea.
Step 2A: Prong 2 analysis:
The judicial exception is not integrated into practical application. In particular, the claim recites the additional elements of:
“the classifier comprises a classifier neural network”. This limitation merely indicates a field of use or technological environment in which the judicial exception is performed (classifier neural network) and thus fails to add an inventive concept to the claims. See MPEP 2106.05(h).
Accordingly at Step 2A: Prong 2, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B analysis:
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception.
The additional element(s) of “the classifier comprises a classifier neural network” is/are directed to particular field(s) of use (classifier neural networks) (MPEP 2106.05(h)) and therefore do not provide
Accordingly, at Step 2B, the additional elements individually or in combination do not amount to significantly more than the judicial exception.
Regarding Claim 19:
Step 2A: Prong 1 analysis:
Claim 19 recites in part:
“the update trainable parameters further comprises updating trainable parameters of the contrastive neural network”. As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgement, or opinion) or with the aid of pencil and paper. For example, this limitation encompasses updating variables.
Accordingly, at Step 2A: Prong 1, the claim is directed to an abstract idea.
Step 2A: Prong 2 analysis:
The judicial exception is not integrated into practical application. In particular, the claim recites the additional elements of:
“the contrastive module comprises a contrastive neural network”. This limitation merely indicates a field of use or technological environment in which the judicial exception is performed (contrastive neural network) and thus fails to add an inventive concept to the claims. See MPEP 2106.05(h).
Accordingly at Step 2A: Prong 2, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B analysis:
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception.
The additional element(s) of “the contrastive module comprises a contrastive neural network” is/are directed to particular field(s) of use (contrastive neural networks) (MPEP 2106.05(h)) and therefore do not provide
Accordingly, at Step 2B, the additional elements individually or in combination do not amount to significantly more than the judicial exception.
Regarding Claim 21:
Due to claim language similar to that of Claim 1, Claim 21 is rejected for the same reasons as presented above in the rejection of Claim 1.
Regarding Claim 22:
Step 2A: Prong 1 analysis:
Claim 22 recites in part:
“labeling the user bio-signal data”. As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgement, or opinion) or with the aid of pencil and paper. For example, this limitation encompasses labeling data.
Accordingly, at Step 2A: Prong 1, the claim is directed to an abstract idea.
Step 2A: Prong 2 analysis:
The judicial exception is not integrated into practical application. In particular, the claim recites the additional elements of:
“receiving user bio-signal data from a user using a bio-signal sensor”. This additional elements is recited at a high level of generality and amounts to extra-solution activity of gathering data i.e. pre-solution activity of gathering data for use in the claimed process.
“using the embedder neural network and the classifier”. This additional element is recited at a high level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component (neural network) (See MPEP 2106.05(f)).
Accordingly at Step 2A: Prong 2, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B analysis:
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception.
The additional element(s) of “receiving user bio-signal data from a user using a bio-signal sensor” is/are recited at a high level of generality and amount(s) 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").
As discussed above, the additional element(s) of “using the embedder neural network and the classifier” is/are recited at a high-level of generality such that it/they amount(s) to no more than mere instructions to apply the exception using generic computer components (See MPEP 2106.05(f)).
Accordingly, at Step 2B, the additional elements individually or in combination do not amount to significantly more than the judicial exception.
Regarding Claim 25:
Due to claim language similar to that of Claim 5, Claim 25 is rejected for the same reasons as presented above in the rejection of Claim 5.
Regarding Claim 26:
Step 2A: Prong 1 analysis:
Claim 26 recites in part:
“the determining a determined set representation based in part on the relative position of the first anchor window and the sampled window further comprises: rejecting the at least one pair if the sampled window is not within the positive context region or the negative context region”. As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgement, or opinion) or with the aid of pencil and paper. For example, this limitation encompasses rejecting data if it does not fall within a predetermined region.
Accordingly, at Step 2A: Prong 1, the claim is directed to an abstract idea.
Step 2A: Prong 2 analysis:
The claim does not recite any additional elements that integrate the judicial exception into a practical application.
Step 2B analysis:
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception.
Regarding Claim 27:
Step 2A: Prong 1 analysis:
Claim 27 recites in part:
“the determining a determined set representation based in part on the relative position of the first anchor window and the sampled window comprises: determining a temporal order of the first anchor window, the sampled window, and the second anchored window”. As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgement, or opinion) or with the aid of pencil and paper. For example, this limitation encompasses determining that timing windows are in the right order temporally.
Accordingly, at Step 2A: Prong 1, the claim is directed to an abstract idea.
Step 2A: Prong 2 analysis:
The judicial exception is not integrated into practical application. In particular, the claim recites the additional elements of:
“the one or more sets of time windows comprise one or more triplets of time windows, each triplet further comprising a second anchor window, wherein the second anchor window is within a positive context region surrounding the first anchor window”. This limitation merely indicates a field of use or technological environment in which the judicial exception is performed (timing windows) and thus fails to add an inventive concept to the claims. See MPEP 2106.05(h).
“the at least one set of the one or more sets comprises at least one triplet of the one or more triplets”. This limitation merely indicates a field of use or technological environment in which the judicial exception is performed (timing windows) and thus fails to add an inventive concept to the claims. See MPEP 2106.05(h).
“the extract a feature representation of the first anchor window and a feature representation of the sampled window using an embedder neural network further comprises extracting a feature representation of the second anchor window”. This additional elements is recited at a high level of generality and amounts to extra-solution activity of gathering data i.e. pre-solution activity of gathering data for use in the claimed process.
Accordingly at Step 2A: Prong 2, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B analysis:
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception.
The additional element(s) of “the one or more sets of time windows comprise one or more triplets of time windows, each triplet further comprising a second anchor window, wherein the second anchor window is within a positive context region surrounding the first anchor window” and “the at least one set of the one or more sets comprises at least one triplet of the one or more triplets” is/are directed to particular field(s) of use (timing windows) (MPEP 2106.05(h)) and therefore do not provide significantly more than the abstract idea, and thus the claim is subject-matter ineligible.
The additional element(s) of “the extract a feature representation of the first anchor window and a feature representation of the sampled window using an embedder neural network further comprises extracting a feature representation of the second anchor window” is/are recited at a high level of generality and amount(s) 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").
Accordingly, at Step 2B, the additional elements individually or in combination do not amount to significantly more than the judicial exception.
Regarding Claim 29:
Due to claim language similar to that of Claim 9, Claim 29 is rejected for the same reasons presented above in the rejection of Claim 9, with the exception of the limitation(s) covered below.
Step 2A: Prong 1 analysis:
Claim 29 recites in part:
“the determining a determined set representation based in part on the relative position of the first anchor window and the sampled window comprises determining that a given sampled window is in the series of sampled windows”. As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgement, or opinion) or with the aid of pencil and paper. For example, this limitation encompasses verifying that the given time window is within the sample of time windows.
Accordingly, at Step 2A: Prong 1, the claim is directed to an abstract idea.
Step 2A: Prong 2 analysis:
The claim does not recite any additional elements that integrate the judicial exception into a practical application.
Step 2B analysis:
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception.
Regarding Claim 35:
Step 2A: Prong 2 analysis:
The judicial exception is not integrated into practical application. In particular, the claim recites the additional elements of:
“uploading the embedder neural network to a server”. This additional elements is recited at a high level of generality and amounts to extra-solution activity of gathering data i.e. pre-solution activity of gathering data for use in the claimed process.
Accordingly at Step 2A: Prong 2, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B analysis:
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception.
The additional element(s) of “uploading the embedder neural network to a server.” is/are recited at a high level of generality and amount(s) 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").
Accordingly, at Step 2B, the additional elements individually or in combination do not amount to significantly more than the judicial exception.
Regarding Claim 36:
Due to claim language similar to that of Claim 19, Claim 36 is rejected for the same reasons as presented above in the rejection of Claim 19.
Regarding Claim 37:
Due to claim language similar to that of Claim 18, Claim 37 is rejected for the same reasons as presented above in the rejection of Claim 18.
Regarding Claim 41:
Due to claim language similar to that of Claims 1 and 21, Claim 41 is rejected for the same reasons as presented above in the rejection of Claims 1 and 21, with the exception of the limitation(s) covered below.
Step 2A: Prong 1 analysis:
Claim 41 recites in part:
“define one or more sets of time windows within the training bio-signal data, each set comprising a series of consecutive anchor windows, a series of consecutive sampled windows, and a set of negative sample windows, and wherein the series of consecutive sampled windows is adjacent to the series of consecutive anchor windows”. As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgement, or opinion) or with the aid of pencil and paper. For example, this limitation encompasses defining a set of timing windows of the training data, where each series of windows is consecutive.
Accordingly, at Step 2A: Prong 1, the claim is directed to an abstract idea.
Step 2A: Prong 2 analysis:
The judicial exception is not integrated into practical application. In particular, the claim recites the additional elements of:
“embed the feature representation of each anchor window of the series of anchor windows using an autoregressive embedder”. This additional element is recited at a high level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component (autoregressive embedder) (See MPEP 2106.05(f)).
Accordingly at Step 2A: Prong 2, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B analysis:
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 element(s) of “embed the feature representation of each anchor window of the series of anchor windows using an autoregressive embedder” is/are recited at a high-level of generality such that it/they amount(s) to no more than mere instructions to apply the exception using generic computer components (See MPEP 2106.05(f)).
Accordingly, at Step 2B, the additional elements individually or in combination do not amount to significantly more than the judicial exception.
Regarding Claim 42:
Due to claim language similar to that of Claims 1, 21, and 41, Claim 42 is rejected for the same reasons as presented above in the rejection of Claims 1, 21, and 41.
Regarding Claim 45:
Due to claim language similar to that of Claims 1, 21, 41, and 42, Claim 45 is rejected for the same reasons as presented above in the rejection of Claims 1, 21, 41, and 42, with the exception of the limitation(s) covered below.
Step 2A: Prong 2 analysis:
The judicial exception is not integrated into practical application. In particular, the claim recites the additional elements of:
“a bio-signal sensor configured to receive bio-signal data from a subject, the bio-signal data comprising unlabeled bio-signal data”. This additional element is recited at a high level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component (sensor) (See MPEP 2106.05(f)).
Accordingly at Step 2A: Prong 2, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B analysis:
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 element(s) of “a bio-signal sensor configured to receive bio-signal data from a subject, the bio-signal data comprising unlabeled bio-signal data” is/are recited at a high-level of generality such that it/they amount(s) to no more than mere instructions to apply the exception using generic computer components (See MPEP 2106.05(f)).
Accordingly, at Step 2B, the additional elements individually or in combination do not amount to significantly more than the judicial exception.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Kiyasseh, D., Zhu, T., & Clifton, D. A. (2020). CLOCS: Contrastive Learning of Cardiac Signals Across Space, Time, and Patients. arXiv [Cs.LG]. Retrieved from http://arxiv.org/abs/2005.13249 – a family of contrastive learning methods, CLOCS, that encourages representations across space, time, and patients to be similar to one another
Kyu-Hwa Jeong, Jian-Wu Xu and J. C. Principe, "An information theoretic approach to adaptive system training using unlabeled data," Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005., Montreal, QC, Canada, 2005, pp. 191-195 vol. 1, doi: 10.1109/IJCNN.2005.1555828. – an information theoretic learning (ITL) approach based on density divergence minimization to obtain an extended training algorithm using unlabeled data during the testing
US 20220095992 A1 – A system for monitoring brain activity of a subject, including an implantable measurement device
US 20200202210 A1 – systems and methods for training a neural network
US 20190387998 A1 – A system and method may be provided for associating bio-signal data (e.g. EEG brain scan data) from at least one user with at least one music data item (e.g. song, or piece of music)
US 9983670 B2 – A computer network implemented system for improving the operation of one or more biofeedback computer system
US 20140223462 A1 – A computer system or method may be provided for modulating content based on a person's brainwave data, including modifying presentation of digital content at least one computing device
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to COREY M SACKALOSKY whose telephone number is (703)756-1590. The examiner can normally be reached M-F 7:30am-3:30pm EST.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Omar Fernandez Rivas can be reached at (571) 272-2589. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/COREY M SACKALOSKY/Examiner, Art Unit 2128
/OMAR F FERNANDEZ RIVAS/Supervisory Patent Examiner, Art Unit 2128
Prosecution Insights