DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claims 1, 6 and 11 have been amended. Claims 2-3, 7-8 and 12-13 have been cancelled. Claims 1, 4-6, 9-11 and 14-15 are pending.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1, 4-6, 9-11 and 14-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Step 1
Claims 1 and 4-5 are drawn to a method for monitoring patient abnormalities and generating recommendations which is within the four statutory categories (i.e. process). Claims 6 and 9-10 are drawn to a system for monitoring patient abnormalities and generating recommendations which is within the four statutory categories (i.e. machine). Claims 11 and 14-15 are drawn to a non-transitory medium for monitoring patient abnormalities and generating recommendations which is within the four statutory categories (i.e. manufacture).
Step 2A, Prong One
Claims 1 and 4-5 (Group I) recite a method for monitoring patient abnormalities and generating recommendations, the method comprising:
identifying, by a monitoring device (apply it, MPEP § 2106.05(f)), at least one patient abnormality based on data associated with a patient and a corresponding ventilator,
wherein the data comprises multimedia content displayed on a ventilator screen, an Electronic Medical Record (EMR) of the patient, patient physiology, and patient efforts,
wherein the multimedia content is captured through at least one camera when the patient and the ventilator are in a Field of View (FoV) of at least one camera, and
wherein the multimedia content comprises at least one of images, a video, or an audio associated with the patient and the ventilator;
upon identification of the at least one patient abnormality, classifying, by the monitoring device (apply it, MPEP § 2106.05(f)), the at least one patient abnormality into a category from a plurality of abnormality categories through a trained Machine Learning (ML) model;
analyzing, by the monitoring device (apply it, MPEP § 2106.05(f)), the classified patient abnormality based on values corresponding to a plurality of predefined parameters through the ML model; and
providing, by the monitoring device (apply it, MPEP § 2106.05(f)), recommendations to resolve at least one patient abnormality based on analysis.
The bolded limitations, given the broadest reasonable interpretation, cover fundamental economic practices, commercial or legal interactions, and/or managing personal behavior or relationships or interactions between people. Any limitations not identified above as part of abstract idea are underlined and are deemed “additional elements,” and will be discussed in further detail below.
Furthermore, the abstract idea for Claims 6 and 9-10 (Group II) and 11 and 14-15 (Group III) is identical as the abstract idea for Claims 1-5 (Group I), because the only difference between the claims is they are directed towards different statutory categories.
Claim 6 further recites the additional elements of a processor (apply it, MPEP § 2106.05(f)); and a computer-readable medium communicatively coupled to the processor, wherein the computer-readable medium stores processor-executable instructions, which, on execution, cause the processor to (apply it, MPEP § 2106.05(f), insignificant extra-solution activity, MPEP § 2106.05(g)). )….
Claim 11 further recites a non-transitory computer-readable storage medium storing computer-executable instructions…(apply it, MPEP § 2106.05(f), insignificant extra-solution activity, MPEP § 2106.05(g)).
Dependent Claims 4-5, 9-10 and 14-15 include other limitations, for example, Claims 4, 9 and 14 recite wherein the plurality of predefined parameters comprises patient safety, patient comfort, and liberation from the ventilator, and Claims 5, 10 and 15 recite wherein the recommendations comprise drug therapy and additional tests required for the patient and modifications to ventilator settings, but these only serve to further limit the abstract idea, and hence are nonetheless directed towards fundamentally the same abstract idea as independent Claims 1, 6 and 10.
Step 2A, Prong 2
Furthermore, Claims 1, 4-6, 9-11 and 14-15 are not integrated into a practical application because the additional elements (i.e. the limitations not identified as part of the abstract idea) amount to no more than limitations which:
amount to mere instructions to apply an exception – for example, the recitation of a monitoring device, processor, a computer-readable medium, and a non-transitory computer-readable storage medium, which amounts to merely invoking a computer as a tool to perform the abstract idea, e.g. see paragraphs [0017], [0019] and [0072] of the present Specification, see MPEP 2106.05(f);
add insignificant extra-solution activity to the abstract idea – for example, the recitation of storing data, which amounts to an insignificant application, see MPEP 2106.05(g); and
generally link the abstract idea to a particular technological environment or field of use – for example, the recitation of computers, which amounts to limiting the abstract idea to the field of computers, see MPEP 2106.05(h))
Step 2B
Furthermore, the Claims do not include additional elements that are sufficient to amount to “significantly more” than the judicial exception because, the additional elements (i.e. the elements other than the abstract idea) amount to no more than limitations which:
amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields, as demonstrated by:
The Specification expressly disclosing that the additional elements are well-understood, routine, and conventional in nature:
paragraphs [0017], [0019] and [0072] of the Specification discloses that the additional elements (i.e. of a monitoring device, processor, a computer-readable medium, and a non-transitory computer-readable storage medium) comprise a plurality of different types of generic computing systems that are configured to perform generic computer functions (i.e. storing data) that are well-understood, routine, and conventional activities previously known to the pertinent industry (i.e. healthcare, patient monitoring);
Relevant court decisions: The following are examples of court decisions demonstrating well-understood, routine and conventional activities, e.g. see MPEP 2106.05(d)(II):
Electronic recordkeeping, e.g. see Alice Corp v. CLS Bank – similarly, the current invention merely recites the storing of program instructions data on a database and/or electronic memory.
Dependent Claims 4-5, 9-10 and 14-15 include other limitations, but none of these functions are deemed significantly more than the abstract idea because the dependent claims do not recite any additional elements beyond those already recited in the independent claims.
Thus, taken alone, the additional elements do not amount to “significantly more” than the above-identified abstract idea. Furthermore, looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually, and there is no indication that the combination of elements improves the functioning of a computer or improves any other technology, and their collective functions merely provide conventional computer implementation.
Therefore, whether taken individually or as an ordered combination, Claims 1, 4-6, 9-11 and 14-15 are nonetheless rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1, 4, 6, 9 and 11 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Steinhauer (U.S. Pub. No. 2013/0104893 A1) in view of Gutierrez (U.S. Pub. No. 2019/0371460 A1).
Regarding claim 1, Steinhauer discloses a method for monitoring patient abnormalities and generating recommendations, the method comprising:
identifying, by a monitoring device, at least one patient abnormality based on data associated with a patient and a corresponding ventilator (Paragraphs [0073-0074], [0120] and [0195-0197] discuss obtaining a medical entity obtaining ventilator data and context data for a patient to assess the function of their ventilator and determining if there is anything wrong, construed as identifying abnormalities.),
wherein the data comprises multimedia content displayed on a ventilator screen (Paragraphs [0095] and [0099] discuss the ventilator including a display screen to display ventilator related data.), an Electronic Medical Record (EMR) of the patient (Paragraphs [0163] and [0286] discuss the data including electronic medical record data.), and patient physiology (Paragraph [0147] discuss the system using unique patient information, including their lab results and test results.),
wherein the multimedia content is captured through at least one camera when the patient and the ventilator are in a Field of View (FoV) of at least one camera (Paragraphs [0101-0102] discuss a camera being part of the system that is capable of capturing images and audio of the patient and the ventilator.), and
wherein the multimedia content comprises at least one of images, a video, or an audio associated with the patient and the ventilator (Paragraphs [0101-0102] discuss a camera being part of the system that is capable of capturing images and audio of the patient and the ventilator.);
upon identification of the at least one patient abnormality, classifying, by the monitoring device, the at least one patient abnormality into a category from a plurality of abnormality categories (Paragraph [0218] discusses the abnormalities may be for a variety of protocols, construed as classifying the abnormalities into different categories.); and
providing, by the monitoring device, recommendations to resolve at least one patient abnormality based on analysis (Paragraphs [0046], [0107], [0205], [0210-0218] and [0258] discuss providing ventilator protocols or recommending changes to patient care based on the results of the data analysis.);
but Steinhauer does not appear to disclose:
wherein the data comprises patient efforts;
classifying through a trained Machine Learning (ML) model; and
analyzing, by the monitoring device, the classified patient abnormality based on values corresponding to a plurality of predefined parameters through the ML model.
Gutierrez teaches:
wherein the data comprises patient efforts (Paragraph [0063] discusses wherein the data analyzed includes patient efforts.);
classifying through a trained Machine Learning (ML) model (Paragraphs [0072], [0077], [0229] and [0259] discuss using machine learning algorithms to classify ventilator issues, such as disconnection or the presence of asynchronous breathing or breath stacking.);
analyzing, by the monitoring device, the classified patient abnormality based on values corresponding to a plurality of predefined parameters through the ML model (Paragraphs [0053-0055], [0060] and [0229] and [0259] discuss the computer using various obtained parameters from the ventilator that are analyzed by the machine learning to detect issues in the different categories.).
Therefore, it would have been obvious to one of ordinary skill in the art of healthcare before the effective filing date of the claimed invention to modify the ventilator monitoring of Steinhauer to include the use of a machine learning model, as taught by Gutierrez, in order to “use feedback and continuous iterative improvement, to improve over time, using machine learning to identify recommended future changes (Gutierrez, Paragraph [0077]).”
Regarding claim 4, Steinhauer discloses wherein the plurality of predefined parameters comprises patient safety and liberation from the ventilator (Paragraphs [0206], [0218] and [0258] discuss parameters including determining if the adhering to proper protocol, construed as patient safety, and weaning the patient from the ventilator.);
but Steinhauer does not appear to explicitly disclose wherein the plurality of predefined parameters include patient comfort.
Gutierrez teaches wherein the plurality of predefined parameters include patient comfort (Paragraph [0059] discusses the parameters including pain, construed as included in an assessment of the patient’s comfort.).
Therefore, it would have been obvious to one of ordinary skill in the art of healthcare before the effective filing date of the claimed invention to modify the ventilator monitoring of Steinhauer to include the patient effort data, as taught by Gutierrez, in order to “use feedback and continuous iterative improvement, to improve over time, using machine learning to identify recommended future changes (Gutierrez, Paragraph [0077]).”
2025Attorney Docket No. 317EP.001US01
Claim 6 recites substantially similar limitations as those already addressed in claim 1, and, as such, is rejected for similar reasons as given above. Claim 6 further recites a processor; and a computer-readable medium communicatively coupled to the processor, wherein the computer-readable medium stores processor-executable instructions, which, on execution, cause the processor to…:, which is disclosed by Steinhauer (Paragraph [0062] discusses the system using processors and computer readable media to execute computer readable instructions.).
Claim 9 recites substantially similar limitations as those already addressed in claim 4, and, as such, is rejected for similar reasons as given above.
Claim 11 recites substantially similar limitations as those already addressed in claim 11, and, as such, is rejected for similar reasons as given above. Claim 11 further includes a non-transitory computer-readable storage medium storing computer-executable instructions, which is disclosed by Steinhauer (Paragraph [0062] discusses the system using processors and computer readable media to execute computer readable instructions.).
Claim 14 recites substantially similar limitations as those already addressed in claim 4, and, as such, is rejected for similar reasons as given above.
Claims 5, 10 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Steinhauer in view of Gutierrez, and in further view of Jain (U.S. Pub. No. 2024/0395419 A1).
Regarding claim 5, Steinhauer discloses wherein the recommendations comprise drug therapy and modifications to ventilator settings (Paragraphs [0046], [0147], [0167], [0216-0218], and [0258] discuss the recommendations including changing ventilator settings and medication treatment.);
however, Steinhauer does not appear to explicitly disclose wherein the recommendations comprise additional tests required for the patient.
Jain teaches disclose wherein the recommendations comprise additional tests required for the patient (Paragraphs [0032] and [0308] discuss the system recommending changing ventilator settings, providing a medication and/or to add a test for a specific disease.).
Therefore, it would have been obvious to one of ordinary skill in the art of healthcare before the effective filing date of the claimed invention to modify the ventilator monitoring of Steinhauer to include recommending additional tests for the patient, as taught by Gutierrez, in order to have “recommendations [that] can be customized for individual users based on information about the users, such as the age, comorbidities, and other attributes that may indicate different levels of risk due to the disease for different individuals (Jain, Paragraph [0019]).”
Claim 10 recites substantially similar limitations as those already addressed in claim 5, and, as such, is rejected for similar reasons as given above.
Claim 15 recites substantially similar limitations as those already addressed in claim 5, and, as such, is rejected for similar reasons as given above.
Response to Arguments
Applicant's arguments filed 01/02/2026 have been fully considered.
Claim Objection
The previous claim objection is withdrawn as the claims have been cancelled.
Rejections under 35 U.S.C. § 101
Applicant argues on pages 8-30 of the Remarks that the claims are directed towards eligible subject matter and traverses the rejection.
Step 2A Prong One
Applicant asserts the claims do not recite a mental process because the claims cannot be practically performed in the human mind (Remarks, page 9-11). This is moot as the claimed invention was not categorized as a mental process.
Applicant disagrees with the interpretation of the claims being directed towards organizing human activity as the “claimed invention does not manage human behavior or social interactions instead focused on monitoring patient abnormalities and generating recommendations (Remarks, page 12).” Examiner strongly disagrees as monitoring patients is a business problem particular to healthcare. The instant specification, [0003], states:
Traditionally, healthcare providers have relied on manual observations and intermittent measurements to assess patients on ventilators. However, the traditional approach has only been effective to a certain extent. The traditional approach presents several limitations such as human errors, increased staff workload, and the requirement for constant vigilance, which may result in delayed responses to critical patient events, ultimately leading to suboptimal patient outcomes.
The claims are directed toward automating the monitoring process to eliminate the human errors that are usually part of the process. The claims are directed towards monitoring the patient to assess a risk to the patient by assessing abnormalities, which is organizing human activity, as it is part of caring for a patient. For example, medical professionals routinely assess patient’s heart rate and/or oxygen saturation levels to determine if the patient is in danger and needs extra care or attention.
Applicant asserts that because the multimedia content is captured though a camera, the claims are not abstract (Remarks, page 13). The camera in the claim is not positively recited, rather it is described in a limitation providing specifics of how the multimedia content is captured. This is considered part of the abstract idea. Examiner notes that even if the camera was positively recited, the camera would be recited at an “apply it” level since it is being used as intended, to take pictures and video. Having a camera point in a particular direction to capture the intended objects is abstract. There is no improvement to the computer or camera itself as a result of this.
Regarding the machine learning aspect, the claim recites using a machine learning algorithm that uses rules to classify things, which is part of organizing human activity.
Applicant argues that providing recommendations is “a technical output (Remarks, page 15).” Examiner disagrees as this is part of the abstract idea. Similar to when a medical professional is monitoring a patient, assessing the situation, the medical professional then suggests a recommended action to correct any issues, making it abstract.
Applicant argues that the claimed invention “provides a technical solution to the real-world challenge of managing patients on mechanical ventilation” and “transforms the way ventilator-patient interactions are monitored and interpreted (Remarks, page 16).” Examiner notes that whether the claim results in a technical solution to a technical problem is a considered under Step 2A, Prong Two, not Step 2A, Prong One. There is no technical problem present, so even if the solution was a technical solution, it would not result in a practical application (or the claim not recited an abstract idea).
Step 2A Prong Two
Examiner notes that in Prong Two, examiners evaluate whether the claim recites additional elements that integrate the judicial exception into a practical application. § 2106.04(II)(A)(2). The only additional elements positively recited in the claims include a monitoring device, processor, a computer-readable medium, and a non-transitory computer-readable storage medium.
Applicant asserts that the entire independent claim “provide[s] a specific technical medical monitoring solution that is meaningfully integrated into a practical application.” Examiner maintains there is not a technical problem, so even if the claims resulted in a technical solution, it would not rise to the level of a practical application.
Applicant asserts that the “claimed invention is not a mere instruction to apply an abstract idea on a computer,” that the “claims do not recite a generic processor performing generic data analysis” and the claims require “a monitoring device particularly configured to identify patient abnormalities” using a variety of data to generate recommendations (Remarks, 20).” The instant specification describes the monitoring device as “for example, a server, a desktop, a laptop, a notebook, a netbook, a tablet, a smartphone, a mobile phone, or any other computing device.” This is a generic computer.
The rest of the claim is considered abstract as it is simply describing the type of data used to make a recommendation.
Applicant is arguing that portions of the abstract idea (the parameters and type of data used in the analysis) result in a practical application. This is not persuasive as the additional elements are considered for this part of the analysis as indicated in the MPEP. Similarly, Applicant argues that the “steps of classification, parameter- based analysis, and recommendation generation are not ancillary data storage or output functions” are not insignificant extra-solution activity (Remarks, age pages 20-21). The “steps of classification, parameter- based analysis, and recommendation generation” are considered part of the abstract idea. Examiner did not assert that those limitations were extra-solution activity. Applicant is reminded that in the above rejection, the bolded portion of the claims are considered abstract and the underlined portions are considered additional elements. Examiner did not claim that these functions were “ancillary data storage or output functions” as asserted by Applicant as they are deemed to be part of the abstract idea. The claims also do not result in a particular treatment or prophylaxis as the claim results in providing recommendations for treatment.
Applicant further asserts that “the claims do not merely link an abstract idea to a technological environment” and that the “invention is not directed to a general concept ‘applied in healthcare.’” The non-final action states that “the recitation of computers, which amounts to limiting the abstract idea to the field of computers (Page 5).” The claims do not go beyond generally linking. Furthermore, the above rejection identifies the additional elements, which are not improved as a result of the claimed invention. Applicant’s arguments require reading the specification into the claims. The claims are much broader than Applicant’s arguments, and therefore, they are not persuasive.
Applicant further argues that “he claimed invention improves the functioning of medical monitoring systems themselves by enabling automated detection, categorization, and parameter-based analysis of patient abnormalities that would otherwise require continuous human supervision (Remarks, pages 21-22).” Examiner maintains that these are part of the abstract idea which cannot be used to integrate itself into a practical application.
Applicant further asserts that the claimed invention “reduces alarm fatigue, improves response timing, and enhances patient safety by producing context-aware recommendations (Remarks, page 21).” Again, these are not technical problems. These are problems that arise from the patient-provider interaction. So even if the claims resulted in a technical solution, they are not solving a technical problem.
Step 2B
Applicant again argues “they reflect a specific and non-conventional technological solution to a long-standing problem relates to monitoring patient abnormalities and generating recommendations and are directed at challenges associated with continuous monitoring and management of patients on ventilators (Remarks, page 25).” As indicated above, this is not a technical problem, and therefore this argument is not persuasive. Applicant’s arguments state “[t]raditionally, healthcare providers have relied on manual observations and intermittent measurements to assess patients on ventilators (Remarks, page 25).” The claims are directed towards automating a known process performed by humans. Mere automation of manual processes, such as using a generic computer to process an application for financing a purchase, Credit Acceptance Corp. v. Westlake Services, 859 F.3d 1044, 1055, 123 USPQ2d 1100, 1108-09 (Fed. Cir. 2017) or speeding up a loan-application process by enabling borrowers to avoid physically going to or calling each lender and filling out a loan application, LendingTree, LLC v. Zillow, Inc., 656 Fed. App'x 991, 996-97 (Fed. Cir. 2016) (non-precedential). See MPEP § 2106.05(a)(I). This is even further evidenced by Applicant’s arguments that “healthcare providers can reduce their workload as the analysis and categorization of patient abnormalities is automated, allowing health care providers to focus more on patient care and less on data interpretation” and that this “helps clinicians to understand patient conditions faster and take timely decisions.” These are not technical problems, rather they are business problems specific to the field of healthcare. The machine learning is part of the abstract idea as its using rules to categorize data. The focus for Step 2B is on the additional elements to be evaluated to determine if the additional elements of the claim provide an inventive concept. See MPEP § 2106(III). As indicated above, the only additional elements positively recited in the claims are generic computer components. Applicant’s arguments are directed towards limitations that are part of the abstract idea and therefore not persuasive.
Therefore, the claims remain rejected as being directed towards ineligible subject matter.
Rejections under 35 U.S.C. § 103
Applicant argues that the Steinhauer and Gutierrez references do not disclose the newly amended limitations of claim 1, which now incorporate the subject matter of previously presented claims 2 and 3, because the “Examiner’s rejections of claims 2 and 3 relied upon a piecemeal analysis of the individual claim limitations without establishing that the prior art teaches or suggests the specific integrated combination of features now recited in claims 1 (Remarks, page 31).”
In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986).
In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., vital signs, respiratory effort waveforms) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
Applicant argues that Steinhauer does not teach the machine learning aspects of the claims. Examiner maintains that those portions of the claim are taught by Gutierrez. In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986). The categories are not specifically defined in the specification, so a parameter could be interpreted under its own category. The specification is not read into the claims and if Applicant wishes for the categories on page 36 of the Remarks to part of the invention, it is recommended they are added to the claim language.
Applicant further argues that Gutierrez does not teach “analyzing the classified patient anomaly (Remarks, page 39).” In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., specific types of clinical abnormalities) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993). Furthermore, Gutierrez explicitly teaches monitoring for ventilator disconnection, which is one of the categories mentioned as a clinical abnormality in both the instant specification and Applicant’s arguments.
Lastly, Applicant argues Steinhauer does not disclose generating a recommendation and resolving the abnormality (Remarks, pages 43-46). This is not persuasive as the protocol recommendation is based on the sensed patient’s conditions. Furthermore, the recommendation is made based on the received data for the patient. The fact that historical data does not take away from the fact that patient’s data is used. Examiner encourages Applicant to view the prior art reference as a whole, rather than just the cited portions. A prior art reference must be considered in its entirety, i.e., as a whole, including portions that would lead away from the claimed invention. W.L. Gore & Assoc., Inc. v. Garlock, Inc., 721 F.2d 1540, 220 USPQ 303 (Fed. Cir. 1983), cert. denied, 469 U.S. 851 (1984). Examiner notes that while Steinhauer is used to disclose this, these arguments contradict Applicant’s assertion that the claimed invention does not use past data from other patients as the claims require a trained machine learning model, which relies on historical data.
Applicant argues that Steinhauer does not analyze the data in real-time. In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., real-time) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Rachelle Reichert whose telephone number is (303)297-4782. The examiner can normally be reached M-F 9-5 MT.
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/RACHELLE L REICHERT/Primary Examiner, Art Unit 3686