DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
The following claim(s) is/are pending in this office action: 1-20
The following claim(s) is/are amended: 1-3, 8-10, 15-17
The following claim(s) is/are new: -
The following claim(s) is/are cancelled: -
Claim(s) 1-20 is/are rejected. This rejection is FINAL.
Previous Rejections Withdrawn
The Double Patenting rejection to claim(s) 1-20 is withdrawn based on the amendment.
The 35 USC 112(b) rejection to claim(s) 15-20 is/are withdrawn based on the amendment.
Response to Arguments
Applicant’s arguments filed in the amendment filed 10/28/2025, have been fully considered but are moot in view of new grounds of rejection. The reasons set forth below.
Applicant’s Invention as Claimed
Claim Objections
Claim(s) 1-7 are objected to because Claim 1 states “in an an environment.” Applicant means “in an environment.”
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.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to observation and judgment without significantly more. The claim(s) recite(s) “a first token, the first token comprising the detected data set representing behaviors [and incentives] of the at least one other stakeholder in an environment; each of the behaviors is represented by a multi-dimensional feature set forming part of a health care profile for the person under care;… a digital twin token, the digital twin token representing previous behaviors and incentives of the person under care in the environment,” which are observations and “compare the first token and the digital twin token…and use game theory to align the first token and the digital twin token” which is a judgment. This judicial exception is not integrated into a practical application because the claims merely command the observation and judgment be done on a computer with artificial intelligence, which improves the ineligible subject matter, not the computer. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the remaining features are conventional computer hardware used to gather, transmit and process data and they do not impart eligibility.
Claims not specifically mentioned are rejected by virtue of dependency and because they do not obviate the above-recited deficiencies.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
Claim(s) 1-14 is/are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention. Claim 2 claims “the at least one stakeholder” which lacks antecedent basis.
Claim limitation “at least one hardware processing unit configured to compare the first token and the digital twin token by comparing behavior and incentives represented by the first token and the digital twin token to detect a misalignment of incentives…and use game theory to align the first token and the digital twin token by adjusting the incentives” and similar limitations in Claim 8 invokes 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function. Therefore, the claim is indefinite and is rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph. Applicant may:
(a) Amend the claim so that the claim limitation will no longer be interpreted as a limitation under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph;
(b) Amend the written description of the specification such that it expressly recites what structure, material, or acts perform the entire claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(c) Amend the written description of the specification such that it clearly links the structure, material, or acts disclosed therein to the function recited in the claim, without introducing any new matter (35 U.S.C. 132(a)).
If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure, material, or acts and clearly links them to the function so that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed function, applicant should clarify the record by either:
(a) Amending the written description of the specification such that it expressly recites the corresponding structure, material, or acts for performing the claimed function and clearly links or associates the structure, material, or acts to the claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(b) Stating on the record what the corresponding structure, material, or acts, which are implicitly or inherently set forth in the written description of the specification, perform the claimed function. For more information, see 37 CFR 1.75(d) and MPEP §§ 608.01(o) and 2181.
The above cited rejections are merely exemplary.
The Applicant(s) are respectfully requested to correct all similar errors.
Claims not specifically mentioned are rejected by virtue of their dependency.
Claim Rejections - 35 USC § 103
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 of this title, 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 1-20 are rejected under 35 U.S.C. 103(a) as being unpatentable over Kapoustin (US Pub. 2020/0137357) in view of Sandholm (US Pub. 2020/0279650), in view of Poon (US Pub. 2021/0045682) and further in view of Yagnyamurthy (US Pub. 2016/0171180).
With respect to Claim 1, Kapoustin teaches a system to align tokens representing the state of a person under care with tokens representing behavior of at least one other stakeholder, comprising: a plurality of environmental sensors configured to monitor a sequence of interactions of a person under care with the at least one other stakeholder in an an environment resulting in a detected data set, (paras. 17-20, 49-51, 54-57, 59; system checks for caregiver fraud and patient abuse by using a wearable device with a multitude of sensors that collect geospatial, thermal, biometric and biomechanical data. Para. 46; system tracks caregiver during patient interactions. Paras. 60-62; device uses GPS and geofenced areas for the patients home that turn the device on. Para. 72; other sensing devices in the environment. para. 74, 76, 79; patient’s well-being is tracked)
and to provide a first token, the first token comprising the detected data set representing behaviors of the at least one other stakeholder (paras. 64-67; device monitors the general physical and emotional state of the caregiver and transmits it to cloud monitoring system. Para. 72; other sensing devices track caregiver arrival and departure time. Paras. 23, 51; current measurements are compared to baseline measurements.)
and incentives of the at least one other stakeholder, (para. 9; $10 billion in improper payments to home healthcare agencies. Para. 10; reporting billing hours. Paras. 24, 51; system combats billing fraud by comparing sensor data with billing data and releases payment if there is no patient abuse.)
wherein each of the behaviors is represented by a multi-dimensional feature set forming part of a health care profile for the person under care; (para. 11, 18; system fights fraud by looking for a pattern of billing anomalies or geospatial movements while caregiver provides a medical service. Para. 59-61; database of patients home/location. paras. 17-20, 49-51, 54-57, 59; system checks for caregiver fraud and patient abuse by using a wearable device with a multitude of sensors that collect geospatial, thermal, biometric and biomechanical data. para. 74, 76, 79; patient’s well-being is tracked)
a fraud avoidance prediction system comprising: a transceiver configured to receive the first token from the plurality of environmental sensors; (Para. 64; data is transmitted to cloud data center. Para. 28; cloud system verifies receipt of data.)
a digital twin token, the digital twin token representing previous behaviors of the person under care in the environment, (A digital twin will be taught later. para. 56; system tracks patient movement and temperature. para. 74, 76, 79; patient’s well-being is tracked. Paras. 23, 51; current measurements are compared to baseline measurements. See also Poon, para. 78; system records biological data of patient.)
and at least one hardware processing unit configured to: compare the first token and the digital twin token, by comparing behavior and incentives represented by the first token and the digital twin token to detect a misalignment of incentives (para. 52; processor. para. 18, 72; system uses machine learning and artificial intelligence to compare the collected caregiver data, environmental data, and billing data and looks for a mismatch. Paras. 23, 51; current measurements are compared to baseline measurements. See also Yagnyamurthy, paras. 76, 79-81; system uses predictive analysis to determine how the wellness of a user will progress and presents incentives to encourage the user to live a healthier lifestyle.)
Invoke an additional sensor or change the configuration of a sensor in the plurality of sensors to provide additional information on the misalignment of incentives; (para. 25; auto activation of the data collection process including geofencing triggers. Paras. 58-59; device battery. Para. 61-63; cloud system monitoring station can control record on/off camera states. System powers features on/off to perform power management. Paras. 66-67; real time data monitoring and analysis to ensure that abuse is not happening. See also Yagnyamurthy, para. 37-41; configuring monitoring devices/sensors. Para. 54; wellness server may provide updated configuration information to the user device. Therefore it would have been obvious to one of ordinary skill prior to the effective filing date to activate fewer sensors to reduce power usage and activate or reconfigure sensors to provide additional data if analysis points to possible fraud or abuse.)
But Kapoustin does not explicitly teach game theory.
Sandholm, however, does teach a non-transitory computer-readable storage medium configured to store (First see Kapoustin, paras. 16, 20; secure cloud storage. Then see Sandholm, para. 19; non-transitory computer readable medium.)
and use game theory to align the first token and the digital twin token. (First see Kapoustin, para. 18, 72; system uses machine learning and artificial intelligence to compare the collected caregiver data, environmental data, and billing data and looks for a mismatch. Then see Sandholm, paras. 14, 27-31, 48; system uses game theory in modelling treatment of a disease.)
It would have been obvious to one of ordinary skill prior to the effective filing date to combine the system of Kapoustin with the game theory in order to improve the course of treatment by identifying ways to successfully attack the problem. (Sandholm, paras. 2-6)
But modified Kapoustin does not explicitly teach a digital twin.
Poon, however, does teach a digital twin. (paras. 67-70, 77-78, 106-107; system uses stored and sensed data to generate a digital twin of an individual in order to replicate or model their metabolic health.)
It would have been obvious to one of ordinary skill prior to the effective filing date to combine the system of modified Kapoustin with the digital twin in order to model the individual in order to predict responses to future inputs. (Poon, para. 7)
But modified Kapoustin does not explicitly teach incentives of the person under care in the environment.
Yagnyamurthy, however, does teach previous behaviors and incentives of the person under care (Behavior was previously taught, but see also paras. 14-16, 23-25; system uses medical records and sensors to identify user wellness. paras. 76, 79-81; system uses predictive analysis to determine how the wellness of a user will progress and presents incentives to encourage the user to live a healthier lifestyle.)
By adjusting the incentives represented by the first token or the digital twin token. (para. 92; system may periodically provide incentives. para. 94; system determines a $25 gift card or a $50 gift card based on user information. para. 99; modifying incentives due to re-performing analysis of user information.)
It would have been obvious to one of ordinary skill prior to the effective filing date to combine the system of Kapoustin with the incentives of the person under care in order to encourage a healthier life to improve health outcomes. (Yagnyamurthy, para. 42; monetary incentives to encourage a healthier lifestyle.)
With respect to Claim 2, modified Kapoustin teaches the system of claim 1, and Yagnyamurthy also teaches wherein the alignment of the first token and the digital twin token is via adjusting the value of an incentive for the at least one stakeholder. (Examiner construes “a stakeholder” to the person under care. para. 92; system may periodically provide incentives. para. 94; system determines a $25 gift card or a $50 gift card based on user information. para. 99; modifying incentives due to re-performing analysis of user information. Further, it would have been obvious to one of ordinary skill prior to the effective filing date to apply the same technique to the other stakeholder incentive to ensure that the incentive motivates appropriate action for the other stakeholder.)
The same motivation to combine as the independent claim applies here.
With respect to Claim 3, modified Kapoustin teaches the system of claim 1, and Yagnyamurthy also teaches wherein changing the configurations of the sensor in the plurality of environmental sensors includes activating an additional sensor capability of the sensor. (Activation was previously taught. para. 21; monitoring device may include blood pressure monitor, heart rate monitor, scale, ECG monitor, etc. which is a plurality of sensor capabilities in a device.)
The same motivation to combine as the independent claim applies here.
With respect to Claim 4, modified Kapoustin teaches the system of claim 3, and Sandholm also teaches wherein the game theory is a cooperative game. (paras. 65-66; game may be modeled as coalitions, which is cooperative. Paragraph 66 also states “if a game is modeled as a non-cooperative game” which suggests that some games are modeled as cooperative games.)
The same motivation to combine as the independent claim applies here.
With respect to Claim 5, modified Kapoustin teaches the system of claim 3, and Sandholm also teaches wherein the game theory is a normal form or extensible form game. (paras. 18, 60; normal form. Paras. 18, 61; extensive form.)
The same motivation to combine as the independent claim applies here.
With respect to Claim 6, modified Kapoustin teaches the system of claim 3, and Sandholm also teaches wherein the game theory is a simultaneous or sequential move game. (paras. 32, 36; simultaneous or sequential moves)
The same motivation to combine as the independent claim applies here.
With respect to Claim 7, modified Kapoustin teaches the system of claim 3, and Sandholm also teaches wherein the game theory is a constant sum, zero sum, non-zero-sum game, symmetric or asymmetric game. (para. 56; zero-sum game, non-zero-sum game.)
The same motivation to combine as the independent claim applies here.
With respect to Claim 8, Kapoustin teaches a system to align tokens representing the state of a person under care with tokens representing behavior of at least one stakeholder, comprising: a transceiver configured to receive (Para. 64; data is transmitted to cloud data center. Para. 28; cloud system verifies receipt of data. paras. 17-20, 49-51, 54-57, 59; system checks for caregiver fraud and patient abuse by using a wearable device with a multitude of sensors that collect geospatial, thermal, biometric and biomechanical data. Para. 46; system tracks caregiver during patient interactions. Paras. 60-62; device uses GPS and geofenced areas for the patients home that turn the device on. Para. 72; other sensing devices in the environment. para. 74, 76, 79; patient’s well-being is tracked)
a detected data set from a plurality of environmental sensors, (paras. 17-20, 49-51, 54-57, 59; system checks for caregiver fraud and patient abuse by using a wearable device with a multitude of sensors that collect geospatial, thermal, biometric and biomechanical data. Para. 46; system tracks caregiver during patient interactions. Paras. 60-62; device uses GPS and geofenced areas for the patients home that turn the device on. Para. 72; other sensing devices in the environment.)
the detected data set representing behaviors (paras. 64-67; device monitors the general physical and emotional state of the caregiver and transmits it to cloud monitoring system. Para. 72; other sensing devices track caregiver arrival and departure time. Paras. 23, 51; current measurements are compared to baseline measurements.)
and incentives of the at least one stakeholder in an environment, (para. 9; $10 billion in improper payments to home healthcare agencies. Para. 10; reporting billing hours. Paras. 24, 51; system combats billing fraud by comparing sensor data with billing data and releases payment if there is no patient abuse.)
wherein each of the behaviors is represented by a multi-dimensional feature set forming part of a health care profile for the person under care; (para. 11, 18; system fights fraud by looking for a pattern of billing anomalies or geospatial movements while caregiver provides a medical service. Para. 59-61; database of patients home/location. paras. 17-20, 49-51, 54-57, 59; system checks for caregiver fraud and patient abuse by using a wearable device with a multitude of sensors that collect geospatial, thermal, biometric and biomechanical data. para. 74, 76, 79; patient’s well-being is tracked)
at least one hardware processing unit configured to receive the detected data set from the transceiver and to create a first token comprising the detected data set; (para. 52; processor. Para. 64; data is transmitted to cloud data center. Para. 28; cloud system verifies receipt of data.)
a digital twin token, the digital twin token representing previous behaviors of the person under care in the environment, (A digital twin will be taught later. para. 56; system tracks patient movement and temperature. para. 74, 76, 79; patient’s well-being is tracked. Paras. 23, 51; current measurements are compared to baseline measurements. See also Poon, para. 78; system records biological data of patient.)
and the at least one hardware processing unit further configured to compare the first token and the digital twin token, by comparing behavior and incentives represented by the first token and the digital twin token to detect misalignment of incentives, (para. 52; processor. para. 18, 72; system uses machine learning and artificial intelligence to compare the collected caregiver data, environmental data, and billing data and looks for a mismatch. Paras. 23, 51; current measurements are compared to baseline measurements. See also Yagnyamurthy, paras. 76, 79-81; system uses predictive analysis to determine how the wellness of a user will progress and presents incentives to encourage the user to live a healthier lifestyle.)
Invoke an additional sensor or change the configuration of a sensor in the plurality of sensors to provide additional information on the misalignment of incentives; (para. 25; auto activation of the data collection process including geofencing triggers. Paras. 58-59; device battery. Para. 61-63; cloud system monitoring station can control record on/off camera states. System powers features on/off to perform power management. Paras. 66-67; real time data monitoring and analysis to ensure that abuse is not happening. See also Yagnyamurthy, para. 37-41; configuring monitoring devices/sensors. Para. 54; wellness server may provide updated configuration information to the user device. Therefore it would have been obvious to one of ordinary skill prior to the effective filing date to activate fewer sensors to reduce power usage and activate or reconfigure sensors to provide additional data if analysis points to possible fraud or abuse.)
But Kapoustin does not explicitly teach game theory.
Sandholm, however, does teach a non-transitory computer-readable storage medium configured to store (First see Kapoustin, paras. 16, 20; secure cloud storage. Then see Sandholm, para. 19; non-transitory computer readable medium.)
and use game theory to align the first token and the digital twin token (First see Kapoustin, para. 18, 72; system uses machine learning and artificial intelligence to compare the collected caregiver data, environmental data, and billing data and looks for a mismatch. Then see Sandholm, paras. 14, 27-31, 48; system uses game theory in modelling treatment of a disease.)
It would have been obvious to one of ordinary skill prior to the effective filing date to combine the system of Kapoustin with the game theory in order to improve the course of treatment by identifying ways to successfully attack the problem. (Sandholm, paras. 2-6)
But modified Kapoustin does not explicitly teach a digital twin.
Poon, however, does teach a digital twin. (paras. 67-70, 77-78, 106-107; system uses stored and sensed data to generate a digital twin of an individual in order to replicate or model their metabolic health.)
It would have been obvious to one of ordinary skill prior to the effective filing date to combine the system of modified Kapoustin with the digital twin in order to model the individual in order to predict responses to future inputs. (Poon, para. 7)
But modified Kapoustin does not explicitly teach incentives of the person under care in the environment.
Yagnyamurthy, however, does teach previous behaviors and incentives of the person under care (Behavior was previously taught, but see also paras. 14-16, 23-25; system uses medical records and sensors to identify user wellness. paras. 76, 79-81; system uses predictive analysis to determine how the wellness of a user will progress and presents incentives to encourage the user to live a healthier lifestyle.)
By adjusting the incentives represented by the first token or the digital twin token. (para. 92; system may periodically provide incentives. para. 94; system determines a $25 gift card or a $50 gift card based on user information. para. 99; modifying incentives due to re-performing analysis of user information.)
It would have been obvious to one of ordinary skill prior to the effective filing date to combine the system of Kapoustin with the incentives of the person under care in order to encourage a healthier life to improve health outcomes. (Yagnyamurthy, para. 42; monetary incentives to encourage a healthier lifestyle.)
With respect to Claims 9-14, they are substantially similar to Claims 2-7, respectively, and are rejected in the same manner, the same art and reasoning applying.
With respect to Claim 15, it is substantially similar to Claim 8 and is rejected in the same manner, the same art and reasoning applying. Further Sandholm also teaches a non-transitory computer-readable storage medium encoded with data and instructions, the instructions when read by a computer causes the computer to: and store, via the non-transitory computer-readable storage medium, (First see Kapoustin, paras. 16, 20; secure cloud storage. Then see Sandholm, para. 19; non-transitory computer readable medium.)
The same motivation to combine as Claim 8 applies here.
With respect to Claims 16-20, they are substantially similar to Claims 2-6, respectively, and are rejected in the same manner, the same art and reasoning applying.
Remarks
Applicant argues at Remarks, pg. 7 that the amended claims are not double patenting over 18/484192. Examiner agrees as to the current amendment state of both claimsets and withdraws the rejection.
Applicant argues at Remarks, pg. 8 that the claims are eligible. Specifically, Applicant argues that the amended claims change the state of the system.
Examiner disagrees. The claims are still directed to observation and judgment. The fact that the system undergoes some change is not “an improvement to the computer itself” because the specification does not identify the inability of the art to configure an additional sensor as a technical problem requiring a technical solution. Nor is there any logical reason that one of ordinary skill reading the specification would think that there was a technical problem in configuring an additional sensor to provide additional information when there was no technical problem in configuring a first plurality of sensors to provide original information. This argument tries to transmute the conventional usage of a sensor to gather information – which Applicant does not argue against Examiner’s view is an ineligible observation act – into the solving of a technical problem that improves a computer. In other words, “more observation” using conventional computer hardware does not become eligible simply because “some observation” was previously claimed.
Examiner maintains the rejection.
Applicant argues at Remarks, pg. 9 that the 112 rejections should be withdrawn. Applicant argues that “quiescent” and “a consequent incentive” have been removed. Examiner agrees and withdraws those grounds.
Applicant argues that “breadth is not indefiniteness.” But the claims were not rejected based upon them being broad, the claims were rejected based upon improper functional usage of 2173.05(g). Examiner frankly still questions whether the claims simply identify a problem to be solved. Applicant claims the problem with the prior art is that incentives may be misaligned (Spec, para. 5) “such that there are systemic and/or individual rorts of these systems and relationships.” To solve this problem Applicant claims “use game theory to align the first token and the digital twin token by adjusting the incentives represented by the first token or the digital twin token.” Examiner can certainly see why Applicant makes the “Breadth is not indefiniteness” argument – the claim essentially claims “solve the problem of incentive misalignment by adjusting incentives to align them” so long as game theory is used along the way. That is indeed stunningly broad. But, relevantly to the rejection, it also gives no direction as to what acts are encompassed in order to “align” the tokens by “adjusting the incentives.” By analogy, it is like saying “We should solve the problem of unsolved crimes by using detective techniques to solve them” or “We should solve the problem of uncurable diseases by using science to identify cures” – the command demands results without making clear what particular acts are embraced by them, which is the essence of a 2173.05(g) rejection.
Examiner will withdraw the rejection because Examiner thinks the eligibility rejection better deals with the claim to the field of nebulous analysis and remediation acts than the indefiniteness of 2173.05(g). Consequently, the argument is unpersuasive but Examiner will sua sponte withdraw the rejection.
Applicant does not concede but does not argue against the determination that “hardware processing unit configured to [perform functions]” invokes means plus. Applicant argues that “particular details of the comparison have been added to the claim.” But the claim still claims a nonce word, modified by function, and not modified by sufficient structure to perform the function. Consequently, the term still invokes means plus, and Applicant does not assert the specification provides an algorithm for performing the functionality. Examiner maintains the ground of rejection.
At Remarks, pg. 10, Applicant argues the claims are nonobvious. Applicant first argues that the references do not teach tokens, but they do. Tokens are just a unit of data, and Applicant does not dispute that the references teach sensors that gather data. Applicant argues that paragraph 56 differentiates tokens from raw sensor data, but the paragraph does not mention raw sensor data, and the thrust of paragraph 56 is that when data is gathered one need “evaluate each individual sensor” so token is being used in that paragraph as only a gathering of data from disparate sources for analysis, which is what the references show.
Applicant argues that Sandholm is silent regarding digital twins and Poon is silent regarding game theory. The argument is unpersuasive because it is a question of what is obvious over the combination of teachings. Kapoustin identifies a mismatch between, e.g., the behavior of a caregiver and the health status of a patient, either because the caregiver is abusing the patient or committing fraud by billing for treatment not done. Sandholm teaches that game theory can be used to model the treatment of a disease, which is the disclosure of a technique applicable to patient care in Kapoustin. Poon is cited for the limited teaching of a digital twin of health data. The combination teaches the amended claim because the only thing that the claim requires is aligning the tokens using game theory. The claim is not more particular in how one goes from misaligned tokens to aligned tokens other than game theory and incentive adjustment is used along the way, and Sandholm teaches that game theory is useful in context.
The new features are taught above. All claims remain rejected.
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 extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/NICHOLAS P CELANI/Examiner, Art Unit 2449