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: 1-8, 11-15, 18-20
The following claim(s) is/are cancelled: -
The following claim(s) is/are new: -
Claim(s) 1-20 is/are rejected.
Previous Rejections Withdrawn
The objection to claim(s) 1-7 is/are withdrawn based on the amendment.
Response to Arguments
Applicant’s arguments filed in the amendment filed 4/8/2026, 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 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 the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of 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) 1-20 is/are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for pre-AIA the inventor(s), at the time the application was filed, had possession of the claimed invention. Claim 1 is representative and claims “executing a game theoretic optimization model on the microprocessor to generate a control output to align the first token and the digital twin token.” Both “a game theoretic optimization model” and “a control output to align the first token and the digital twin token” are new matter. Applicant cites no specification paragraphs as support for the amendment (see Remarks, 4/8/2026) and Examiner does not believe any exists.
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 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 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 comprising a microprocessor, operatively coupled to the transceiver and configured, under control of the software instructions, 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.)
automatically 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 software instructions and (First see Kapoustin, paras. 16, 20; secure cloud storage. Then see Sandholm, para. 19; non-transitory computer readable medium.)
and use game theory by executing a game theoretic optimization model on the microprocessor to generate a control output 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. Para. 18; system sends alter notifications based on machine learning analysis. Then see Sandholm, paras. 14, 27-31, 48; system uses game theory in modelling treatment of a disease. Para. 80; optimizations in game theory application.)
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 based on the additional information. (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 other 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 theoretic optimization model 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 theoretic optimization model 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 theoretic optimization model 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 theoretic optimization model is a constant sum game, zero sum game, 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 of the at least one stakeholder in an environment, (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. 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 comprising a microprocessor in communication with a transceiver 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.)
wherein the at least one hardware processing unit is further configured to compare behavior represented by the first token and the digital twin token to detect a misalignment, (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.)
and based on the alignment of the first token and the digital twin token 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.)
use a game theoretic optimization model 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. Para. 18; system sends alter notifications based on machine learning analysis. Then see Sandholm, paras. 14, 27-31, 48; system uses game theory in modelling treatment of a disease. Para. 80; optimizations in game theory application.)
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 behaviors of the person under care in the environment.
Yagnyamurthy, however, does teach previous behaviors of the person under care (For behaviors, 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. 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 behavior 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 objection to claims 1-7 is moot in view of amendments. Examiner agrees.
Applicant argues at Remarks, pg. 7 that the 112b rejection should be withdrawn from all claims. Examiner agrees as to the antecedent basis ground of Claim 2.
With respect to the 112b in view of f, Applicant amends Claim 1 to “at least one hardware processing unit comprising a microprocessor, operatively coupled to the transceiver and configured, under control of the software instructions to [do functions].” Claim 8 is amended to “at least one hardware processing unit comprising a microprocessor in communication with the transceiver…the at least one hardware processing unit is further configured to [do functions].”
Applicant argues that when a claim lacks the word means it is strongly presumed that 112f does not apply, and that “Courts have repeatedly held that claim terms such as ‘processor’ ‘processing unit’ and ‘microprocessor’ denote sufficiently definite structure and therefore do no invoke 112(f)” citing Apple v. Motorola, 757 F.3d 1286, 1300 (Fed. Cir. 2014).
Except Apple v. Motorola does not say that “processing unit” denotes sufficiently definite structure. The claims do not claim a processor. Examiner agrees that “microprocessor” is a structure, but microprocessor is not the 112f term here. MPEP 2181 defines a three prong analysis for determining if a claim invokes means-plus. The first prong is if the claim uses means or a generic placeholder. “Unit for” is explicitly listed as one of the non-structural generic placeholders that invoke means-plus. The second prong is that the generic placeholder is modified by functional language. Applicant does not appear to dispute that “configured to” perform an array of processing functions is functional language. The third prong is that the generic placeholder must not be modified by sufficient structure for achieving the function. Here the “unit for” is relevantly modified by the words “hardware processing” “comprising a microprocessor” and “coupled to a transceiver.” “Hardware” denotes no structure at all, merely that there is some physical component. “Processing” is itself another function, and alone or in context with the word “hardware” does not denote a structure. Nor does “coupled to a transceiver” impose any meaningful structure for the functions claimed, because the fact that the element has some structural connection to a transceiver does not provide sufficient structure for the particular processing claimed such as “compare the first token and the digital twin token by comparing behavior and incentives…”
That leaves the phrase “comprising a microprocessor.” Here MPEP 2181(II)(B) guides, and specifically states that a microprocessor absent an algorithm for performing the function is not a sufficient structure for achieving specialized programming. Therefore, a “unit for” doing specialized functions is not modified by sufficient structure for achieving the function merely by stating it comprises a microprocessor. All three prongs are met, and the term invokes means plus.
Examiner notes that Applicant could strike the unit from the claim and claim the microprocessor, which would take the term out of means-plus, i.e. “at least one microprocessor operatively coupled to the transceiver and configured, under control of the software instructions to: [do functions]” would not be in means-plus because now there is no nonce term of “unit for” in the claim. But once the claim includes a “unit for” it is employing a nonce term, and the recitation of the microprocessor is not sufficient structure to draw the nonce term out of a means-plus invocation because it is not a sufficient structure for performing the function.
Regardless, being in means-plus is not the end of the discussion. Once a claim term is in means-plus, the specification must be evaluated to identify the structure for performing the function. As above, the MPEP explicitly states that a microprocessor absent an algorithm is insufficient structure to describe specialized programming. Applicant argues “the Specification clearly discloses corresponding structure for performing the recited functions including a microprocessor executing software instructions to compare the tokenized data sets and apply game-theoretic analysis.” This argument is unpersuasive because a microprocessor executing software instructions is not a sufficient structure. The language “to compare the tokenized data sets and apply game theoretic analysis” is simply a restatement of the functionality claimed. To the extent “the Specification clearly discloses corresponding structure for performing” points to something other than the microprocessor and “software instructions” the argument does not identify any algorithm and is a mere allegation of patentability. “Mere reference to a general purpose computer with appropriate programming without providing an explanation of the appropriate programming, or simply reciting ‘software’ without providing detail about the means to accomplish a specific software function, would not be an adequate disclosure of the corresponding structure to satisfy the requirements of 35 USC 112(b).” (MPEP 2181(II)(B))
Examiner maintains the 112b in view of f to all claims.
Applicant argues at Remarks, pgs. 8-13 that the claims are eligible. Applicant casts the claims as a processing that “is used to align configurations of the plurality of environmental sensors.”
Examiner disagrees, the claims are used generate data sets that “represent[] behaviors of [] at least one other stakeholder and incentives of the at least one other stakeholder” and “represent[] previous behaviors and incentives of [a] person under care” and then “to detect a misalignment of incentives” and to “adjust the incentives.” Spec, para. 2 identifies the field of disclosure as “align tokens representing the state of a person under care with at least one stakeholder represented by further tokens.” Spec, paras. 2-5 discuss the related art including incentives related to people under care.
The feature Applicant relies upon is “automatically 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.” Applicant points to no disclosure in the specification, and Examiner does not believe it to be the case, that turning on a sensor was a technical problem requiring a technical solution. Similarly, changing the configuration of a sensor invokes no technical problem or solution. Nor does the claim identify a particular configuration related to particular data.
Applicant argues at Remarks, pgs. 8-9 that the claims are integrated into a practical application. Applicant argues that the analysis triggers changes in configuration of the plurality of environmental sensors, but the claims do not relate a particular analysis to a particular change in sensors. Applicant further argues that the claims “modify how the system itself senses and interacts with the environment” but the fact that a system has changed does not make the claims a practical application. One can press the “On” button on a computer and effectuate a change in a technical system. That does not make it a practical application. Every processing of computer software instructions “modify the system itself.” Modifying “how the system itself senses and interacts with the environment” is true of every usage of a sensor, but sensor usage does not inherently impart eligibility. Applicant does not identify a plausible practical application such as an improvement to the functioning of a computer, Applicant merely states the claims are a practical application because they, e.g., turn on a sensor and turning on a sensor makes some sort of change in the physical world. The argument is unpersuasive.
Applicant argues at Remarks, pg. 9 that the claims contain significantly more than the abstract idea, pointing to tokenization, data storage, application of game theory, and use of a sensor. The features are either part of the abstract idea, and therefore do not constitute significantly more, or are conventional implementations of computer hardware and techniques.
Applicant argues at Remarks, pg. 10 that Claims 8-15 are not directed to mental processes because receive data from sensors, generate tokens, and apply game-theoretic processing. Applicant provides no evidence that game theory cannot be performed in the mind, and the other features are mental processes because a claim that requires a computer may still recite a mental process, such as performing a mental process on a generic computer or in a computing environment see MPEP 2106.04(a)(2)(III)(C).
Applicant further argues that Claims 8 and 15 are not methods of organizing human activity, again citing to computational processing and computer data structures. The claims are directed to organizing human activity, which would be another basis of rejecting the claims. However, the rejection is based on observation and judgment as mental processes. The argument is irrelevant to the rejection.
At Remarks, pg. 11, Applicant argues Claims 8 and 15 are integrated into a practical application. The same response as to Claim 1 applies.
At Remarks, pg. 12, Applicant argues Claim 15 is not software in the abstract because it includes a non-transitory computer readable medium. The assertion is irrelevant to the rejection.
At Remarks, pg. 12, Applicant argues Claims 8 and 15 recite significantly more. The same response as to Claim 1 applies.
Examiner maintains the 101 rejection.
Applicant argues at Remarks, pgs. 13-14, that Kapoustin “does not disclose or suggest reconfiguring environmental sensors.” Examiner cited, in part, Kapoustin para. 25 which teaches automatically activating a sensor. Applicant does not explain why this fails to teach the claim limitation.
Applicant argues at Remarks, pg. 14 that the prior art does not teach or suggest a digital twin token representing prior behavior used as a baseline for sensor alignment. The argument is not commensurate with the scope of the claims. To the extent Applicant also argues that storing historical data is not a digital twin, Examiner cited Poon to teach a digital twin.
Applicant argues at Remarks, pgs. 14-15, that “the Office Action does not articulate a legally sufficient motivation to combine [the elements].” The argument is unpersuasive as a mere allegation of patentability. Applicant argues that nothing in Kapoustin suggests modifying a monitoring system to incorporate game-theoretic concepts. But game theory is an analysis technique applicable to human behavior, and both Kapoustin and Yagnyamurthy disclose monitoring behavior. Yagnyamurthy discloses predictive analysis on how incentives will influence behavior. Game theory is a species of predictive analysis and therefore logically commends its usage incentive analysis. Sandholm uses game theory in treating disease, and therefore logically commends game theory application to a caregiver environment.
At Remarks, pg. 15, Applicant argues that “Claims 8 and 15 require comparing a first token representing current, sensor-derived behavior against a digital twin token representing prior behavior” and that “none of the cited references teach or suggest this architecture.”
As above, Kapoustin and Yagnyamurthy disclose using sensors in measuring behavior and incentives, Poon discloses a digital twin in particular, and Sandholm discloses using game theory in analysis. The combination teaches the claim features. Examiner notes that generically discussing large sections of the claim and not discussing any of the particular references or teaching citations is largely unhelpful to the analysis.
At Remarks, pgs. 15-16, Applicant argues no reference teach or suggest using game theory to resolve token misalignment. As above, Yagnyamurthy discloses, e.g., predictive behavioral analysis with respect to wellness incentives, and Sandholm discloses game theory in treatment.
The amended claims are taught above. All claims remain rejected.
Conclusion
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/NICHOLAS P CELANI/Examiner, Art Unit 2449
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