DETAILED ACTION
The present office action represents a final action on the merits.
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 .
Priority
This application claims the priority date of provisional application 62/910,232 of October 3, 2019, provisional application 63/066,488 of August 17, 2020, continuation in part of 17/021,895 of September 15, 2020, continuation application 17/150,938 of January 15, 2021, provisional application 63/194,772 of May 28, 2021, and continuation in part of 17/739,906 of May 9, 2022.
Status of Claims
Claims 1 and 19-20 are amended and claims 1-20 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 1-20 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.
Claims 1-18 are drawn to a method for mathematical modelling for prediction of occupational task readiness and enhancement of incentives for rehabilitation into occupational task readiness, which is within the four statutory categories (i.e., process). Claim 19 is drawn to a tangible, non-transitory computer-readable medium storing instructions, which is within the four statutory categories (i.e., machine). Claim 20 is drawn to a system for mathematical modelling for prediction of occupational task readiness and enhancement of incentives for rehabilitation into occupational task readiness, which is within the four statutory categories (i.e., machine)
Claims 1-18 recite a method comprising, using one or more processors:
receiving first data pertaining to a first user using an electromechanical machine to perform a treatment plan, wherein the first data comprises at least one attribute of the first user and at least one attribute of an occupational task associated with the first user;
receiving second data pertaining to a second user, wherein the second data comprises at least one attribute of the second user and at least one attribute of an occupational task associated with the second user;
determining whether the at least one attribute of the second user matches with the at least one attribute of the first user, and whether the at least one attribute of the occupational task associated with the second user matches with the at least one attribute of the occupational task associated with the first user;
responsive to determining that the at least one attribute of the second user matches with the at least one attribute of the first user and that the at least one attribute of the occupational task associated with the second user matches with the at least one attribute of the occupational task associated with the first user, predicting, via an artificial intelligence engine, an estimate of when the second user performing the treatment plan would be capable of performing the occupational task associated with the second user;
based on the estimate associated with the treatment plan, determining, via the artificial intelligence engine, one or more incentives associated with a likelihood of the user adhering to the treatment plan;
transmitting, to a computing device associated with the second user, the one or more incentives to be presented on a user interface of the computing device;
receiving an indication of a selection of an incentive from among the one or more incentives; and
responsive to the indication of the selection and during performance, using the electromechanical machine, of the treatment plan, controlling the user interface to display information about the incentive.
Claim 19 recites tangible, non-transitory computer-readable medium storing instructions that, when executed, cause a processing device to:
receive first data pertaining to a first user using an electromechanical machine to perform a treatment plan, wherein the first data comprises at least one attribute of the first user and at least one attribute of an occupational task associated with the first user;
receive second data pertaining to a second user, wherein the second data comprises at least one attribute of the second user and at least one attribute of an occupational task associated with the second user;
determine whether the at least one attribute of the second user matches with the at least one attribute of the first user, and whether the at least one attribute of the occupational task associated with the second user matches with the at least one attribute of the occupational task associated with the first user;
responsive to determining that the at least one attribute of the second user matches with the at least one attribute of the first user and the that at least one attribute of the occupational task associated with the second user matches with the at least one attribute of the occupational task associated with the first user, predict, via an artificial intelligence engine, an estimate of when the second user performing the treatment plan would be capable of performing the occupational task associated with the second user;
based on the estimate associated with the treatment plan, determine, via the artificial intelligence engine, one or more incentives associated with a likelihood of the user adhering to the treatment plan;
receive an indication of a selection of an incentive from among the one or more incentives; and
responsive to the indication of the selection and during performance, using the electromechanical machine, of the treatment plan, control the user interface to display information about the incentive.
Claim 20 recites a system comprising:
a memory device storing instructions;
a processing device communicatively coupled to the memory device, the processing device executes the instructions to:
receive first data pertaining to a first user using an electromechanical machine to perform a treatment plan, wherein the first data comprises at least one attribute of the first user and at least one attribute of an occupational task associated with the first user;
receive second data pertaining to a second user, wherein the second data comprises at least one attribute of the second user and at least one attribute of an occupational task associated with the second user;
determine whether the at least one attribute of the second user matches with the at least one attribute of the first user, and whether the at least one attribute of the occupational task associated with the second user matches with the at least one attribute of the occupational task associated with the first user;
responsive to determining that the at least one attribute of the second user matches with the at least one attribute of the first user and that the at least one attribute of the occupational task associated with the second user matches with the at least one attribute of the occupational task associated with the first user, predict, via an artificial intelligence engine, an estimate of when the second user performing the treatment plan would be capable of performing the occupational task associated with the second user;
based on the estimate associated with the treatment plan, determine, via the artificial intelligence engine, one or more incentives associated with a likelihood of the user adhering to the treatment plan;
transmit, to a computing device associated with the second user, the one or more incentives to be presented on a user interface of the computing device;
receive an indication of a selection of an incentive from among the one or more incentives; and
responsive to the indication of the selection and during performance, using the electromechanical machine, of the treatment plan, control the user interface to display information about the incentive.
The bolded limitations, given the broadest reasonable interpretation, cover a certain method of organizing human activity and mathematical concepts, but for the recitation of generic computer components (e.g., obtaining patient information; managing patient information, in this case mathematical modeling for prediction of occupational task readiness and enhancement of incentives for rehabilitation into occupational task readiness). The underlined limitations are not part of the identified abstract idea (the method of organizing human activity) and are deemed “additional elements,” and will be discussed in further detail below.
Dependent claims 2-18 are similarly rejected because they either further define/narrow the abstract idea and/or do not further limit the claim to a practical application or provide as inventive concept such that the claims are subject matter eligible even when considered individually or as an ordered combination. These limitations only serve to further limit the abstract idea (or contain the same additional elements found in the independent claim), and hence are nonetheless directed towards fundamentally the same abstract idea as independent claims 1, 19, and 20.
The dependent claims recite additional limitations, 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, 19, and 20.
The additional elements from claim 1 includes:
one or more processors (apply it, MPEP 2106.05(f)).
The additional elements from claims 1, 19, and 20 include:
artificial intelligence engine (apply it, MPEP 2106.05(f)).
a user interface (apply it, MPEP 2106.05(f)).
a computing device (apply it, MPEP 2106.05(f)).
one or more control instructions (apply it, MPEP 2106.05(f)).
electromechanical machine
The additional elements from claim 19 include:
tangible, non-transitory computer-readable medium storing instructions that, when executed, cause a processing device to (apply it, MPEP 2106.05(f)).
The additional elements from claim 20 include:
a system (apply it, MPEP 2106.05(f)).
a memory device storing instructions (apply it, MPEP 2106.05(f)).
a processing device communicatively coupled to the memory device, the processing device executes the instructions to (apply it, MPEP 2106.05(f)).
The dependent claims include the following additional elements beyond those recited in the independent claims:
during a telemedicine session (generally linking, MPEP 2106.05(h)).
These additional elements, in the independent claims 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 “control, via the artificial intelligence engine, operation of at least one pedal of the electromechanical machine that is used by the second user to perform the treatment plan”, “an artificial intelligence engine”, “tangible, non-transitory computer-readable medium storing instructions that, when executed, cause a processing device to”, “a system”, “a memory device storing instructions”, “a processing device communicatively coupled to the memory device, the processing device executes the instructions to”, and “a computing device”, which amounts to merely invoking a computer as a tool to perform the abstract idea e.g., see Specification Paragraphs [0035], [0037], [0044]-[0045], [0115]-[0116], [0142], [0150], and [0222] (See MPEP 2106.05(f)).
Generally linking - during a telemedicine session and control, via the artificial intelligence engine, operation of at least one pedal of the electromechanical machine that is used by the second user to perform the treatment plan (See MPEP 2106.05(h)).
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 discloses that the additional elements are well-understood, routine, and conventional in nature (i.e., the Specification Paragraphs [0035], [0037], [0044]-[0045], [0115]-[0116], [0142], [0150], and [0222] discloses that the additional elements (i.e., control, via the artificial intelligence engine, operation of at least one pedal of the electromechanical machine that is used by the second user to perform the treatment plan, the one or more control instructions, operation of the physical portion of the electromechanical machine that is used by the second user to perform the treatment plan, an artificial intelligence engine, tangible, non-transitory computer-readable medium storing instructions that, when executed, cause a processing device to, a system, a memory device storing instructions, a processing device communicatively coupled to the memory device, the processing device executes the instructions to, and a computing device) comprise a plurality of different types of generic computing systems that are configured to perform generic computer functions that are well understood routine, and conventional activities previously known to the pertinent industry (i.e., healthcare, mathematical modeling for prediction of occupational task readiness and enhancement of incentives for rehabilitation into occupational task readiness);
Relevant court decisions: The following example of court decision demonstrating well understood, routine and conventional activities, e.g., see MPEP 2106.05(d)(II): Receiving patient physical therapy data, e.g., see Intellectual Ventures v. Symantec – similarly, the current invention receives user’s information and task results.
Dependent claims 2-18 include other limitations, but none of these functions are deemed significantly more than the abstract idea. 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 any other technology, and their collective functions merely provide conventional computer implementation.
The application, is an attempt to organize human activity and mathematical concepts, using systems and methods for remote medical assistance. The inventive concept is mathematical modeling for prediction of occupational task readiness and enhancement of incentives for rehabilitation into occupational task readiness, which is not patentable. Therefore, whether taken individually or as an ordered combination, claims 1-20 are nonetheless rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Response to Arguments
Applicant’s arguments filed July 7, 2026 have been fully considered.
Claim Rejections under 112(a):
Examiner withdraws the claim rejections in light of Applicant’s amendments.
Rejections under 35 U.S.C. 101:
With respect to claim 1 and the Prong 1 35 U.S.C. 101 rejection, Applicant’s amendment fails to overcome the previous rejection. Claim 1 as amended recites an abstract idea, a method of organizing human activity and mathematical concepts. See MPEP 2106.04(a)(2)(II)(C) Managing Personal Behavior or Relationships or Interactions Between People. Applicant states, “Applicant's claims at most merely involve an exception and can only be alleged to recite an abstract idea when considered at too high a level of abstraction. Therefore, Applicant's claims are in fact not directed to a judicial exception. For example, claim 1 recites, inter alia, executing various steps using one or more processors, including steps related to using an artificial intelligence machine, transmitting to a computing device, and controlling a human interface.” (Remarks, page 13). Examiner respectfully disagrees. Claim 1 is high level and there is no indication as to what type of control is occurring and there is no specificity related to the structure and control as it relates to the electromechanical machine. Here, controlling the electromechanical machine does not appear to have any nexus to the recited abstract idea as the treatment plan relates to incentives and not the functioning of the electromechanical machine. Applicant states, “the limitations of claim 1 include performing functions that are not performed by a human, including, inter alia, performing a prediction via an artificial intelligence engine, transmitting incentives to be presented on a user interface, and controlling a user interface to display information. These functions are not instructions that are simply relayed to a human and then performed by a human. As such, the method is not implemented merely by the actions of the user.” (Remarks, page 14). Controlling of the user interface is just displaying information, there is no control of the electromechanical machine. Applicant should consider incorporating controlling the electromechanical machine to the treatment plan to detail what type of control is happening, recite details of how a solution to a problem is accomplished, and how is the electromechanical machine part of the treatment plan. See Specification Paragraph [0091] and 2106.05(f)(1). The improvement is to the abstract idea, mathematical modeling for prediction of occupational task readiness and enhancement of incentives for rehabilitation into occupational task readiness.
Applicant states, “the claims do not recite any mathematical formula, equation, calculation, or mathematical relationship. Instead, the claims recite specific, processor-implemented steps (e.g., steps for receiving data, predicting an estimate via an artificial intelligence engine responsive to the data, determining one or more incentives, etc.) that, at most, merely involve the use of a calculation.” (Remarks, page 15). Examiner respectfully disagrees. Here, the Application is using an artificial intelligence engine to predict an estimate of when the second user performing the treatment plan would be capable of performing the occupational task and based on the estimate associated with the treatment plan, determining, via the artificial intelligence engine, one or more incentives associated with a likelihood of the user adhering to the treatment plan. Predicting an estimate is a mathematical concept.
While practical application is a way to overcome the Prong 2 35 U.S.C. 101 rejection, claim 1 as written fails to result in a practical application. Applicant states, “claims integrate the alleged judicial exception into a practical application.” (Remarks, page 16). Examiner respectfully disagrees. Under the broadest reasonable interpretation controlling the user interface without more does not detail whether the control is to the electromechanical machine as it relates to the treatment plan – for example, is there an increase or decrease in resistance or speed based on sensor information and analysis of the treatment plan, etc. Here, controlling the user interface and using the electromechanical machine does not have any nexus to the treatment plan, there is no indication of what is being transmitted based on the treatment plan, and there are no details how the control is actually changing the electromechanical machine pursuant to the treatment plan. Here, the application is organizing human activity or mathematical concepts, directed to the abstract idea of organizing patient readiness information, specifically, mathematical modeling for prediction of occupational task readiness and enhancement of incentives for rehabilitation into occupational task readiness. The additional elements in claim 1 include an artificial intelligence engine, a computing device, and a user interface, however, they do not result in a practical application as they are recited at an apply it level, as stated above.
Applicant states, “the claims provide specific improvements over prior systems and recite additional elements that "apply[] or use[] the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment.” (Remarks, page 17). Examiner respectfully disagrees. Here, controlling operation of the user interface and using the electromechanical machine does not have any nexus to the treatment plan. It is unclear how the limitations improve an existing technological process. All components in the claims are being used for their intended purpose and as written do not result in a practical application or significantly more than the abstract idea. For the reasons stated above, claim similarly fails to overcome the 35 U.S.C. 101 rejection.
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 DAWN TRINAH HAYNES whose telephone number is (571)270-5994. The examiner can normally be reached M-F 7:30-5:15PM.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jason Dunham can be reached on (571)272-8109. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/DAWN T. HAYNES/
Art Unit 3686
/RACHELLE L REICHERT/Primary Examiner, Art Unit 3686
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