DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicants’ submission filed on May 20, 2026, has been entered.
Information Disclosure Statement
The information disclosure statements (IDS) received on February 23, 2024, October 16, 2024, December 30, 2024, March 6, 2025, May 21, 2025, July 21, 2025, September 17, 2025, November 11, 2025, 2025, and January 26, 2026, have been considered by examiner.
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 1-19 are rejected under 35 U.S.C. 101 because the claims are not directed to patent eligible subject matter.
Claims 1-19 do fall within at least one of the four categories of patent eligible subject matter because the claims recite a machine (i.e., non-transitory computer-readable medium and system) and process (i.e., a method).
Although claims 1-19 fall under at least one of the four statutory categories, it should be determined whether the claim wholly embraces a judicially recognized exception, which includes laws of nature, physical phenomena, and abstract ideas, or is it a particular practical application of a judicial exception (See MPEP 2106 I and II).
Claims 1-19 are directed to a judicial exception (i.e., a law of nature, natural phenomenon, or abstract idea) without significantly more.
Part I: Step 2A, Prong One: Identify the Abstract Idea
Under step 2A, Prong One of the Alice framework, the claims are analyzed to determine if the claims are directed to a judicial exception. MPEP §2106.04(a). The determination consists of a) identifying the specific limitations in the claim that recite an abstract idea; and b) determining whether the identified limitations fall within at least one of the three subject matter groupings of abstract ideas (i.e., mathematical concepts, mental processes, and certain methods of organizing human activity). See 2019 Revised Patent Subject Matter Eligibility Guidance (“PEG” 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. No. 4, 50-57 (Jan. 7, 2019)).
The identified limitations of independent claim 1 (representative of independent claims 18 and 19) recite (in bold and italics):
receiving, at the at least one computing device, treatment data pertaining to use of a treatment device, by a user, to perform a treatment plan, wherein the treatment data comprises at least one of characteristics of the user, treatment measurement information pertaining to the user while the user uses the treatment device, characteristics of the treatment device, and at least one aspect of the treatment plan, and wherein the treatment device includes an electromechanical machine;
receiving, at least one computing device, activity data generated at the treatment device while the user engages in at least one activity using the electromechanical machine;
generating, at the at least one computing device, treatment information using the treatment data and the activity data;
writing to an associated memory of the at least one computing device, for access by a healthcare provider, the treatment information;
modifying, at the at least one computing device, at least one aspect of the treatment plan in response to receiving, from the healthcare provider, treatment plan input including at least one modification to the at least one aspect of the treatment plan; and
controlling, by the at least one computing device and based on the modified treatment plan, at least one operating characteristic of the electromechanical machine as the user engages in an activity using the electromechanical machine
The identified limitations, under their broadest reasonable interpretations, cover performance of the limitations in the mind. The claim limitations fall within the Mental Processes groupings of abstract ideas. The performance of the claim limitations using generic computing components (i.e., memory, computing device, treatment device, and electromechanical machine) does not preclude the claim limitations from being in the Mental Processes activity grouping. That is, but for the recitation of the generic computer components, the limitations encompass a person (e.g., healthcare provider) writing out treatment and activity information of a patient and modifying a treatment plan (in writing) based on observations of the patient’s activity (e.g., riding on an exercise bike). Thus, the claimed invention recites a judicial exception.
Part I: Step 2A, prong two: additional elements that integrate the judicial exception into a practical application
Under step 2A, Prong Two of the Alice framework, the claims are analyzed to determine whether the claims recite additional elements that integrate the judicial exception into a practical application. In particular, the claims are evaluated to determine if there are additional elements or a combination of elements that apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claims are more than a drafting effort designed to monopolize the judicial exception (PEG 2019, Pg. 54).
As a whole, the memory, computing device, treatment device, and electromechanical machine in the steps are recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
Dependent claims 2-17, when analyzed as a whole are held to be patent ineligible under 35 U.S.C. 101 because the additional recited limitations fail to establish that the claims are not directed to an abstract idea:
claim 3, wherein the healthcare provider includes at least an artificial intelligence engine configured to use at least one machine learning model that generates, using the treatment information, the treatment plan input (reciting conventional machine learning models without specific improvements to the technology itself (Desjardins)).
claim 4, wherein the artificial intelligence engine is disposed on at least one of the treatment device, a remotely located server computing device, and a computing device of a healthcare provider (reciting conventional machine learning models without specific improvements to the technology itself (Desjardins)).
claim 13, wherein the at least one wearable device includes a goniometer (apply it—nominal expected use of medically-specific device).
claim 14, wherein the at least one wearable device includes a pedometer (apply it--nominal expected use of medically-specific device).
claim 15, wherein the at least one wearable device includes a goniometer and a pedometer (apply it--nominal expected use of medically-specific device).
claim 16, wherein generating the treatment information using the treatment data and the activity data includes:
using an artificial intelligence engine configured to use at least one machine learning model to generate, based on the treatment data and the activity data, at least one output indicating at least a treatment progress of the user (reciting conventional machine learning models without specific improvements to the technology itself (Desjardins)); and
generating the treatment information using the at least one output (reciting conventional machine learning models without specific improvements to the technology itself (Desjardins)).
Since these claims are directed to an abstract idea, the Office must determine whether the remaining limitations “do significantly more” than describe the abstract idea.
Part II. Determine whether any Element, or Combination, Amounts to“Significantly More” than the Abstract Idea itself
Under Part II, the steps of the claims, when considered individually and as an ordered combination, do not improve another technology or technical field, do not improve the functioning of the computer itself, and are not enough to qualify as "significantly more". For example, the steps require no more than a conventional computer to perform generic computer functions. As stated above, the memory, computing device, treatment device, and electromechanical machine, in the steps are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Therefore, based on the two-part Mayo analysis, there are no meaningful limitations in the claim that transform the exception into a patent eligible application such that the claim amounts to significantly more than the exception itself. Claims 1-19, when considered individually and as an ordered combination, are rejected as ineligible subject matter under 35 U.S.C. 101.
Dependent claims 2-17 when analyzed as a whole are held to be patent ineligible under 35 U.S.C. 101 because the additional claims do no recite significantly more than an abstract idea.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-6 and 8-19 are rejected under 35 U.S.C. 103 as being obvious over Mason (US 2021/0391091 A1) in view of Basta et al. (US 2022/0054893 A1).
The applied reference of Mason has a common Assignee with the instant application. Based upon the earlier effectively filed date of the reference, it constitutes prior art under 35 U.S.C. 102(a)(2).
This rejection under 35 U.S.C. 103 might be overcome by: (1) a showing under 37 CFR 1.130(a) that the subject matter disclosed in the reference was obtained directly or indirectly from the inventor or a joint inventor of this application and is thus not prior art in accordance with 35 U.S.C.102(b)(2)(A); (2) a showing under 37 CFR 1.130(b) of a prior public disclosure under 35 U.S.C. 102(b)(2)(B); or (3) a statement pursuant to 35 U.S.C. 102(b)(2)(C) establishing that, not later than the effective filing date of the claimed invention, the subject matter disclosed and the claimed invention were either owned by the same person or subject to an obligation of assignment to the same person or subject to a joint research agreement. See generally MPEP § 717.02.
Regarding claims 1, 18, and 19, Mason discloses a method, performed by at least one computing device, comprising:
receiving, at the at least one computing device, treatment data pertaining to use of a treatment device, by a user, to perform a treatment plan, wherein the treatment data comprises at least one of characteristics of the user, treatment measurement information pertaining to the user while the user uses the treatment device, characteristics of the treatment device, and at least one aspect of the treatment plan (Paragraph [0097]: At 802, the processing device may receive, from a data source 15, clinical information 700 pertaining to results of performing particular treatment plans using the treatment apparatus 70 for people having certain characteristics), and wherein the treatment device includes an electromechanical machine (Fig. 4; Paragraph [0066] treatment apparatus 70 with pedals 102);
receiving, at the at least one computing device, activity data generated at the treatment device while the user engages in at least one activity using the electromechanical machine (Paragraph [0066]: FIG. 4 shows the patient wearing the ambulation sensor 82 on his wrist, with a note showing “STEPS TODAY 1355”, indicating that the ambulation sensor 82 has recorded and transmitted that step count to the patient interface 50);
generating, at least one computing device, treatment information using the treatment data and the activity data (Paragraph [0100]: based on the portion of the clinical information 700 described by the medical description language 702 and a set of characteristics pertaining to a patient, the optimal treatment plan 600 for the patient to follow when using the treatment apparatus 70 to achieve a desired result.);
writing to an associated memory of the at least one computing device, for access by a healthcare provider, the treatment information (Paragraph [0106]: the processing device may provide the optimal treatment plan to be presented in a user interface (e.g., overview display 120) on a computing device (e.g., assistant interface 94) of a medical professional. In addition, any other generated optimal treatment plans 600 may be provided to the computing device of the medical professional).
Mason discloses the limitations above. Mason does not explicitly disclose, but Basta teaches:
modifying, at the at least one computing device, at least one aspect of the treatment plan in response to receiving, from the healthcare provider, treatment plan input including at least one modification to the at least one aspect of the treatment plan (Paragraph [0177]: The system will allow for review and modification of a recommended user program by the associated physical therapist or trainer); and
controlling, by the at least one computing device and based on the modified treatment plan, at least one operating characteristic of the electromechanical machine as the user engages in an activity using the electromechanical machine (Paragraph [0177]: the training device or systems have editing capabilities on a display/control unit associated with the treadmill).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Mason to disclose modifying, at the at least one computing device, at least one aspect of the treatment plan in response to receiving, from the healthcare provider, treatment plan input including at least one modification to the at least one aspect of the treatment plan; and controlling, by the at least one computing device and based on the modified treatment plan, at least one operating characteristic of the electromechanical machine as the user engages in an activity using the electromechanical machine as taught by Basta. Using the method of gait evaluation of Basta would improve upon a user's progression along the continuum of care (Basta Paragraph [0180]).
Regarding claim 2, Mason discloses the method of claim 1, wherein the at least one activity wherein the user uses the treatment advice further includes an activity in addition to using the treatment device (Paragraph [0034]).
Regarding claim 3, Mason discloses the method of claim 1, wherein the healthcare provider includes at least an artificial intelligence engine configured to use at least one machine learning model that generates, using the treatment information, the treatment plan input (Paragraph [0044]).
Regarding claim 4, Mason discloses the method of claim 3, wherein the artificial intelligence engine is disposed on at least one of the treatment device, a remotely located server computing device, and a computing device of a healthcare provider (Paragraph [0044]).
Regarding claim 5, Mason discloses the method of claim 1, wherein the healthcare provider includes a human healthcare provider at least partially responsible for treatment of the user (Paragraph [0068]).
Regarding claim 6, Mason discloses the method of claim 5, further comprising communicating with an interface, at a computing device of the healthcare provider, wherein the interface is configured to receive the treatment plan input (Paragraph [0054]).
Regarding claim 8, Mason discloses the method of claim 1, wherein the user uses the treatment device during a telemedicine session (Paragraph [0059]).
Regarding claim 9, Mason discloses the method of claim 1, wherein the treatment measurement information includes, while the user uses the treatment device, at least one of a vital sign of the user, a respiration rate of the user, a heartrate of the user, a temperature of the user, and a blood pressure of the user (Paragraph [0022]).
Regarding claim 10, Mason discloses the method of claim 1, wherein at least some of the treatment data corresponds to at least some of the sensor data from a sensor associated with the treatment device (Paragraph [0050]).
Regarding claim 11, Mason discloses the method of claim 1, wherein, while the user uses the treatment device, at least some of the treatment data corresponds to at least some of the sensor data from a sensor associated with a wearable device worn by the user (Paragraph [0066]).
Regarding claim 12, Mason discloses the method of claim 1, wherein, while the user engages in the at least one activity, at least some of the activity data corresponds to at least some sensor data from a one sensor associated with at least one wearable device worn by the user (Paragraph [0066]).
Regarding claim 13, Mason discloses the method of claim 12, wherein the at least one wearable device includes a goniometer (Paragraph [0066]).
Regarding claim 14, Mason discloses the method of claim 12, wherein the at least one wearable device includes a pedometer (Paragraph [0066]).
Regarding claim 15, Mason discloses the method of claim 12, wherein the at least one wearable device includes a goniometer and a pedometer (Paragraph [0066]).
Regarding claim 16, Mason discloses the method of claim 1, wherein generating the treatment information using the treatment data and the activity data includes:
using an artificial intelligence engine configured to use at least one machine learning model to generate, based on the treatment data and the activity data, at least one output indicating at least a treatment progress of the user (Paragraph [0100]); and
generating the treatment information using the at least one output (Paragraph [0106]).
Regarding claim 17, Mason discloses the method of claim 16, wherein the at least one output further includes at least one treatment recommendation associated with the treatment progress of the user (Paragraph [0106]).
Response to Arguments
Applicant's arguments filed with respect to the rejection under 35 U.S.C. 101 have been fully considered but are moot in view of new ground of rejection (application of Desjardins to machine learning and AI recitations, and nominal expected use of medically specific devices).
Conclusion
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/CHINYERE MPAMUGO/Primary Examiner, Art Unit 3685
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