Prosecution Insights
Last updated: April 19, 2026
Application No. 19/000,211

DIGITALLY GUIDED PREHAB EXPERIENCES

Non-Final OA §101§103
Filed
Dec 23, 2024
Examiner
BARR, MARY EVANGELINE
Art Unit
3682
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
Deepwell Dtx
OA Round
1 (Non-Final)
36%
Grant Probability
At Risk
1-2
OA Rounds
3y 7m
To Grant
68%
With Interview

Examiner Intelligence

Grants only 36% of cases
36%
Career Allow Rate
100 granted / 278 resolved
-16.0% vs TC avg
Strong +32% interview lift
Without
With
+31.9%
Interview Lift
resolved cases with interview
Typical timeline
3y 7m
Avg Prosecution
41 currently pending
Career history
319
Total Applications
across all art units

Statute-Specific Performance

§101
38.8%
-1.2% vs TC avg
§103
33.2%
-6.8% vs TC avg
§102
7.1%
-32.9% vs TC avg
§112
16.8%
-23.2% vs TC avg
Black line = Tech Center average estimate • Based on career data from 278 resolved cases

Office Action

§101 §103
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 . DETAILED ACTION Status of the Application Claims 1-20 are currently pending in this case and have been examined and addressed below. This communication is a Non-Final Rejection in response to the Claims filed on 12/23/2024. 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 because the claimed invention is directed to an abstract idea without significantly more. Step 1 Claims 1-16 fall within the statutory category of an apparatus or system. Claims 7-13 fall within the statutory category of a process. Claims 14-20 fall within the statutory category of an article of manufacture as a computer-readable medium. Step 2A, Prong One As per Claims 1, 7, and 14, the limitations of retrieving a fitness metric and a prehabilitation experience associated with a user in response to an activation signal, wherein the prehabilitation experience comprises an intervention associated with the user; determine a current state comprising a mental fitness and a physical fitness of the user based on the fitness metric; generate an adaptive target state based on a baseline biometric, a historical feedback response, a predetermined transition threshold associated with the prehabilitation experience, and the current state of the user; induce the user to progress from the current state to the adaptive target state, by generating: a readiness metric of the user to perform the intervention (Claim 1), and a motor imagery to induce the user to imagine one or more physical activities to be performed, such that the mental fitness and the physical fitness are triggered to progress towards a predetermined threshold required to perform the intervention, under its broadest reasonable interpretation, covers management of personal behaviors or personal interactions. Generation of an intervention based on a user’s mental and physical fitness is activity which is routinely performed by a care provider in the treatment of a person with the purpose of progressing a user to a target state. This is a care provider recommending activity to a patient based on their current status to improve the patient to target status to prepare for a particular surgery or procedure, which is interaction between a care provider and patient. The motor imagery is described in the specification as merely information configured to enhance understanding of a surgery when the surgery is to be performed to the user and experience-associated stories ([0034]), which does not limit the motor imagery to anything more than information and therefore is included in recommendations generated by a physician. Although the motor imagery is described by example as potentially being generated by AI ([0034]), the generation of the motor imagery is not recited in the claims, merely the instructions or stories themselves. If a claim limitation, under its broadest reasonable interpretation, covers the management of personal behavior or interactions between people, then it falls within the “certain methods of organizing human activity” grouping of abstract ideas. Accordingly, the claims recite an abstract idea. Step 2A, Prong Two The judicial exception is not integrated into a practical application because the additional elements and combination of additional elements do not impose meaningful limits on the judicial exception. In particular, Claim 1 recites the additional element – a system comprising a data store comprising a program of instructions, a processor operably coupled to the data store such that the processor causes operations to be performed when the processor execute the program of instructions. Claim 14 recites a computer program product comprising a program of instructions tangibly embodied on a non-transitory computer readable medium, wherein the instructions are executed on a processor. The data store, processor, and computer program product embodied on a non-transitory computer readable medium in these steps is recited at a high-level of generality, such that it amounts to 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 claims also recite the additional element of a user device which receives the immersive digital prehabilitation package which is the use of computers as a tool where the use of a computer or other machinery in its ordinary capacity for tasks such as receiving data, as per MPEP 2106.05(f)(2). The user device is a general purpose computer as the specification merely describes system as including internet of things devices ([0082]). The claims also recite generating an immersive digital prehabilitation package to a user device. The immersive digital prehabilitation package is not described beyond digital data which includes a readiness metric and motor imagery, which are part of the abstract idea as described above. Generating an immersive digital prehabilitation package and sending to a user device amounts to mere instructions to apply the exception similar to generating a second menu and sending to another location as performed by generic computer components (MPEP 2106.05(f)(2). Because the additional elements do not impose meaningful limitations on the judicial exception, the claim is directed to an abstract idea. Step 2B The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea. As discussed above with the respect to integration of the abstract idea into a practical application, the additional element of a system comprising a data store comprising a program of instructions, a processor operably coupled to the data store such that the processor causes operations to be performed when the processor execute the program of instructions and a computer program product comprising a program of instructions tangibly embodied on a non-transitory computer readable medium, wherein the instructions are executed on a processor to perform the method of the invention amounts to no more than mere instructions to apply the exception using a generic computing component. The system including the data store and processor are recited at a high level of generality and are recited as generic computer components by reciting programmable devices such as microprocessor and any data stores that provide digital data storage capability (Specification, [0072]), which do not add meaningful limitations to the abstract idea beyond mere instructions to apply an exception. The computer program products are described as including software on a storage medium such as an electronic, magnetic, or rotating storage device (Specification [0073]), which do not add meaningful limitations to the abstract idea beyond mere instructions to apply an exception. The claims also include generating an immersive digital prehabilitation package, which amounts to mere instructions to apply the exception, as described above. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claims also include the additional element of a user device which receives the immersive digital prehabilitation package which is a well-understood, routine and conventional computer functions in the field of data management because they are claimed at a high level of generality and include receiving or transmitting data as well, which have been found to be well-understood, routine and conventional computer functions by the Court (MPEP 2106.05(d)(II)(i) Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014) ("Unlike the claims in Ultramercial, the claims at issue here specify how interactions with the Internet are manipulated to yield a desired result‐‐a result that overrides the routine and conventional sequence of events ordinarily triggered by the click of a hyperlink." (emphasis added). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of the computer or improves another technology. The claims do not amount to significantly more than the underlying abstract idea. Dependent Claims Dependent Claims 2-6, 8-13, and 15-20 add further limitations which are also directed to an abstract idea. For example, Claims 2, 9, and 16 include determining whether the readiness metric exceeds the predetermined transition threshold, generating a signal indicating a readiness for the user to progress into rehabilitation experience associated with the prehabilitation experience, generating a new adaptive target state based on the baseline biometric, the historical feedback response, the rehabilitation experience, and the current state of the user, and generating a new immersive digital prehabilitation package to induce the user to progress from the current state to the new adaptive target state which describe behavior of a care provider in the treatment of a patient in preparing for rehabilitation after prehabilitation. This falls into the abstract idea of certain methods of organizing human activity for the same reasons as the independent claims. Claims 8 and 15 include a description of the immersive digital prehabilitation package similar to Claim 1 and is directed to an abstract idea for the same reasons. Claims 3, 5-6, 10, 12-13, 17, and 19-20 further specify or limit the element of the independent claims and are therefore directed to the same abstract idea as the independent claims. Claims 4, 11, and 18 include identifying a user preference which is applied to reduce an effort comprising time to induce the user to progress from the current state to the adaptive target state which falls into the abstract grouping of certain methods of organizing human activity for the same reasons as the independent claims. 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 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Llarno et al. (US 2023/0377714 A1), hereinafter Llarno, in view of Mason et al. (US 2021/0138304 A1), hereinafter Mason. As per Claims 1, 7, and 14, Llarno discloses a system comprising: a data store comprising a program of instructions ([0057-0058] processor and memory communicably connected to the processor and including machine readable instructions to implement the modules); and a processor operably coupled to the data store such that, when the processor executes the program of instructions, the processor causes operations to be performed to automatically generate an immersive digital prehabilitation package to a user device based on a dynamically determined fitness metric associated with the user device ([0054] processing circuit including processors and memory/storage, [0057-0058] processor and memory communicably connected to the processor and including machine readable instructions to implement the modules), the operations comprising: in response to an activation signal, retrieve a fitness metric and a prehabilitation experience associated with a user associated with the user device, wherein the prehabilitation experience comprises an intervention associated with the user (See Fig. 3 preoperative data includes a patient readiness score, i.e. fitness score, and activity quality score, as well as the planned procedure/surgical plan which Examiner interprets to be the intervention associated with the user, Fig. 23 receive preoperative data; [0052] preoperative data including data collected prior to procedure; [0056] communication module in response to uplink of data to receive data, [0077-0078] collecting preoperative data using sensors and user interfaces which are entered in response to a prompt, i.e. activation signal, [0263] calculating prehabilitation plan from collection of preoperative data in response to an input signal); determine a current state comprising a mental fitness and a physical fitness of the user based on the fitness metric ([0094] determining scores for the patient including psychosocial score, and physical related scores such as joint stiffness score, bone shape score, etc.); generate a goal state based on a baseline biometric, a historical feedback response, a predetermined transition threshold associated with the prehabilitation experience, and the current state of the user ([0261-0263] treatment for the patient is continuously calculated using updated data during the preoperative period where the new treatment is calculated using preoperative algorithms which are based on kinematics, biometrics, lifestyle and psychosocial data, [0189-0190] determining a patient readiness is above or below a threshold, i.e. transition threshold, and is based on historical feedback of patients based on outcome data); and generate the immersive digital prehabilitation package configured to induce the user to progress from the current state to the adaptive target state ([0012] determining a prehabilitation plan for the patient, [0014] determining the timing of the prehabilitation plan, [0094-0095] output of the preoperative algorithm includes the prehabilitation plan which includes instructions for the patient in preparing for medical procedure/surgery such as strengthening muscles, [0179] determine prehabilitation plan ), wherein the immersive digital prehabilitation package comprises: a readiness metric of the user to perform the intervention ([0014] determining a patient readiness score, [0188] where the readiness score indicates that the patient is ready or not yet ready for a procedure). However, Llarno may not explicitly disclose the following which is taught by Mason: the generated goal state for the patient is an adaptive target state ([0074] the portions of the treatment plan have target state such as a target angle of extension, target angle of flex, etc., [0195] prehabilitation plan includes goals to achieve on the plan, i.e. target state); a motor imagery configured to induce the user to imagine one or more physical activities to be performed, such that the mental fitness and the physical fitness are triggered to progress towards a predetermined threshold required to perform the intervention ([0083] user interface presents screens to a user which allow the user to view the treatment plan, [0154] user interfaces which user can view during the treatment plan execution, Fig. 22-26). Therefore, it would have been obvious to a person of ordinary skill in the art before the filing of the present invention to combine the known concept of generating an adaptive target state for a patient and providing visual information to the patient to perform activities to progress towards a goal for a procedure from Mason with the generation of a prehabilitation plan for a patient based on patient readiness from Llarno in order to generate improvement in a patient to prepare for surgery (Mason [0003]). As per Claims 8 and 15, Llarno and Mason discloses the limitations of Claims 7 and 14. Llarno also teaches the immersive digital prehabilitation package further comprises a readiness metric of the user to perform the intervention ([0014] determining a patient readiness score, [0188] where the readiness score indicates that the patient is ready or not yet ready for a procedure). As per Claims 2, 9, and 16, Llarno and Mason discloses the limitations of Claims 1, 8, and 15. Llarno also teaches a rehabilitation experience, wherein the operations further comprise: determine whether the readiness metric exceeds the predetermined transition threshold ([0188] patient readiness threshold level compared to the patient readiness score); generate a signal indicating a readiness for the user to progress into the rehabilitation experience associated with the prehabilitation experience ([0106] patient readiness is calculated and based on the physical and mental factors, [0188] when a patient readiness is low the patient is not ready for prehabilitation, which inherently indicates that the patient is ready for the plan when the readiness is not low, [0077-0078] collecting preoperative data using sensors and user interfaces which are entered in response to a prompt, i.e. activation signal, [0263] calculating prehabilitation plan from collection of preoperative data in response to an input signal); upon receiving a confirmation signal, generate a new adaptive target state based on the baseline biometric, the historical feedback response, the rehabilitation experience, and the current state of the user ([0188] based on the patient readiness score, determine if the patient needs further exercises to increase the readiness score, i.e. a new target state); and generate a new immersive digital prehabilitation package configured to induce the user to progress from the current state to the new adaptive target state ([0188] based on the patient readiness score, determine if the patient needs further exercises to increase the readiness score, i.e. a new target state). As per Claims 3, 10, and 17, Llarno and Mason discloses the limitations of Claims 1, 7, and 14. Llarno also teaches the fitness metric comprises a surgical experience, a pharmaceutical experience, a mental experience, and a physical experience ([0014] patient readiness score is based on kinematics data, [0106] patient readiness score is based on stress, biometrics, kinematics, [0064] medical history includes prior medications/drug use, prior surgeries, [0189] patient readiness is based on medical history, type of procedure, etc.). As per Claims 4, 11, and 18, Llarno and Mason discloses the limitations of Claims 1, 7, and 14. However, Llarno may not explicitly disclose the following which is taught by Mason: identify a user preference, wherein the immersive digital prehabilitation package is selected by applying the user preference to an immersive digital prehabilitation package selection model, wherein the immersive digital prehabilitation package selection model is configured to reduce an effort comprising time to induce the user to progress from the current state to the adaptive target state (see Fig. 14/[0157] user settings are identified for the activities of the prehabilitation plan and the treatment plan is applied to the settings in order to increase user comfort in executing the plan, [0060] treatment plan is executed to improve a body characteristic to reach normal operability, i.e. target state, see Fig. 22 where the progress is displayed to reach target goal for the prehabilitation plan). Therefore, it would have been obvious to a person of ordinary skill in the art before the filing of the present invention to combine the known concept of identifying user preferences and incorporating into the prehabilitation plan from Mason with the generation of a prehabilitation plan for a patient based on patient readiness from Llarno in order to generate improvement in a patient to prepare for surgery (Mason [0003]). As per Claims 5, 12, and 19, Llarno and Mason discloses the limitations of Claims 1, 7, and 14. Llarno also teaches the mental fitness comprises a pain threshold response ([0065] psychosocial information includes perceived pain level, [0078] psychosocial information includes perceived or evaluated pain as reported by a patient, [0173] collected data includes response as it associates to level of pain). As per Claims 6, 13, and 20, Llarno and Mason discloses the limitations of Claims 1, 7, and 14. Llarno also teaches the predetermined transition threshold is generated as a function of the baseline biometric, a minimum threshold associated with the prehabilitation experience, and an aggregated threshold identified based on historical outcomes of individuals undergoing a same prehabilitation experience ([0188-0190] determining a patient readiness is above or below a threshold, i.e. transition threshold, and is based on historical feedback of patients based on outcome data, the predetermined thresholds are based on normal, typical, or healthy status and successful patient outcomes from previous similar procedures). Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Andrew Bates, et al. (Bates, A.; West, M.A.; Jack, S.; Grocott, M.P.W. Preparing for and Not Waiting for Surgery. Curr. Oncol. 23 January 2024, 31, pp. 629–648.) teaches generating personalized prehabilitation prescription to prepare for surgery. Any inquiry concerning this communication or earlier communications from the examiner should be directed to Evangeline Barr whose telephone number is (571)272-0369. The examiner can normally be reached Monday to Friday 8:00 am to 4:00 pm. 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, Fonya Long can be reached at 571-270-5096. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /EVANGELINE BARR/Primary Examiner, Art Unit 3682
Read full office action

Prosecution Timeline

Dec 23, 2024
Application Filed
Feb 02, 2026
Non-Final Rejection — §101, §103 (current)

Precedent Cases

Applications granted by this same examiner with similar technology

Patent 12597509
SYSTEMS AND METHODS FOR MEDICAL DEVICE TASK GENERATION AND MANAGEMENT
2y 5m to grant Granted Apr 07, 2026
Patent 12525344
IMMERSIVE MEDICINE TRANSLATIONAL ENGINE FOR DEVELOPMENT AND REPURPOSING OF NON-VERIFIED AND VALIDATED CODE
2y 5m to grant Granted Jan 13, 2026
Patent 12476000
MACHINE LEARNING TO MANAGE SENSOR USE FOR PATIENT MONITORING
2y 5m to grant Granted Nov 18, 2025
Patent 12475977
Health Safety System, Service, and Method
2y 5m to grant Granted Nov 18, 2025
Patent 12437862
RARE INSTANCE ANALYTICS FOR DIVERSION DETECTION
2y 5m to grant Granted Oct 07, 2025
Study what changed to get past this examiner. Based on 5 most recent grants.

AI Strategy Recommendation

Get an AI-powered prosecution strategy using examiner precedents, rejection analysis, and claim mapping.
Powered by AI — typically takes 5-10 seconds

Prosecution Projections

1-2
Expected OA Rounds
36%
Grant Probability
68%
With Interview (+31.9%)
3y 7m
Median Time to Grant
Low
PTA Risk
Based on 278 resolved cases by this examiner. Grant probability derived from career allow rate.

Sign in with your work email

Enter your email to receive a magic link. No password needed.

Personal email addresses (Gmail, Yahoo, etc.) are not accepted.

Free tier: 3 strategy analyses per month