Prosecution Insights
Last updated: April 19, 2026
Application No. 18/557,249

AUGMENTED REALITY PATIENT ASSESSMENT MODULE

Non-Final OA §103
Filed
Oct 25, 2023
Examiner
LHYMN, SARAH
Art Unit
2613
Tech Center
2600 — Communications
Assignee
Zimmer, Inc.
OA Round
3 (Non-Final)
65%
Grant Probability
Favorable
3-4
OA Rounds
2y 4m
To Grant
81%
With Interview

Examiner Intelligence

Grants 65% — above average
65%
Career Allow Rate
357 granted / 546 resolved
+3.4% vs TC avg
Strong +15% interview lift
Without
With
+15.2%
Interview Lift
resolved cases with interview
Typical timeline
2y 4m
Avg Prosecution
30 currently pending
Career history
576
Total Applications
across all art units

Statute-Specific Performance

§101
5.4%
-34.6% vs TC avg
§103
63.2%
+23.2% vs TC avg
§102
5.9%
-34.1% vs TC avg
§112
15.3%
-24.7% vs TC avg
Black line = Tech Center average estimate • Based on career data from 546 resolved cases

Office Action

§103
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 . Response to Amendment / Arguments Applicant amended the claims to add “set of” to “current range of motion measurement values” in the independent claims. The examiner is not persuaded that the addition of “set of” changes the interpretation of “current range of motion measurement values”, for reasons that follow. First, to Applicant’s specification. “Set of” isn’t in the spec in relation to measurement values or range of motion. Its present six times, none of which to range of motion or measurement value, or both in the same term. Nor is the term “measurement value” or even “measurement” in the spec. Left now with “range of motion”, see Applicant’s Figs. 2A-2B: 255. Here, the range of motion is illustrated as a path the user’s arm is presumably moving. Applicant’s Fig. 2A is reproduced below for convenience. PNG media_image1.png 464 648 media_image1.png Greyscale Second, to the Wells reference. Like Applicant’s Fig. 2A, the Wells reference also illustrates a circular range of motion. In this case, it is the patient’s leg that is moving (not the arm, of Applicant’s Fig. 2A). See below, from the Wells reference, which is a guide for a user. And in practice, Wells teaches a therapist or other individual to “perform a complete clinical movement, which may include one or more waypoints along the complete clinical movement, the waypoints representing progress points” (para. 49). PNG media_image2.png 558 604 media_image2.png Greyscale “The full range of motion may be broken down into partial range of motion segments, which may be displayed (e.g., progressively) to a patient in an augmented reality environment. The segments may be coupled to increase the range of motion targets progressively (e.g., each day adding another target with a wider range of motion). The range of motion may include functional measures that may be achieved by a patient” (para. 49). See also Fig. 4 and related description: assessing whether a patient’s motion is within the intended starting location, ending location, and within edges of a “path region” (see para. 54) – all of this teaches and corresponds to a “set of current range of motion measurement values”. Accordingly, the rejections under 103 are maintained. Please see remainer of this office action for details, where the examiner has provided several more instances of Wells teaching the above “set of current range of motion measurement values” and related claim language. Claim Rejections - 35 USC § 103 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. Claim(s) 1, 3, 5, 6, 12, 14, 16, 17, 23 and 25 are rejected under 35 U.S.C. 103 as being unpatentable over Lang (U.S. Patent App. Pub. No. 2019/0380784 A1) in view of Wells (U.S. Patent App. Pub. No. 2018/0121728 A1; cited in IDS), and further in view of Nash (U.S. Patent App. Pub. No. 2018/0256258). Regarding claim 1: Lang teaches: a system for augmented reality patient assessment (see e.g., claim 31, system, in combination with para. 1529, augmented reality system related to patient care), the system comprising: an augmented reality (AR) head-mounted display (HMD) (claim 31, a see-through optical head mounted display); a depth sensor to generate depth sensor data for a patient (see paras. 250-251, which teach depth sensors that can be used to obtain live data of a patient) during a musculoskeletal assessment activity (see claim 53, which describes one example of a musculoskeletal assessment activity of a patient’s knee being moved into different positions, or moved through a range of motion); processing circuitry; and a memory that includes instructions, the instructions, when executed by the processing circuitry, cause the processing circuitry to (see claim 31, processor, in combination with para. 884, memory storing executable software): generate a skeletal model based on the depth sensor data (see e.g. para. 1168, which teaches using 3D image data to generate a patient model, in combination with para. 802, which teaches that Lang applies to musculoskeletal procedures. Modifying Lang, in view of same, such to have included a skeletal model (i.e. for patient musculoskeletal procedures, is taught by Lang, and would have been obvious to one of ordinary skill in the art. See MPEP 2143(A). Alternative mapping: see Figs. 16A-B of Lang, which summarize model generation. Per paras. 1330-1333 (related to Fig. 16B), subsurface anatomic patient models can be generated. This includes skeletal. Second alternative mapping: Nash, para. 43, overlaying a skeletal model on a patient is known, via an AR device that has a depth camera (para. 21), such to obtain patient data to generate said model); track a patient motion during the musculoskeletal assessment activity (claims 53-54 patient motion is being tracked through a range of motion, or movement (examples: knee, hip or shoulder)). Re: the remaining features of claim 1, it would have been obvious for one of ordinary skill in the art to have combined and modified the applied reference(-s), in view of same, to have obtained: determine a set of current range of motion measurement values based on the patient motion; and output the set of current range of motion measurement values overlaid on the patient for display on the AR HMD while the patient is being viewed through the AR HMD, and the results of the modification would have been obvious and predictable to one of ordinary skill in the art as of the effective filing date of the claimed invention. See MPEP §2143(A). Re: determine step,t he Wells reference also illustrates a circular range of motion. In this case, it is the patient’s leg that is moving (not the arm, of Applicant’s Fig. 2A). See below, from the Wells reference, which is a guide for a user. And in practice, Wells teaches a therapist or other individual to “perform a complete clinical movement, which may include one or more waypoints along the complete clinical movement, the waypoints representing progress points” (para. 49). PNG media_image2.png 558 604 media_image2.png Greyscale “The full range of motion may be broken down into partial range of motion segments, which may be displayed (e.g., progressively) to a patient in an augmented reality environment. The segments may be coupled to increase the range of motion targets progressively (e.g., each day adding another target with a wider range of motion). The range of motion may include functional measures that may be achieved by a patient” (para. 49). See also Fig. 4 and related description: assessing whether a patient’s motion is within the intended starting location, ending location, and within edges of a “path region” (see para. 54) – all of this teaches and corresponds to a “set of current range of motion measurement values”. OR see Wells, e.g. para. 52: “The video/animation evaluation component 404 includes an actual path the patient performed, with an actual starting location 408, an actual ending location 414, and an actual path of motion 412. T…In another example, if the actual path of motion 412 falls outside the intended edges 418 and 420, the patient's attempt at a clinical movement may be determined to be a failure. In another example, some amount of error may be tolerated, such as a brief movement outside the intended edges 418 and 420.” OR see para. 60: “The processor 502 may be used to receive information… such as a clinical movement captured using the movement capture apparatus 503. The processor 502 may analyze the clinical movement to determine a path of motion of the clinical movement, such as a path of motion on video captured by the movement capture apparatus 503. The processor 502 may automatically define a path region, such as by using the path of motion. The processor 502 may receive information about a movement of a patient along the path of motion, such as movement of the patient captured using the movement capture apparatus 503. The processor 502 may determine whether the movement was within the path region. In an example, the processor 502 may send feedback, such as to the feedback controller 508 or the display 510. The feedback may indicate whether the movement was within the path region. The display 510 may display the feedback, such as by visually indicating (e.g., on a user interface) whether the movement was within or outside the path region or where the movement may have been outside the path region. The feedback controller 508 may be used to send the feedback to the display 510, issue an audible alert, provide haptic feedback, or the like. In an example, the display 510 may be a screen, an augmented reality display, a virtual reality display, or the like.” See also para. 61: “The processor 502 may determine a start position or an end position automatically for the clinical movement, and the start position or the end position may be included in the path region. For example, to determine whether the movement was within the path region may include determining whether the movement started in the start position or ended in the end position. The display 510 may be used by a therapist (e.g., on a therapist user interface) to modify the path region, the start position, or the end position. The processor 502 may be used to create a video or animation using the path region and the information about the clinical movement. For example, the video may include the path region superimposed on captured video or animation of the clinical movement. The video may be played on the display 510. While playing the video on the display 510, the movement capture apparatus 503 may be used to capture the movement of the patient. The captured video may be stored in the video storage 512. The animation may be stored in the animation storage 514. In an example, a video may be retrieved from the video storage 512. The retrieved video may include an automatically added path region, start position, or end position. In another example, an animation may be retrieved from the animation storage 514. The retrieved animation may include an automatically added path region, start position, or end position.” At least these paragraphs teach determining a current range of motion measurement values based on patient motion (i.e. measurement values needed to determine the clinical path, a start and end position, and whether the patient’s movement as within the path region or clinical goals). Re: output step, Wells teaches outputting AR graphics/information related to a patient current range of motion. As mapped above, Lang teaches a HMD that can be used in clinical settings, such as viewing a patient (i.e. OHMD including live data of the patient. See para. 4, Figs. 1 and 14, for example). With respect to outputting range of motion measurement values, Nash teaches that it is known to have an AR device and an AR display that can display virtual and real (e.g. patient) components, whereby the virtual components can include “measurements, angles” etc. See para. 13 of Nash. Modifying Lang, such to superimpose or overlay a current range of motion measurement values, as per Nash and Wells, when Lang also teaches obtaining range of motion information of a patient (see mapping above), and when Lang also teaches the overlaying of virtual data on a patient’s live data as seen through HMD (Lang, para. 204), is all of taught and suggested by the prior art, and would have been obvious and predictable to one of ordinary skill in the art as of the effective filing date of the claimed invention. See MPEP §2143(A). Further motivation is found in the prior art, to provide for a simultaneous visualization of live patient data with virtual data to facilitate patient care (Lang, para. 4). The prior art included each element recited in claim 1, although not necessarily in a single embodiment, with the only difference being between the claimed element and the prior art being the lack of actual combination of certain elements in a single prior art embodiment, as described above. One of ordinary skill in the art could have combined the elements as claimed by known methods, and in that combination, each element merely performs the same function as it does separately. One of ordinary skill in the art would have also recognized that the results of the combination were predictable as of the effective filing date of the claimed invention. Regarding claim 3: It would have been obvious for one of ordinary skill in the art to have further modified the applied reference(-s), in view of same, to have obtained: the system of claim 1, the instructions further causing the processing circuitry to: determine a target range of motion based on the musculoskeletal assessment activity (Lang, para. 867, target or desired range of motion is known) (Wells, targets are also known. See para. 20, 49 (target range of motion), 63 and claim 2); and output a graphical indication of the target range of motion for display on the AR HMD while the patient is being viewed through the AR HMD, (see Wells, para 49, Fig. 3). Modifying the applied references, such to include outputting a graphical element related to target range of motion, per Lang, with all references relevant to motion and ranges of motion of patients, for display on the HMD while the patient is viewed, per both references (Nash, para. 13) (Lang, para. 204)), would have been obvious and predictable to one of ordinary skill in the art as of the effective filing date of the claimed invention. See MPEP §2143(A). The prior art included each element recited in claim 3, although not necessarily in a single embodiment, with the only difference being between the claimed element and the prior art being the lack of actual combination of certain elements in a single prior art embodiment, as described and mapped above. One of ordinary skill in the art could have combined the elements as claimed by known methods, and in that combination, each element merely performs the same function as it does separately. One of ordinary skill in the art would have also recognized that the results of the combination were predictable as of the effective filing date of the claimed invention. Regarding claim 5: It would have been obvious for one of ordinary skill in the art to have further modified the applied reference(-s), in view of same, to have obtained: the system of claim 1, the instructions further causing the processing circuitry to receive motion sensor data from a motion sensor attached to a patient, the motion sensor data characterizing a musculoskeletal motion of the patient; wherein the generation of the skeletal model is further based on the sensor data, and the results of the modification would have been obvious and predictable to one of ordinary skill in the art as of the effective filing date of the claimed invention. See MPEP §2143(A). Lang teaches that motion sensors to obtain human/patient movement data is known (paras. 136-37), such to obtain movement information from range of motion tests (claims 53-55, para. 867). This corresponds to motion sensor data characterizing a musculoskeletal motion of the patient. Lang also teaches that its patient models can be adjusted/modified, using intra-operative data (such as when the patient is performing range of motion tests, per Lang, and mapped in claim 1) (see para. 1168). Lang also teaches that its patient models can be further deformed/changed based on patient related features (para. 1144-1146). Modifying Lang, in view of same, such to include the above, and to generate a skeletal model (mapped in claim 1), based on range of motion data (also taught by Lang), when Lang also teaches/motivates this by describing range of motion, desired movement, and ligamentous laxity as three factors that a surgeon should consider while planning/performing surgery (para. 867), is taught, suggested and motivated by the prior art, and would have been obvious and predictable to one of ordinary skill. One of ordinary skill in the art could have combined the elements as claimed by known methods, and in that combination, each element merely performs the same function as it does separately. One of ordinary skill in the art would have also recognized that the results of the combination were predictable as of the effective filing date of the claimed invention. Regarding claim 6: Lang teaches: the system of claim 1, the instructions further causing the processing circuitry to receive medical imaging data of a musculoskeletal joint of the patient; wherein the generation of the skeletal model is further based on the medical imaging data (para. 1168, patient models can be adjusted/modified, using intra-operative data. This can be imaging data. Id. See also para. 1271). It would have been obvious for one of ordinary skill in the art, as of the effective filing date of Applicant’s claims, to have further modified the applied references, in view of Lang, to have obtained the above, motivated to be able to use and present the most recent and relevant patient information during medical procedures. Regarding claim 12: see also claim 1. The method of claim 12 corresponds to the functions performed by the system of claim 1; the same rationale for rejection applies. Regarding claim 14: see claim 3. These claims are similar; the same rationale for rejection applies. Regarding claim 16: see claim 5. These claims are similar; the same rationale for rejection applies. Regarding claim 17: see claim 6. These claims are similar; the same rationale for rejection applies. Regarding claim 23: see also claim 1. Lang teaches: a non-transitory machine-readable storage medium, comprising instructions that, (para. 884, memory storing executable software) responsive to being executed with processing circuitry of a computer-controlled device (para. 884, executed by processors, such as those of the system claim 31), cause the processing circuitry to: The instructions correspond to the functions performed by the system of claim 1; the same rationale for rejection applies. Regarding claim 25: see claim 3. These claims are similar; the same rationale for rejection applies. Claim(s) 2, 4, 13, 15 and 24 are rejected under 35 U.S.C. 103 as being unpatentable over Lang in view of Wells and Nash, and further in view of Dalvin (U.S. Patent App. Pub. No. 2019/0239850 A1). Regarding claim 2: It would have been obvious for one of ordinary skill in the art to have combined and modified the applied reference(-s), in view of same, to have obtained: the system of claim 1, the instructions further causing the processing circuitry to: receive a selection of the musculoskeletal assessment activity (Dalvin, para. 39 and/or Fig. 2); and output a description of the musculoskeletal assessment activity for display on the AR HMD while the patient is being viewed through the AR HMD (Dalvin, para 6), and the results of the modification would have been obvious and predictable to one of ordinary skill in the art as of the effective filing date of the claimed invention. See MPEP §2143(A). As mapped above Dalvin teaches systems/methods for the “guidance of health-related examinations…via augmented and/or mixed reality…capable of displaying digital information to the user, examinee or other observer via augmented reality and/or mixed reality” (quoting para. 6). Guidance can be provided in the form of text instructions, or guiding graphics, which can be displayed on an AR display device, such as head-mounted display device (para. 6). Users can provide input and make selections (para. 39 and Fig. 2). Modifying the applied references, such to include the functionality of Dalvin, i.e. to guide a user/medical professional in the range of motion procedures as taught in Lang, is all of taught and suggested by the prior art, would have been obvious and predictable to one of ordinary skill, and that same person of ordinary skill would have been motivated to do so in order to “improve the quality of the data acquired during the examination, reduce inter-operator variability, or enable a clinician to do a medical examination that was previously difficult or impossible to perform with good results due to limitations in skill or capability” (motivation quoted directly from Dalvin, para. 6). One of ordinary skill in the art could have combined the elements as claimed by known methods, and in that combination, each element merely performs the same function as it does separately. One of ordinary skill in the art would have also recognized that the results of the combination were predictable as of the effective filing date of the claimed invention. Regarding claim 4: Dalvin teaches: the system of claim 1, the instructions further causing the processing circuitry to output a guided musculoskeletal activity for display on the AR HMD, the guided musculoskeletal activity providing a patient motion instruction for conducting the musculoskeletal assessment activity (para. 6, which teaches outputting guidance in the form of graphics or text instructions to assist users and medical practitioners with examinations). Modifying the applied references, such to include the functionality of Dalvin, i.e. to guide a user/medical professional in the range of motion procedures as taught in Lang, is all of taught and suggested by the prior art, would have been obvious and predictable to one of ordinary skill as of the effective filing date of Applicant’s claims, and that same person of ordinary skill would have been motivated to do so in order to “improve the quality of the data acquired during the examination, reduce inter-operator variability, or enable a clinician to do a medical examination that was previously difficult or impossible to perform with good results due to limitations in skill or capability” (motivation quoted directly from Dalvin, para. 6). See MPEP §2143(A). One of ordinary skill in the art could have combined the elements as claimed by known methods, and in that combination, each element merely performs the same function as it does separately. One of ordinary skill in the art would have also recognized that the results of the combination were predictable as of the effective filing date of the claimed invention. Regarding claim 13: see claim 2. These claims are similar; the same rationale for rejection applies. Regarding claim 15: see claim 4. These claims are similar; the same rationale for rejection applies. Regarding claim 24: see claim 2. These claims are similar; the same rationale for rejection applies. Claim(s) 7 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Lang in view of Wells and Nash, and further in view of Palo (U.S. Patent App. Pub. No. 2018/0289434 A1). Regarding claim 7: The applied references to claim 1 do not proactively teach claim 7. Consider the following. In analogous art, Palo teaches: the system of claim 1, the instructions further causing the processing circuitry to: receive a selection of a model surgical procedure (para. 35, select surgical templates; and/or para.41: from a drop-down menu of surgical procedures); generate a patient procedure model based on the model surgical procedure and the skeletal model (paras. 41-47, user can create a patient procedure model, and, para. 46, use images and files to do so. Modifying the applied references, such to use the skeletal model mapped in claim 1, as a file/image to use to create the procedure model of Palo, is all of taught and suggested by the prior art, would have been obvious and predictable to one of ordinary skill in the art as of the effective filing date of the claimed invention. See MPEP §2143(A)); and output the patient procedure model for display on the AR HMD while the patient is being viewed through the AR HMD (see mapping to claim 1; Fig. 1 of Lang, output to OHMD). It would have been obvious for one of ordinary skill in the art, as of the effective filing date of Applicant’s claims, to have further modified the applied references, in view of same, to have obtained the above, motivated to be able to use and present the most recent and relevant patient information during medical procedures. Regarding claim 18: see claim 7. These claims are similar; the same rationale for rejection applies. Claim(s) 8, 9, 19 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Lang in view of Wells and Nash, and further in view of Kurniawan (U.S. Patent App. Pub. No. 2020/0327986 A1). Regarding claim 8: It would have been obvious for one of ordinary skill in the art to have combined and modified the applied reference(-s), in view of same, to have obtained: the system of claim 1, the instructions further causing the processing circuitry to: generate a predicted postoperative skeletal model based on the skeletal model, the skeletal model including a preoperative skeletal model, the predicted postoperative skeletal model including an improved range of motion based on a surgical procedure; and output the predicted postoperative skeletal model overlaid on the patient for display on the AR HMD while the patient is being viewed through the AR HMD, and the results of the modification would have been obvious and predictable to one of ordinary skill in the art as of the effective filing date of the claimed invention. See MPEP §2143(A). Lang teaches generating patient models (i.e. a skeletal model), as mapped in claim 1 (see Figs. 16A-B of Lang). This includes post-operative models (para. 1329, models can be based on post-op patient images), and models can be output for HMD display (mapping to claim 1, and Figs. 16A-B). In terms of a “predictive” postoperative model, Kurniawan teaches that it is known in the art of medical/patient care to include predictive analytics in a prediction system which collected health data from various sensors, and carries out predictive analysis through a virtual reality device (para. 5). For reference, six aspects of the system/methods of Kurniawan are listed in paras. 39-44, and the instant reference is not limited to any specific medical field (see paras. 54-56). Kurniawan also further teaches prediction in terms of 3D depth prediction, plane estimation, and 3D depth reconstruction (paras. 80, 139). Modifying the applied references, such to incorporate the teachings of Kurniawan, into a post-operative skeletal model (per Lang), that is based predictive analysis, per Kurniawan (i.e. predictive range of motion from a procedure of Lang, with pre-op/intra-op data on range of movement already collected, per Lang, and mapped above in claim 1), is all of taught, suggested and motivated by the prior art, and would have been obvious and predictable to one of ordinary skill. Motivations and problems that can be solved by including predictive analysis are also articulated in the Kurniawan reference (see paras. 2-3). One of ordinary skill in the art could have combined the elements as claimed by known methods, and in that combination, each element merely performs the same function as it does separately. One of ordinary skill in the art would have also recognized that the results of the combination were predictable as of the effective filing date of the claimed invention. Regarding claim 9: It would have been obvious for one of ordinary skill in the art to have further modified the applied reference(-s), in view of same, to have obtained: the system of claim 8, the depth sensor further to generate postoperative depth sensor data for the patient during a postoperative musculoskeletal assessment activity; the instructions further causing the processing circuitry to: generate a revised postoperative skeletal model based on the postoperative depth sensor data; a output the revised postoperative skeletal model overlaid on the preoperative skeletal model for display on the AR HMD, and the results of the modification would have been obvious and predictable to one of ordinary skill in the art as of the effective filing date of the claimed invention. See MPEP §2143(A). Lang teaches obtaining post-op images for model generation/revision (see mapping to claim 1 or claim 8), whereby images can be obtained via depth sensor (mapping to claim 1). Modifying the applied references, in view of Lang, such to revise a postop skeletal model based on postop images, all taught by Lang, would have been obvious and predictable to one of ordinary skill, with the additional motivation to use relevant patient data to revise/add information/edit patient models. One of ordinary skill in the art could have combined the elements as claimed by known methods, and in that combination, each element merely performs the same function as it does separately. One of ordinary skill in the art would have also recognized that the results of the combination were predictable as of the effective filing date of the claimed invention. Regarding claim 19: see claim 8. These claims are similar; the same rationale for rejection applies. Regarding claim 20: see claim 9. These claims are similar; the same rationale for rejection applies. Claim(s) 10, 11, 21 and 22 are rejected under 35 U.S.C. 103 as being unpatentable over Lang in view of Wells and Nash, and further in view of Kurniawan and Palo. Regarding claim 10: Palo and Kurniawan teach: the system of claim 8, the instructions further causing the processing circuitry to receive a surgical procedure selection (Palo, para. 35, select surgical templates; and/or para.41: from a drop-down menu of surgical procedures), wherein the predicted postoperative skeletal model is further based on the surgical procedure selection (Kurniawan, see para. 5, the predictive system analyzes health data to provide recommendations. This includes patient information (para. 148)). Modifying the applied references, such that the relevant patient info/health data for which to perform predictive analysis, per Kurniawan, includes the patient’s surgical procedure (either performed or to be performed), selected in a menu based system of Palo, would have been obvious and predictable to one of ordinary skill, with the additional motivation to use relevant patient data to revise/add information/edit patient models. See also MPEP 2143(a). One of ordinary skill in the art could have combined the elements as claimed by known methods, and in that combination, each element merely performs the same function as it does separately. One of ordinary skill in the art would have also recognized that the results of the combination were predictable as of the effective filing date of the claimed invention. Regarding claim 11: It would have been obvious for one of ordinary skill in the art to have further modified the applied reference(-s), in view of same, to have obtained: the system of claim 10, the instructions further causing the processing circuitry to: identify a list of surgical procedures associated with the musculoskeletal assessment activity; and output a selection prompt for the list of surgical procedures for display on the AR HMD, and the results of the modification would have been obvious and predictable to one of ordinary skill in the art as of the effective filing date of the claimed invention. See MPEP §2143(A). Palo teaches that it is known to link different layers of information in a hierarchical fashion as it related to medical data, and teaches using the data to populate database fields for selection (e.g. claims 2-7). All of the analogous references are relevant to surgical procedures. Modifying the applied references, such to link a musculoskeletal activity (like range of motion/ movement, per Lang, and mapped in claim 1), to a surgical procedure (also per Lang, mapped in claim 1, and also taught by Palo), for selection prompt, per Palo, and display on a AR HMD (Lang, mapped throughout), is all of taught, suggested and motivated by the prior art, and would have been obvious and predictable to one of ordinary skill. Additional motivation would be to streamline linked data entry and display, per Palo. One of ordinary skill in the art could have combined the elements as claimed by known methods, and in that combination, each element merely performs the same function as it does separately. One of ordinary skill in the art would have also recognized that the results of the combination were predictable as of the effective filing date of the claimed invention. Regarding claim 21: see claim 10. These claims are similar; the same rationale for rejection applies. Regarding claim 22: see claim 11. These claims are similar; the same rationale for rejection applies. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to Sarah Lhymn whose telephone number is (571)270-0632. The examiner can normally be reached M-F, 9:00 AM to 6:00 PM EST. 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, Xiao Wu can be reached at 571-272-7761. 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. Sarah Lhymn Primary Examiner Art Unit 2613 /Sarah Lhymn/Primary Examiner, Art Unit 2613
Read full office action

Prosecution Timeline

Oct 25, 2023
Application Filed
May 31, 2025
Non-Final Rejection — §103
Sep 03, 2025
Response Filed
Sep 17, 2025
Final Rejection — §103
Nov 19, 2025
Response after Non-Final Action
Dec 16, 2025
Request for Continued Examination
Dec 19, 2025
Response after Non-Final Action
Feb 19, 2026
Non-Final Rejection — §103 (current)

Precedent Cases

Applications granted by this same examiner with similar technology

Patent 12602882
AUGMENTED REALITY DISPLAY DEVICE AND AUGMENTED REALITY DISPLAY SYSTEM
2y 5m to grant Granted Apr 14, 2026
Patent 12602764
METHODS OF ARTIFICIAL INTELLIGENCE-ASSISTED INFRASTRUCTURE ASSESSMENT USING MIXED REALITY SYSTEMS
2y 5m to grant Granted Apr 14, 2026
Patent 12602746
SYSTEM AND METHOD FOR BACKGROUND MODELLING FOR A VIDEO STREAM
2y 5m to grant Granted Apr 14, 2026
Patent 12585888
AUTOMATICALLY GENERATING DESCRIPTIONS OF AUGMENTED REALITY EFFECTS
2y 5m to grant Granted Mar 24, 2026
Patent 12586163
INTERACTIVELY REFINING A DIGITAL IMAGE DEPTH MAP FOR NON DESTRUCTIVE SYNTHETIC LENS BLUR
2y 5m to grant Granted Mar 24, 2026
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

3-4
Expected OA Rounds
65%
Grant Probability
81%
With Interview (+15.2%)
2y 4m
Median Time to Grant
High
PTA Risk
Based on 546 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