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 .
Status of the Claims
The office action is in response to the claims filed on November 26, 2024 for the application filed on November 26, 2024, which is a continuation-in-part of Application No. 18/219,910 filed on July 10, 2023. Claims 1 – 20 are currently pending and have been examined as discussed below.
Specification
The disclosure is objected to because of the following informalities: the multiple instances of the term “regime” in Lines 6 of Paragraph [0028], Lines 17 – 19 of Paragraph [0032], and Lines 18 – 25 of Paragraph [0033] of the Specification as filed should be replaced with the term “regimen”.
Appropriate correction is required.
Claim Objections
Claims 1, 5 – 6, 11, and 15 are objected to because of the following informalities: the term “a recovery program” in line 9 of claim 1 and in lines 8 – 9 of claim 11 should be replaced with “an osteoporosis recovery program”; the term “a current osteoporosis state” in lines 1 – 2 in claim 6 should be replaced with “the current osteoporosis state”; the term “exercise regime” in lines 2 – 3 of claim 5 and line 3 of claim 15 should be replaced with “exercise regimen”. Appropriate correction is required.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1 and 11 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over an associated one of claims 1 and 11 of Mahmud ‘943 (U.S. Patent No. 12,164,943 B1) in view of Mahmud ‘254 (U.S. Pub. No. 2022/0093254 A1).
Regarding independent claims 1 and 11 of the instant application, claims 1 and 11 of Mahmud ‘943 read on the associated limitations of representative claim 1 identified in bold as:
A system of dynamic user interface generation (Claim 1 of Mahmud ‘943. In the instant application, the broadest reasonable interpretation of “a system of dynamic user interface generation” reads on the limitation in Mahmud ‘943 (Claim 1) of the system of dynamic user interface generation.), wherein the system comprises:
a computing device, wherein the computing device is configured to (Claim 1 of Mahmud ‘943. In the instant application, the broadest reasonable interpretation of “a computing device, wherein the computing device is configured to” reads on the limitation in Mahmud ‘943 (Claim 1) of the computing device being configured to.):
configure, using an initial display data structure, a remote device to display a user interface having a first input field (Claim 1 of Mahmud ‘943. In the instant application, the broadest reasonable interpretation of “configure, using an initial display data structure, a remote device to display a user interface having a first input field” reads on the limitation in Mahmud ‘943 (Claim 1) of configuring, using an initial display data structure, a remote device to display a user interface having a first input field.);
capture user interaction data comprising osseous tissue data using the first input field (Claim 1 of Mahmud ‘943. In the instant application, the broadest reasonable interpretation of “capture user interaction data … using the first input field” reads on the limitation in Mahmud ‘943 (Claim 1) of capturing user interaction data using the first input field and from an engagement module comprising a dispersive signal touch screen communicatively connected to the user interface, wherein the user interaction data comprises subtle details of user interactions with the user interface, wherein the user interactions comprise at least a pressure applied by a user during touching contact with the dispersive signal touch screen.);
prioritize the user interaction data as a function of a user interaction data extraction template generated by the computing device (Claim 1 of Mahmud ‘943. In the instant application, the broadest reasonable interpretation of “prioritize the user interaction data as a function of a user interaction data extraction template generated by the computing device” reads on the limitation in Mahmud ‘943 (Claim 1) of prioritizing the user interaction data as a function of a user interaction data extraction template generated by the computing device.);
receive server feedback data through a communication module wherein the server feedback data comprises at least an update to a recovery program and data validation (Claim 1 of Mahmud ‘943. In the instant application, the broadest reasonable interpretation of “receive server feedback data through a communication module wherein the server feedback data comprises at least an update to a recovery program and data validation” reads on the limitation in Mahmud ‘943 (Claim 1) of receiving server feedback data through a communication module wherein the server feedback data comprises at least an update to a recovery program and data validation etc.);
determine a current user interface state comprising a current osteoporosis state as a function of the captured user interaction data and the server feedback data (Claim 1 of Mahmud ‘943. In the instant application, the broadest reasonable interpretation of “determine a current user interface state … as a function of the captured user interaction data and the server feedback data” reads on the limitation in Mahmud ‘943 (Claim 1) of determining a current user interface state as a function of the captured user interaction data and the server feedback data.);
select an optimal user interface state as a function of the prioritized user interaction data and the current user interface state (Claim 1 of Mahmud ‘943. In the instant application, the broadest reasonable interpretation of “select an optimal user interface state as a function of the prioritized user interaction data and the current user interface state” reads on the limitation in Mahmud ‘943 (Claim 1) of selecting an optimal user interface state as a function of the prioritized user interaction data and the current user interface state.), wherein the selecting comprises:
receiving training data, wherein the training data correlates the user interaction data and the server feedback data to states of the user interfaces (Claim 1 of Mahmud ‘943. In the instant application, the broadest reasonable interpretation of “receiving training data, wherein the training data correlates the user interaction data and the server feedback data to states of the user interfaces” reads on the limitation in Mahmud ‘943 (Claim 1) of receiving training data, wherein the training data correlates the user interaction data and the server feedback data to states of user interfaces.);
training a user interface adaptation machine-learning model as a function of the training data (Claim 1 of Mahmud ‘943. In the instant application, the broadest reasonable interpretation of “training a user interface adaptation machine-learning model as a function of the training data” reads on the limitation in Mahmud ‘943 (Claim 1) of training a user interface adaptation machine-learning model as a function of the training data.); and
selecting the optimal user interface state as the function of the prioritized user interaction data and the server feedback data, wherein the optimal user interface state includes at least an optimal event action (Claim 1 of Mahmud ‘943. In the instant application, the broadest reasonable interpretation of “selecting the optimal user interface state as the function of the prioritized user interaction data and the server feedback data, wherein the optimal user interface state includes at least an optimal event action” reads on the limitation in Mahmud ‘943 (Claim 1) of selecting the optimal user interface state as the function of the prioritized user interaction data and the server feedback data, wherein the optimal user interface state includes at least an optimal event action.); and
generate, as a function of the selected optimal user interface state, the captured user interaction data, and the current user interface state, an updated display data structure for the remote device (Claim 1 of Mahmud ‘943. In the instant application, the broadest reasonable interpretation of “generate, as a function of the selected optimal user interface state, the captured user interaction data, and the current user interface state, an updated display data structure for the remote device” reads on the limitation in Mahmud ‘943 (Claim 1) of generating, as a function of the selected optimal user interface state, the captured user interaction data, and the current user interface state, an updated display data structure etc.).
Claim 1 of Mahmud ‘943 does not appear to explicitly recite, but Mahmud ‘254 teaches the limitations identified in bold as “capture user interaction data comprising osseous tissue data using the first input field” (Paragraphs [0015] and [0020] of Mahmud ‘254. In the instant application, the broadest reasonable interpretation of “osseous tissue data” reads on the osseous tissue data in Mahmud ‘254 (Paragraphs [0015] and [0020]) of a user measured by an osseous measurement device and transmitted to a to computing device.).
Claim 1 of Mahmud ‘943 does not appear to explicitly disclose, but Mahmud ‘254 teaches the limitations identified in bold as “determine a current user interface state comprising a current osteoporosis state as a function of the captured user interaction data and the server feedback data” (Paragraphs [0015] and [0020] of Mahmud ‘254. In the instant application, the broadest reasonable interpretation of “a current osteoporosis state” reads on the current osteoporosis state in Mahmud ‘254 (Paragraphs [0015] and [0020]) determined as a function of osseous tissue data.).
Therefore, it would have been obvious to one of ordinary skill in the art of computer-aided diagnosis systems at the time of filing to modify the system and method of Mahmud ‘943 (Claims 1 and 11) to: implement the osseous tissue data and the current osteoporosis state, as taught by Mahmud ‘254 (Paragraphs [0015] and [0020]), in order to improve systems for monitoring osteoporosis (Paragraph [0003] of Mahmud ‘254).
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.
Examiners should determine whether a claim satisfies the criteria for subject matter eligibility by evaluating the claim in accordance with the flowchart in MPEP 2016(III).
Eligibility Step 1:
Under Step 1 of the 2019 Revised Patent Subject Matter Eligibility Guidance, it must be determined whether each claim as a whole falls within one of the statutory categories of invention (i.e., a process, machine, manufacture, or composition of matter). See MPEP 2106.03. In the instant application, claims 1 – 10 are directed to a system of dynamic user interface generation (i.e., a machine), and claims 11 – 20 are directed to a method of dynamic user interface generation (i.e., a process).
While each one of claims 1 – 20 appears to fall within one or more statutory categories of invention, the Office has determined that the full eligibility analysis is required because there is doubt as to whether the applicant is effectively seeking coverage for a judicial exception itself. The eligibility of each claim is not self-evident at least because each claim as a whole did not appear to clearly improve a technology or computer functionality. To the contrary, each claim as a whole appeared to merely apply one or more judicial exceptions on a computer.
Accordingly, it has been determined that each one of claims 1 – 20 as a whole falls within one or more statutory categories under Step 1, and the Office proceeds with the full eligibility analysis (the Alice/Mayo test described in MPEP 2106(III)) as discussed below.
Eligibility Step 2A, Prong One:
Under Step 2A, Prong One of the 2019 Revised Patent Subject Matter Eligibility Guidance, it must be determined whether each claim is directed to one or more of the judicial exceptions (i.e., an abstract idea, law of nature, or natural phenomenon). See MPEP 2106.04(II)(A)(1). After evaluation, it has been determined that claims 1 – 20 are directed to judicial exceptions because claims 1 – 20 recite an abstract idea. (The Office will not determine that a claim is not directed to a judicial exception under Step 2A, Prong One for the mere reason that claim further recites one or more additional elements beyond the judicial exception.)
Independent claims 1 and 11 are determined to be directed to a judicial exception including abstract ideas (i.e., mental process). Representative claim 1 recites the mental process identified in bold as:
A system of dynamic user interface generation, wherein the system comprises:
a computing device, wherein the computing device is configured to:
configure, using an initial display data structure, a remote device to display a user interface having a first input field;
capture user interaction data comprising osseous tissue data using the first input field;
prioritize the user interaction data as a function of a user interaction data extraction template generated by the computing device;
receive server feedback data through a communication module wherein the server feedback data comprises at least an update to a recovery program and data validation;
determine a current user interface state comprising a current osteoporosis state as a function of the captured user interaction data and the server feedback data;
select an optimal user interface state as a function of the prioritized user interaction data and the current user interface state, wherein the selecting comprises:
receiving training data, wherein the training data correlates the user interaction data and the server feedback data to states of the user interfaces;
training a user interface adaptation machine-learning model as a function of the training data; and
selecting the optimal user interface state as the function of the prioritized user interaction data and the server feedback data, wherein the optimal user interface state includes at least an optimal event action; and
generate, as a function of the selected optimal user interface state, the captured user interaction data, and the current user interface state, an updated display data structure for the remote device.
Claim 1 recites the combination of limitations identified as “capture user interaction data comprising osseous tissue data,” “prioritize the user interaction data,” “determine a current user interface state comprising a current osteoporosis state as a function of the captured user interaction data and the server feedback data,” “select an optimal user interface state as a function of the prioritized user interaction data and the current user interface state,” and “wherein the selecting comprises: … selecting the optimal user interface state as the function of the prioritized user interaction data and the server feedback data, wherein the optimal user interface state includes at least an optimal event action.” A broadest reasonable interpretation of this combination amounts to recommending an osteoporosis recovery program (e.g., an exercise regimen or nutrition plan) aimed at the predicted advancement of osteoporosis (i.e., the predicted advancement determined as a function of the osseous tissue data and the server feedback data; see Paragraphs [0018] – [0019] and [0028] of the Specification as filed). This activity may be practically performed in the human mind using observation, evaluation, judgment, and opinion, and thus represents an abstract idea falling in the “mental process” grouping.. With the exception of generic computer-implemented steps, there is nothing in each of claims 1 and 11 themselves that forecloses them from being performed by a human, mentally or with tools such as pen and paper. Thus, this activity is an abstract idea in the "mental process" grouping.
Accordingly, claims 1 and 11 are recite judicial exceptions under Step 2A, Prong One.
Dependent claims 2 – 10 and 12 – 20 are directed to one or more judicial exceptions (i.e., abstract idea exceptions) under Step 2A, Prong One of the full eligibility analysis as follows:
Regarding claims 2 – 10 and 12 – 20, each combination of limitations identified in bold as “capturing the user interaction data comprising the osseous tissue data … wherein the user interaction data comprises details of user interactions” in claims 2 and 12, “the osseous tissue data comprises a bone density of a user” in claims 3 and 13, “the optimal user interface state comprises an osteoporosis recovery program and wherein the osteoporosis recovery program includes at least a nutrition plan” in claims 4 and 14, “the optimal user interface state comprises an osteoporosis recovery program and wherein the osteoporosis recovery program includes an exercise regime configured to increase a bone density of a user” in claims 5 and 15, “determining the current user interface state comprising a current osteoporosis state as a function of the captured user interaction data and the server feedback data comprises generating a predicted advancement of osteoporosis” in claims 6 and 16, “the predicted advancement of osteoporosis comprises a probability of bone loss” in claims 7 and 17, “selecting the optimal user interface state associated as a function of the prioritized user interaction data further comprises selecting the optimal user interface state as a function of the predicted advancement of osteoporosis” in claims 8 and 18, “the at least the optimal event action … to perform the at least the optimal event action” in claims 9 and 19, and “capturing the user interaction data comprising osseous tissue data” in claims 10 and 20 defines the activity of recommending an osteoporosis recovery program (e.g., an exercise regimen or nutrition plan) based on the predicted advancement of osteoporosis. These activities may be practically performed in the human mind using observation, evaluation, judgment, and opinion, and thus represents an abstract idea falling in the “mental process” grouping.. With the exception of generic computer-implemented steps, there is nothing in each of claims 2 – 10 and 12 – 20 themselves that forecloses them from being performed by a human, mentally or with tools such as pen and paper.
Accordingly, claims 2 – 10 and 12 – 20 are recite judicial exceptions under Step 2A, Prong One.
Eligibility Step 2A, Prong Two:
Claims 1 and 11 recite additional limitations beyond the judicial exceptions. Representative claim 1 recites the additional limitations identified in bold as:
A system of dynamic user interface generation, wherein the system comprises:
a computing device, wherein the computing device is configured to:
configure, using an initial display data structure, a remote device to display a user interface having a first input field;
capture user interaction data comprising osseous tissue data using the first input field;
prioritize the user interaction data as a function of a user interaction data extraction template generated by the computing device;
receive server feedback data through a communication module wherein the server feedback data comprises at least an update to a recovery program and data validation;
determine a current user interface state comprising a current osteoporosis state as a function of the captured user interaction data and the server feedback data;
select an optimal user interface state as a function of the prioritized user interaction data and the current user interface state, wherein the selecting comprises:
receiving training data, wherein the training data correlates the user interaction data and the server feedback data to states of the user interfaces;
training a user interface adaptation machine-learning model as a function of the training data; and
selecting the optimal user interface state as the function of the prioritized user interaction data and the server feedback data, wherein the optimal user interface state includes at least an optimal event action; and
generate, as a function of the selected optimal user interface state, the captured user interaction data, and the current user interface state, an updated display data structure for the remote device.
Claim 1 recites the additional limitations identified in bold as “a system of dynamic user interface generation,” “configure, using an initial display data structure, a remote device to display a user interface having a first input field,” “using the first input field,” “generated by the computing device,” “receive server feedback data through a communication module wherein the server feedback data comprises at least an update to a recovery program and data validation,” “receiving training data, wherein the training data correlates the user interaction data and the server feedback data to states of the user interfaces,” “training a user interface adaptation machine-learning model as a function of the training data,” and “generate … an updated display data structure for the remote device.” Each of these elements is an additional limitation beyond the judicial exception (i.e., the mental process of recommending an osteoporosis recovery program, such as an exercise regimen or nutrition plan, based on a predicted advancement of osteoporosis). At best, looking at the combination of all additional elements and the judicial exception, the claim as a whole amounts to a computing device having a user interface used for necessary data gathering (i.e., necessary osseous tissue data used for predicting an individual’s advancement of osteoporosis and recommending treatment for same) and data output (i.e., the osteoporosis recovery program).
MPEP 2106.05(a) states: “In determining patent eligibility, examiners should consider whether the claim ‘purport(s) to improve the functioning of the computer itself’ or ‘any other technology or technical field.’… [A]n improvement in the abstract idea itself is not an improvement in technology.” Furthermore, MPEP 2106.05(a)(II) states: “Merely adding generic computer components to perform the method is not sufficient.” In the instant application, claim 1 as a whole does not improve the functioning of the computing device, the user interface adaptation machine-learning model, the remote computing device, the user interface, or the initial display data structure; nor does the claim as a whole improve any other technology or technical field. The computing device, the user interface adaptation machine-learning model, the remote computing device, the user interface, and the initial display data structure are general purpose computer components added post-hoc to the abstract idea of recommending an osteoporosis recovery program (e.g., an exercise regimen or nutrition plan) that prevents, treats, reduces, or reverses a predicted advancement of osteoporosis. In fact, the Specification as filed (Paragraph [0028]) admitted that the process of generating the osteosis recovery program as a function of the predicted advancement of osteoporosis was described in “US Nonprovisional Application Ser. No. 17/477,730, filed on September 17, 2021 and entitled ‘METHODS AND SYSTEMS FOR PREVENTING AND REVERSING OSTEOPOROSIS’” (U.S. Pub. No. 2022/0093254 A1 by Mahmud). The claim as a whole improves exclusively upon the abstract idea itself by using conventional and generic computer technology in the nascent but well known environment of artificial intelligence to automate the manual process of recommending an osteoporosis recovery program (e.g., an exercise regimen or nutrition plan) aimed at a predicted advancement of osteoporosis. See MPEP 2106.05(a). The claim as a whole represents mere instructions to apply the abstract idea to conventional and generic computer technology recited at a high level of generality. See MPEP 2106.05(f). Regarding the consideration under MPEP 2106.05(g), the limitations of “configure, using an initial display data structure, a remote device to display a user interface having a first input field,” “capture user interaction data comprising osseous tissue data using the first input field,” “a user interaction data extraction template generated by the computing device,” and “receive server feedback data through a communication module wherein the server feedback data comprises at least an update to a recovery program and data validation” are determined to not add no more than insignificant extra-solution activities to the judicial exception. These limitations represent the well-known pre-solution activity of necessary data gathering because the claim as a whole represents an activity incidental to the primary process of the claim as a whole (i.e., recommending an osteoporosis recovery program for a predicted advancement of osteoporosis) and thus those limitations are merely nominal or tangential additions to the claim. Regarding the consideration under MPEP 2106.05(h), the additional limitations, individually or in combination, also amount to merely indicating a field of use or technological environment in which to apply the judicial exception. In the instant application, the additional limitations (i.e., the computing device, the user interface adaptation machine-learning model, the remote computing device, the user interface, or the initial display data structure) do no more than link the abstract idea (i.e., recommending an osteoporosis recovery program) to the particular technological environment of artificial intelligence. Thus, the additional limitations fail to add an inventive concept to the claims.
Accordingly, in view of these considerations, the Office has determined that each one of claims 1 and 11 as a whole does not integrate the abstract idea exception into a practical application under Step 2A, Prong Two, and thus each claim as a whole is directed to a judicial exception under Step 2A.
Dependent claims 2 – 10 and 12 – 20 present additional information in tandem with further details regarding elements and the abstract idea from an associated one of independent claims 1 and 11 and are therefore directed to an abstract idea for similar reasons as given Under Step 2A, Prong One above. Claims 3 – 8 and 13 – 18 do not recite any additional limitations beyond the abstract idea of recommending an osteoporosis recovery program as a function of an individual’s predicted advancement of osteoporosis. Claims 2, 9 – 10, 12, and 19 – 20 further recite additional limitations, and these additional limitations fail to integrate the abstract idea into a practical application under Step 2A, Prong Two as follows:
Claims 2, 9 – 10, 12, and 19 – 20 recite the additional limitations identified in bold as “capturing the user interaction data comprising the osseous tissue data using the first input field comprises capturing the user interaction data using the first input field and from an engagement module comprising a dispersive signal touch screen communicatively connected to the user interface” in claims 2 and 12, “the updated display data structure includes at least a second input field associated with the at least the optimal event action and the updated display data structure configures the remote device to display the at least the second input field and to perform the at least the optimal event action upon activation of the at least the second input field” in claims 9 and 19, and “capturing the user interaction data comprising osseous tissue data using the first input field comprises receiving the user interaction data using a measurement device” in claims 10 and 20. Regarding the consideration under MPEP 2106.05(g), the Office has determined that each one of claims 2, 9 – 10, 12, and 19 – 20 as a whole fails to add more than insignificant extra-solution activities to the judicial exception. Each one of claims 2, 10, 12, and 20 as a whole represents the well-known pre-solution activity of necessary data gathering because each claim as a whole is incidental to the primary process of recommending an osteoporosis recovery program for a predicted advancement of osteoporosis. The broadest reasonable interpretation of each one of claims 9 and 19 as a whole reads on using the second input field of the user interface to either display one or more steps of the recommended osteoporosis recovery program (i.e., data outputting under MPEP 2106.05(g)) or record performance of one or more steps of the recommended osteoporosis recovery program (See MPEP 2106.05(g) explaining that storing data to a process computing the area of space does not add meaningful limitation to the process of computing the area under). Regarding the consideration under MPEP 2106.05(h), the additional limitations, individually or in combination, also amount to merely indicating a field of use or technological environment in which to apply the judicial exception (i.e., artificial intelligence). Thus, the additional limitations fail to add an inventive concept to the claims.
Accordingly, in view of these considerations, the Office has determined that each one of claims 2 – 10 and 12 – 20 as a whole does not integrate the abstract idea exception into a practical application under Step 2A, Prong Two, and thus each claim as a whole is directed to a judicial exception under Step 2A.
Eligibility Step 2B:
Regarding independent claims 1 and 11, the Office carries over its identification of the additional elements (and combinations thereof) from Step 2A, Prong Two so as to apply the same additional elements in Step 2B. See MPEP 2106.05(II). The Office further carries over its conclusions from the considerations discussed in MPEP 2106.05(a) through (c), (e) through (h) in Step 2A, Prong Two so as to apply the same considerations in Step 2B.
Under Step 2B of the 2019 Revised Patent Subject Matter Eligibility Guidance, it must be determined whether the claim provides an inventive concept by determining if the claims include additional elements or a combination of elements that are sufficient to amount to significantly more than the judicial exception. After evaluation, there is no indication that an additional element or combination of elements are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, each claim as a whole does not provide an improvement to technology or technical field under MPEP 2106.05(a). The additional limitations amount to mere instructions to apply an abstract idea under MPEP 2106.05(f) and/or necessary data gathering under MPEP 2106.05(g). Each claim as a whole recites the computing device, the user interface adaptation machine-learning model, the remote computing device, the user interface, and the initial display data structure at a high level of generality, with their functions claimed in a merely generic manner such that each claim as a whole represents the well‐understood, routine, and conventional functions of receiving and transmitting data over a network to gather data. Evidence that receiving or transmitting data over a network to gather data is a well‐understood, routine, and conventional function is provided by MPEP 2106.05(d), subsection II. Evidence that using the computing device, the user interface adaptation machine-learning model, the remote computing device, the user interface, and the initial display data structure to recommend an osteoporosis recovery program is well-understood, routine, and conventional is provided by Mahmud ‘254 (U.S. Pub. No. 2022/0093254 A1).
Furthermore, looking at the limitations individually or as any ordered combination adds nothing that is not already present when looking at each claim as a whole. There is no indication that the individual elements or combinations of elements amount to an inventive concept.
Therefore, claims 1 and 11 are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Regarding claims 2 – 10 and 12 – 20, the Office carries over its determination from Step 2A, Prong Two that claims 2, 9 – 10, 12, and 19 – 20 further recite additional limitations and claims 3 – 8 and 13 – 18 do not recite additional elements so as to apply the same determination in Step 2B. See MPEP 2106.05(II). The Office further carries over its conclusions from the considerations discussed in MPEP 2106.05(a) through (c), (e) through (h) in Step 2A, Prong Two so as to apply the same considerations in Step 2B. The dependent claims merely present additional abstract information in tandem with further details regarding the elements from the independent claims and are, therefore, directed to an abstract idea for similar reasons as given above. Claims 3 – 8 and 13 – 18 do not recite any additional limitations beyond the abstract idea of recommending an osteoporosis recovery program as a function of an individual’s predicted advancement of osteoporosis. Claims 2, 9 – 10, 12, and 19 – 20 further recite additional limitations, and these additional limitations do not amount to significantly more than the judicial exception under Step 2B as follows:
Each claim as a whole does not provide an improvement to technology or technical field under MPEP 2106.05(a), but rather only improves the abstract idea itself. Each claim as a whole amounts to mere instructions to apply the abstract idea to the engagement module and the dispersive signal touch screen in claims 2 and 12, the second input field (i.e., of the user interface) and the remote device in claims 9 and 19, and the measurement device in claim 10 and 20 under MPEP 2106.05(f) and/or necessary data gathering under MPEP 2106.05(g). The engagement module and the dispersive signal touch screen in claims 2 and 12, the second input field (i.e., of the user interface) and the remote device in claims 9 and 19, and the measurement device in claim 10 and 20 are recited at a high level of generality, with their functions claimed in a merely generic manner such that each claim as a whole represents the well‐understood, routine, and conventional functions of receiving and transmitting data over a network to gather data. Evidence that receiving or transmitting data over a network to gather data is a well‐understood, routine, and conventional function is provided by MPEP 2106.05(d), subsection II. With further regard to claims 2 and 12, evidence that using the engagement module and the dispersive signal touch screen to capture user interaction data is well-understood, routine, and conventional is provided by Teller (U.S. Pub. No. 2015/0234518 A1). Regarding claims 9 and 19, evidence that using the second input field (i.e., of the user interface) and the remote device to perform the optimal event action is well-understood, routine, and conventional is provided by Mahmud ‘254 (U.S. Pub. No. 2022/0093254 A1). Regarding claims 10 and 20, evidence that using the measurement device for necessary data gathering is well-understood, routine, and conventional is provided by Mahmud ‘254 and Almecija (U.S. Pub. No. 2018/0365025 A1).
Therefore, claims 2 – 10 and 12 – 20 are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
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.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
Determining the scope and contents of the prior art.
Ascertaining the differences between the prior art and the claims at issue.
Resolving the level of ordinary skill in the pertinent art.
Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1, 3 – 11, and 13 – 20 are rejected under 35 U.S.C. 103(a) as being unpatentable over Mahmud ‘254 (U.S. Pub. No. 2022/0093254 A1) in view of Sjöstrand (U.S. Pat. No. 11,544,407 B1) and .
Regarding independent claims 1 and 11, Mahmud ‘254 teaches the limitations of representative claim 1 identified in bold as:
A system of dynamic user interface generation (Abstract and Paragraphs [0005] and [0017] of Mahmud ‘254. In the instant application, the broadest reasonable interpretation of “system of dynamic user interface generation” reads on the system in Mahmud ‘254 (Abstract and Paragraph [0005] and [0017]) for osteoporosis monitoring and including the computing device configured to display and update an osteoporosis recovery program and the remote computing device having an interactive graphical user interface.), wherein the system comprises:
a computing device, wherein the computing device is configured to (Paragraph [0017] of Mahmud ‘254. In the instant application, the broadest reasonable interpretation of “a computing device” reads on the computing device in Mahmud ‘254 (Paragraph [0017]).):
configure, using an initial display data structure, a remote device to display a user interface having a first input field (Paragraphs [0004] – [0005], [0015] – [0016], and [0040] of Mahmud ‘254. In the instant application, the broadest reasonable interpretation of “configure, using an initial display data structure, a remote device to display a user interface having a first input field” reads on the remote computing device in Mahmud ‘254 (Paragraphs [0004] – [0005], [0015] – [0016], and [0040]) having an interactive graphical user interface (GUI) configured to obtain user input (e.g., the user’s physiological data) and display the osteoporosis recovery program, the predicted advancement of osteoporosis, the osseous tissue data, the current osteoporosis state, and/or other data pertaining to user. The Office has determined that it was well known in the art of computer-aided diagnosis systems at the time of filing that GUIs have underlying data structures to organize, manage, present, and receive information. The Office has further determined that one of ordinary skill in the art will understand that the GUI of Mahmud ‘254 (Paragraphs [0004] – [0005] , [0015] – [0016], and [0040]) uses a data structure to manage one or more input fields, i.e., the first input field.);
capture user interaction data comprising osseous tissue data using the first input field (Paragraphs [0004] – [0005], [0015] – [0016], [0019] – [0020], and [0040] of Mahmud ‘254. In the instant application, the broadest reasonable interpretation of “capture user interaction data comprising osseous tissue data” reads on the activities in Mahmud ‘254 (Paragraphs [0015] – [0016], [0019] – [0020], and [0040]) of obtaining, by using the measurement device, the user’s physiological data (i.e., the user’s osseous tissue data including the user’s bone mineral density, bone mobility, bone weight, bone strength, bone thickness, bone fragility, bone brittleness, and the like) and transmitting the osseous tissue data to the computing device.);
prioritize the user interaction data as a function of a user interaction data extraction template generated by the computing device (Paragraph [0041] of Mahmud ‘254. In the instant application, the broadest reasonable interpretation of “as a function of a user interaction data extraction template generated by the computing device” reads on the activity in Mahmud ‘254 (Paragraph [0041]) of guiding the collection of osseous tissue data as a function of the osseous tissue data extraction template generated by the computing device.);
receive server feedback data through a communication module wherein the server feedback data comprises at least an update to a recovery program and data validation (Paragraphs [0031] – [0036], [0041], [0073], and [0078] and FIG. 6 of Mahmud ‘254. In the instant application, the broadest reasonable interpretation of “a communication module” reads on the network interface device of the computing device in Mahmud ‘254 (Paragraphs [0073] and [0078] and FIG. 6) for connecting the computing device to one or more of a variety of networks, such as a local area network (e.g., WiFi) and providing a direct connection between two computing devices (e.g., Bluetooth). The broadest reasonable interpretation of “receive server feedback data … wherein the server feedback data comprises at least an update to a recovery program and data validation” reads on the activity in Mahmud ‘254 (Paragraphs [0031] – [0036] and [0041]) of receiving the one or more limitations and/or preferences, wherein the limitations and/or preferences are used to adjust the classifiers and/or machine learning models to output the adjusted osteoporosis recovery program.);
determine a current user interface state comprising a current osteoporosis state as a function of the captured user interaction data and the server feedback data (Paragraphs [0015] – [0016], [0022], [0036], and [0040] of Mahmud ‘254. In the instant application, the broadest reasonable interpretation of “determine a current user interface state comprising a current osteoporosis state as a function of the captured user interaction data and the server feedback data” reads on the activity in Mahmud ‘254 (Paragraphs [0015] – [0016] and [0036]) of determining the current osteoporosis state as a function of osseous tissue data and adjusting/recalibrating the machine learning models (i.e., the server feedback data) to output an adjusted osteoporosis recovery program. The interactive GUI in Mahmud ‘254 (Paragraphs [0015] – [0016], [0022], and [0040]) is configured to display the current osteoporosis state and the predicted advancement of osteoporosis (i.e., the current user interface state comprising the current osteoporosis state.);
select an optimal user interface state as a function of the prioritized user interaction data and the current user interface state (Paragraphs [0015] – [0016], [0030] – [0031], and [0040] of Mahmud ‘254. In the instant application, the broadest reasonable interpretation of “select an optimal user interface state as a function of the prioritized user interaction data and the current user interface state” reads on the activity in Mahmud ‘254 (Paragraphs [0030] – [0031]) of selecting a recovery program (i.e., the optimal user interface state) from a plurality of available recovery programs and further reads on the GUI in Mahmud ‘254 (Paragraphs [0015] – [0016], and [0040]) configured to display the osteoporosis recovery program (i.e., the optimal user interface state) as a function of the osseous tissue data (i.e., the prioritized user interaction data) and the current osteoporosis state and the predicted advancement of osteoporosis (i.e., the current user interface state comprising the current osteoporosis state).), wherein the selecting comprises:
receiving training data, wherein the training data correlates the user interaction data and the server feedback data to states of the user interfaces (Paragraphs [0015] – [0016], [0020], [0022], and [0049] of Mahmud ‘254. In the instant application, the broadest reasonable interpretation of “receiving training data, wherein the training data correlates the user interaction data and the server feedback data to states of the user interfaces” reads on the activities in Mahmud ‘254 (Paragraphs [0015] – [0016], [0020], [0022], and [0049]) of receiving training data, wherein the training data may correlate states of osteoporosis and/or osseous tissue data (i.e., the user interaction data) to predicted advancements of osteoporosis (i.e., the server feedback data).);
training a user interface adaptation machine-learning model as a function of the training data (Paragraph [0022] of Mahmud ‘254. In the instant application, the broadest reasonable interpretation of “training a user interface adaptation machine-learning model as a function of the training data” reads on the activity in Mahmud ‘254 (Paragraph [0022]) of training the osteoporosis advancement machine learning model on one or more sets of training data.); and
selecting the optimal user interface state as the function of the prioritized user interaction data and the server feedback data, wherein the optimal user interface state includes at least an optimal event action (Paragraphs [0015] – [0016], [0019] – [0020], [0024], [0030] – [0032], [0036] – [0037], and [0040] – [0041] of Mahmud ‘254. In the instant application, the broadest reasonable interpretation of “selecting the optimal user interface state as the function of the prioritized user interaction data and the server feedback data” reads on the activity in Mahmud ‘254 (Paragraphs [0030] – [0031]) of selecting a recovery program (i.e., the optimal user interface state) from a plurality of available recovery programs and further reads on the interactive GUI in Mahmud ‘254 (Paragraphs [0015] – [0016], [0036] – [0037] and [0040] – [0041]) being configured to display the osteoporosis recovery program (i.e., the optimal user interface state) as a function of osseous tissue data (i.e., the prioritized user interaction data comprising osseous tissue data), with the osteoporosis recovery program being adjusted by the classifiers and/or machine models adjusted via the limitations and/or the preferences (i.e., the server feedback data). The broadest reasonable interpretation of “the optimal user interface state includes at least an optimal event action” reads on the osteoporosis treating exercise routine in Mahmud ‘254 (Paragraph [0031]) including specific repetitions, sets, variations, forms, and the like for a user to follow in order to treat a form of osteoporosis and further reads on the osteoporosis treating nutrition plan in Mahmud ‘254 (Paragraph [0032]) that may include a user consuming more diary.); and
generate, as a function of the selected optimal user interface state, the captured user interaction data, and the current user interface state, an updated display data structure for the remote device (Paragraphs [0004] – [0005], [0015] – [0016], [0030] – [0032], and [0040] – [0041] of Mahmud ‘254. In the instant application, the broadest reasonable interpretation of “generate, as a function of the selected optimal user interface state, the captured user interaction data, and the current user interface state, an updated display data structure for the remote device” reads on the interactive graphical user interface of the remote computing device in Mahmud ‘254 (Paragraphs [0004] – [0005], [0015], [0036] – [0037] and [0040] – [0041]) being configured to display the osteoporosis recovery program (i.e., the optimal user interface state) as a function of the osteoporosis recovery program (i.e., the optimal user interface state), the osseous tissue data (i.e., the captured user interaction data comprising the osseous tissue data), and the adjusted machine models (i.e., the server feedback data) for adjusting the osteoporosis recovery program. The Office has determined that it was well known in the art of computer-aided diagnosis systems at the time of filing that GUIs have underlying data structures to organize, manage, present, and receive information. The Office has further determined that one of ordinary skill in the art will understand that the GUI of Mahmud ‘254 (Paragraphs [0004] – [0005] , [0015] – [0016], and [0040]) uses a data structure (i.e., the updated display data structure) to manage and present the osteoporosis recovery program (i.e., the selected optimal user interface state), such as the nutrition plan and/or the exercise regimen.).
Mahmud ‘254 does not appear to explicitly disclose, but Sjöstrand teaches the limitation identified in bold as “capture user interaction data comprising osseous tissue data using the first input field” (Column 16, Lines 24 – 55 of Sjöstrand. The broadest reasonable interpretation of “using the first input field” reads on the activities in Sjöstrand (Column 16, Lines 24 – 55) of displaying, using a GUI, selectable graphical control elements (i.e., in order to allow a user to select, review, and upload files comprising medical images and associated metadata, e.g., a PET image and associated PET image data) and displaying, after a user selection of a selectable element, a listing of individual processed files, with each processed file represented by an icon.).
Mahmud ‘254 does not appear to explicitly disclose, but Senanayake teaches the limitation identified in bold as “prioritize the user interaction data as a function of a user interaction data extraction template generated by the computing device” (Paragraphs [0031], [0055], [0057], [0066], and [0110] of Senanayake. The broadest reasonable interpretation of “prioritize the user interaction data” reads on the activity in Senanayake (Paragraph [0057]) of considering the user’s own interaction pattern is more relevant to the current interaction context than the crowd-sourced interaction pattern, based on factors that that are more personal to the user and thus are of potentially greater significance.).
Therefore, it would have been obvious to one of ordinary skill in the art of computer-aided diagnosis systems at the time of filing to modify the system and method of Mahmud ‘254 to: implement the activity of capturing user interaction data comprising osseous tissue data using the first input field, as taught by Sjöstrand (Column 16, Lines 24 – 55), in order to improve the automated analysis of medical imaging studies and communication of those results, diagnoses, prognoses, treatment recommendations, and associated risks to a patient (Column 2, Lines 51 – 55 of Sjöstrand); and implement the activity of prioritizing the user interaction data as a function of a user interaction data extraction template generated by the computing device, as taught by Senanayake (Paragraphs [0031], [0055], [0057], [0066], and [0110]), in order to continuously improve its understanding of the current interaction context of the computing device and thereby predict next interactions more intelligently (Paragraph [0032] of Senanayake).
Regarding claims 3 and 13, Mahmud ‘254 as modified by Sjöstrand and Senanayake and applied to an associated one of claims 1 and 12 teaches the limitations of representative claim 3 identified in bold as “the osseous tissue data comprising a bone density of a user” (Paragraphs [0019] – [0020] of Mahmud ‘254. In the instant application, the broadest reasonable interpretation of “the osseous tissue data comprising a bone density of a user” reads on the user’s osseous tissue data in Mahmud ‘254 (Paragraphs [0019] – [0020]) including the user’s bone density.).
Regarding claims 4 and 14, Mahmud ‘254 as modified by Sjöstrand and Senanayake and applied to an associated one of claims 1 and 11 teaches the limitations of representative claim 4 identified in bold as “the optimal user interface state comprising an osteoporosis recovery program and wherein the osteoporosis recovery program includes at least a nutrition plan” (Paragraphs [0015] – [0016], [0032], and [0065] of Mahmud ‘254. In the instant application, the broadest reasonable interpretation of “the optimal user interface state comprising an osteoporosis recovery program and wherein the osteoporosis recovery program includes at least a nutrition plan” reads on the osteoporosis recovery program in Mahmud ‘254 (Paragraphs [0015] – [0016], [0032], and [0065]) displayed on the interactive graphical user interface of the remote computing device and including a diet regime and nutrient consumption.).
Regarding claims 5 and 15, Mahmud ‘254 as modified by Sjöstrand and Senanayake and applied to an associated one of claims 1 and 11 teaches the limitations of representative claim 5 identified in bold as “the optimal user interface state comprising an osteoporosis recovery program and wherein the osteoporosis recovery program includes an exercise regime configured to increase a bone density of a user” (Paragraphs [0015] – [0016], [0032], and [0065] of Mahmud ‘254. In the instant application, the broadest reasonable interpretation of “the optimal user interface state comprising an osteoporosis recovery program and wherein the osteoporosis recovery program includes an exercise regime configured to increase a bone density of a use” reads on the osteoporosis recovery program in Mahmud ‘254 (Paragraphs [0015] – [0016], [0030], and [0065]) displayed on the interactive graphical user interface of the remote computing device and including an exercise regimen, such as a weigh-lifting exercise that may increase a bone density of user.).
Regarding claims 6 and 16, Mahmud ‘254 as modified by Sjöstrand and Senanayake and applied to an associated one of claims 1 and 11 teaches the limitations of representative claim 6 identified in bold as “determining the current user interface state comprising a current osteoporosis state as a function of the captured user interaction data and the server feedback data comprises generating a predicted advancement of osteoporosis” (Paragraphs [0022] and [0036] of Mahmud ‘254. In the instant application, the broadest reasonable interpretation of “determining the current user interface state comprising a current osteoporosis state as a function of the captured user interaction data and the server feedback data comprises generating a predicted advancement of osteoporosis” reads on the activities in Mahmud ‘254 (Paragraph [0022] and [0036]) of using the adjusted classifiers and/or machine learning models and inputting osseous tissue data and the current osteoporosis state into the prediction engine and outputting the predicted advancement of osteoporosis from the prediction engine.).
Regarding claims 7 and 17, Mahmud ‘254 as modified by Sjöstrand and Senanayake and applied to an associated one of claims 6 and 16 teaches the limitations of representative claim 7 identified in bold as “the predicted advancement of osteoporosis comprises a probability of bone loss” (Paragraph [0024] of Mahmud ‘254. In the instant application, the broadest reasonable interpretation of “the predicted advancement of osteoporosis comprises a probability of bone loss” reads on the predicted advancement of osteoporosis in Mahmud ‘254 (Paragraph [0024]) including a probability of bone loss.).
Regarding claims 8 and 18, Mahmud ‘254 as modified by Sjöstrand and Senanayake and applied to an associated one of claims 6 and 16 teaches the limitations of representative claim 8 identified in bold as “selecting the optimal user interface state associated as a function of the prioritized user interaction data further comprises selecting the optimal user interface state as a function of the predicted advancement of osteoporosis” (Paragraphs [0004] – [0005], [0015] – [0016], [0019] – [0020], [0024], [0030] – [0031], [0036] – [0037], and [0040] – [0041] of Mahmud ‘254. In the instant application, the broadest reasonable interpretation of “selecting the optimal user interface state associated as a function of the prioritized user interaction data further comprises selecting the optimal user interface state as a function of the predicted advancement of osteoporosis” reads on the activity in Mahmud ‘254 (Paragraph [0030] – [0031]) of selecting a recovery program from a plurality of available recovery programs and further reads on the interactive graphical user interface of the remote computing device in Mahmud ‘254 (Paragraphs [0004] – [0005], [0015] – [0016], and [0040] – [0041]) being configured to display the osteoporosis recovery program (i.e., the optimal user interface state) as a function of a predicted advancement of a stage of osteoporosis of a user (i.e., the current user interface state comprising the current osteoporosis state of the user), osseous tissue data (i.e., the prioritized user interaction data comprising osseous tissue data, such as the bone density measured by the measurement device), and the current osteoporosis state of the user.).
Regarding claims 9 and 19, Mahmud ‘254 as modified by Sjöstrand and Senanayake and applied to an associated one of claims 1 and 11 teaches the limitations of representative claim 9 identified in bold as “the updated display data structure includes at least a second input field associated with the at least the optimal event action and the updated display data structure configures the remote device to display the at least the second input field and to perform the at least the optimal event action upon activation of the at least the second input field” (Paragraphs [0004] – [0005], [0015] – [0016], [0030] – [0032], [0040], and [0066] of Mahmud ‘254. In the instant application, the broadest reasonable interpretation of “generate, as a function of the selected optimal user interface state, the captured user interaction data, and the current user interface state, an updated display data structure for the remote device” reads on the interactive graphical user interface of the remote computing device in Mahmud ‘254 (Paragraphs [0004] – [0005], [0015], [0036] – [0037] and [0040] – [0041]) being configured to display one or more steps of the osteoporosis recovery program (e.g., exercise, nutrient consumption, etc.) and record completion of those steps.).
Regarding claims 10 and 20, Mahmud ‘254 as modified by Sjöstrand and Senanayake and applied to an associated one of claims 1 and 11 teaches the limitations of representative claim 10 identified in bold as “capturing the user interaction data comprising osseous tissue data using the first input field comprises receiving the user interaction data using a measurement device” (Paragraphs [0004] – [0005], [0015] – [0016], [0019] – [0020] and [0040] – [0041] of Mahmud ‘254. In the instant application, the broadest reasonable interpretation of “capturing the user interaction data comprising osseous tissue data using the first input field comprises receiving the user interaction data using a measurement device” reads on the activities in Mahmud ‘254 (Paragraphs [0004] – [0005], [0015] – [0016], [0019] – [0020] and [0040] – [0041]) of measuring, using the measurement device, physiological data (i.e., osseous tissue data) and inputting that data into the interactive graphical user interface of the remote device.).
Claims 2 and 12 are rejected under 35 U.S.C. 103(a) as being unpatentable over Mahmud ‘254 as modified by Sjöstrand and Senanayake and applied to an associated one of claim 1 and 11, and further in view of Teller (U.S. Pub. No. 2015/0234518 A1).
Regarding claims 2 and 12, Mahmud ‘254 as modified by Sjöstrand and Senanayake and applied to an associated one of claims 1 and 11 does not appear to explicitly disclose, but Teller teaches the limitations of representative claim 2 identified in bold as “capturing the user interaction data comprising the osseous tissue data using the first input field comprises capturing the user interaction data using the first input field and from an engagement module comprising a dispersive signal touch screen communicatively connected to the user interface, wherein the user interaction data comprises details of user interactions with the user interface” (Paragraphs [0004] – [0005], [0015] – [0016], [0019] – [0020], and [0040] of Mahmud ‘254; and Paragraphs [0125] and [0135] of Teller. In the instant application, the broadest reasonable interpretation of “capture user interaction data comprising osseous tissue data” reads on the activities in Mahmud ‘254 (Paragraphs [0015] – [0016], [0019] – [0020], and [0040]) of obtaining, by using the measurement device, the user’s physiological data (i.e., the user’s osseous tissue data including the user’s bone mineral density, bone mobility, bone weight, bone strength, bone thickness, bone fragility, bone brittleness, and the like) and transmitting the osseous tissue data to the computing device. In the instant application, the broadest reasonable interpretation of “an engagement module comprising a dispersive signal touch screen communicatively connected to the user interface, wherein the user interaction data comprises details of user interactions with the user interface” reads on the touch-based interface in Teller (Paragraphs [0125] and [0135]) implementing dispersive-signal touch (DST) technology and enabling a user to interact with the interface by varying the pressure that the user applies to the interface.).
Therefore, it would have been obvious to one of ordinary skill in the art of computer-aided diagnosis systems at the time of filing to modify the system and method of Mahmud ‘254 as modified by Sjöstrand and Senanayake to implement the activity of capturing the user interaction data comprising the osseous tissue data using the first input field comprises capturing the user interaction data using the first input field and from an engagement module comprising a dispersive signal touch screen communicatively connected to the user interface, wherein the user interaction data comprises details of user interactions with the user interface, as taught by Teller (Paragraphs [0125] and [0135]), in order to improve the convenience, efficiency, and intuitiveness of the manner in which users interact with the computing system (Paragraph [0006] of Teller).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure and all the references on PTO-892 Notice of Reference Cited should be duly noted by the Applicant as they can be subsequently used during prosecution, at least note the following:
U.S. Pub. No. 2018/0365025 A1 by Almecija; see Abstract: “Methods and system for adapting user interfaces are proposed. According to certain embodiments, a user experience level is determined based on usage of a software application and other detected factors. Based on the user experience level, at least in part, a user interface is adapted to provide an improved experience for the user of the adaptive user interface.”
U.S. Pub. No. 2020/0134388 A1 by Rohde; see Abstract: “Techniques are disclosed relating to refining, based on user feedback, one or more machine learning engines for automatically generating component-based user interfaces. In various embodiments, a computer system stores template information that defines a plurality of component types and one or more display parameters identified for one or more user interfaces. The computer system may receive a request to generate a user interface, where the request specifies a data set to be displayed. Further, the computer system may automatically generate a user interface, where the generating is performed by one or more machine learning engines that use the template information and the data set as inputs. The computer system may then provide the user interface to one or more users, receive user feedback associated with the user interface, and train at least one of the one or more machine learning engines based on the user feedback.”
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/V.C.I./Examiner, Art Unit 3686
/DEVIN C HEIN/Examiner, Art Unit 3686