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 Claims
This Office action is in response to correspondence received January 28, 2026.
Claim 1 is amended. Claims 1-4 are pending and have been examined.
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 1-4 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s)
providing disposable absorbent product selection and use support to perform a method comprising: (A) receiving, from a customer, a request for information related to at least one of a plurality of disposable absorbent products; (B) providing a response to the request for information, the step of providing comprising: (1) accessing, information pertaining to a plurality of disposable absorbent products, including the following: (i) pictures of the plurality of disposable products; (ii) description of components corresponding to each disposable absorbent product; (iii) instructions for use corresponding to each disposable absorbent product; (iv) training material corresponding to each disposable absorbent product; and (v) contact information associated with each disposable absorbent product; (2) retrieving, response data responsive to the request for information, the response data associated with the information pertaining to the plurality of disposable absorbent products contained in data stores; (3) providing, the response data to the customer; (4) determining, whether the response data is satisfactory; (5) if the response data is determined to be not satisfactory, accessing [information to] determine an appropriate clinician or other representative to provide the requested information; (6) if the response data is determined to be satisfactory, determining that the request for information is complete.
The abstract idea recited above is a mental process or, alternatively, a certain method of organizing human activity. This is because the steps describe providing information on disposable absorbent products, which one could do mentally by observing and choosing information, such as in a book or stack of how-to guides. One could also do this as managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions) see MPEP 2106.04(a). This is because what is being requested are instructions, as claimed, “instructions for use corresponding to each disposable absorbent product” and training material and other information are either further instructions or are related information that further define the abstract idea. For example, determining an appropriate clinician is teaching, where someone is being taught how to use a disposable absorbent product. Therefore, for these reasons, claim 1 recites an abstract idea that is patent ineligible.
This judicial exception is not integrated into a practical application. The additional elements are apply it instructions to use computers and ordinary computer components like a database in order to implement the abstract idea. See MPEP 2106.05(f)(1-2). The additional elements are:
A computer system for
comprising: one or more processors; and non-transitory computer-readable memory operatively connected to the one or more processors and having stored thereon machine-readable instructions that, when executed by the one or more processors, cause the one or more processors
at/by one or more computers,
one or more databases containing
These elements alone and in combination amount to generic computing components. For example, processors, memory, and instructions describe all programmed computers which is nearly all computers in existence. Databases are the most common form of relational data storage, which can be taught by a table such as a spreadsheet. Therefore, in combination this amounts to a couple of computers communicating with each other (such as over the internet) and one computer accessing a database with information (such as an excel spreadsheet). This is a generic configuration and therefore would not be a practical application of an abstract idea.
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the reasoning from the practical application step is carried over and for the same reasons that there is not a practical application, there is not significantly more than the abstract idea.
Claims 2-4 recite additional elements such as webpages, software applications, chat feature, texting feature, chatbot, that are applied elements. Rejected for the same reason as the computers and database in claim 1, they are not a practical application of the abstract idea as they are “provided” elements that are generically recited.
Therefore, claims 1-4 are rejected under 35 USC 101.
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 for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Stanley et al., US PGPUB 20210241352 A1 (“Stanley”) in view of Adibi et al., US PGPUB 20210136206 A1 (“Adibi”) further in view of Glass et al. US PGPUB 20150350444 A1 (“Glass”), further in view of Meretei, US PGPUB 20160125765 A1 (“Meretei”).
Per claim 1, Stanley teaches A computer system for providing disposable absorbent product selection and use support comprising: one or more processors in par 003: “by a disposable article recommendation computing system in data store, a plurality of disposable article sizing models that correspond to a respective plurality of pre-made disposable articles available for purchase. The method further comprises receiving, by the disposable article recommendation computing system, an image collected by at least one camera, wherein the image comprises a representation of a subject and the subject is a consumer of pre-made disposable articles.”
Stanley then teaches and non-transitory computer-readable memory operatively connected to the one or more processors and having stored thereon machine-readable instructions that, when executed by the one or more processors, cause the one or more processors to perform a method comprising: (A) receiving, at one or more computers, from a customer, a request for information related to at least one of a plurality of disposable absorbent products in par 024: “In some configurations, the systems and methods described herein can receive one or more digital images of a subject, and by way of various image processing techniques, determine physical attributes of the subject. The subject can be, for example, an infant, a baby, a toddler, or other wearer of an absorbent article. The particular physical attributes determined by the present systems and methods can vary based on implementation, but in some configurations, image analysis is performed to determine various fit parameters. Examples of fit parameters include an estimated waist circumference of the subject, an estimated thigh circumference of the subject, and an estimated rise measurement of the subject, as measured from naval to the lower back.”
Stanley then teaches (B) providing, by the one or more computers, a response to the request for information, the step of providing comprising: (1) accessing, by one or more computers, one or more databases containing information pertaining to a plurality of disposable absorbent products, including the following: in par 039: “Data used by disposable article recommendation computing system 100 can be from various sources, such as the database(s) 106, which can be electronic computer databases, for example. The data stored in the database(s) 106 can be stored in a non-volatile computer memory, such as a hard disk drive, a read only memory (e.g., a ROM IC), or other types of non-volatile memory. In some embodiments, one or more databases 106 can be stored on a remote electronic computer system, for example. As it to be appreciated, a variety of other databases, or other types of memory storage structures, can be utilized or otherwise associated with the disposable article recommendation computing system 100.” This teaches the databases of information pertaining to the plurality of disposable absorbent products.
Stanley then teaches (ii) description of components corresponding to each disposable absorbent product in par 034: “A plurality of sizing models 108 for pre-made absorbent articles can be stored within a database 106. Generally, each pre-made absorbent article can have an associated sizing model 108 that includes fit parameter ranges for that particular article. In the illustrated embodiment, for example, each sizing model 108 is a three-dimensional model that includes a range of waist circumferences, a range of thigh circumferences, and a range of rise measurements associated with a particular absorbent article.”
Further taught in in par 035: “Referring still to FIG. 1, a recommendation 120 can be provided to the user 122 via a suitable user interface 116. The user interface 116 can be any suitable device or method capable of communicating information to the user 122, such as the display screen of a computing device, a text message, an email message, an in-app message, and so forth. The scope of the recommendation 120 can vary. In some implementations, the recommendation 120 identifies a size of absorbent article that is suitable for the subject 124, shown as product size recommendation 134. In some implementations, the recommendation 120 can include additional information, such as a product type recommendation 132 and a product lineup recommendation 136. This additional information can provide recommendations regarding whether the subject 124 should wear a taped-diaper or a training pant diaper, for example.”
Stanley then teaches and (v) contact information associated with each disposable absorbent product in par 036: “The recommendation 120 can also provide purchase information, such as identifying an online or brick-and-mortar retailer selling the recommended product, and/or provide information regarding a subscription purchase program. Generally, a subscription purchase program can routinely send the user 122 batches of the recommended size of the disposable articles over time. In some cases, the size of the disposable articles provided in the batches can be automatically increased over time to account for the growth of the subject 124.” Stores where items can be purchased teach contact information because the identity of a retailer is information that one can contact the retailer and it is associated with the absorbent product.
Stanley then teaches (2) retrieving, by the one or more computers, response data from the one or more databases responsive to the request for information; the response data associated with the information pertaining to the plurality of disposable absorbent products contained in the one or more databases; in pars 039 and 034. Par 039: “Data used by disposable article recommendation computing system 100 can be from various sources, such as the database(s) 106, which can be electronic computer databases, for example. The data stored in the database(s) 106 can be stored in a non-volatile computer memory, such as a hard disk drive, a read only memory (e.g., a ROM IC), or other types of non-volatile memory. In some embodiments, one or more databases 106 can be stored on a remote electronic computer system, for example. As it to be appreciated, a variety of other databases, or other types of memory storage structures, can be utilized or otherwise associated with the disposable article recommendation computing system 100.” Par 034: “A plurality of sizing models 108 for pre-made absorbent articles can be stored within a database 106. Generally, each pre-made absorbent article can have an associated sizing model 108 that includes fit parameter ranges for that particular article. In the illustrated embodiment, for example, each sizing model 108 is a three-dimensional model that includes a range of waist circumferences, a range of thigh circumferences, and a range of rise measurements associated with a particular absorbent article. In other embodiments, the sizing models can utilize different fit parameters.” It is noted that the above information is both accessed and retrieved, where in par 039 the data is accessed from the database, “can be from various sources, such as the database(s)” and then retrieved as it is sent to the consumer’s remote computer.
Stanley then teaches (3) providing, by the one or more computers, the response data to the customer in par 035: “Referring still to FIG. 1, a recommendation 120 can be provided to the user 122 via a suitable user interface 116. The user interface 116 can be any suitable device or method capable of communicating information to the user 122, such as the display screen of a computing device, a text message, an email message, an in-app message, and so forth. The scope of the recommendation 120 can vary.” The recommendation taught by Stanley is the response data provided to the customer.
Stanley does not teach (4) determining, by the one or more computers, whether the response data is satisfactory; (5) if the response data is determined to be not satisfactory, accessing, by the one or more computers, to determine an appropriate clinician or other representative to provide the requested information; (6) if the response data is determined to be satisfactory, determining, by the one or more computers, that the request for information is complete.
Adibi teaches virtual agents that can transfer to live agents. See abstract.
Adibi teaches (4) determining, by the one or more computers, whether the response data is satisfactory in par 045: “The virtual agent engine 314 assigns the customer 110 to a virtual agent and will manage the message flows between the virtual agent and the customer. In some implementations, the virtual agent engine 314 maintains a map of queues serviced by virtual agents, tracks virtual agent sessions for recording/reporting agent events in a set of system statistics, reads site configuration values to identify which agents are virtual and which chat queues are serviced by virtual agents, and/or processes escalation rules and assigns chats requiring escalation to an appropriate live agent chat queue. The virtual agent engine 314 may associate a particular customer, organization, product, category, etc. with certain virtual agents, each having its own personality, capabilities, etc. as described below. In some implementations, the virtual agent engine 314 may apply rules to select an appropriate virtual agent. The rules may account for a product category, (e.g., smartphone, exercise equipment, etc.), customer identity (e.g., a high value customer), geographic location, time of day, etc. The rules may escalate a customer to a live agent 120. Upon an assignment of a customer 110 to a virtual agent, the virtual agent engine 314 updates a mapping between the selected virtual agent and the customer 110. The mapping may be used to route communication between the customer 110 and the selected virtual agent. If the assigned virtual agent is able to satisfy the customer's needs, the virtual agent engine 314 may update a reporting database and delete the mapping.”
Adibi then teaches (5) if the response data is determined to be not satisfactory, accessing, by the one or more computers, to determine an appropriate clinician or other representative to provide the requested information in par 045: “However, if the assigned virtual agent is unable to satisfy the customer's needs, the customer may be escalated to an agent 120 or supervisor. The escalation may include notes from the interaction such that the agent or supervisor can seamlessly attend to the customer's needs. An example implementation of such notes is provided in attorney docket number 11133-123US1, filed Oct. 30, 2019, entitled, “SYSTEM AND METHOD FOR ESCALATION USING AGENT ASSIST WITHIN A CLOUD-BASED CONTACT CENTER,” which is incorporated herein by reference in its entirety. The mapping between the customer and the virtual agent is then deleted.”
(6) if the response data is determined to be satisfactory, determining, by the one or more computers, that the request for information is complete in par 045: “The virtual agent engine 314 assigns the customer 110 to a virtual agent and will manage the message flows between the virtual agent and the customer. In some implementations, the virtual agent engine 314 maintains a map of queues serviced by virtual agents, tracks virtual agent sessions for recording/reporting agent events in a set of system statistics, reads site configuration values to identify which agents are virtual and which chat queues are serviced by virtual agents, and/or processes escalation rules and assigns chats requiring escalation to an appropriate live agent chat queue. The virtual agent engine 314 may associate a particular customer, organization, product, category, etc. with certain virtual agents, each having its own personality, capabilities, etc. as described below. In some implementations, the virtual agent engine 314 may apply rules to select an appropriate virtual agent. The rules may account for a product category, (e.g., smartphone, exercise equipment, etc.), customer identity (e.g., a high value customer), geographic location, time of day, etc. The rules may escalate a customer to a live agent 120. Upon an assignment of a customer 110 to a virtual agent, the virtual agent engine 314 updates a mapping between the selected virtual agent and the customer 110. The mapping may be used to route communication between the customer 110 and the selected virtual agent. If the assigned virtual agent is able to satisfy the customer's needs, the virtual agent engine 314 may update a reporting database and delete the mapping.”
It would have been obvious to one ordinarily skilled in the art before the effective filing date of the claimed invention to modify the absorbent product customer assistance teaching of Stanley with the customer assistance teaching of Adibi because Stanley teaches in par 072 where Stanley is receiving feedback from customers, and Adibi’s teaching enhances virtual agents to improve interactions with contact centers. Par 001. One would be motivated to modify Stanley with Adibi because in par 001 the virtual agents are personalized so that customers have a better experience. As this combination would help people to have a better experience in contacting a company, one would be motivated to combine Stanley with Adibi.
Stanley does not teach accessing, by the one or more computers, the one or more databases to determine an appropriate clinician or other representative to provide the requested information.
Glass teaches a multi channel communication system. See abstract.
Glass teaches accessing, by the one or more computers, the one or more databases to determine an appropriate clinician or other representative to provide the requested information in par 045: “In an embodiment, a context electronic device may determine an escalation action based on what action has the quickest resolution timeframe. For example, if an escalation action involves connecting a customer with an agent over a voice communication, a context electronic device may determine which agent will be available to speak with the customer the soonest. Referring to the above example, an escalation action may be to connect the customer with a sizing expert over a voice communication. The context electronic device may access a load database to determine the most lightly loaded queue serviced by a sizing expert. The context electronic device may generate a notification that includes one or more instructions for contacting the identified sizing expert.” The load database teaches accessing a database to determine an appropriate … other representative to provide requested information because one that has a lightly loaded queue is an appropriate representative.
It would have been obvious to one ordinarily skilled in the art before the effective filing date of the claimed invention to modify the recommendation of absorbent product teaching of Stanley with the access a database to determine an appropriate representative teaching of Glass because Glass teaches in par 046 that the customer can be let know that they have the agent/representative with the shortest queue. One would be motivated to modify Stanley with Glass so that people felt they were getting the best service possible. This would increase customer satisfaction and for this reason one would be motivated to modify Stanley with Glass.
Stanley does not teach (i) pictures of the plurality of … products; (iii) instructions for use corresponding to each … product; (iv) training material corresponding to each…product;
Meretei teaches training an individual on product usage in the medical field. See abstract and par 0001.
Meretei teaches (i) pictures of the plurality of … products in par 024: “For example, the representation may be one or more 2D or 3D images of the product stored on a drive (e.g., a disk drive or solid-state drive) present in the computer. In other aspects, the physical computer readable medium where the representation is stored is present in a remote server.” See also par 026: “According to certain embodiments, displaying the representation of the product includes displaying an image of the product. Images of interest include, but are not limited to, a photo, a drawing, an animation, and/or a video. When the representation is an image of the product, the image displayed may be a two-dimensional (2D) or three-dimensional (3D) image of the product. In certain aspects, the 2D or 3D image is displayed such that the individual may view the image from multiple selectable angles and/or orientations to familiarize the individual with the product and facilitate usage training.” Plurality is taught in pars 018-020 where the product includes at least one of but is not limited to, and then a plurality of products is listed. Further as the product could be composed of multiple products according to this description that, under a broadest reasonable interpretation, teaches pictures of the plurality of products. See also par 013: “It must be noted that as used herein and in the appended claims, the singular forms “a”, “an”, and “the” include plural referents unless the context clearly dictates otherwise. Thus, for example, reference to “an electrode” includes a plurality of such electrodes and reference to “the signal” includes reference to one or more signals, and so forth.”
Meretei then teaches iii) instructions for use corresponding to each … product in par 029: “For example, when the product is a medical device, methods of the present disclosure may include presenting to the individual information relating to the medical device, including but not limited to, technical information (e.g., information relating to properties (e.g., construction material, performance features, test data, etc.) of the medical device or components/regions thereof and/or alternative medical devices (e.g., marketed a competitor)); ordering information (e.g., enabling the individual to place an order for the medical device), instructions for using the medical device,”
Meretei then teaches (iv) training material corresponding to each…product in par 031: “the methods of the present disclosure may be methods of training an individual on usage of a medical device. In certain aspects, the methods employ an augmented reality technology that includes the following components: a unique code or trigger placed on the packaging of a medical device and/or the medical device itself, allowing the identification of the particular medical device by brand, product code number, and/or the like; and a software package installed on a mobile computing device, such as a tablet computer, smartphone, or laptop computer, that has a touch-sensitive screen and a camera. The software package may include one or more modules including, but not limited to: a module to recognize the code or trigger attached to the medical device packaging; a training module with multiple functions that provide interactive information on the medical device; a reporting module that tracks the use of the training module, and analyzes usage to identify possible improvement opportunities in the training module's content, organization and overall functionality; and/or an ordering module that allows the trainee to place and order for the same or another product.”
It would have been obvious to one ordinarily skilled in the art before the effective filing date of the claimed invention to modify the disposable absorbent product information teaching of Stanley with the medical device pictures, instructions, and training teaching of Meretei because Meretei teaches an improvement on earlier training methods such as “textbooks, manuals, lectures, and videotapes.” See par 002. Better training avoids dangers presented by medical devices, or dangers from errors in use, see par 011. As this would make using medical products safer, one would be motivated to modify Stanley with Meretei.
Per claim 2, Stanley, Adibi, Glass, and Meretei teach the limitations of claim 1, above. Stanley further teaches wherein the steps (A) and/or (B) of receiving and/or providing comprises providing, by the one or more computers, a webpage or a software application in par 043: “An alternative embodiment of a disposable article recommendation computing system 200 is illustrated in FIG. 2 and can be similar to, or the same in many respects as, the disposable article recommendation computing system 100 illustrated in FIGS. 1. For example, the disposable article recommendation computing system 200 can include a memory unit 202, processor 204, and a database 206 for storing sizing models 208. The disposable article recommendation computing system 100 can comprise various software programs such as system programs and applications to provide computing capabilities in accordance with the described embodiments. System programs can include, without limitation, an operating system (OS), device drivers, programming tools, utility programs, software libraries, application programming interfaces (APIs), and so forth. Exemplary operating systems can include local operating systems as well as utilize cloud-based computing services, such as MICROSOFT AZURE SERVER, AMAZON WEB SERVICES (AWS), ALIBABA CLOUD, among others.”
Per claim 3, Stanley, Adibi, Glass, Meretei teach the limitations of claim 1, above. Stanley does not teach wherein the steps (A) and/or (B) of receiving and/or providing comprises providing, by the one or more computers, a website chat feature.
Adibi teaches wherein the steps (A) and/or (B) of receiving and/or providing comprises providing, by the one or more computers, a website chat feature in par 024: “Customers 110 may initiate inbound communications (e.g., telephony calls, emails, chats, video chats, social media posts, etc.) to the contact center 150 via an end user device. End user devices may be a communication device, such as, a telephone, wireless phone, smart phone, personal computer, electronic tablet, etc., to name some non-limiting examples. Customers 110 operating the end user devices may initiate, manage, and respond to telephone calls, emails, chats, text messaging, web-browsing sessions, and other multi-media transactions.” See also pars 028-029: “web chat…web RTC.”
It would have been obvious to one ordinarily skilled in the art before the effective filing date of the claimed invention to modify the absorbent product customer assistance teaching of Stanley with the customer assistance teaching of Adibi because Stanley teaches in par 072 where Stanley is receiving feedback from customers, and Adibi’s teaching enhances virtual agents to improve interactions with contact centers. Par 001. One would be motivated to modify Stanley with Adibi because in par 001 the virtual agents are personalized so that customers have a better experience. As this combination would help people to have a better experience in contacting a company, one would be motivated to combine Stanley with Adibi.
Per claim 4, Stanley, Adibi, Glass, Meretei teach the limitations of claim 3, above. Stanley does not teach wherein the website chat feature is a texting feature or a chatbot.
Adibi teaches wherein the website chat feature is a texting feature or a chatbot in par 044: “FIG. 3 shows example components and information flows 300 within the cloud-based contact center 150 that implement the virtual agent of the present disclosure. The components may be implemented as part of, or in addition to, the automation infrastructure 200. In operation, a customer 110 will contact the cloud-based contact center 150 through one or more of the channels 140. as shown in FIG. 1. The virtual agent to whom the customer 110 is routed may “listen” to the customer 110 by a speech engine (components 206, 210 and/or 212 and/or translation 324) processing the customer's speech. The processed speech may be forwarded to a speech adapter 316 within a virtual agent engine 314. The virtual agent may interact with the customer over other channels/third-party solutions 322, e.g., chat, SMS, email, etc., that are input to respective adapters (i.e., a chat adapter 318, SMS adapter 320 and others) exposed via APIs 214.”
It would have been obvious to one ordinarily skilled in the art before the effective filing date of the claimed invention to modify the absorbent product customer assistance teaching of Stanley with the customer assistance teaching of Adibi because Stanley teaches in par 072 where Stanley is receiving feedback from customers, and Adibi’s teaching enhances virtual agents to improve interactions with contact centers. Par 001. One would be motivated to modify Stanley with Adibi because in par 001 the virtual agents are personalized so that customers have a better experience. As this combination would help people to have a better experience in contacting a company, one would be motivated to combine Stanley with Adibi.
Therefore, claims 1-4 are rejected under 35 USC 103.
Response to Remarks
35 USC 103
Applicant argues that Stanley does not teach providing training materials or instructions for using the absorbent article. Examiner agrees but as Applicant has amended the claims further search and consideration was required and new art was found that teaches training materials or instructions for using the absorbent article. The argument that it is for a single manufacturer or supplier, however, does not have support in Applicant’s claim limitations. One manufacturer or supplier, which one familiar with the industry would know, could contain thousands of distinct products. Therefore this is not persuasive. As further search and consideration resulted in new art applied, the rejection is maintained.
35 USC 101
Applicant argues:
In this case, as discussed in the present application, a technological problem exists with conventional absorbent product support systems in that customers are not able to obtain information and support on a variety of different available brands and types of absorbent products through a single information hub. The claimed invention provides a technological solution to this technological problem by providing a central computerized information hub through which consumers, case managers, customer service representatives, nursing home staff and the like may access information about and obtain support for absorbent products available from a variety of suppliers and distributors.
Examiner responds: One ordinarily skilled in the art would not recognize this as necessarily describing a technological improvement, nor is a technological problem and improvement claimed or described in the specification. MPEP 2106.05(a) describes how a technological problem and solution is identified:
“If it is asserted that the invention improves upon conventional functioning of a computer, or upon conventional technology or technological processes, a technical explanation as to how to implement the invention should be present in the specification. That is, the disclosure must provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. The specification need not explicitly set forth the improvement, but it must describe the invention such that the improvement would be apparent to one of ordinary skill in the art. Conversely, if the specification explicitly sets forth an improvement but in a conclusory manner (i.e., a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art), the examiner should not determine the claim improves technology. An indication that the claimed invention provides an improvement can include a discussion in the specification that identifies a technical problem and explains the details of an unconventional technical solution expressed in the claim, or identifies technical improvements realized by the claim over the prior art. For example, in McRO, the court relied on the specification’s explanation of how the particular rules recited in the claim enabled the automation of specific animation tasks that previously could only be performed subjectively by humans, when determining that the claims were directed to improvements in computer animation instead of an abstract idea. McRO, 837 F.3d at 1313-14, 120 USPQ2d at 1100-01. In contrast, the court in Affinity Labs of Tex. v. DirecTV, LLC relied on the specification’s failure to provide details regarding the manner in which the invention accomplished the alleged improvement when holding the claimed methods of delivering broadcast content to cellphones ineligible. 838 F.3d 1253, 1263-64, 120 USPQ2d 1201, 1207-08 (Fed. Cir. 2016).”
Here, the description by Applicant appears more of a business application problem. It is not clear what technical hurdle or problem exists that prevents this variety information being available to diverse parties. At the time of filing, it is common knowledge that both Amazon and Walmart have vast amounts of information about products easily accessed, and youtube.com has videos on product explanations from many different parties. But, there’s no identified technical problem with computers that prevents this, at the time of filing from happening. Further, there’s no technical solution as the implementation is with generic computing devices and elements. Therefore, this is not persuasive.
Applicant remarks: “Accordingly, the claims as a whole integrate the judicial exception into a practical application, and thus are patent eligible under section 101.
Further, although the claims satisfy the "practical application" test under Step 2A, Prong Two, and thus further analysis is not necessary, the claims recite additional elements that amount to "significantly more" than any alleged abstract idea and thus satisfy the requirements of Step 2B. Specifically, the claimed invention recites limitations that are not well-understood, routine or conventional, such as, for example, providing access in response to a query to one or more databases containing information pertaining to a plurality of disposable absorbent products available from different manufacturers and/or brands, determining whether a response to the query is acceptable and providing access to a clinician if the response is not satisfactory.”
It is not clear which additional elements in combination are argued to be a practical application. Examiner found the elements listed above to be apply it, in combination, because they were generic, high level basic computing elements that in combination amount to applying a computer to the abstract idea steps. There was no finding of well-understood, routine, and conventional, nor is that necessary, as the elements being “apply it” (see MPEP 2106.05(f)) is, in itself, not significantly more than the abstract idea.
Therefore, for these reasons, the claims are patent ineligible.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Conclusion
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/RICHARD W. CRANDALL/ Primary Examiner, Art Unit 3619