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 .
IDS
The information disclosure statement (IDS) submitted on March 14, 2024 is being considered by the Examiner.
Drawing
The drawing filed on September 29, 2023 is accepted by the Examiner.
Specification
The specification has not been checked to the extent necessary to determine the presence of all possible minor errors. Applicant’s cooperation is requested in correcting any errors of which applicant may become aware in the specification.
Claim rejection – 35 U.S.C. §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.
Claims 1-8 and 13-20 are rejected under 35 U.S.C. 103 as being unpatentable over Folkens et al. (U.S. Patent No. 10,223,454, hereon Folkens) in view of Stueckemann et al. (U.S. PAP. 2024/0185978, hereon Stueckemann)
In reference to claim 1: Folkens discloses a device for providing product assistance (image directed search) (see Folkens, Abstract), the device comprising:
a processor (see Folkens, Fig. 9, a processor 950), wherein the processor is configured to:
receive a first message from a user interface (see Folkens, Fig. 13, receive descriptors), wherein the first message indicates a request from a user to identify an object (see Folkens, column 4, lines 39-49);
determine a portion of the object using a camera of the device (see Folkens, column 40, lines 31-36);
generate confidence level associated with the product (see Folkens, column 40, lines 38-58), wherein the generated confidence level indicates a confidence that the object is the product (see Folkens, column 45, lines 55-67), wherein the generated confidence level is based on the portion of the object (the manual review image) and a product detection model (computer generated image), and wherein the product detection model has been trained using synthetic product detection data that comprises at least computer-generated image of the product (see Folkens, column 27, line 58 to column 28, line 3);
identify the object as the product when the confidence level satisfies the threshold (see Folkens, column 40, lines 46-58); and
send a second message to the user interface when the object is identified (images and features are sent) wherein the second message indicates that the object is the product, indicates a product identifier for the product (see Folkens, column 33, lines 36-46, such as QR codes, barcodes etc..), and indicates a product data (see Folkens, column 33, lines 47-59).
However, Folkens does not provide a product specifically related to medical products.
Stueckemann discloses a medical product assistant (see Stueckemann, Abstract). The device allows requesting information regarding specific product information (see Stueckemann, paragraph [0011]). The device transmits patient intake information and prescription product information (see Stueckemann, paragraph [0012]).
Therefore, it would have been obvious to a person of ordinary skill in the art at the time the invention was made to modify a device for providing a product assistant as taught by Folkens and incorporate a medical product, such as prescription medicine and other related medical products for the purposes of managing patient related tasks for providing service to remote patients as the image directed search used by Folkens would provide a wider service in processing medical prescription application.
With regard to claim 2: Folkens in view of Stueckemann further discloses that the processor is configured to determine the portion of the object using the camera device by determining a video stream using the camera (see Folkens, column 6, lines 16-21, the number of times the video images being seen using image tags); determining images from video streams (image capture screen) (see Folkens, Fig. 2, column 24, lines 23-29), and determining the portion of the object using the image (see Folkens, column 24, lines 37-42, association with a portion of an image to be tagged).
With regard to claim 3: Folkens in view of Stueckemann further discloses that the first message indicates that a request for medical product information (see Folkens, Fig. 4, receive image, and Stueckemann, paragraph [0009], prescription items]).
With regard to claim 4: Folkens in view of Stueckemann further discloses that the first message further indicates request for instruction for use, and wherein the medical product data comprises the instruction for use (see Stueckemann, paragraph [0012]).
With regard to claim 5: Folkens in view of Stueckemann further discloses that the portion of the object comprises at least a product identifier, a label, a code, a quick response (QR) code, a brand name, a model name, a model number, or a regulator identifier (see Folkens, column 33, lines 43-46; and Stueckemann, paragraph [0150]).
With regard to claim 6: Folkens in view of Stueckemann further discloses the medical product data is retrieved from a database (see Stueckemann, paragraph [0009] and [0060]).
With regard to claim 7: Folkens in view of Stueckemann further discloses that the processor is configured to train the product detection model with product detection data that includes image of the medical product (see Folkens, Fig. 1, includes image marking logic, content processing logic and image ranker).
With regard to claim 8: Folkens in view of Stueckemann further discloses that the processor is configured to generate the computer-generated image of the medical product using computer-aided drawing associated with the medical product (see Folkens, column 10, lines 14-46).
In reference to claim 13: Folkens discloses a method used by a device for providing a product assistant (image directed search) (see Folkens, Abstract), the metho comprising:
receiving a first message from a user interface, (see Folkens, Fig. 13, descriptors); wherein, wherein the first message indicates a request from a user to identify an object (see Folkens, column 4, lines 39-49);
determining a portion of the object using a camera of the device (see Folkens, column 40, lines 31-36);
generating confidence level associated with the product (see Folkens, column 40, lines 38-58), wherein the generated confidence level indicates a confidence that the object is the product (see Folkens, column 45, lines 55-67), wherein the generated confidence level is based on the portion of the object (the manual review image) and a product detection model (computer generated image), and wherein the product detection model has been trained using synthetic product detection data that comprises at least computer-generated image of the product (see Folkens, column 27, line 58 to column 28, line 3);
identifying the object as the product when the confidence level satisfies the threshold (see Folkens, column 40, lines 46-58); and
sending a second message to the user interface when the object is identified (images and features are sent) wherein the second message indicates that the object is the product, indicates a product identifier for the product (see Folkens, column 33, lines 36-46, such as QR codes, barcodes etc..), and indicates a product data (see Folkens, column 33, lines 47-59).
However, Folkens does not provide a product specifically related to medical products.
Stueckemann discloses a medical product assistant (see Stueckemann, Abstract). The device allows requesting information regarding specific product information (see Stueckemann, paragraph [0011]). The device transmits patient intake information and prescription product information (see Stueckemann, paragraph [0012]).
Therefore, it would have been obvious to a person of ordinary skill in the art at the time the invention was made to modify a device for providing a product assistant as taught by Folkens and incorporate a medical product, such as prescription medicine and other related medical products for the purposes of managing patient related tasks for providing service to remote patients as the image directed search used by Folkens would provide a wider service in processing medical prescription application.
With regard to claim 14: Folkens in view of Hammad further discloses that the method comprises
determining the portion of the object using the camera device by determining a video stream using the camera (see Folkens, column 6, lines 16-21, the number of times the video images being seen using image tags);
determining images from video streams (image capture screen) (see Folkens, Fig. 2, column 24, lines 23-29), and
determining the portion of the object using the image (see Folkens, column 24, lines 37-42, association with a portion of an image to be tagged).
With regard to claim 15: Folkens in view of Stueckemann further discloses that the first message indicates that a request for medical product information (see Folkens, Fig. 4, receive image, and Stueckemann, paragraph [0009], prescription items]).
With regard to claim 16: Folkens in view of Stueckemann further discloses that the first message further indicates request for instruction for use, and wherein the medical product data comprises the instruction for use (see Stueckemann, paragraph [0012]).
With regard to claim 17: Folkens in view of Stueckemann further discloses that the portion of the object comprises at least a product identifier, a label, a code, a quick response (QR) code, a brand name, a model name, a model number, or a regulator identifier (see Folkens, column 33, lines 43-46; and Stueckemann, paragraph [0150]).
With regard to claim 18: Folkens in view of Stueckemann further discloses the medical product data is retrieved from a database (see Stueckemann, paragraph [0009] and [0060]).
With regard to claim 19: Folkens in view of Stueckemann further discloses that the processor is configured to train the product detection model with product detection data that includes image of the medical product (see Folkens, Fig. 1, includes image marking logic, content processing logic and image ranker).
With regard to claim 20: Folkens in view of Stueckemann further discloses that the processor is configured to generate the computer-generated image of the medical product using computer-aided drawing associated with the medical product (see Folkens, column 10, lines 14-46).
Claims 9 is rejected under 35 U.S.C. 103 as being unpatentable over Folkens and Stueckemann in view of Tremblay et al. (U.S. PAP 2019/0355150, hereon Tremblay).
With regard to claim 9: Folkens and Stueckemann discloses further discloses that the processor is configured to generate the computer-generated image, but it does not explicitly talk about how the image is generated.
Trembly discloses a computer-generated image using domain randomization to assist product detection model (see Trembly, paragraph [0055]).
Therefore, it would have been obvious to a person of ordinary skill in the art at the time the invention was made to modify the processor that is configured to generate computer-generated image as taught by Folkens in view of Stueckemann and incorporate a device using domain randomization to assist product detection model in order to determine characteristics of the product by comparing measured statistics of observed manipulation to simulation of manipulation using a simulator trained with likelihood free inference engine so that the trained model would operate correctly when it estimates real-world data.
Claim Objection
Claims 10-12 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims because none of the references considered in the prosecution of the instant application anticipate or make obvious of the subject matter noted in claims 10, 11 or 12: “the medical environment image is an image of least one of a hospital room, a medical office, or operating room; and generating the computer-generated image of the medical product by imposing the synthetic product image onto the medical environment image”, “generating a medical environment image, wherein the medical environment image is an image of least one of a hospital room, a medical office, or operating room; generating a medical object, wherein the medical object is associated with the medical product and at least one of the hospital room, the medical office, or the operating room; and generating the computer-generated image of the medical product by imposing the synthetic product image and the medical object onto the medical environment image” or “generate a second confidence level associated with a counterfeit product, wherein the generated second confidence level is based on the portion of the object and a counterfeit detection model that has been trained using counterfeit detection data, and wherein the counterfeit detection data comprises at least an image of a counterfeit product; and identify the object as an authentic product when the confidence level satisfies a second threshold.”
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Zalewski et al. (U.S. Patent No. 10,140,820) discloses method for tracking items in a store for processing casher-less purchase transaction. The method includes detecting portable wireless coded communication device in a physical store.
Kiley et al. (U.S. Patent No. 8,725,851) discloses method for contextual data platform which generally relate to internet communications and mechanisms that would enable contextual data to be exchanged between web clients and web servers.
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/ELIAS DESTA/
Primary Examiner, Art Unit 2857