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
Claims 1-20 were previously pending and subject to a non-final office action filed on March 17, 2026 (the “March 17, 2026 Non-Final Office Action”). On June 15, 2026, Applicant amended claims 1, 9, 10, 18, and 19 in an amendment (the “June 15, 2026 Amendment”). As such, claims 1-20, as recited in the June 15, 2026 Amendment, are currently pending and subject to the final office action below.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on June 15, 2026 is in compliance with the provisions of 37 CFR 1.97(c)(1), and has been considered by the examiner.
Response to Applicant’s Remarks
Response to Applicant’s Remarks Concerning Non-Statutory Double Patenting Rejections
Upon further consideration and based on Applicant’s terminal disclaimer filed on June 15, 2026, the non-statutory double patenting rejections of claims 1-20 are withdrawn. Please see the Terminal Disclaimer Section below for further clarification and complete analysis.
Response to Applicant’s Remarks Concerning Claim Objections
Applicant’s arguments, see Applicant’s Remarks, p. 6, Claim Objections Section, filed June 15, 2026, with respect to the claim objections of claims 1-20 have been considered, but they are moot in light of Applicant’s amendments to independent claims 1, 10, and 19. Specifically, Applicant amended claims 1, 10, and 19 to correct an antecedent basis issue. As such, the claim objections of claims 1-20 are no longer necessary and are hereby withdrawn.
Response to Applicant’s Remarks Concerning Rejections under 35 U.S.C. § 112(b)
Applicant’s arguments, see Applicant’s Remarks, pp. 6-7, Claim Rejections Under 35 U.S.C. § 112 Section, filed June 15, 2026, with respect to the § 112(b) of claims 1-20 have been considered, but they are moot in light of Applicant’s amendments to independent claims 1, 10, and 19. Specifically, Applicant amended claims 1, 10, and 19 to correct an antecedent basis issue. As such, the rejections of claims 1-20 under § 112(b) are no longer necessary and are hereby withdrawn.
Response to Applicant’s Remarks Concerning Rejections under 35 U.S.C. § 101
Applicant’s arguments, see Applicant’s Remarks, p. 7, Claim Rejections Under 35 U.S.C. § 101 Section, filed June 15, 2026, with respect to rejections of claims 1-20 under 35 U.S.C. § 101, have been fully considered and are persuasive. While it can be argued that the claims include limitations that are directed to an abstract idea within the Mental Processes grouping of abstract ideas by disclosing a method for therapy delivery for diabetes treatment, comprising: (1) identifying an object as a food item based on a representation of the object; (2) generating nutrition information or volume information [or the portion information] of the food item; (3) determining that the nutrition information or the volume information [or the portion information] of the food item exceeds a threshold; (4) determining that a patient’s glucose level will rise based on the nutrition information or the volume information [or the portion information] exceeding a threshold; and (5) responsive to determining that the patient’s glucose level will rise, determining an insulin dosage for the patient/generating therapy information for the patient based on the determination that the patient’s glucose level will rise, wherein the therapy information includes an insulin dosage (e.g., steps described in independent claims 1, 10, and 19), the claims are patient eligible because they are deemed to recite a combination of additional elements that are indicative of integrating an abstract concept into a practical application under Prong Two of Step 2A of the Alice/Mayo Test as described in the 2019 Revised Patent Subject Matter Eligibility Guidance (the “2019 Revised PEG”). See MPEP § 2106. Specifically, independent claims 1 and 10 recite the following limitations:
A system for therapy delivery for diabetes treatment, the system comprising:
one or more processors; and
one or more processor-readable media storing instructions which, when executed by the one or more processors, cause performance of:
identifying an object as a food item based on a representation of the object;
generating nutrition information or volume information of the food item;
determining that the nutrition information or the volume information of the food item exceeds a threshold;
determining that a patient’s glucose level will rise based on the nutrition information or the volume information exceeding the threshold;
responsive to determining that the patient’s glucose level will rise, determining an insulin dosage for the patient; and
automatically administering insulin to the patient in accordance with the insulin dosage to cause the glucose level of the patient to lower to within a predetermined range.
Similarly, independent claim 19 recites the following limitations:
A method for therapy delivery for diabetes treatment, the method comprising:
generating nutrition information or portion information of a food item based on a representation of the food item obtained from one or more sensors;
determining that the nutrition information or the portion information of the food item exceeds a threshold;
determining that a patient’s glucose level will rise based on the nutrition information or the portion information exceeding the threshold;
generating therapy information for the patient based on the determination that the patient’s glucose level will rise, wherein the therapy information includes an insulin dosage; and
automatically administering insulin to the patient in accordance with the insulin dosage to cause the glucose level of the patient to lower.
When viewed as a whole, the additional elements are interpreted to integrate the abstract idea into a practical application by applying or using the judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition. See MPEP § 2106.04(d)(2). Examples of “treatment” and “prophylaxis” limitations encompass limitations that treat or prevent a disease or medical condition, including, e.g., acupuncture, administration of medication, dialysis, organ transplants, phototherapy, physiotherapy, radiation therapy, surgery, and the like. See id. For example, in Classen Immunotherapies, Inc. v. Biogen IDEC, an immunization step that integrated the abstract idea into a specific process of immunizing that lowered the risk that immunized patients will later develop chronic immune-mediated diseases was considered to be a particular prophylaxis limitations that practically applied the abstract idea. See id.
Similarly, the present claims provide a specific process for administering insulin to a patient by determining the insulin dosage for diabetes treatment to cause a patient’s glucose level to lower to within a predetermined range, after the system (i) determines that the nutrition information or volume information [or portion information] exceeds a threshold; and (ii) determines that a patient’s glucose level will rise based on the nutrition information or the volume information [or portion information] exceeds the threshold. The administration steps in the present claims is particular, because it administers the insulin dosage that was generated for the patient in response to aforementioned determination and therapy generation steps, and it integrates the mental analyses steps into a practical application. Therefore, the claims are deemed to integrate any potential abstract idea into a practical application by providing a particular treatment or prophylaxis for diabetes patients. See MPEP § 2106.04(d)(2).
Therefore, the additional elements of claims 1, 10, and 19 nonetheless integrate any potential abstract idea into a practical application under Prong Two of Step 2A of the Alice/Mayo Test revised in the 2019 Revised PEG, and thus claims 1, 10, and 19 are deemed to be patent eligible under § 101. Dependent claims 2-9, 11-18, and 20 are also deemed to be patent eligible under § 101 for similar reasons as described above. As such, the claim rejections under 35 U.S.C. § 101 set forth in the March 17, 2026 Non-Final Office Action are withdrawn.
Response to Applicant’s Remarks Concerning Rejections under 35 U.S.C. § 103
Applicant’s arguments, see Applicant’s Remarks, pp. 7-9, Claim Rejections Under 35 U.S.C. § 103 Section, filed June 15, 2026, with respect to rejections of claims 1-20 under 35 U.S.C. § 103, have been fully considered, but they are moot in light of Applicant’s amendments to independent claims 1, 10, and 19. Therefore, the combinations of the references previously cited in the March 17, 2026 Non-Final Office Action, are not relied upon to teach the newly amended claim limitations in claims 1, 10, and 19. Please see amended rejections to claims 1-20 under 35 U.S.C. § 103 below, for further clarification and complete analysis.
Terminal Disclaimer
The terminal disclaimer filed on June 15, 2026 disclaiming the terminal portion of any patent granted on this application which would extend beyond the expiration date of U.S. Patent No. 12, 233,238, issued on February 25, 2025, has been reviewed and is accepted.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 2, 4, 7, 9-11, 13, 16, and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over:
- Chiu et al. (Pub. No. US 2019/0341149), in view of:
- Bennett et al. (Pub. No. US 2015/0194071); and
- Wei et al. (Pub. No. US 2018/0197628).
Regarding claims 1, 10, and 19,
- Chiu et al. (Pub. No. US 2019/0341149) teaches:
- a system for therapy delivery for diabetes treatment (Chiu, paragraphs [0033] and [0081]; Paragraph [0081] teaches that a processing system that facilitates a client application 708 that supports communicating with the medical device 702 via the network 710. Paragraph [0033] teaches that the subject matter described herein can be utilized more generally in the context of overall diabetes management or other physiological conditions (i.e., the system is for therapy delivery for diabetes treatment).), the system comprising (as described in claim 1):
- one or more processors (as described in claim 1) (Chiu, paragraph [0081]; Paragraph [0081] teaches that the processing system is implemented using any suitable processing system and/or device, such as, for example, one or more processors.); and
- one or more processor-readable media storing instructions which, when executed by the one or more processors (as described in claim 1) (Chiu, paragraph [0096]; Paragraph [0096] teaches that the control module 802 [of the client computing device 706 - see paragraph [0093]] may be realized using any sort of non-transitory computer-readable medium capable of storing programming instructions for execution by the control module 802 (i.e., one or more processor-readable media storing instructions), where the computer-executable programming instructions are read and executed by the control module 802 (executed by the one or more processors).), cause performance of:
- a method for therapy delivery for diabetes treatment (Chiu, paragraphs [0008] and [0033]; Paragraph [0008] teaches a method of providing guidance to a patient. Paragraph [0033] teaches that the subject matter described herein can be utilized more generally in the context of overall diabetes management or other physiological conditions (i.e., the method is for therapy delivery for diabetes treatment).), the method comprising (as described in claim 10):
- a method for therapy delivery for diabetes treatment (Chiu, paragraphs [0008] and [0033]; Paragraph [0008] teaches a method of providing guidance to a patient. Paragraph [0033] teaches that the subject matter described herein can be utilized more generally in the context of overall diabetes management or other physiological conditions (i.e., the method is for therapy delivery for diabetes treatment).), the method comprising (as described in claim 19):
- identifying an object as a food item based on a representation of the object (as described in claims 1 and 10) (Chiu, paragraph [0036]; Paragraph [0036] teaches that food, beverages, or other consumable items (or indicia thereof) may be identified within a captured image (i.e., identifying an object as a food item based on a representation of the object).);
- generating nutrition information or volume information of the food item (as described in claims 1 and 10); and generating nutrition information or portion information of a food item based on a representation of the food item obtained from one or more sensors (as described in claim 19) (Chiu, paragraph [0036]; Paragraph [0036] teaches that carbohydrate amounts or other attributes (e.g., fiber, fat, protein, and/or the like) associated with the captured consumable(s) may be estimated from the consumables captured by the imaging device (i.e., generating nutrition information based on a representation of the food item that was obtained from one or more sensors). Further, paragraph [0037] teaches that when a patient is about to begin consuming a meal, an image of the meal may be analyzed to identify the type of food being consumed, the nutritional characteristics or other content of the meal device (i.e., generating nutrition information based on a representation of the food item that was obtained from one or more sensors), the estimated portion size device (i.e., generating portion information based on a representation of the food item that was obtained from one or more sensors), and/or the like. The estimated portion size, nutritional characteristics or food type, and other attributes identified based on the captured image may be utilized to calculate or otherwise determine an estimated amount of carbohydrates expected to be consumed by the patient device (i.e., generating nutrition information based on a representation of the food item that was obtained from one or more sensors).);
…
- determining that a patient’s glucose level will rise based on the nutrition information or the volume information of the particular food item … (as described in claims 1 and 10); and determining that a patient's glucose level will rise based on the nutrition information or the portion information of the particular food item … (as described in claim 19) (Chiu, paragraph [0128]; Paragraph [0128] teaches that a graphical overlay may be provided visually overlying or adjacent to captured content corresponding to a lifestyle event that indicates how much a patient’s glucose levels are predicted to rise or fall if that lifestyle event corresponding to the captured image is engaged in by the patient in the predicted manner (i.e., determining whether the patient’s glucose level will rise [or fall] based on the determination of the nutrition information, volume information, or portion information of the particular food item).); and
- responsive to determining that the patient’s glucose level will rise, determining an insulin dosage for the patient (as described in claim 1); responsive to determining that the patient’s glucose level will rise, generating therapy information for the patient, wherein the therapy information includes an insulin dosage (as described in claim 10); and generating therapy information for the patient based on the determination that the patient’s glucose level will rise, wherein the therapy information includes an insulin dosage (as described in claim 19) (Chiu, paragraphs [0075] and [0089]; Paragraph [0089] teaches that one or more aspects of the infusion device 102, 200, 402 that control or regulate insulin delivery may then be modified or adjusted (i.e., generating therapy information for a patient) to proactively account for the patient’s likely meal activity and glycemic response (i.e., in response to determining that the patient’s glucose level will rise, generating therapy information for the patient). Paragraph [0075] teaches that the PID control parameters are applied to the difference between the target glucose level at input 602 and the measured glucose level at input 604 to generate or otherwise determine a dosage (or delivery) command provided at output 630 (i.e. responsive to determine that the patient’s glucose level will rise, determining a dosage for the patient). Further, paragraph [0075] teaches that based on that delivery command, the motor control module 412 operates the motor 432 to deliver insulin to the body of the patient (i.e., the determined dosage is an insulin dosage) to influence the patient’s glucose level, and thereby reduce the difference between a subsequently measured glucose level and the target glucose level.); and
- automatically administering insulin to the patient in accordance with the insulin dosage to cause the glucose level of the patient to lower within a predetermined range (as described in claims 1 and 10); and automatically administering insulin to the patient in accordance with the insulin dosage to cause the glucose level of the patient to lower (as described in claim 19) (Chiu, paragraph [0075]; Paragraph [0075] teaches that the PID control parameters are applied to the difference between the target glucose level at input 602 and the measured glucose level at input 604 to generate or otherwise determine a dosage (or delivery) command provided at output 630 (i.e. responsive to determine that the patient’s glucose level will rise, determining a dosage for the patient); and based on that delivery command, the motor control module 412 operates the motor 432 to deliver insulin to the body of the patient to influence the patient’s glucose level, and thereby reduce the difference between a subsequently measured glucose level and the target glucose level (i.e., automatically administering the insulin dosage to the patient to cause the glucose level of the patient to lower within a predetermined range).).
- Chiu does not explicitly teach, however, in analogous art of systems and methods for providing personalized nutritional analysis and recommendations based on a user’s current nutritional intake, Bennett et al. (Pub. No. US 2015/0194071) a system and method for therapy delivery for diabetes treatment, comprising:
- determining that the nutrition information or the volume information of the food item exceeds a threshold (as described in claims 1 and 10); and determining that the nutrition information or the portion information of the food item exceeds a threshold (as described in claim 19) (Bennett, paragraphs [0155] and [0165]; Paragraph [0165] teaches that the method provides an analysis of the nutritional content of the food consumed by the user in comparison to nutrient levels recommended for or specified by the user, according to the user's health-related goals. For example, paragraph [0165] teaches that the index is calculated by determining the nutritional content of the consumed food and identifying a deviation between the nutrient levels in the consumed food and target nutrient levels (i.e., determining that the nutrition information of the food item exceeds a threshold, where the target nutrient levels described in Bennett is interpreted as a threshold of the nutrition information). Paragraph [0155] teaches that this feature is beneficial for determining an index based on the nutrient content of a consumed food and target nutrient levels.).
Therefore, it would have been obvious to one of ordinary skill in the art of systems and methods for providing personalized nutritional analysis and recommendations based on a user’s current nutritional intake at the time of the effective filing date of the claimed invention to modify the system and methods for facilitating operation of a medical device to provide diabetes therapy to a user taught by Chiu, to incorporate a step and feature directed to determining that the nutrition information of a food item exceeds a threshold, as taught by Bennett, in order to determine an index based on the nutrient content of a consumed food and target nutrient levels. See Bennett, paragraph [0155]; see also MPEP § 2143 G.
- Further, the combination of: Chiu, as modified in view of Bennett, does not explicitly teach, however, in analogous art of systems and methods for generating therapy for diabetes treatment, Wei et al. (Pub. No. US 2018/0197628) a system and method for therapy delivery for diabetes treatment, comprising:
- determining that a patient’s glucose level will rise based on the nutrition information or the volume information exceeding the threshold (as described in claims 1 and 10); and determining that a patient’s glucose level will rise based on the determination the nutrition information or the portion information of the particular food item exceeds the threshold (as described in claim 19) (Wei, paragraphs [0090] and [0161]; Paragraph [0090] teaches that a reader device 120 can algorithmically process the collected analyte data (i.e., nutrition information) and determine whether a glucose excursion or a meal event has occurred (i.e., determining that a patient’s glucose level will change) at 306, using a meal event detector, which examines the analyte data for one or more analyte values that violate a threshold or other condition that is indicative of the occurrence of a glucose excursion or a meal event (i.e., determining that a patient’s glucose level will change based on the nutrition information exceeding the threshold), where paragraph [0161] teaches that the glucose excursion can be a rapid rise or high glucose level (i.e., the determination of the glucose level comprises determining that a patient’s glucose level will rise).); and
- While Chiu teaches the following limitations described in claims 1, 10, and 19, the Examiner notes that Wei also teaches a system and method, comprising:
- automatically administering insulin to the patient in accordance with the insulin dosage to cause the glucose level of the patient to lower within a predetermined range (as described in claims 1 and 10); and automatically administering insulin to the patient in accordance with the insulin dosage to cause the glucose level of the patient to lower (as described in claim 19) (Wei, paragraphs [0160] and [0162]; Paragraph [0160] teaches that an output issued at 320 can cause the user’s drug delivery device 160 to administer medication to treat a potential or actual high glucose condition, such as by administration of a bolus dose or by a modification to a basal dosage profile or schedule (i.e., administering insulin to the patient in accordance with the insulin dosage, which naturally causes the patient’s glucose level to lower to within a predetermined range), and this can be done automatically without the user’s approval (i.e., the administration of the insulin dosage is automatic). Paragraph [0162] teaches that these features are beneficial for reducing the occurrence of errors in medication administration.).
Therefore, it would have been obvious to one of ordinary skill in the art of systems and methods for generating therapy for diabetes treatment at the time of the effective filing date of the claimed invention to further modify the system and methods for facilitating operation of a medical device to provide diabetes therapy to a user taught by Chiu, as modified in view of Bennett, to incorporate a step and feature directed to determining that the patient’s glucose level will rise based on a determination of the nutrition information exceeds a threshold, as taught by Wei, in order to a reduce the occurrence of errors in medication administration. See Wei, paragraph [0162]; see also MPEP § 2143 G.
Regarding claim 2 and 11,
- The combination of: Chiu, as modified in view of: Bennett and Wei, teaches the limitations of: claim 1 (which claim 2 depends on) and claim 10 (which claim 11 depends on), as described above.
- Chiu teaches a system and method, wherein:
- the system further comprises one or more sensors, and wherein the representation of the object is obtained from the one or more sensors (as described in claim 2); and wherein the representation of the object is obtained from the one or more sensors (as described in claim 11) (Chiu, paragraphs [0036] and [0095]; Paragraph [0095] teaches that the imaging device 808 is realized as a camera (i.e., the system further comprises one or more sensors), where paragraph [0036] teaches that the consumable items are captured by the imaging device (i.e., the representation of the object is obtained from the one or more sensors).).
The motivations and rationales for modifying the system and method for facilitating operation of a medical device to provide diabetes therapy to a user taught by Chiu, in view of: Bennett and Wei, described in the analysis of the obviousness rejection of claims 1, 10, and 19 above similarly apply to this obviousness rejection, and are incorporated herein by reference.
Regarding claims 4 and 13,
- The combination of: Chiu, as modified in view of: Bennett and Wei, teaches the limitations of: claim 1 (which claim 4 depends on) and claim 10 (which claim 13 depends on), as described above.
- Chiu teaches a system and method, wherein:
- the system further comprises a wearable device, and wherein the representation of the object is obtained from the wearable device (as described in claim 4); and wherein the representation of the object is obtained from a wearable device (as described in claim 13) (Chiu, paragraph [0123] and FIG. 8; Paragraph [0123] teaches that the computing device 706, 800 implementing the proactive guidance process 1800 is realized as smartglasses or another head-worn device (i.e., the system further comprises a wearable device) where the imaging device 808 continually captures images (i.e., the representation of the object is obtained from the imaging device that is part of the wearable device – see FIG. 8, where the imaging device 808 is part of the electronic device 800, which paragraph [0123] explicitly teaches may be realized as smartglasses or another head-worn device), the control module 802 may continually analyze and monitor the captured images output by the imaging device 808 to recognize or identify one or more items that correspond to a lifestyle event (e.g., an item of food, an exercise machine, or the like).).
The motivations and rationales for modifying the system and method for facilitating operation of a medical device to provide diabetes therapy to a user taught by Chiu, in view of: Bennett and Wei, described in the analysis of the obviousness rejection of claims 1, 10, and 19 above similarly apply to this obviousness rejection, and are incorporated herein by reference.
Regarding claims 7, 16, and 20,
- The combination of: Chiu, as modified in view of: Bennett and Wei, teaches the limitations of: claim 1 (which claim 7 depends on); claim 10 (which claim 16 depends on); and claim 19 (which claim 20 depends on), as described above.
- Bennett teaches a system and method, wherein:
- determining that the nutrition information or the volume information of the food item exceeds the threshold comprises accessing a food library that defines the threshold (as described in claims 7 and 16); and the threshold is specified in a food library, and wherein determining that the nutrition information or the portion information of the food item exceeds the threshold is determined by accessing the food library (as described in claim 20) (Bennett, paragraphs [0007], [0083], and [0091]; Paragraph [0007] teaches that target level of the first nutrient (i.e., the threshold of the nutrition information) is received from at least one electronic database (i.e., the threshold is defined by accessing a food library, where the electronic database is deemed to be the equivalent of a food library). Paragraph [0083] teaches that the electronic database includes data representative of a target nutrition profile for a person, which includes target levels of nutrients (i.e., the threshold is specified in a food library) that are indicative of a suggested or required amount of the nutrient over the predetermined time period and is determined according to a user-specified nutritional goal (i.e., determining that the nutrition information of the food item exceeds the threshold comprises accessing a food library that defines the threshold). Paragraph [0091] teaches that this feature is beneficial for providing an assessment of an impact on an alignment between the user's diet and the user's dietary goals).
Therefore, it would have been obvious to one of ordinary skill in the art of systems and methods for generating therapy for diabetes treatment at the time of the effective filing date of the claimed invention to further modify the system and methods for facilitating operation of a medical device to provide diabetes therapy to a user taught by Chiu, as modified in view of: Bennett and Wei, to incorporate a step and feature directed to accessing a food library that defines the threshold, as taught by Bennett, in order to provide an assessment of an impact on an alignment between the user's diet and the user's dietary goals. See Bennett, paragraph [0091]; see also MPEP § 2143 G.
Regarding claims 9 and 18,
- The combination of: Chiu, as modified in view of: Bennett and Wei, teaches the limitations of: claim 1 (which claim 9 depends on) and claim 10 (which claim 18 depends on), as described above.
- Wei teaches a system and method, wherein:
- the instructions further cause performance of determining an insulin type, and wherein automatically administering the insulin to the patient is in accordance with the insulin type (as described in claim 9); and the therapy information comprises an insulin type (as described in claim 18) (Wei, paragraphs [0159] and [0160]; Paragraph [0159] teaches that the output information can be used by the treatment program in determining whether a modification to a user’s treatment profile (e.g., a basal insulin delivery schedule or a bolus dose) is warranted (i.e., determining an insulin type, where a basal insulin delivery schedule or a bolus dose are insulin types). Further, paragraph [0160] teaches that an output issued to the user’s drug delivery device can be the administration of a bolus dose or a basal dosage profile or schedule (i.e., automatically administering the insulin to the patient is in accordance with the insulin type).).
The motivations and rationales for modifying the system and method for facilitating operation of a medical device to provide diabetes therapy to a user taught by Chiu, in view of: Bennett and Wei, described in the analysis of the obviousness rejection of claims 1, 10, and 19 above similarly apply to this obviousness rejection, and are incorporated herein by reference.
Claims 3 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over:
- The combination of: Chiu et al. (Pub. No. US 2019/0341149), as modified in view of: Bennett et al. (Pub. No. US 2015/0194071) and Wei et al. (Pub. No. US 2018/0197628), as applied to claims 2 and 11 above, and further in view of:
- Fitzpatrick (Pub. No. US 2019/0000382).
Regarding claims 3 and 12,
- The combination of: Chiu, as modified in view of: Bennett and Wei, teaches the limitations of: claim 2 (which claim 3 depends on) and claim 11 (which claim 12 depends on), as described above.
- Chiu further teaches a system and method, wherein:
- the one or more sensors includes a camera configured to capture a two-dimensional image of the object … (as described in claims 3 and 12) (Chiu, paragraphs [0036] and [0095]; Paragraph [0095] teaches that the imaging device 808 is realized as a camera (i.e., the one or more sensors includes a camera), where paragraph [0036] teaches that the consumable items are captured by the imaging device (i.e., the capture naturally captures a two-dimensional image of the objects).).
- The combination of: Chiu, as modified in view of: Bennett and Wei, does not explicitly teach, however, in analogous art of systems and methods for systems and methods for analyzing items using image recognition technology, Fitzpatrick (Pub. No. US 2019/0000382) teaches a system and method, wherein:
- the one or more sensors includes a LiDAR sensor configured to capture a three-dimensional representation of the object (as described in claims 3 and 12) (Fitzpatrick, paragraphs [0022], [0038], and [0202]; Paragraph [0023] teaches that the system is for analyzing items, including analyzing foods whether they are in a store, on a plate, on a menu, in a picture, and the like, and paragraph [0032[ teaches that the system allows a user to keep track and analyze all of the food they use, eat, buy, and consume. Paragraph [0202] teaches that some embodiments of database interface 201 provide multiple types of abstracted APIs that allow unified access to different categories of indexed data, such as: (i) imagery data (e.g., Electro-Optic (EO). Multi-/Hyper-spectral Imagery (MSI/HSI), etc.) and (ii) three-dimensional data (e.g., Light Detection and Ranging (LIDAR) (i.e., the one or more sensors includes a LiDAR sensor configured to capture a three-dimensional representation of an object). Paragraph [0022] teaches that this feature is beneficial for identifying and analyzing the composition of items through image recognition.).
Therefore, it would have been obvious to one of ordinary skill in the art of systems and methods for analyzing items using image recognition technology at the time of the effective filing date of the claimed invention to further modify the system and methods for facilitating operation of a medical device to provide diabetes therapy to a user taught by Chiu, as modified in view of: Bennett and Wei, to incorporate a step and feature directed to using a LiDAR sensor to capture three-dimensional images of objects, as taught by Fitzpatrick, in order to identify and analyze the composition of items through image recognition. See Fitzpatrick, paragraph [0022]; see also MPEP § 2143 G.
Claims 5 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over:
- The combination of: Chiu et al. (Pub. No. US 2019/0341149), as modified in view of: Bennett et al. (Pub. No. US 2015/0194071) and Wei et al. (Pub. No. US 2018/0197628), as applied to claims 1 and 10 above, and further in view of:
- Zadeh et al. (Pub. No. US 2018/0204111).
Regarding claims 5 and 14,
- The combination of: Chiu, as modified in view of: Bennett and Wei, teaches the limitations of: claim 1 (which claim 5 depends on) and claim 10 (which claim 14 depends on), as described above.
- The combination of: Chiu, as modified in view of: Bennett and Wei, does not explicitly teach, however, in analogous art of systems and methods for image and pattern recognition, Zadeh et al. (Pub. No. US 2018/0204111) teaches a system and method, wherein:
- generating the nutrition information comprises generating a mesh model of the object and based on the mesh model, determine which one amongst a plurality of food items corresponds to the object (as described in claims 5 and 14) (Zadeh, paragraphs [1868] and [2054]; Paragraph [1868] teaches that the computer generated types are based on real images of real objects, as well, which are classified as different types by the computer, and an average or typical sample is stored as an example of that specific type in the database. In one embodiment, the storage of the example is either analytical, e.g. mathematical formulation of curves and meshes (i.e., generating mesh models of the object), to mimic the surfaces in 3-D, or brute force storage as a point-by-point storage of coordinates of data points, in 3-D (x, y, z) coordinates. Paragraph [2054] teaches that from a picture of food plate, the system extracts the objects and recognizes them, e.g. peanut, and from the library (i.e., determining which amongst a plurality of food items corresponds to the object). Paragraph [2054] teaches that this feature is beneficial for getting all of the nutritional facts and proper diet for a person when compared to a recommended regimen for the specific person.).
Therefore, it would have been obvious to one of ordinary skill in the art of systems and methods for image and pattern recognition at the time of the effective filing date of the claimed invention to further modify the system and methods for facilitating operation of a medical device to provide diabetes therapy to a user taught by Chiu, as modified in view of: Bennett and Wei, to incorporate a step and feature directed to generating mesh models and using the models to determine the food items corresponding to the object, as taught by Zadeh, in order to identify all of the nutritional facts and proper diet for a person when compared to a recommended regimen for the specific person. See Zadeh, paragraph [2054]; see also MPEP § 2143 G.
Claims 6 is rejected under 35 U.S.C. 103 as being unpatentable over:
- The combination of: Chiu et al. (Pub. No. US 2019/0341149), as modified in view of: Bennett et al. (Pub. No. US 2015/0194071); Wei et al. (Pub. No. US 2018/0197628); and Zadeh et al. (Pub. No. US 2018/0204111), as applied to claim 5 above, and further in view of:
- Schloter (Pub. No. US 2020/0090417).
Regarding claim 6,
- The combination of: Chiu, as modified in view of: Bennett; Wei; and Zadeh, teaches the limitations of claim 5 (which claim 6 depends on), as described above.
- The combination of: Chiu, as modified in view of: Bennett; Wei; and Zadeh, does not explicitly teach, however, in analogous art of systems and methods for generating images of objects, Schloter (Pub. No. US 2020/0090417) teaches a system, wherein:
- the instructions further cause performance of aligning a three-dimensional mesh model of the object and a two-dimensional mesh model of the object to generate a co-registered mesh model of the object from which the food item of the plurality of food items is identified (Schloter, paragraphs [0014] and [0032]; Paragraph [0032] teaches that the image aligning module 116 may perform UV mapping to align the portions of the image and model. UV mapping, PTEX, or similar methods may be used to project two dimensional (2D) image data onto a surface of a three dimensional (3D) model for texture mapping. (i.e., aligning a three-dimensional mesh model of the object and a two-dimensional mesh model of the object to generate a co-registered mesh model of the object). Paragraph [0014] teaches that this feature is beneficial for providing an enhanced appearance and more accurately depicting an environment.).
Therefore, it would have been obvious to one of ordinary skill in the art of systems and methods for generating images of objects at the time of the effective filing date of the claimed invention to further modify the system and methods for facilitating operation of a medical device to provide diabetes therapy to a user taught by Chiu, as modified in view of: Bennett; Wei; and Zadeh, to incorporate a step and feature directed to aligning images by projecting two-dimensional images onto a surface of three-dimensional images, as taught by Schloter, in order to provide an enhanced appearance and more accurately depict an environment. See Schloter, paragraph [0014]; see also MPEP § 2143 G.
Claims 8 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over:
- The combination of: Chiu et al. (Pub. No. US 2019/0341149), as modified in view of: Bennett et al. (Pub. No. US 2015/0194071) and Wei et al. (Pub. No. US 2018/0197628), as applied to claims 7 and 16 above, and further in view of:
- Tran et al. (Pub. No. US 2017/0323481).
Regarding claims 8 and 17,
- The combination of: Chiu, as modified in view of: Bennett and Wei, teaches the limitations of: claim 7 (which claim 8 depends on) and claim 16 (which claim 17 depends on), as described above.
- The combination of: Chiu, as modified in view of: Bennett and Wei, does not explicitly teach, however, in analogous art of systems and methods for assisting in monitoring diabetic patients, Tran et al. (Pub. No. US 2017/0323481) teaches a system and method, wherein:
- the food library comprises a trained machine learning model (as described in claims 8 and 17) (Tran, paragraphs [0146], [0173], and [0174]; Paragraph [0173] teaches that data concerning food consumption can be analyzed to identify and track consumption of selected types and amounts of foods, ingredients, or nutrient consumed using one or more methods selected from the group consisting of: linear regression and/or multivariate linear regression, logistic regression and/or probit analysis, Fourier transformation and/or fast Fourier transform (FFT), linear discriminant analysis, non-linear programming, analysis of variance, chi-squared analysis, cluster analysis, energy balance tracking, factor analysis, principal components analysis, survival analysis, time series analysis, volumetric modeling, neural network and machine learning (i.e., generating the food item information is based on machine learning). Paragraph [0174] teaches that food pictures can be analyzed for automated food identification using methods selected from the group consisting of: image attribute adjustment or normalization; inter-food boundary determination and food portion segmentation; image pattern recognition and comparison with images in a food database to identify food type; comparison of a vector of food characteristics with a database of such characteristics for different types of food; scale determination based on a fiduciary marker and/or three-dimensional modeling to estimate food quantity (i.e., the machine learning model is trained); and association of selected types and amounts of ingredients or nutrients with selected types and amounts of food portions based on a food database that links common types and amounts of foods with common types and amounts of ingredients or nutrients. Paragraph [0146] teaches that this feature is beneficial for automatically analyzing and identifying the types and quantities of foods consumed.).
Therefore, it would have been obvious to one of ordinary skill in the art of systems and methods for assisting in monitoring diabetic patients at the time of the effective filing date of the claimed invention to further modify the system and methods for facilitating operation of a medical device to provide diabetes therapy to a user taught by Chiu, as modified in view of: Bennett and Wei, to incorporate a step and feature directed to the food library comprising a trained machine learning model, as taught by Tran, in order to automatically analyzing and identifying the types and quantities of foods consumed. See Tran, paragraph [0146]; see also MPEP § 2143 G.
Claim 15 is rejected under 35 U.S.C. 103 as being unpatentable over:
- The combination of: Chiu et al. (Pub. No. US 2019/0341149), as modified in view of: Bennett et al. (Pub. No. US 2015/0194071) and Wei et al. (Pub. No. US 2018/0197628), as applied to claim 13 above, and further in view of:
- Schloter (Pub. No. US 2020/0090417).
Regarding claim 15,
- The combination of: Chiu, as modified in view of: Bennett and Wei, teaches the limitations of claim 13 (which claim 15 depends on), as described above.
- The combination of: Chiu, as modified in view of: Bennett and Wei, does not explicitly teach, however, in analogous art of systems and methods for generating images of objects, Schloter (Pub. No. US 2020/0090417) teaches a method, further comprising:
- aligning a three-dimensional mesh model of the object and a two-dimensional mesh model of the object to generate a co-registered mesh model of the object from which the food item of the plurality of food items is identified (Schloter, paragraphs [0014] and [0032]; Paragraph [0032] teaches that the image aligning module 116 may perform UV mapping to align the portions of the image and model. UV mapping, PTEX, or similar methods may be used to project two dimensional (2D) image data onto a surface of a three dimensional (3D) model for texture mapping. (i.e., aligning a three-dimensional mesh model of the object and a two-dimensional mesh model of the object to generate a co-registered mesh model of the object). Paragraph [0014] teaches that this feature is beneficial for providing an enhanced appearance and more accurately depicting an environment.).
Therefore, it would have been obvious to one of ordinary skill in the art of systems and methods for generating images of objects at the time of the effective filing date of the claimed invention to further modify the system and methods for facilitating operation of a medical device to provide diabetes therapy to a user taught by Chiu, as modified in view of: Bennett and Wei, to incorporate a step and feature directed to aligning images by projecting two-dimensional images onto a surface of three-dimensional images, as taught by Schloter, in order to provide an enhanced appearance and more accurately depict an environment. See Schloter, paragraph [0014]; see also MPEP § 2143 G.
Conclusion
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Nicholas Akogyeram II whose telephone number is (571)272-0464. The examiner can normally be reached Monday - Friday, between 8:00am - 5:00pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jason Dunham can be reached at (571) 272-8109. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
Official replies to this Office action may now be submitted electronically by registered
users of the EFS-Web system. Information on EFS-Web tools is available on the Internet at:
http://www.uspto.gov/patents/processlfi!elefslguidance/index.isp. An EFS-Web Quick-Start
Guide is available at: http://www.uspto.gov/ebc/portallefslquick-start.pdf.
Alternatively, official replies to this Office Action may still be submitted by any one of fax, mail, or hand delivery.
Faxed replies should be directed to the central fax at (571) 273-8300.
Mailed replies should be addressed to:
United States Patent and Trademark Office:
Commissioner of Patents and Trademarks
P.O. Box 1450
Alexandria, VA 22313-1450
Hand delivered responses should be brought to the United States Patent and Trademark Office Customer Service Window:
Randolph Building
401 Dulany Street
Alexandria, VA 22314-1450
/N.A.A./Examiner, Art Unit 3686
/JONATHON A. SZUMNY/Primary Examiner, Art Unit 3686
Prosecution Insights