DETAILED ACTION
Notices to Applicant
This communication is a final rejection. Claims 1-10 and 12-18, as filed 10/30/2025, are currently pending and have been considered below.
Priority is generally acknowledged as shown on the 11/21/2023 filing receipt with the earliest priority date being 05/13/2022.
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . 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 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.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
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, 6, 8, 10, and 14-18 are rejected under 35 U.S.C. 103 as being unpatentable over Murray (USP App. Pub. No. 2022/0022537) in view of Adoni (USP App. Pub. No. 2017/0011145).
Regarding claim 1, Murray discloses: An electrical condition data management apparatus comprising: a control unit; a storage unit; and a communication unit (“The main body or smoking substitute apparatus may comprise a wireless interface, which may be configured to communicate wirelessly with another device, for example a mobile device,” [0087]; “The mobile device may be communicatively coupled to the controller via a wireless connection (e.g., Bluetooth, Wi-Fi) or via a wired connection (e.g., USB). The mobile device and controller being communicatively coupled may mean that the mobile device and controller are capable of exchanging data (e.g., transmitting data to, and receiving data from, one another),” [0801]), wherein
--the storage unit stores electrical condition data that changes a feeling of taste (“The mouthpiece may further include a connection interface for receiving a stimulation signal from the smoking substitute apparatus, to enable stimulation of the user's tongue based on the received stimulation signal, ” [0766]), and
the control unit comprising:
--a reading-out unit that reads out the electrical condition data from the storage unit (“Thus, the mobile device may transmit a test control signal to the controller to stimulate the user's tongue. The test control signal may, for example, correspond to a test flavor. The user may then record, via the user interface on the mobile device, what flavor they experienced when their tongue was stimulated. The user interface may include multiple selectable options corresponding to possible flavors experienced by the user. The mobile device may record the user's response,” [0807]);
--a first transmission unit that transmits the electrical condition data read out by the reading-out unit to an instrument including a communication unit, the instrument being capable of generating electricity corresponding to the electrical condition data received via the communication unit and causing the generated electricity to flow through a human body (“The mouthpiece may further include a connection interface for receiving a stimulation signal from the smoking substitute apparatus, to enable stimulation of the user's tongue based on the received stimulation signal, ” [0766]; “The flavor simulation may be controlled by controlling an electrical signal (e.g., voltage or current) delivered to the tongue via the one or more electrodes,” [0759]);
--an input unit that inputs an impression of a taste held by a user in a state where the electricity corresponding to the electrical condition data transmitted by the first transmission unit flows through the user via the instrument (“The mobile device may be further configured to adjust the test control signal transmitted to the controller, based on the indication received from the user. In this manner, the control signal may be adjusted in real-time based on the user's response. The control signal may be adjusted until the user indicates that a desired flavor is perceived by the user. This may enable fine-tuning of the flavor simulation, so that a desired flavor may be accurately simulated for that user,” [0809]; “receiving from a user, via a user interface on the mobile device, an indication of a flavor perceived by the user,” [0806]); and
--a reflection unit that reflects the impression input by the input unit in the electrical condition data stored in the storage unit (“This procedure may be repeated for multiple different test control signals, with the user indicating each time via the user interface the flavor which they perceived. In this manner, it may be possible to build up a mapping between the different control signals and flavors experienced by the user. This mapping may then be used to when generating a control signal to simulate a desired flavor. As a result, flavors may be simulated more accurately for the user, as generation of the control signal may take into account how the user responded to previous simulations,” [0808]).
Murray does not expressly disclose but Adoni teaches:
--wherein a plurality of pieces of the electrical condition data are stored in the storage unit (“The alpha model includes taste vectors for each taste characteristic (e.g., salty, sweet, bitter, sour, and umami). The alpha model also includes various health vectors. In some embodiments, the user chooses which health vectors are included in the alpha model,” [0028]; [0019]),
--the control unit further comprises an acquisition unit that acquires preference information of the user, and a determination unit that determines, based on the preference information acquired by the acquisition unit, the electrical condition data matching a preference of the user from among the pieces of electrical condition data stored in the storage unit (“a user of client device 110 receives electronic pulses via simulator 114 that mimics the flavor profile of a dish. The user interacts with user interface 116 to provide feedback on the flavor profile,” [0021]), and
--the reading-out unit reads out, from the storage unit, the electrical condition data determined by the determination unit (“the user feedback is used to determine a beta model. In these embodiments, the taste vectors and health vectors of the alpha model are modified to reflect a specific user's preference. In some embodiments, the user feedback is used to recommend restaurants and dishes to a user. For example, user feedback is used in a social media platform. In this example, a user's feedback is compared to user's with a similar taste profile to make recommendations,” [0031]).
One of ordinary skill in the art would have been motivated before the effected filing date to expand Murray’s electrical taste fine-tuning with the taste combinations of Adoni because using this would allow the food to be more tailored to the user’s preferences (see Adoni [0011]).
Regarding claim 6, Murray further discloses:
--wherein the storage unit further stores at least one of personal information on the user, instrument information on the instrument, food information on food, and environmental information on an intake environment (“The mobile device 1058 may be connected to a cloud server (not shown), so that user data relating to taste profiles and calibration data may be stored in the cloud,” [1686]), and
--the reflection unit further reflects the at least one information in the electrical condition data stored in the storage unit (“This procedure may be repeated for multiple different test control signals, with the user indicating each time via the user interface the flavor which they perceived. In this manner, it may be possible to build up a mapping between the different control signals and flavors experienced by the user. This mapping may then be used to when generating a control signal to simulate a desired flavor. As a result, flavors may be simulated more accurately for the user, as generation of the control signal may take into account how the user responded to previous simulations,” [0808]).
Regarding claim 8¸Murray further discloses: the control unit further comprises: a generation unit that generates the electrical condition data; and a registration unit that registers, in the storage unit, the electrical condition data generated by the generation unit (“This procedure may be repeated for multiple different test control signals, with the user indicating each time via the user interface the flavor which they perceived. In this manner, it may be possible to build up a mapping between the different control signals and flavors experienced by the user. This mapping may then be used to when generating a control signal to simulate a desired flavor. As a result, flavors may be simulated more accurately for the user, as generation of the control signal may take into account how the user responded to previous simulations,” [0808]).
Regarding claim 10¸Murray further discloses: wherein the control unit further comprises a second transmission unit that transmits the electrical condition data to another electrical condition data management apparatus (“The mobile device 1058 may be connected to a cloud server (not shown), so that user data relating to taste profiles and calibration data may be stored in the cloud. The mobile device 1058 may also access a “flavor library” stored in the cloud, which includes information on how to simulate various flavors (e.g., parameters of the stimulation signal for simulating the various flavors). In this manner, the user may have access to a wide range of flavors stored in the cloud,” [1686]).
Regarding claim 14¸ Murray further discloses: the storage unit further stores expression data including a plurality of expressions related to the taste, and the input unit causes the user to select the appropriate expression from among the expressions (“The user interface may include multiple selectable options corresponding to possible flavors experienced by the user. The mobile device may record the user's response,” [0807]).
Regarding claim 15¸ Murray further discloses: wherein the electrical condition data changes the feeling of the taste (“Different electrical signals delivered to the user's tongue may result in different flavor sensations for the user. Properties of the electrical signal delivered to the user's tongue such as voltage, current level, frequency, etc. may be varied to simulate different flavors,” [0759]).
Regarding claim 16¸ Murray further discloses: wherein the electrical condition data includes at least one of a numerical value of an intensity of the electricity, a numerical value of a frequency of the electricity, and a numerical value of a duty ratio (“Different electrical signals delivered to the user's tongue may result in different flavor sensations for the user. Properties of the electrical signal delivered to the user's tongue such as voltage, current level, frequency, etc. may be varied to simulate different flavors,” [0759]; “The one or more electrodes arranged to electrically stimulate the user's tongue may include a pair of electrodes. The pair of electrodes may be arranged to pass an electrical current through the user's tongue. In this manner, the user's tongue may be stimulated by passing a current through a part of the user's tongue located between the pair of electrodes. Preferably the current may be delivered to user's tongue in pulses. Parameters such as magnitude of the current, pulse duration, and/or pulse frequency may be controlled to simulate a desired flavor,” [0760]).
Claims 17 and 18 are substantially similar to claim 1 and are rejected with the same reasoning.
Claims 2-5 and 12-13 are rejected under 35 U.S.C. 103 as being unpatentable over Murray (USP App. Pub. No. 2022/0022537) in view of Adoni (USP App. Pub. No. 2017/0011145) and Lawless (“Metallic taste from electrical and chemical stimulation”).
Regarding claim 2, Murray discloses parameters may be adapted to a given user's physiology and sensitivity to electrical stimulation via the electrodes in [1665] which suggests a biological component to the determination but the claimed biological data is interpreted in light of [0041] of the published application as data received with a biological measurement apparatus rather than the user’s reported experience. Murray does not expressly disclose but Lawless teaches: wherein the electrical condition data is determined based on biological data (comparing electric stimulus from a battery with contact with a metal as shown in Figure 1).
One of ordinary skill in the art would have been motivated before the effected filing date to expand Murray and Adoni’s electrical taste fine-tuning with the receptor activation detection of Lawless because this would provide a more accurate fine-tuning by using an objective metric combined with the patient’s reported experience.
Regarding claim 3, Murray does not expressly disclose but Lawless teaches: wherein the biological data is activation data of an in vivo protein used when an organism feels the taste (comparing electric stimulus from a battery with contact with a metal as shown in Figure 1).
The motivation to combine is the same as in claim 2.
Regarding claim 4, Murray does not expressly disclose but Lawless teaches: wherein the in vivo protein is a receptor or an ion channel (comparing electric stimulus from a battery with contact with a metal as shown in Figure 1; oral chemoreceptors in Abstract; “Electrical stimulation is widely accepted to occur via activation of taste receptors,” page 9).
The motivation to combine is the same as in claim 2.
Regarding claim 5, Murray does not expressly disclose but Lawless teaches: wherein a numerical value of the electrical condition data is a numerical value corresponding to an intensity of the electrical condition data required to activate, even when a certain substance is not provided to the in vivo protein, the in vivo protein to the same extent as when the certain substance is provided to the in vivo protein (comparing electric stimulus from a battery with contact with a metal as shown in Figure 1 includes numerical readings that are equivalent to contact with the substance).
The motivation to combine is the same as in claim 2.
Regarding claim 12, Murray further discloses:
--wherein the storage unit further stores classification data including a plurality of classifications of the food, the electrical condition data in the storage unit is stored in association with the classification of the food, the control unit further includes a selection unit that causes the user to select the classification of the food (The mobile device may store sets of parameters of stimulation signals corresponding to various simulated flavors. To cause simulation of a desired flavor, the mobile device may then transmit a control signal include the parameters for the stimulation signal associated with the desired flavor, [0804]; “The mobile device 1058 includes software installed thereon for generating a user interface 1060 to enable a user to select a flavor to be simulated by the apparatus 102 p-2. In the example shown, the user interface is arranged to present a user with multiple selectable flavor options 1062. In the example shown, the user interface 1060 includes selectable flavor options A, B, C, D and E,” [1681]),
--the reading-out unit reads out, from the storage unit, the electrical condition data associated with the classification selected by the selection unit (“Parameters such as magnitude of the current, pulse duration, and/or pulse frequency may be controlled to simulate a desired flavor,” [0760]).
Murray does not expressly disclose, but Lawless teaches: the input unit inputs the impression of the taste when the user ingests an actual food corresponding to the selected classification in the state (subject consumes substance and reports impression, “salty and sour tastes reported for the mixture” on page 5).
The motivation to combine is the same as in claim 2.
Regarding claim 13, Murray further discloses: further comprising an imaging unit (“For example, the activator may be an optical scanner configured to scan and recognize an image (e.g., a barcode or QR code) printed on a surface the aerosol forming device to confirm its presence,” [0292]; [0447]-[0448]),
--wherein the electrical condition data in the storage unit is stored in association with the classification of the food (“The mobile device may store sets of parameters of stimulation signals corresponding to various simulated flavors. To cause simulation of a desired flavor, the mobile device may then transmit a control signal include the parameters for the stimulation signal associated with the desired flavor,” [0804]),
--the control unit includes a reading unit that reads a figure pattern from an image obtained by imaging, by the imaging unit, a subject on which the figure pattern in which the classification of the food is recorded is displayed and from which the classification of the food is visually recognizable (“Although not shown, the main body 102 and consumable 103 may comprise a further interface which may, for example, be in the form of an RFID reader, a barcode or QR code reader. This interface may be able to identify a characteristic (e.g., a type) of a consumable 103 engaged with the main body 102,” [1230]),
--the reading-out unit reads out, from the storage unit, the electrical condition data associated with the classification recorded in the figure pattern read by the reading unit (“This interface may be able to identify a characteristic (e.g., a type) of a consumable 103 engaged with the main body 102,” [1230]), and
Murray does not expressly disclose, but Lawless teaches: the input unit inputs the impression of the taste when the user ingests an actual food corresponding to the classification visually recognized from the subject in the state (subject consumes substance and reports impression, “salty and sour tastes reported for the mixture” on page 5).
The motivation to combine is the same as in claim 2.
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Murray (USP App. Pub. No. 2022/0022537) in view of Adoni (USP App. Pub. No. 2017/0011145) and Bradski (US20210103340A1).
Regarding claim 7, Murray does not expressly disclose but Adoni teaches:
Bradski teaches: wherein the reflection unit inputs the electrical condition data after the at least one information corresponding to the user and the impression are reflected to a (“In step 210, modeling program 104 determines a beta model. Modeling program 104 uses the vectors from the alpha model and user feedback to determine a variance between the two values. A direction of the variance is also determined. For example, modeling program 104 determines whether a dish need more or less sweet. The variance is determined for each taste vector,” [0033]; the beta model and variance are within the broadest reasonable interpretation of the congeniality degree because it is a metric indicating the appropriateness of the electrical signal based on the user’s experience or impression. Further, the beta flavor model is generated when the variance is greater than a threshold which is analogous to determining that congeniality is not good (high variance). “the user feedback has to match the model within a threshold variance. If modeling program 104 determines that the model does not match the user feedback (decision 208, NO branch), then modeling program 104 determines a beta model (step 210),” [0032])
Murray and Adoni do not expressly disclose that the model is updated using a machine learning model. Bradski teaches this: “One or more remote servers can be used to perform the processing 11602 (e.g., machine learning processing) to analyze sensor data” in [0844], determining user satisfaction in [1201], and machine learning techniques in [1194].
One of ordinary skill in the art would have been motivated before the effected filing date to expand Murray and Adoni’s electrical taste fine-tuning with the machine learning of Bradski because continuously monitoring user condition and learning to better understand satisfy a user’s preferences with machine learning would improve user satisfaction with the output (Bradski [0702]).
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Murray (USP App. Pub. No. 2022/0022537) in view of Adoni (USP App. Pub. No. 2017/0011145) and Sakaki (USP App. Pub. No. 2019/0082722).
Regarding claim 9, Murray does not expressly disclose but Sakaki teaches: wherein
the storage unit further stores a plurality of templates related to the electrical condition data, and
the generation unit causes the user to generate the electrical condition data by causing the user to select a desired template from among the templates and causing the user to rewrite the selected template (“The taste reproduction data is data on a component ratio of taste components for reproducing the taste by combining a plurality of the taste components. The taste reproduction device obtains a taste reproduced material such that the taste reproduction device selects at least two taste components among the plurality of the taste components based on the taste reproduction data and combines the selected taste components according to the component ratio,” [0008]; “The taste reproduction device combines a plurality of the taste components based on the taste reproduction data, thus reproducing the taste of the original food,” [0047]).
One of ordinary skill in the art would have been motivated before the effected filing date to expand Murray’s electrical taste fine-tuning with the taste combinations of Sakaki because using this would allow the stimulation to more accurately reproduce the desired taste experience (see Sakaki [0047]).
Response to arguments
Applicant's arguments filed 10/30/2025 have been fully considered and are discussed below.
Regarding the prior art rejections, Applicant argues that claim 1 is not obvious in view of Murray and Adoni because Adoni “fails to disclose the acquisition unit and the determination unit as claimed”. Remarks pages 11-12. As described above and in the previous Office action, Adoni teaches receiving “user feedback” via a user interface and modifying the model to reflect the user’s preferences. This amounts to an acquisition unit. Adoni also teaches using user feedback to determine a beta model and modify vectors to reflect a user’s preferences. This amounts to a determination unit. Applicant provides no specific rebuttal to the examiner’s mapping of the features of Adoni to the features of claim 1 (previously analyzed as claim 11). Applicant fails to consider that the broadest reasonable interpretation of these claimed terms includes Adoni’s features despite Adoni using different terminology. For these reasons, the arguments are not persuasive.
The arguments regarding the other claims are moot because the currently pending claims are rejected on different grounds, namely, combinations including Adoni and/or Bradski.
Conclusion
Applicant’s amendment necessitated the new ground(s) of rejection presented in this Office Action (See MPEP 706.07(a)). Accordingly, THIS ACTION IS MADE FINAL. 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 extension fee 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 JOSHUA BLANCHETTE whose telephone number is (571)272-2299. The examiner can normally be reached on Monday - Thursday 7:30AM - 6:00PM, EST.
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/JOSHUA B BLANCHETTE/ Primary Examiner, Art Unit 3624
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