Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 04/20/2026 has been entered.
DETAILED ACTION
Notices to Applicant
This communication is a non-final rejection. Claims 1-10 and 12-23, as filed 04/20/2026, 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 § 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.
Claim 17 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim does not fall within at least one of the four categories of patent eligible subject matter because it recites subject matter that does not fall within a statutory category. The claim recites a “product” but this product includes transitory signals per se. See MPEP 2106.03(II): For example, the BRI of machine readable media can encompass non-statutory transitory forms of signal transmission, such as a propagating electrical or electromagnetic signal per se. See In re Nuijten, 500 F.3d 1346, 84 USPQ2d 1495 (Fed. Cir. 2007). When the BRI encompasses transitory forms of signal transmission, a rejection under 35 U.S.C. 101 as failing to claim statutory subject matter would be appropriate. Thus, a claim to a computer readable medium that can be a compact disc or a carrier wave covers a non-statutory embodiment and therefore should be rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Paragraph [000100] of the specification suggests but does not require that the program be non-transitory. The claim should be amended to clarify that the program is a non-transitory computer-readable recording medium as set forth in that paragraph.
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, 14, 16-18, and 23 are rejected under 35 U.S.C. 103 as being unpatentable over Murray (USP App. Pub. No. 2022/0022537).
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]);
--the storage unit further stores information selected from the group consisting of: a) instrument information on the instrument, b) food information on food, c) environmental information on an intake environment, and d) combinations thereof (“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]); and
--the reflection unit further reflects the information in the electrical condition data stored in the storage unit (flavor library in [1686] is used to cause stimulation corresponding with desired flavor in, e.g., [0804]).
Murray’s real-time flavor personalization does not expressly disclose that the storage unit further stores information selected from the Markush group of this claim and that the reflection unit further reflects the information in the electrical condition data stored in the storage unit. However, this feature taught by Murray’s “flavor library” with parameters for stimulating various flavors in [1686]. To simulate a flavor, the device sends a control signal that includes the stored parameters associated with that flavor in [0804] and adapts those parameters for the user in [1665], thereby reflecting the stored electrical condition data. One of ordinary skill in the art before the effective filing date would have been motivated to expand Murray’s flavor personalization embodiment to include the stored flavor library embodiment because the flavor library would give users access to a wide range of flavors and adapting those flavors for the particular user would generate a more accurate and personalized output.
Additionally, it can be seen that each element is taught by either embodiment of Murray. The flavor library does not affect the normal functioning of the elements of the claim which are taught by Murray’s fine-tuning. Because the elements do not affect the normal functioning of each other, the results of their combination would have been predictable. Therefore, before the effective filing date of the claimed invention, it would have been obvious to combine the teachings of Murray as described above since the result is merely a combination of old elements, and, since the elements do not affect the normal functioning of each other, the results of the combination would have been predictable.
Regarding claim 6, Murray further discloses:
--wherein the storage unit further stores information selected from the group consisting of instrument information on the instrument, environmental information on an intake environment, and combinations thereof (“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 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]; [1665]).
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 16¸ Murray further discloses: wherein the electrical condition data includes 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.
Regarding claim 23, Murray discloses: the communication units included in the electrical condition data management apparatus and the instrument are devices conforming to a short-range wireless communication standard; the first transmission unit transmits the electrical condition data to the instrument via the communication unit (“Preferably, they may be communicatively coupled via a Bluetooth connection or other near-field communication method. In the example shown, the mobile device 1058 is a smartphone, however other types of mobile device may be used (e.g., tablet computer, laptop, etc.),” [1679]; [0243]).
Claims 15 and 19 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 15¸ Murray further discloses: wherein the electrical condition data changes a feeling of a (“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]).
Murray does not expressly disclose a basic taste, but Adoni teaches “taste vectors include[ing] sweet, salty, sour, bitter, and umami” in [0016] (see also [0028] and [0019]).
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 basic 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 19¸ Murray does not expressly disclose but Adoni teaches wherein the basic taste is a salty taste in [0016]. The motivation to combine is the same as in claim 15
Claims 2-5, 12-13, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Murray (USP App. Pub. No. 2022/0022537) in view of 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’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.
Regarding claim 20, Murray does not expressly disclose but Lawless teaches: wherein the electricity flows through the user who is ingesting food (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: 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]). The motivation to combine Murray and Adoni is the same as in claim 15. The Examiner further notes that Adoni’s modeling would bring further fine-tuning of the output signal.
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 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]).
Claim 21 and 22 are rejected under 35 U.S.C. 103 as being unpatentable over Murray (USP App. Pub. No. 2022/0022537) in view of Sazonov (USP App. Pub. No. 2018/0242908).
Regarding claim 21, Murray does not expressly disclose but Sazonov teaches: wherein the environmental information indicates whether the user is eating (monitoring food intake in FIGs. 26A-26C).
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 actual eating monitoring of Sazonov because automatically detecting whether a user is eating enables the taste augmentation to be tuned to the user’s actual meal context, thereby improving the accuracy of the taste fine-tuning of Murray.
Additionally, it can be seen that each element is taught by Murray or Sazonov. The eating monitor of Sazonov does not affect the normal functioning of the elements of the claim which are taught by Murray. Because the elements do not affect the normal functioning of each other, the results of their combination would have been predictable. Therefore, before the effective filing date of the claimed invention, it would have been obvious to combine the teachings of Murray and Sazonov as described above since the result is merely a combination of old elements, and, since the elements do not affect the normal functioning of each other, the results of the combination would have been predictable.
Regarding claim 22, Murray does not expressly disclose but Sazonov teaches: wherein the environmental information includes a meal timing (detecting meal time in [0066]; “The timing and duration of food intake instances may be measured and monitored along with the number of bites, chews and swallows,” [0081]).
The motivation to combine is ethe same as in claim 21.
Response to arguments
Applicant's arguments filed 04/20/2026 have been fully considered and are discussed below.
Regarding the prior art rejections, Applicant generally argues that the argues that combination of Murray and Adoni does not teach or suggest the amended claim 1, i.e., storing instrument information, food information, or environmental information. Remarks page 11. The Examiner partially agrees in that the previously relied-upon embodiment of Murray [0808] is better understood to “reflect “ the impression rather than storing this profile data. However, as described above, Murray [1686] discloses stored “taste profiles and calibration data” and stored “flavor library” which describes instrument parameters used for simulating various flavors. Thus claim 1 is obvious over Murray as described in greater detail above.
Conclusion
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/JOSHUA B BLANCHETTE/ Primary Examiner, Art Unit 3624
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