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 .
Response to Arguments
The reply filed on 02/27/2026 has been entered. Claims 1-22 are pending in this application and have been considered below. Claim 18 is canceled by the applicant. Claim objections of claims 11, 12, and 19 and claim rejection under 35 U.S.C. 112(a) of claim 4 are withdrawn.
Applicant's arguments filed 02/27/2026 have been fully considered but they are not persuasive.
Argument 1:
The applicant argues that Moheb teaches taking one or more images of a gap, identified by the dentist, not the tooth.
Response:
The examiner maintains that Moheb teaches a camera to take images of a tooth, then the images are analyzed and it is among this analyzation that the interproximal gap can be identified (“First, in step 1, a dentist or dentists auxiliary uses a camera or scanner (for example camera 134) to take one or more images of a tooth. In step 2, the images are analyzed based on several criteria, and as a result a health assessment is provided in step 3 as a result of the analysis.” par. 36).
Argument 2:
The applicant argues that Moheb teaches a comparison of diagnostics of conditions of a same gap while claim 1 compares a characteristic of a gap to a previously identified gap.
Response:
The arguments of counsel cannot take the place of evidence in the record. In re Schulze, 346 F.2d 600, 602, 145 USPQ 716, 718 (CCPA 1965); In re Geisler, 116 F.3d 1465, 43 USPQ2d 1362 (Fed. Cir. 1997) ("An assertion of what seems to follow from common experience is just attorney argument and not the kind of factual evidence that is required to rebut a prima facie case of obviousness."). See MPEP § 716.01(c) for examples of attorney statements which are not evidence and which must be supported by an appropriate affidavit or declaration.
The examiner maintains that Moheb teaches comparing a characteristic of a gap to another gap (“Comparison module 1540 may then compare the output of each of the detection modules to decrease the chance of erroneous detection or false positive. Once the results are checked, an image that is appropriate for measurement by the measurement module 1550 is then used to determine the size of the lesions and/or interproximal invasions,” par. 63). While the examiner agrees that this embodiment of Moheb does not teach comparing a gap to a previously identified gap in the same session, this amendment can be overcome with the combination of the embodiment wherein; ("a dentist or dentists auxiliary uses a camera or scanner (for example camera 134) to take one or more images of a tooth. In step 2, the images are analyzed based on several criteria, and as a result a health assessment is provided in step 3 as a result of the analysis," par. 36) wherein multiple images are taken and multiple gaps can be identified in the same session. This combination is justified by Moheb wherein; (“It should be appreciated that the device 100 is only one example of a device 100, and that the device 100 may have more or fewer components than shown, may combine two or more components, or a may have a different configuration or arrangement of the components,” par. 26) and has been mapped in the following rejection below.
Priority
Receipt is acknowledged that application is a National Stage application of PCT
PCT/GB2021/052762. Priority to GB2020017.6 with a priority date of 12/17/2020 is
acknowledged under 35 USC 119(e) and 37 CFR 1.78.
Information Disclosure Statement
The IDSs dated 10/09/2025, 08/13/2025, 01/09/2025, 04/19/2024, 09/17/2023, and 08/21/2023 that have been previously considered remain placed in the application file. The IDS dated 02/09/2026 has been considered and placed in the application file.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. -An element in a claim for a combination may be
expressed as a means or step for performing a specified function without the recital of
structure, material, or acts in support thereof, and such claim shall be construed to cover the
corresponding structure, material, or acts described in the specification and equivalents
thereof.
The claims in this application are given their broadest reasonable interpretation
using the plain meaning of the claim language in light of the specification as it would be
understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the
description in the specification when 35 U.S.C. 112(f), is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the
following three-prong test will be interpreted under 35 U.S.C. 112(f):
(A) the claim limitation uses the term "means" or "step" or a term used as a substitute for "means" that is a generic placeholder (also called a nonce term or a nonstructural term having no specific structural meaning) for performing the claimed function;
(B) the term "means" or "step" or the generic placeholder is modified by functional language, typically, but not always linked by the transition word "for'' (e.g.,
"means for'') or another linking word or phrase, such as "configured to" or "so
that"; and
(C) the term "means" or "step" or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Absence of the word "means" (or "step") in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f). The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f), is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
This application includes one or more claim limitations that do not use the word "means," but are nonetheless being interpreted under 35 U.S.C. 112(f), because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier.
Such claim limitation is:
a controller configured to: process the generated image data to identify an
interproximal gap between adjacent teeth in the oral cavity of the user ... ; in claim 1.
Because this claim limitation is/are being interpreted under 35 U.S.C. 112(f), they
are being interpreted to cover the corresponding structure described in the specification
as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35
U.S.C. 112(f), applicant may: (1) amend the claim limitation(s) to avoid iUthem being
interpreted under 35 U.S. C. 112(f) (e.g., by reciting sufficient structure to perform the
claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s)
sufficient structure to perform the claimed function so as to avoid iUthem being
interpreted under 35 U.S.C. 112(f).
Claim Interpretation
Under MPEP 2143.03, "All words in a claim must be considered in judging the patentability of that claim against the prior art." In re Wilson, 424 F.2d 1382, 1385, 165 USPQ 494, 496 (CCPA 1970). As a general matter, the grammar and ordinary meaning of terms as understood by one having ordinary skill in the art used in a claim will dictate whether, and to what extent, the language limits the claim scope. Language that suggests or makes a feature or step optional but does not require that feature or step does not limit the scope of a claim under the broadest reasonable claim interpretation. In addition, when a claim requires selection of an element from a list of alternatives, the prior art teaches the element if one of the alternatives is taught by the prior art. See, e.g., Fresenius USA, Inc. v. Baxter Int’l, Inc., 582 F.3d 1288, 1298, 92 USPQ2d 1163, 1171 (Fed. Cir. 2009).
Claim 19 recite “at least one of” then listing “a shape of…,” “an appearance of…,” and “a position of….” Since “at least one of” is disjunctive, any one of the elements found in the prior art is sufficient to reject the claim. While citations have been provided for completeness and rapid prosecution, only one element is required. Because, on balance, it appears the disjunctive interpretation enjoys the most specification support and for that reason the disjunctive interpretation (one of A, B OR C) is being adopted for the purposes of this Office Action. Applicant’s comments and/or amendments relating to this issue are invited to clarify the claim language and the prosecution history.
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.
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 1-21 are rejected under 35 U.S.C. 103 as obvious over US Patent Publication 2021 0267733 A1, (Benetti) in view of US Patent Publication 2023 0248243 A1, (Moheb).
Claim 1
Regarding Claim 1, Benetti teaches an oral treatment device for use in treating an oral cavity of a user, the oral treatment device comprising: image sensor equipment operable to generate image data representing at least a portion of the oral cavity of the user; ("The detecting means may be arranged to transmit an optical signal or an audio signal towards the oral cavity. For example, the detecting means may comprise at least one acoustic transceiver or at least one optical transceiver. As another example, the detecting means may comprise one or more light transmitters, such as LEDs, for illuminating the oral cavity, and a camera for receiving light returned from the oral cavity and capturing an image of the oral cavity," par. 14) and a controller configured to: process the generated image data to identify an interproximal gap between adjacent teeth in the oral cavity of the user (The wavelength and/or intensity of the returned signal can also be indicative of the transmission of the signal into an interproximal gap between adjacent teeth of the user," par. 6) and control the oral treatment device to perform an action based on a result of the comparison ("The controller is preferably configured to sample a signal received from the detecting means when the detecting means is in a said reference position," par. 18).
Benetti does not explicitly teach all of a controller configured to: compare at least one characteristic of the image identified interproximal gap with at least one characteristic of one or more previously identified interproximal gaps of the oral cavity of the user identified during the same oral treatment session.
However, Moheb teaches a controller configured to: compare at least one characteristic of the image identified interproximal gap with at least one characteristic of [AltContent: textbox (Figure 15 shows the modules that compare the results of the detection modules.)]
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gaps of the oral cavity of the user ("As shown in FIG. 15 the output of these modules are analyzed by comparison module 1540. Comparison module 1540 may then compare the output of each of the detection modules to decrease the chance of erroneous detection or false positive," par. 63) identified during the same oral treatment session ("a dentist or dentists auxiliary uses a camera or scanner (for example camera 134) to take one or more images of a tooth. In step 2, the images are analyzed based on several criteria, and as a result a health assessment is provided in step 3 as a result of the analysis," par. 36).
It would have been obvious to a person having ordinary skill in the art before the time of the effective filing date of the claimed invention of the instant application to modify the oral cleaning appliance as taught by Benetti to use systems for detecting and measuring certain dental defects as taught by Moheb.
The suggestion/motivation for doing so would have been that, “It will be understood that the novel embodiments of the invention provide several advantages: a system for detecting various issues such as lesions can be used in combination with a software that considers issues such as health conditions, medications and lifestyle to classify a patent's risk and recommend proper restorative actions and/or maintenance program. Such a system brings about increased efficiency in a dental practice which in turn saves a considerable amount of cost and overhead, especially where more senior dentists need to evaluate the work on more junior dentists.” as noted by the Moheb disclosure in paragraph [0067].
It is recognized that the citations and evidence provided above are derived from potentially different embodiments of a single reference. Nevertheless, it 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 to employ combinations and sub-combinations of these complementary embodiments, because Moheb explicitly motivates doing so at least in paragraph [26] including “It should be appreciated that the device 100 is only one example of a device 100, and that the device 100 may have more or fewer components than shown, may combine two or more components, or a may have a different configuration or arrangement of the components” and otherwise motivating experimentation and optimization.
The rejection system of claim 1 above applies mutatis mutandis to the corresponding limitations of method claim 20 and computer program claim 21 while noting that the rejection above cites to both device and method disclosures. Claims 20 and 21 are mapped below for clarity of the record and to specify any new limitations not included in claim 1.
Claim 2
Regarding Claim 2, Benetti and Moheb teach the oral treatment device according to claim 1 as noted above. Benetti teaches the controller configured to: control the oral treatment device based on the determined similarity metric ("In the context of the present invention, a classification is done on a tooth, and then if there are lesions or interproximal invasions they will be detected and then they are segmented. Once the detected objects, which in this context will be lesions and interproximal invasions, are segmented, we can measure them," par. 57).
Benetti does not explicitly teach all of the controller configured is to: calculate, in dependence on a result of the comparison, a similarity metric indicating a level of similarity between the identified interproximal gap and the one or more previously identified interproximal gaps.
However, Moheb teaches the controller is configured to: calculate, in dependence on a result of the comparison, a similarity metric indicating a level of similarity between the identified interproximal gap and the one or more previously identified interproximal gaps ("a neural network can be trained to detect presence of lesions and interproximal invasions. Once a NN is trained, it can be fed an input, if the input has similarity within a degree to any of the sample data that was used during the training process, the NN then “classifies” the input and outputs a classification result," par. 51,52).
Benetti and Moheb are combined as per claim 1.
Claim 3
Regarding Claim 3, Benetti and Moheb teach the oral treatment device according to claim 2 as noted above. Benetti teaches the controller is configured to: control the oral treatment device to deliver a treatment to the identified interproximal gap ("a neural network can be trained to detect presence of lesions and interproximal invasions. Once a NN is trained, it can be fed an input, if the input has similarity within a degree to any of the sample data that was used during the training process, the NN then “classifies” the input and outputs a classification result," par. 51,52).
Benetti does not explicitly teach all of in response to the similarity metric indicating that the identified interproximal gap is different from the one or more previously identified interproximal gaps.
However, Moheb teaches in response to the similarity metric indicating that the identified interproximal gap is different from the one or more previously identified interproximal gaps (The controller is preferably configured to … actuate the treatment of the oral cavity of the user depending on the sampled signal," par. 18).
Benetti and Moheb are combined as per claim 1.
Claim 4
Regarding Claim 4, Benetti and Moheb teach the oral treatment device according to claim 2 as noted above.
Benetti does not explicitly teach all of in response to the similarity metric indicating that the identified interproximal gap is different from the one or more previously identified interproximal gaps, store image data representing the identified interproximal gap in a memory for use in subsequent identification of interproximal gaps.
However, Moheb teaches in response to the similarity metric indicating that the identified interproximal gap is different from the one or more previously identified interproximal gaps ("a neural network can be trained to detect presence of lesions and interproximal invasions. Once a NN is trained, it can be fed an input, if the input has similarity within a degree to any of the sample data that was used during the training process, the NN then “classifies” the input and outputs a classification result," par. 51,52), store image data representing the identified interproximal gap in a memory for use in subsequent identification of interproximal gaps ("Once the results are checked, an image that is appropriate for measurement by the measurement module 1550 is then used to determine the size of the lesions and/or interproximal invasions. Referring back to FIG. 1, the elements of FIG. 15 may be stored on memory 102 and the processor 110 can run the NN," par. 63,64).
Benetti and Moheb are combined as per claim 1.
Claim 5
Regarding Claim 5, Benetti and Moheb teach the oral treatment device according to claim 2 as noted above. Benetti teaches the controller is configured to: control the oral treatment device to prevent treatment delivery to the identified interproximal gap (The controller is preferably configured to … actuate the treatment of the oral cavity of the user depending on the sampled signal," par. 18).
Benetti does not explicitly teach all of in response to the similarity metric indicating that the identified interproximal gap is the same as at least one of the one or more previously identified interproximal gaps.
However, Moheb teaches in response to the similarity metric indicating that the identified interproximal gap is the same as at least one of the one or more previously identified interproximal gaps ("a neural network can be trained to detect presence of lesions and interproximal invasions. Once a NN is trained, it can be fed an input, if the input has similarity within a degree to any of the sample data that was used during the training process, the NN then “classifies” the input and outputs a classification result," par. 51,52).
Benetti and Moheb are combined as per claim 1.
Claim 6
Regarding Claim 6, Benetti and Moheb teach the oral treatment device according to claim 2 as noted above. Benetti teaches the controller is configured to:
determine an elapsed time from when the at least one of the one or more previously identified interproximal gaps was previously identified; ("In this embodiment, the control circuit 56 is arranged to temporarily switch, for example, from the first operating mode to the second operating mode when the button 18 is depressed for a duration which is longer than the preset period of time," par. 69) compare the determined elapsed time with a predetermined threshold; and control the oral treatment device based on a result of the comparison of the determined elapsed time with the predetermined threshold (Once the button 18 has been depressed for that period of time, the control circuit 56 operates the appliance 10 in the second operating mode until the button 18 is released by the user. If, whilst the appliance 10 is in the second operating mode, the button 18 is depressed for a duration which is shorter than the preset period of time, the control circuit 56 actuates a single treatment of the oral cavity, as in the first operating mode," par. 69).
Benetti does not explicitly teach all of in response to the similarity metric indicating that the identified interproximal gap is the same as at least one of the one or more previously identified interproximal gaps.
However, Moheb teaches in response to the similarity metric indicating that the identified interproximal gap is the same as at least one of the one or more previously identified interproximal gaps ("a neural network can be trained to detect presence of lesions and interproximal invasions. Once a NN is trained, it can be fed an input, if the input has similarity within a degree to any of the sample data that was used during the training process, the NN then “classifies” the input and outputs a classification result," par. 51,52).
Benetti and Moheb are combined as per claim 1.
Claim 7
Regarding Claim 7, Benetti and Moheb teach the oral treatment device according to claim 7 as noted above. Benetti teaches the controller is configured to: in response to the determined elapsed time being greater than the predetermined threshold, control the oral treatment device to deliver a treatment to the identified interproximal gap; ("Once the button 18 has been depressed for that period of time, the control circuit 56 operates the appliance 10 in the second operating mode until the button 18 is released by the user," par. 69 wherein the controller starts the treatment when the button is released instead of stopping it) and in response to the determined elapsed time being less than the predetermined threshold, control the oral treatment device to prevent treatment delivery to the identified interproximal gap ("If, whilst the appliance 10 is in the second operating mode, the button 18 is depressed for a duration which is shorter than the preset period of time, the control circuit 56 actuates a single treatment of the oral cavity, as in the first operating mode," par. 69 wherein the controller stops the treatment instead of starting it).
Benetti and Moheb are combined as per claim 1.
Claim 8
Regarding Claim 8, Benetti and Moheb teach the oral treatment device according to claim 1 as noted above.
Benetti does not explicitly teach all of the controller is configured to: process the generated image data using a data analysis algorithm configured to detect interproximal gaps.
However, Moheb teaches the controller is configured to: process the generated image data using a data analysis algorithm configured to detect interproximal gaps ("As part of detection of lesions and interproximal invasions, an output of a convolutional neural network needs to go through segmentation to isolate the perimeter of the lesion or the interproximal invasion for measurement," par. 57).
Benetti and Moheb are combined as per claim 1.
Claim 9
Regarding Claim 9, Benetti and Moheb teach the oral treatment device according to claim 8 as noted above.
Benetti does not explicitly teach all of the data analysis algorithm comprises a classification algorithm.
However, Moheb teaches the data analysis algorithm comprises a classification algorithm ("In the context of the present invention, a classification is done on a tooth, and then if there are lesions or interproximal invasions they will be detected and then they are segmented. Once the detected objects, which in this context will be lesions and interproximal invasions, are segmented, we can measure them," par. 57).
Benetti and Moheb are combined as per claim 1.
Claim 10
Regarding Claim 10, Benetti and Moheb teach the oral treatment device according to claim 8 as noted above.
Benetti does not explicitly teach all of the data analysis algorithm comprises a trained classification algorithm.
However, Moheb teaches the data analysis algorithm comprises a trained classification algorithm ("The NN can be trained by the training set to detect the presence of lesions and interproximal invasions," par. 62).
Benetti and Moheb are combined as per claim 1.
Claim 11
Regarding Claim 11, Benetti and Moheb teach the oral treatment device according to claim 1 as noted above.
Benetti does not explicitly teach all of the controller is configured to: process the generated image data to determine at least one characteristic of the identified interproximal gap.
However, Moheb teaches the controller is configured to: process the generated image data to determine at least one characteristic of the identified interproximal gap ("Once the detected objects, which in this context will be lesions and interproximal invasions, are segmented, we can measure them," par. 57).
Benetti and Moheb are combined as per claim 1.
Claim 12
Regarding Claim 12, Benetti and Moheb teach the oral treatment device according to claim 11 as noted above.
Benetti does not explicitly teach all of the controller is configured to: determine the at least one characteristic by processing the generated image data using a machine learning algorithm, the machine learning algorithm being trained to identify information for use in distinguishing between interproximal gaps.
However, Moheb teaches the controller is configured to: determine the at least one characteristic by processing the generated image data using a machine learning algorithm, the machine learning algorithm being trained to identify information for use in distinguishing between interproximal gaps ("In the context of the present invention, a classification is done on a tooth, and then if there are lesions or interproximal invasions they will be detected and then they are segmented. Once the detected objects, which in this context will be lesions and interproximal invasions, are segmented, we can measure them," par. 57).
Benetti and Moheb are combined as per claim 1.
Claim 13
Regarding Claim 13, Benetti and Moheb teach the oral treatment device according to claim 1 as noted above. Benetti teaches that the image sensor equipment comprises an intraoral camera ("the detecting means may comprise … a camera for receiving light returned from the oral cavity and capturing an image of the oral cavity," par. 14).
Benetti and Moheb are combined as per claim 1.
Claim 14
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Regarding Claim 14, Benetti and Moheb teach the oral treatment device according to claim 1 as noted above. Benetti teaches a head, and wherein the image sensor equipment is at least partially comprised in the head ("the control circuit 56 also transmits signals to, and receives signals from, a sensor 66. With reference to FIGS. 2(b) and 2(c), the sensor 66 is mounted on the head 22 of the appliance," par. 55).
Benetti and Moheb are combined as per claim 1.
Claim 15
Regarding Claim 15, Benetti and Moheb teach the oral treatment device according to claim 1 as noted above. Benetti teaches a handle, and wherein the image sensor equipment is at least partially comprised in the handle ("The controller is preferably located in the handle of the appliance. Whilst signals may be transmitted wirelessly from the detecting means to the controller, it is preferred that signals are transmitted from the detecting means to the controller along a physical transmission path located within the appliance," par. 24).
Benetti and Moheb are combined as per claim 1.
Claim 16
Regarding Claim 16, Benetti and Moheb teach the oral treatment device according to claim 1 as noted above. Benetti teaches a fluid delivery system for delivering working fluid to the oral cavity of the user ("the dental treatment system preferably comprises a fluid delivery system for delivering a working fluid to the oral cavity of the user," par. 29), and wherein the controller is configured to output a control signal to the fluid delivery system to control delivery of the working fluid based on a result of the comparison ("controller for actuating the delivery of working fluid depending on the received signal," par. 16).
Benetti and Moheb are combined as per claim 1.
Claim 17
Regarding Claim 17, Benetti and Moheb teach the oral treatment device according to claim 16 as noted above. Benetti teaches that the fluid delivery system comprises a fluid reservoir for storing the working fluid in the oral treatment device ("the present invention provides a dental treatment appliance comprising a fluid reservoir for storing a working fluid," par. 16).
Benetti and Moheb are combined as per claim 1.
Claim 19
Regarding Claim 19, Benetti and Moheb teach the oral treatment device according to claim 1 as noted above.
Benetti does not explicitly teach all of at least one characteristic of the identified interproximal gap is indicative of at least one of: a shape of the identified interproximal gap, an appearance of the identified interproximal gap , and a position of the identified interproximal gap.
However, Moheb teaches at least one characteristic of the identified interproximal gap is indicative of at least one of: a shape of the identified interproximal gap, an appearance of the identified interproximal gap, and a position of the identified interproximal gap ("Assume the that we can count the total number of pixels that represent the surface area of a tooth. After detection and segmentation of a lesion or interproximal invasion, we can count the number of pixels occupied by those and understand the relative measurement of the lesions or the interproximal invasion compared to the total surface area of the tooth," par. 58).
Benetti and Moheb are combined as per claim 1.
Claim 20
Regarding Claim 20, Benetti teaches a method of: operating an oral treatment device for use in treating an oral cavity of a user, the oral treatment device comprising: image sensor equipment operable to generate image data representing the oral cavity of the user; ("The detecting means may be arranged to transmit an optical signal or an audio signal towards the oral cavity. For example, the detecting means may comprise at least one acoustic transceiver or at least one optical transceiver. As another example, the detecting means may comprise one or more light transmitters, such as LEDs, for illuminating the oral cavity, and a camera for receiving light returned from the oral cavity and capturing an image of the oral cavity," par. 14) and a controller, ("The controller is preferably configured to sample a signal received from the detecting means when the detecting means is in a said reference position," par. 18) the method comprising, at the controller: processing the generated image data to identify an interproximal gap between adjacent teeth in the oral cavity of the user; (The wavelength and/or intensity of the returned signal can also be indicative of the transmission of the signal into an interproximal gap between adjacent teeth of the user," par. 6) and controlling the oral treatment device to perform an action based on a result of the comparison (The controller is preferably configured to … actuate the treatment of the oral cavity of the user depending on the sampled signal," par. 18).
Benetti does not explicitly teach all of comparing at least one characteristic of the identified interproximal gap with at least one characteristic of one or more previously identified interproximal gaps of the oral cavity of the user identified during the same oral treatment session.
However, Moheb teaches comparing at least one characteristic of the identified interproximal gap with at least one characteristic of one or more previously identified interproximal gaps of the oral cavity of the user ("As shown in FIG. 15 the output of these modules are analyzed by comparison module 1540. Comparison module 1540 may then compare the output of each of the detection modules to decrease the chance of erroneous detection or false positive," par. 63) identified during the same oral treatment session ("a dentist or dentists auxiliary uses a camera or scanner (for example camera 134) to take one or more images of a tooth. In step 2, the images are analyzed based on several criteria, and as a result a health assessment is provided in step 3 as a result of the analysis," par. 36).
It would have been obvious to a person having ordinary skill in the art before the time of the effective filing date of the claimed invention of the instant application to modify the oral cleaning appliance as taught by Benetti to use systems for detecting and measuring certain dental defects as taught by Moheb.
Benetti and Moheb are combined as per claim 1.
Claim 21
Regarding Claim 21, Benetti teaches a method of: operating an oral treatment device for use in treating an oral cavity of a user, the oral treatment device comprising image sensor equipment operable to generate image data representing the oral cavity of the user, ("The detecting means may be arranged to transmit an optical signal or an audio signal towards the oral cavity. For example, the detecting means may comprise at least one acoustic transceiver or at least one optical transceiver. As another example, the detecting means may comprise one or more light transmitters, such as LEDs, for illuminating the oral cavity, and a camera for receiving light returned from the oral cavity and capturing an image of the oral cavity," par. 14) the method comprising: processing the generated image data to identify an interproximal gap between adjacent teeth in the oral cavity of the user; ("The controller is preferably configured to sample a signal received from the detecting means when the detecting means is in a said reference position," par. 18) and controlling the oral treatment device to perform an action based on a result of the comparison (The controller is preferably configured to … actuate the treatment of the oral cavity of the user depending on the sampled signal," par. 18).
Benetti does not explicitly teach all of a computer program comprising a set of instructions which, when executed by a computerised device, cause the computerised device to perform a method of comparing at least one characteristic of the identified interproximal gap with at least one characteristic of one or more previously identified interproximal gaps of the oral cavity of the user identified during the same oral treatment session.
However, Moheb teaches a computer program comprising a set of instructions which, when executed by a computerised device, ("The data structures and code described in this detailed description are typically stored on a computer-readable storage medium, which may be any device or medium that can store code and/or data for use by a computer system," par. 69) cause the computerised device to perform a method of comparing at least one characteristic of the identified interproximal gap with at least one characteristic of one or more previously identified interproximal gaps of the oral cavity of the user ("As shown in FIG. 15 the output of these modules are analyzed by comparison module 1540. Comparison module 1540 may then compare the output of each of the detection modules to decrease the chance of erroneous detection or false positive," par. 63) identified during the same oral treatment session ("a dentist or dentists auxiliary uses a camera or scanner (for example camera 134) to take one or more images of a tooth. In step 2, the images are analyzed based on several criteria, and as a result a health assessment is provided in step 3 as a result of the analysis," par. 36).
It would have been obvious to a person having ordinary skill in the art before the time of the effective filing date of the claimed invention of the instant application to modify the oral cleaning appliance as taught by Benetti to use systems for detecting and measuring certain dental defects as taught by Moheb.
Benetti and Moheb are combined as per claim 1.
Claim 22
Regarding Claim 22, Benetti and Moheb teach the oral treatment device according to claim 1 as noted above.
Benetti does not explicitly teach all of wherein the at least one characteristic of one or more previously identified interproximal gaps is based on image data generated during the same oral treatment session using the same image sensor equipment.
However, Moheb teaches wherein the at least one characteristic of one or more previously identified interproximal gaps is based on image data ("As shown in FIG. 15 the output of these modules are analyzed by comparison module 1540. Comparison module 1540 may then compare the output of each of the detection modules to decrease the chance of erroneous detection or false positive," par. 63) generated during the same oral treatment session using the same image sensor equipment ("a dentist or dentists auxiliary uses a camera or scanner (for example camera 134) to take one or more images of a tooth. In step 2, the images are analyzed based on several criteria, and as a result a health assessment is provided in step 3 as a result of the analysis," par. 36).
Benetti and Moheb are combined as per claim 1.
Conclusion
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 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.
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/Karsten F. Lantz/Examiner, Art Unit 2664
Date: 4/23/2026
/JENNIFER MEHMOOD/Supervisory Patent Examiner, Art Unit 2664
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