Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
This office action for the 18/865574 application is in response to the communications filed November 13, 2024.
Claims 1-15 were initially submitted November 13, 2024.
Claims 1, 3-7, 9-12 and 14 were amended November 13, 2024.
Claims 1-15 are currently pending and considered below.
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.
Claims 1-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
As per claim 1,
Step 1: The claim recites subject matter within a statutory category as a process.
Step 2A is a two-prong inquiry, in which Prong 1 determines whether a claim recites a judicial exception. Prong 2 determines if the additional limitations of the claim integrates the recited judicial exception into a practical application. If the additional elements of the claim fail to integrate the judicial exception into a practical application, claim is directed to the recited judicial exception, see MPEP 2106.04(II)(A).
Step 2A Prong 1: The claim contains subject matter that recites an abstract idea, with the steps of a method for facilitating interaction between a primary user and a secondary user of an oral care system, wherein the primary user is a user of an oral care device and the secondary user is a dental care professional, the method comprising: receiving as user input from the secondary user, oral examination findings corresponding to the primary user, wherein the findings comprise user-input values for a pre-defined set of standardized oral parameters which together define an examination finding set; applying an advice generation algorithm adapted to convert an examination finding set to oral care advice comprising one or more oral care advice items, the advice generation algorithm defining mappings between different possible values for the pre-defined set of standardized oral parameters and output oral care advice items; wherein each oral care advice item includes an encoded representation of acceptable parameter values for one or more oral cleaning parameters; and wherein the method further comprises, at a second location: an oral care device obtaining sensor data during one or more oral cleaning sessions of the primary user from sensors integrated in the oral care device, applying a sensor data conversion algorithm for converting the sensor data to an estimation of values for the one or more oral cleaning parameters for at least one oral cleaning session, comparing the estimated values for the one or more oral cleaning parameters with the acceptable parameter values encoded in the oral care advice, and generating an output based on the comparison.. These steps, as drafted, under the broadest reasonable interpretation recite:
certain methods of organizing human activity (e.g., fundamental economic principles or practices including: hedging; insurance; mitigating risk; etc., commercial or legal interactions including: agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations; etc., managing personal behavior or relationships or interactions between people including: social activities; teaching; following rules or instructions; etc.) but for recitation of generic computer components. That is, other than reciting steps as performed by the generic computer components, nothing in the claim element precludes the step from being directed to certain methods of organizing human activity. The identified abstract idea, law of nature, or natural phenomenon identified above, in the context of this claim, encompasses a certain method of organizing human activity, namely managing personal behavior or relationships or interactions between people. [Provide reasoning]. If a claim limitation, under its broadest reasonable interpretation, covers at least the recited methods of organizing human activity above, but for the recitation of generic computer components, then it falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. Accordingly, the claim recites an abstract idea. See MPEP 2106.04(a).
Step 2A Prong 2: The claim does not recite additional elements that integrate the judicial exception into a practical application. In particular, the additional elements do not integrate the abstract idea into a practical application, other than the abstract idea per se, because the additional elements amount to no more than limitations which:
add insignificant extra-solution activity to the abstract idea, see MPEP 2106.05(g), such as:
“at an input device at a first location” and “uploading the oral care advice to a record in a user database, the record associated with the identity of the primary user” which corresponds to mere data gathering and/or output.
Accordingly, this claim is directed to an abstract idea.
Step 2B: The claim does not recite additional elements that amount to significantly more than the judicial exception. As discussed above with respect to discussion of integration of the abstract idea into a practical application, the additional elements amount to no more than mere instructions to apply an exception, add insignificant extra-solution activity to the abstract idea, and/or generally link the abstract idea to a particular technological environment or field of use. Additionally, the additional limitations, identified as insignificant extra-solution activity to the abstract idea, amount to no more than limitations which amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields such as:
computer functions that have been identified by the courts as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity, see MPEP 2106.05(d)(II), such as:
“at an input device at a first location” which corresponds to receiving or transmitting data over a network.
“uploading the oral care advice to a record in a user database, the record associated with the identity of the primary user” which corresponds to storing and retrieving information in memory.
Looking at the limitations of the claim as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely recite an abstract idea and/or provide conventional computer implementation which does not impose a meaningful limit to integrate the abstract idea into a practical application and/or amount to no more than limitations which amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields.
As per claim 2,
Claim 2 depends from claim 1 and inherits all the limitations of the claim from which it depends. Claim 2 merely further defines the abstract idea and/or introduces additional elements that are insufficient to provide a practical application or something significantly more:
“wherein application of the sensor data conversion algorithm and/or the comparing of the estimated values for the cleaning parameters is performed by a processor of the oral care device or by a processor of a computing device communicably linked with the oral care device” introduces additional elements that is insufficient to provide a practical application or significantly more:
Step 2A Prong 2: In particular, the additional elements do not integrate the abstract idea into a practical application, other than the abstract idea per se, because the additional elements amount to no more than limitations which:
amount to mere instructions to apply an exception, see MPEP 2106.05(f), such as:
“wherein application of the sensor data conversion algorithm and/or the comparing of the estimated values for the cleaning parameters is performed by a processor of the oral care device or by a processor of a computing device communicably linked with the oral care device” which corresponds to merely using a computer as a tool to perform an abstract idea. Page 2 Lines 31-35 of the as-filed specification describes that the hardware that implements the steps of the abstract idea amounts to nothing more than a generic computer. Implementing an abstract idea on a generic computer, does not integrate the abstract idea into a practical application in Step 2A Prong Two or add significantly more in Step 2B, similar to how the recitation of the computer in the claim in Alice amounted to mere instructions to apply the abstract idea of intermediated settlement on a generic computer.
Looking at the limitations of the claim as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely recite an abstract idea and/or provide conventional computer implementation which does not impose a meaningful limit to integrate the abstract idea into a practical application and/or amount to no more than limitations which amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields.
As per claim 3,
Claim 3 depends from claim 1 and inherits all the limitations of the claim from which it depends. Claim 3 merely further defines the abstract idea and/or introduces additional elements that are insufficient to provide a practical application or something significantly more:
“wherein the one or more oral care advice items output from the advice generation algorithm are presented to the secondary user via a user interface, and wherein the secondary user is prompted to confirm, reject, or refine the one or more advice items using the user interface” further defines an additional element that was insufficient to provide a practical application and/or significantly more. The claim with this further defining limitation still corresponds to mere data gathering and/or output and receiving or transmitting data over a network.
Looking at the limitations of the claim as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely recite an abstract idea and/or provide conventional computer implementation which does not impose a meaningful limit to integrate the abstract idea into a practical application and/or amount to no more than limitations which amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields.
As per claim 4,
Claim 4 depends from claim 1 and inherits all the limitations of the claim from which it depends. Claim 4 merely further defines the abstract idea and/or introduces additional elements that are insufficient to provide a practical application or something significantly more:
“wherein the method further comprises, responsive to a user-activation of the oral care device, transmitting a notification signal to a computing device, the computing device establishing communication with the user database responsive to the activation signal and downloading the oral care advice and generating a user-perceptible output at the computing device or the oral care device indicative of the oral care advice” further defines an additional element that was insufficient to provide a practical application and/or significantly more. The claim with this further defining limitation still corresponds to mere data gathering and/or output and receiving or transmitting data over a network.
Looking at the limitations of the claim as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely recite an abstract idea and/or provide conventional computer implementation which does not impose a meaningful limit to integrate the abstract idea into a practical application and/or amount to no more than limitations which amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields.
As per claim 5,
Claim 5 depends from claim 1 and inherits all the limitations of the claim from which it depends. Claim 5 merely further defines the abstract idea and/or introduces additional elements that are insufficient to provide a practical application or something significantly more:
“wherein the oral care device is a powered toothbrush, and the sensors include one or more of: pressure sensors for sensing brushing pressure, an inertial measurement unit for use in determining a pose of the oral care device, and one or more optical sensors for optical interaction with oral surfaces during use of the device” introduces additional elements that is insufficient to provide a practical application or significantly more:
Step 2A Prong 2: In particular, the additional elements do not integrate the abstract idea into a practical application, other than the abstract idea per se, because the additional elements amount to no more than limitations which:
amount to mere instructions to apply an exception, see MPEP 2106.05(f), such as:
“wherein the oral care device is a powered toothbrush, and the sensors include one or more of: pressure sensors for sensing brushing pressure, an inertial measurement unit for use in determining a pose of the oral care device, and one or more optical sensors for optical interaction with oral surfaces during use of the device” which corresponds to merely using a computer as a tool to perform an abstract idea. Page 2 Lines 31-35 of the as-filed specification describes that the hardware that implements the steps of the abstract idea amounts to nothing more than a generic computer. Implementing an abstract idea on a generic computer, does not integrate the abstract idea into a practical application in Step 2A Prong Two or add significantly more in Step 2B, similar to how the recitation of the computer in the claim in Alice amounted to mere instructions to apply the abstract idea of intermediated settlement on a generic computer.
Looking at the limitations of the claim as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely recite an abstract idea and/or provide conventional computer implementation which does not impose a meaningful limit to integrate the abstract idea into a practical application and/or amount to no more than limitations which amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields.
As per claim 6,
Claim 6 depends from claim 1 and inherits all the limitations of the claim from which it depends. Claim 6 merely further defines the abstract idea and/or introduces additional elements that are insufficient to provide a practical application or something significantly more:
“wherein the method comprises presenting at said input device at the first location a graphical user interface, the graphical user interface defining discrete input fields, each corresponding to one of the standardized oral parameters, and wherein the oral examination findings are received as user input to the graphical user interface” further defines an additional element that was insufficient to provide a practical application and/or significantly more. The claim with this further defining limitation still corresponds to mere data gathering and/or output and receiving or transmitting data over a network.
Looking at the limitations of the claim as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely recite an abstract idea and/or provide conventional computer implementation which does not impose a meaningful limit to integrate the abstract idea into a practical application and/or amount to no more than limitations which amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields.
As per claim 7,
Claim 7 depends from claim 1 and inherits all the limitations of the claim from which it depends. Claim 7 merely further defines the abstract idea and/or introduces additional elements that are insufficient to provide a practical application or something significantly more:
“wherein the method comprises generating a user compliance report based on the comparison, indicative of a degree of compliance of the primary user with the oral care advice” further describes the abstract idea. This claim limitation is still directed to “Certain Methods of Organizing Human Activity” and therefore continues to recite an abstract idea.
“transmit the compliance report to a further device as a data package” further defines an additional element that was insufficient to provide a practical application and/or significantly more. The claim with this further defining limitation still corresponds to mere data gathering and/or output and receiving or transmitting data over a network.
Looking at the limitations of the claim as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely recite an abstract idea and/or provide conventional computer implementation which does not impose a meaningful limit to integrate the abstract idea into a practical application and/or amount to no more than limitations which amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields.
As per claim 8,
Claim 8 depends from claim 7 and inherits all the limitations of the claim from which it depends. Claim 8 merely further defines the abstract idea and/or introduces additional elements that are insufficient to provide a practical application or something significantly more:
“wherein the method further comprises uploading the compliance report to a server and storing it at the server in such a way as to be accessible by the secondary user via a computing device communicatively linked to the server” further defines an additional element that was insufficient to provide a practical application and/or significantly more. The claim with this further defining limitation still corresponds to mere data gathering and/or output and receiving or transmitting data over a network.
Looking at the limitations of the claim as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely recite an abstract idea and/or provide conventional computer implementation which does not impose a meaningful limit to integrate the abstract idea into a practical application and/or amount to no more than limitations which amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields.
As per claim 9,
Claim 9 depends from claim 1 and inherits all the limitations of the claim from which it depends. Claim 9 merely further defines the abstract idea and/or introduces additional elements that are insufficient to provide a practical application or something significantly more:
“wherein, following the generating of the oral care advice, the oral care advice is uploaded to a digital patient record associated with the primary user in a patient record database” further defines an additional element that was insufficient to provide a practical application and/or significantly more. The claim with this further defining limitation still corresponds to mere data gathering and/or output and storing and retrieving information in memory.
Looking at the limitations of the claim as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely recite an abstract idea and/or provide conventional computer implementation which does not impose a meaningful limit to integrate the abstract idea into a practical application and/or amount to no more than limitations which amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields.
As per claim 10,
Claim 10 depends from claim 1 and inherits all the limitations of the claim from which it depends. Claim 10 merely further defines the abstract idea and/or introduces additional elements that are insufficient to provide a practical application or something significantly more:
“wherein the output is a user-perceptible output indicative of the oral care advice, and optionally wherein the user- perceptible output is generated by the oral care device, e.g. by illumination of a subset of one or more LEDs comprised by the device, to provide a coded indication of the advice, or by control of an acoustic output device of the oral care device to play a spoken-language indication of the advice” further defines an additional element that was insufficient to provide a practical application and/or significantly more. The claim with this further defining limitation still corresponds to mere data gathering and/or output and receiving or transmitting data over a network.
Looking at the limitations of the claim as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely recite an abstract idea and/or provide conventional computer implementation which does not impose a meaningful limit to integrate the abstract idea into a practical application and/or amount to no more than limitations which amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields.
As per claim 11,
Claim 11 depends from claim 1 and inherits all the limitations of the claim from which it depends. Claim 11 merely further defines the abstract idea and/or introduces additional elements that are insufficient to provide a practical application or something significantly more:
“wherein the one or more oral care advice items output from the advice generation algorithm are items from a pre- determined list of oral care advice items” further describes the abstract idea. This claim limitation is still directed to “Certain Methods of Organizing Human Activity” and therefore continues to recite an abstract idea.
Looking at the limitations of the claim as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely recite an abstract idea and/or provide conventional computer implementation which does not impose a meaningful limit to integrate the abstract idea into a practical application and/or amount to no more than limitations which amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields.
As per claim 12,
Claim 12 depends from claim 1 and inherits all the limitations of the claim from which it depends. Claim 12 merely further defines the abstract idea and/or introduces additional elements that are insufficient to provide a practical application or something significantly more:
“wherein the advice generation algorithm comprises a lookup table which maps between findings and advice items” further describes the abstract idea. This claim limitation is still directed to “Certain Methods of Organizing Human Activity” and therefore continues to recite an abstract idea.
Looking at the limitations of the claim as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely recite an abstract idea and/or provide conventional computer implementation which does not impose a meaningful limit to integrate the abstract idea into a practical application and/or amount to no more than limitations which amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields.
As per claim 13,
Claim 13 is substantially similar to claim 1. Accordingly, claim 13 is rejected for the same reasons as claim 1.
Claim 14 further recites “A computer program product comprising code means configured when executed by a processor to perform either one of two methods according to a selected mode, wherein the method according to a first mode comprises” which is insufficient to provide a practical application or something significantly more because:
“A computer program product comprising code means configured when executed by a processor to perform either one of two methods according to a selected mode, wherein the method according to a first mode comprises” introduces additional elements that is insufficient to provide a practical application or significantly more:
Step 2A Prong 2: In particular, the additional elements do not integrate the abstract idea into a practical application, other than the abstract idea per se, because the additional elements amount to no more than limitations which:
amount to mere instructions to apply an exception, see MPEP 2106.05(f), such as:
“wherein the oral care device is a powered toothbrush, and the sensors include one or more of: pressure sensors for sensing brushing pressure, an inertial measurement unit for use in determining a pose of the oral care device, and one or more optical sensors for optical interaction with oral surfaces during use of the device” which corresponds to merely using a computer as a tool to perform an abstract idea. Page 2 Lines 31-35 of the as-filed specification describes that the hardware that implements the steps of the abstract idea amounts to nothing more than a generic computer. Implementing an abstract idea on a generic computer, does not integrate the abstract idea into a practical application in Step 2A Prong Two or add significantly more in Step 2B, similar to how the recitation of the computer in the claim in Alice amounted to mere instructions to apply the abstract idea of intermediated settlement on a generic computer.
Looking at the limitations of the claim as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely recite an abstract idea and/or provide conventional computer implementation which does not impose a meaningful limit to integrate the abstract idea into a practical application and/or amount to no more than limitations which amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields.
As per claim 14,
Claim 14 is substantially similar to claim 1. Accordingly, claim 14 is rejected for the same reasons as claim 1.
Claim 14 further recites “A system for use in facilitating interaction between a primary user and a secondary user, wherein the primary user is a user of an oral care device and the secondary user is a dental care professional, the system comprising: a first device at a first location comprising one or more processors and adapted to” which is insufficient to provide a practical application or something significantly more because:
“A system for use in facilitating interaction between a primary user and a secondary user, wherein the primary user is a user of an oral care device and the secondary user is a dental care professional, the system comprising: a first device at a first location comprising one or more processors and adapted to” introduces additional elements that is insufficient to provide a practical application or significantly more:
Step 2A Prong 2: In particular, the additional elements do not integrate the abstract idea into a practical application, other than the abstract idea per se, because the additional elements amount to no more than limitations which:
amount to mere instructions to apply an exception, see MPEP 2106.05(f), such as:
“wherein the oral care device is a powered toothbrush, and the sensors include one or more of: pressure sensors for sensing brushing pressure, an inertial measurement unit for use in determining a pose of the oral care device, and one or more optical sensors for optical interaction with oral surfaces during use of the device” which corresponds to merely using a computer as a tool to perform an abstract idea. Page 2 Lines 31-35 of the as-filed specification describes that the hardware that implements the steps of the abstract idea amounts to nothing more than a generic computer. Implementing an abstract idea on a generic computer, does not integrate the abstract idea into a practical application in Step 2A Prong Two or add significantly more in Step 2B, similar to how the recitation of the computer in the claim in Alice amounted to mere instructions to apply the abstract idea of intermediated settlement on a generic computer.
Looking at the limitations of the claim as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely recite an abstract idea and/or provide conventional computer implementation which does not impose a meaningful limit to integrate the abstract idea into a practical application and/or amount to no more than limitations which amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields.
As per claim 15,
Claim 15 depends from claim 14 and inherits all the limitations of the claim from which it depends. Claim 15 merely further defines the abstract idea and/or introduces additional elements that are insufficient to provide a practical application or something significantly more:
“wherein the second device is the oral care device or is a mobile computing device communicatively linked with the oral care device.” further defines an additional element that was insufficient to provide a practical application and/or significantly more. The claim with this further defining limitation still corresponds to merely using a computer as a tool to perform an abstract idea.
Looking at the limitations of the claim as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely recite an abstract idea and/or provide conventional computer implementation which does not impose a meaningful limit to integrate the abstract idea into a practical application and/or amount to no more than limitations which amount to elements that have been recognized as well-understood, routine, and conventional activity in particular fields.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1, 2, 4-7, and 9-15 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Gerhardt et al. (US 2023/0240438; herein referred to as Gerhardt).
As per claim 1,
Gerhardt discloses method for facilitating interaction between a primary user and a secondary user of an oral care system, wherein the primary user is a user of an oral care device and the secondary user is a dental care professional, the method comprising: receiving as user input from the secondary user, at an input device at a first location, oral examination findings corresponding to the primary user, wherein the findings comprise user-input values for a pre-defined set of standardized oral parameters which together define an examination finding set;
(Paragraphs [0098]-[0100] of Gerhardt. The teaching describes input for receiving oral geometry information in respect of a user [primary user] for whom an accessory is to be recommended. In one example, the oral geometry information is 3D scan data 30 received from an external database, which is for example populated by a dentist [secondary user] when an oral scan is prepared. In other example, the oral geometry information is extracted from 2D images. These may again be stored in a remoted database, but they may equally be generated by a camera of the mobile phone or by a special 3D camera for insertion into the mouth cavity fitted to a pole, which is activated within the oral cavity to capture 3D images. Oral scan data may for example be used as an input to a finite element or computer vision fitting algorithm to determine the cleaning efficacy.)
Gerhardt further discloses applying an advice generation algorithm adapted to convert an examination finding set to oral care advice comprising one or more oral care advice items, the advice generation algorithm defining mappings between different possible values for the pre-defined set of standardized oral parameters and output oral care advice items:
(Paragraphs [0102]-[0104] of Gerhardt. The teaching describes. an ideal oral care accessory, for example based on the modelling of brush head designs generated by selected building blocks (building sets which when assembled together will form a semi-customized brush head design) so that eventually a user-specific design can be manufactured. To enable a recommendation to be made, the external processor 23 is used to perform cleaning efficacy simulations. In particular, the interaction between an oral care accessories and the oral geometry of the user is modelled, based on the way the user performs their oral care routine. From this modelling, a cleaning metric can be derived representing the effectiveness of the oral care routine when using said one or more oral care accessories. A recommendation of a suitable oral care accessory to be used, from a set of different oral care accessories, is then provided.)
Gerhardt further discloses uploading the oral care advice to a record in a user database, the record associated with the identity of the primary user; wherein each oral care advice item includes an encoded representation of acceptable parameter values for one or more oral cleaning parameters:
(Paragraph [0105] of Gerhardt. The teaching describes that external processor 23 processes the geometry information and the user behavioral information thereby to provide this recommendation of a suitable oral care accessory from the set of pre-defined different oral care accessories. There is also the optional additional feature of designing an ideal oral care accessory by a design optimization process using predefined building blocks and building sets which when assembled together form a brush head. Such an optimal personalized design may be then provided to a digital manufacturing plant 35, or shared with a connected platform or system 36 of a dental professional, insurance or oral care provider for example to obtain endorsement, or enable policy negotiations for subscription models allowing them to track progress of oral health conditions or oral care compliance when the new brush head is used.)
Gerhardt further discloses wherein the method further comprises, at a second location: an oral care device obtaining sensor data during one or more oral cleaning sessions of the primary user from sensors integrated in the oral care device, applying a sensor data conversion algorithm for converting the sensor data to an estimation of values for the one or more oral cleaning parameters for at least one oral cleaning session, comparing the estimated values for the one or more oral cleaning parameters with the acceptable parameter values encoded in the oral care advice, and generating an output based on the comparison:
(Paragraphs [0113]-[0120], [0173] and [0174] of Gerhardt. The teaching describes a recommendation can be based on modelling of how the user performs their cleaning routine (e.g. brushes or cleans or flosses) in combination with general and/or specific characteristics of the teeth and mouth. The outcome of the oral care routine can be optimized by varying certain parameters, e.g. brush head type, trim profile, brushing speed, force, brushing angles, time spend on each tooth element. The software algorithms and models implemented by the processor 23 are used to assess the brush head cleaning efficacy and enable performance prediction simulations. The recommendation is for example based on a bristle reach and contact stress model. The inputs for the recommendation system comprise: (i) A digital geometric model (CAD) or oral scan data sets of the subject's dentition. This can for example be obtained via intra-oral scanning or by first creating a mold of the dentition and creating a digital model from the scan or the mold, or from images/scans derived from sensor-based feedback. The scanning of the dentition and/or production of the models only has to be performed once, and can be performed either at a dentist's office or at a brush head resale point. This can also be done at home using dedicated equipment or via a smart phone extension or via a built-in camera system in the brush head. (ii) User specific brush handling data, such as orientation, force and movement. This data can be generated by a suitably sensorized brush head and/or brush handle, possibly in combination with external hardware, such as a camera or motion tracking system. (iii) Data related to the oral cleaning device: geometry, design limits, frequency, amplitude, material properties, etc. The system then makes use of a computational model using the subject-specific input in order to calculate the cleaning efficacy. The model can then be adapted to optimize efficacy. Variables that can be optimized can either be related to the brush head or the user handling technique or both. The model takes into account the relevant physics related to cleaning of the teeth through brushing, e.g. bending of bristles, contact and friction between bristles and between the bristles and teeth and gums. One example of the invention enables actual (or alternatively ideal) brushing behavior, in terms of forces, angles and speeds) and brush head geometries (trim profile, layout, materials) to be combined to create a personalized solution. One possible goal may be to predict a best performing brush head for a particular gum line or interdental arrangement, the most critical tooth region or geometry of a user (molar, pre-molar, incisor, canine, upper or lower jaw) based on historical medical data such as plaque maps or images, or for overall cleaning. The best performing brush head may be selected from a list of existing brush heads, based on parametric fitting, feature extraction and/or contact stress mapping as explained above.)
As per claim 2,
Gerhardt discloses the limitations of claim 1.
Gerhardt further discloses wherein application of the sensor data conversion algorithm and/or the comparing of the estimated values for the cleaning parameters is performed by a processor of the oral care device or by a processor of a computing device communicably linked with the oral care device:
(Paragraphs [0113]-[0120], [0173] and [0174] of Gerhardt. The teaching describes a recommendation can be based on modelling of how the user performs their cleaning routine (e.g. brushes or cleans or flosses) in combination with general and/or specific characteristics of the teeth and mouth. The outcome of the oral care routine can be optimized by varying certain parameters, e.g. brush head type, trim profile, brushing speed, force, brushing angles, time spend on each tooth element. The software algorithms and models implemented by the processor 23 are used to assess the brush head cleaning efficacy and enable performance prediction simulations. The recommendation is for example based on a bristle reach and contact stress model. The inputs for the recommendation system comprise: (i) A digital geometric model (CAD) or oral scan data sets of the subject's dentition. This can for example be obtained via intra-oral scanning or by first creating a mold of the dentition and creating a digital model from the scan or the mold, or from images/scans derived from sensor-based feedback. The scanning of the dentition and/or production of the models only has to be performed once, and can be performed either at a dentist's office or at a brush head resale point. This can also be done at home using dedicated equipment or via a smart phone extension or via a built-in camera system in the brush head. (ii) User specific brush handling data, such as orientation, force and movement. This data can be generated by a suitably sensorized brush head and/or brush handle, possibly in combination with external hardware, such as a camera or motion tracking system. (iii) Data related to the oral cleaning device: geometry, design limits, frequency, amplitude, material properties, etc. The system then makes use of a computational model using the subject-specific input in order to calculate the cleaning efficacy. The model can then be adapted to optimize efficacy. Variables that can be optimized can either be related to the brush head or the user handling technique or both. The model takes into account the relevant physics related to cleaning of the teeth through brushing, e.g. bending of bristles, contact and friction between bristles and between the bristles and teeth and gums. One example of the invention enables actual (or alternatively ideal) brushing behavior, in terms of forces, angles and speeds) and brush head geometries (trim profile, layout, materials) to be combined to create a personalized solution. One possible goal may be to predict a best performing brush head for a particular gum line or interdental arrangement, the most critical tooth region or geometry of a user (molar, pre-molar, incisor, canine, upper or lower jaw) based on historical medical data such as plaque maps or images, or for overall cleaning. The best performing brush head may be selected from a list of existing brush heads, based on parametric fitting, feature extraction and/or contact stress mapping as explained above.)
As per claim 4,
Gerhardt discloses the limitations of claim 1.
Gerhardt further discloses wherein the method further comprises, responsive to a user-activation of the oral care device, transmitting a notification signal to a computing device, the computing device establishing communication with the user database responsive to the activation signal and downloading the oral care advice and generating a user-perceptible output at the computing device or the oral care device indicative of the oral care advice:
(Paragraphs [0106], [0113]-[0120], [0173] and [0174] of Gerhardt. The teaching describes a recommendation can be based on modelling of how the user performs their cleaning routine (e.g. brushes or cleans or flosses) in combination with general and/or specific characteristics of the teeth and mouth. The outcome of the oral care routine can be optimized by varying certain parameters, e.g. brush head type, trim profile, brushing speed, force, brushing angles, time spend on each tooth element. The software algorithms and models implemented by the processor 23 are used to assess the brush head cleaning efficacy and enable performance prediction simulations. The recommendation is for example based on a bristle reach and contact stress model. The inputs for the recommendation system comprise: (i) A digital geometric model (CAD) or oral scan data sets of the subject's dentition. This can for example be obtained via intra-oral scanning or by first creating a mold of the dentition and creating a digital model from the scan or the mold, or from images/scans derived from sensor-based feedback. The scanning of the dentition and/or production of the models only has to be performed once, and can be performed either at a dentist's office or at a brush head resale point. This can also be done at home using dedicated equipment or via a smart phone extension or via a built-in camera system in the brush head. (ii) User specific brush handling data, such as orientation, force and movement. This data can be generated by a suitably sensorized brush head and/or brush handle, possibly in combination with external hardware, such as a camera or motion tracking system. (iii) Data related to the oral cleaning device: geometry, design limits, frequency, amplitude, material properties, etc. The system then makes use of a computational model using the subject-specific input in order to calculate the cleaning efficacy. The model can then be adapted to optimize efficacy. Variables that can be optimized can either be related to the brush head or the user handling technique or both. The model takes into account the relevant physics related to cleaning of the teeth through brushing, e.g. bending of bristles, contact and friction between bristles and between the bristles and teeth and gums. One example of the invention enables actual (or alternatively ideal) brushing behavior, in terms of forces, angles and speeds) and brush head geometries (trim profile, layout, materials) to be combined to create a personalized solution. One possible goal may be to predict a best performing brush head for a particular gum line or interdental arrangement, the most critical tooth region or geometry of a user (molar, pre-molar, incisor, canine, upper or lower jaw) based on historical medical data such as plaque maps or images, or for overall cleaning. The best performing brush head may be selected from a list of existing brush heads, based on parametric fitting, feature extraction and/or contact stress mapping as explained above. An animation of the optimal cleaning technique may also be generated, e.g. by the external processor 23, for display to the user on the mobile phone 22. These simulations may include user feedback relating to the expected cleaning performance of the brush head on the oral geometry of the user.)
As per claim 5,
Gerhardt discloses the limitations of claim 1.
Gerhardt further discloses wherein the oral care device is a powered toothbrush, and the sensors include one or more of: pressure sensors for sensing brushing pressure, an inertial measurement unit for use in determining a pose of the oral care device, and one or more optical sensors for optical interaction with oral surfaces during use of the device:
(Paragraphs [0113]-[0120], [0173] and [0174] of Gerhardt. The teaching describes a recommendation can be based on modelling of how the user performs their cleaning routine (e.g. brushes or cleans or flosses) in combination with general and/or specific characteristics of the teeth and mouth. The outcome of the oral care routine can be optimized by varying certain parameters, e.g. brush head type, trim profile, brushing speed, force, brushing angles, time spend on each tooth element. The software algorithms and models implemented by the processor 23 are used to assess the brush head cleaning efficacy and enable performance prediction simulations. The recommendation is for example based on a bristle reach and contact stress model. The inputs for the recommendation system comprise: (i) A digital geometric model (CAD) or oral scan data sets of the subject's dentition. This can for example be obtained via intra-oral scanning or by first creating a mold of the dentition and creating a digital model from the scan or the mold, or from images/scans derived from sensor-based feedback. The scanning of the dentition and/or production of the models only has to be performed once, and can be performed either at a dentist's office or at a brush head resale point. This can also be done at home using dedicated equipment or via a smart phone extension or via a built-in camera system in the brush head. (ii) User specific brush handling data, such as orientation, force and movement. This data can be generated by a suitably sensorized brush head and/or brush handle, possibly in combination with external hardware, such as a camera or motion tracking system. (iii) Data related to the oral cleaning device: geometry, design limits, frequency, amplitude, material properties, etc. The system then makes use of a computational model using the subject-specific input in order to calculate the cleaning efficacy. The model can then be adapted to optimize efficacy. Variables that can be optimized can either be related to the brush head or the user handling technique or both. The model takes into account the relevant physics related to cleaning of the teeth through brushing, e.g. bending of bristles, contact and friction between bristles and between the bristles and teeth and gums. One example of the invention enables actual (or alternatively ideal) brushing behavior, in terms of forces, angles and speeds) and brush head geometries (trim profile, layout, materials) to be combined to create a personalized solution. One possible goal may be to predict a best performing brush head for a particular gum line or interdental arrangement, the most critical tooth region or geometry of a user (molar, pre-molar, incisor, canine, upper or lower jaw) based on historical medical data such as plaque maps or images, or for overall cleaning. The best performing brush head may be selected from a list of existing brush heads, based on parametric fitting, feature extraction and/or contact stress mapping as explained above.)
As per claim 6,
Gerhardt discloses the limitations of claim 1.
Gerhardt further discloses wherein the method comprises presenting at said input device at the first location a graphical user interface, the graphical user interface defining discrete input fields, each corresponding to one of the standardized oral parameters, and wherein the oral examination findings are received as user input to the graphical user interface:
(Paragraphs [0098]-[0100] of Gerhardt. The teaching describes input for receiving oral geometry information in respect of a user [primary user] for whom an accessory is to be recommended. In one example, the oral geometry information is 3D scan data 30 received from an external database, which is for example populated by a dentist [secondary user] when an oral scan is prepared. In other example, the oral geometry information is extracted from 2D images. These may again be stored in a remoted database, but they may equally be generated by a camera of the mobile phone or by a special 3D camera for insertion into the mouth cavity fitted to a pole, which is activated within the oral cavity to capture 3D images. Oral scan data may for example be used as an input to a finite element or computer vision fitting algorithm to determine the cleaning efficacy.)
As per claim 7,
Gerhardt discloses the limitations of claim 1.
Gerhardt further discloses wherein the method comprises generating a user compliance report based on the comparison, indicative of a degree of compliance of the primary user with the oral care advice and to transmit the compliance report to a further device as a data package:
(Paragraphs [0105] and [0106] of Gerhardt. The teaching describes that the external processor 23 processes the geometry information and the user behavioral information thereby to provide this recommendation of a suitable oral care accessory from the set of pre-defined different oral care accessories. There is also the optional additional feature of designing an ideal oral care accessory by a design optimization process using predefined building blocks and building sets which when assembled together form a brush head. Such an optimal personalized design may be then provided to a digital manufacturing plant 35, or shared with a connected platform or system 36 of a dental professional, insurance or oral care provider for example to obtain endorsement, or enable policy negotiations for subscription models allowing them to track progress of oral health conditions or oral care compliance when the new brush head is used. An animation of the optimal cleaning technique may also be generated, e.g. by the external processor 23, for display to the user on the mobile phone 22. These simulations may include user feedback relating to the expected cleaning performance of the brush head on the oral geometry of the user.)
As per claim 9,
Gerhardt discloses the limitations of claim 1.
Gerhardt further discloses wherein, following the generating of the oral care advice, the oral care advice is uploaded to a digital patient record associated with the primary user in a patient record database:
(Paragraphs [0024] and [0025] of Gerhardt. The teaching describes that recommendation can be based on modelling the shear energy (sliding work) or frictional power. For example, a pressure threshold can be used to distinguish between cleaned and non-cleaned areas, where the thresholds can for example cover ranges of pressures such as <1 kPa, 1-10 kPa, 10-30 kPa, 30-50 kPa, and >50 kPa, depending on the material to be removed. This information can be translated into area fractions of cleaned teeth or percentages of clean tooth and then further be utilized in providing the recommendation, and/or other advice and feedback to the user. For example, a video animation of the person-specific simulated cleaning process can be send to an App of a user providing him indirect feedback or information on the effectiveness of the recommended or currently used brush head, and how the cleaning effectiveness will change if a different brushing technique (which is referred to as “behavioral information” in the text below) is used. It can also show the effect of the oral accessory (brush head) wearing out over time. The system may comprise an input for receiving input data comprising medical information for the user. This medical information is for example not specific to the use of the device, and may comprise age, gender, and electronic medical record (EMR) information such as information on pregnancy or other comorbidities of relevance to oral healthcare. The EMR is for example accessible through a communication system to one or more databases of a hospital, insurance provider, dental provider, or government databases. For example, there may be oral health indices such as relating to plaque levels, stains, gum condition, halitosis. This information for example includes plaque maps (on top of the oral geometry information) or stain index images or other health related information such as pregnancy, gingivitis patient etc. As additional data is collected from the patient, this behavior information is understood to be uploaded to the medical record.)
As per claim 10,
Gerhardt discloses the limitations of claim 1.
Gerhardt further discloses wherein the output is a user-perceptible output indicative of the oral care advice, and optionally wherein the user- perceptible output is generated by the oral care device, e.g. by illumination of a subset of one or more LEDs comprised by the device, to provide a coded indication of the advice, or by control of an acoustic output device of the oral care device to play a spoken-language indication of the advice:
(Paragraphs [0105] and [0106] of Gerhardt. The teaching describes that the external processor 23 processes the geometry information and the user behavioral information thereby to provide this recommendation of a suitable oral care accessory from the set of pre-defined different oral care accessories. There is also the optional additional feature of designing an ideal oral care accessory by a design optimization process using predefined building blocks and building sets which when assembled together form a brush head. Such an optimal personalized design may be then provided to a digital manufacturing plant 35, or shared with a connected platform or system 36 of a dental professional, insurance or oral care provider for example to obtain endorsement, or enable policy negotiations for subscription models allowing them to track progress of oral health conditions or oral care compliance when the new brush head is used. An animation of the optimal cleaning technique may also be generated, e.g. by the external processor 23, for display to the user on the mobile phone 22. These simulations may include user feedback relating to the expected cleaning performance of the brush head on the oral geometry of the user.)
As per claim 11,
Gerhardt discloses the limitations of claim 1.
Gerhardt further discloses wherein the one or more oral care advice items output from the advice generation algorithm are items from a pre-determined list of oral care advice items:
(Paragraph [0174] of Gerhardt. The teaching describes predicting a best performing brush head for a particular gum line or interdental arrangement, the most critical tooth region or geometry of a user (molar, pre-molar, incisor, canine, upper or lower jaw) based on historical medical data such as plaque maps or images, or for overall cleaning. The best performing brush head may be selected from a list of existing brush heads, based on parametric fitting, feature extraction and/or contact stress mapping as explained above.)
As per claim 12,
Gerhardt discloses the limitations of claim 1.
Gerhardt further discloses wherein the advice generation algorithm comprises a lookup table which maps between findings and advice items:
(Paragraph [0109] of Gerhardt. The teaching describes that brushing behavior improvement may be achieved by recommending a reduction in force, a brushing angle change (increase or decrease), a longer brushing time, or a personalized device firmware update. The brushing behavior recommendation may be given by mapping of the actual and ideally intended brushing behavior (forces, angles, speeds, time per tooth location) onto the digitized personal dentition information [construed as a look-up table which maps information between findings and advice items] and running sensitivity analyses for critical brushing factors (i.e., computational modelling and simulations of interactions with different factors and settings) and providing the user with feedback as to how this affects the predicted cleaning performance of his chosen brush head.)
As per claim 13,
Claim 13 is substantially similar to claim 1. Accordingly, claim 13 is rejected for the same reasons as claim 1.
As per claim 14,
Claim 13 is substantially similar to claim 1. Accordingly, claim 13 is rejected for the same reasons as claim 1.
As per claim 15,
Gerhardt discloses the limitations of claim 14.
Gerhardt further discloses wherein the second device is the oral care device or is a mobile computing device communicatively linked with the oral care device:
(Paragraphs [0113]-[0120], [0173] and [0174] of Gerhardt. The teaching describes a recommendation can be based on modelling of how the user performs their cleaning routine (e.g. brushes or cleans or flosses) in combination with general and/or specific characteristics of the teeth and mouth. The outcome of the oral care routine can be optimized by varying certain parameters, e.g. brush head type, trim profile, brushing speed, force, brushing angles, time spend on each tooth element. The software algorithms and models implemented by the processor 23 are used to assess the brush head cleaning efficacy and enable performance prediction simulations. The recommendation is for example based on a bristle reach and contact stress model. The inputs for the recommendation system comprise: (i) A digital geometric model (CAD) or oral scan data sets of the subject's dentition. This can for example be obtained via intra-oral scanning or by first creating a mold of the dentition and creating a digital model from the scan or the mold, or from images/scans derived from sensor-based feedback. The scanning of the dentition and/or production of the models only has to be performed once, and can be performed either at a dentist's office or at a brush head resale point. This can also be done at home using dedicated equipment or via a smart phone extension or via a built-in camera system in the brush head. (ii) User specific brush handling data, such as orientation, force and movement. This data can be generated by a suitably sensorized brush head and/or brush handle, possibly in combination with external hardware, such as a camera or motion tracking system. (iii) Data related to the oral cleaning device: geometry, design limits, frequency, amplitude, material properties, etc. The system then makes use of a computational model using the subject-specific input in order to calculate the cleaning efficacy. The model can then be adapted to optimize efficacy. Variables that can be optimized can either be related to the brush head or the user handling technique or both. The model takes into account the relevant physics related to cleaning of the teeth through brushing, e.g. bending of bristles, contact and friction between bristles and between the bristles and teeth and gums. One example of the invention enables actual (or alternatively ideal) brushing behavior, in terms of forces, angles and speeds) and brush head geometries (trim profile, layout, materials) to be combined to create a personalized solution. One possible goal may be to predict a best performing brush head for a particular gum line or interdental arrangement, the most critical tooth region or geometry of a user (molar, pre-molar, incisor, canine, upper or lower jaw) based on historical medical data such as plaque maps or images, or for overall cleaning. The best performing brush head may be selected from a list of existing brush heads, based on parametric fitting, feature extraction and/or contact stress mapping as explained above.)
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 3 and 8 are rejected under 35 U.S.C. 103 as being unpatentable over Gerhardt in view of Lamb et al. (US 2013/0282695; herein referred to as Lamb).
As per claim 3,
Gerhardt discloses the limitations of claim 1.
Gerhardt does not explicitly teach wherein the one or more oral care advice items output from the advice generation algorithm are presented to the secondary user via a user interface, and wherein the secondary user is prompted to confirm, reject, or refine the one or more advice items using the user interface.
However, Lamb teaches one or more oral care advice items output from the advice generation algorithm are presented to the secondary user via a user interface, and wherein the secondary user is prompted to confirm, reject, or refine the one or more advice items using the user interface:
(Paragraphs [0034], [0035] and [0042]-[0050] of Lamb. The teaching describes evaluation of data from smart toothbrushes. It is understood that similar teachings could be applied to other field/types of devices (e.g., renal, cardiothoracic, etc.), a dental example is depicted and described for ease of illustration and simplicity purposes. As indicated in the diagram, this approach may provide dentists, toothbrush users, toothbrush manufacturers, dental practitioners, toothpaste and floss manufacturers, etc., with the analytics reports required to significantly improve tooth brushing. For example, this approach may be used to improve: tooth brush design (e.g., battery life, layout of bristles, mechanical brushing capabilities); methods of brushing (e.g., time of day, length of time brushing, frequency of brushing, amount of pressure used, etc.); and/or toothpaste design (e.g., amount of grit, whitening agents, decay prevention, plaque prevention, etc.). In step P1, data may be collected from a dental provider. Such data may comprise: cavity information (e.g., tooth position and surface); root canal information (e.g., tooth and surface); gum recession information; tooth sensitivity information; whiteness measurement information, etc. In step P2, data may be collected from the sensor-enabled toothbrush. Such data may comprise: brush position (e.g., tooth and surface, angle, etc.); brushing pressure; length of brushing time; battery charge time; battery current charge amount/level; type of brush head installed and when installed (e.g., engine 50 could determine an optimal time to change head); unique unit design identification (e.g., for brush and mechanism design parameters, such as speed, rotary, or back and forth, etc. to be accessed). In step P3, data may be collected from a user of the toothbrush. Such data may comprise: the type of toothpaste being used (e.g., received a scan, or other input such as separate input via a cloud application or the like); times of eating; types of food eaten; flossing times and amount; type of flossing used (string or tape or toothpick, etc.); whether the user is right-handed or left-handed, etc. Still yet, as shown in step P4, data may be collected from the toothbrush and/or toothpaste manufacturer(s). Such data may comprise: information pertaining to a design of the brush head (e.g., bristle material, size of bristles, length of bristles, number of bristles, angle of bristle cut, etc.); and information pertaining to the design of the mechanism (e.g., battery, type of brushing: rotary or back and forth, etc.); information pertaining to any toothpaste whitening agents present; fluoride types and other decay prevention agents; amount of toothpaste grit; plaque prevention agent(s) present; etc. It is understood that since the data collected in step P4 may be collected from a variety of sources, such data may be filtered and/or placed into a standard data format P5 that is recognizable/usable by the system. Regardless, once some or all of this data has been collected (and filtered/standardized), such data may be processed and analyzed in step P6, and potentially stored in step P7, so as to determine a user's dental progress and or hygiene. A set of reports may then be generated in step P8. As shown, such reports may be provided to a variety of recipients such as patient empowerment systems P9A, customer relationship management (CRM) system P9B, toothbrush manufacturers P9C, toothbrush users P9D, dental practitioners P9N, etc. The following steps may be performed: 1. A patient decides to enroll in a toothpaste/toothbrush program; 2. A dentist sends information regarding the patient's cavities (e.g., location and other related data), whiteness factors, enamel factors, etc., to the analytics engine; 3. The engine matches the patient's data to highest aggregate percentages of other patients in a database; 4. The engine analyzes these matched records to find the most effective toothpaste/toothbrush/frequency, pressure, bristle type, etc., for this type of patient; 5. Recommendations are passed back to the patient via the dentist; 6. The sensor-enabled toothbrush may monitor and provide real-time feedback to the patient if they are following the recommendations; 7. Follow up with the dentist by dentist inputting the resulting data from the sensor-enabled toothbrush and any dental exams; and8. The process may be repeated for follow-up care.)
It would have been obvious to one or ordinary skill in the art before the time of filing to add to the tooth brush teachings of Gerhardt, the toothbrush teachings of Lamb. Paragraph [0034] of Lamb teaches that the disclosed methods of its invention significantly improve tooth brushing. For example, this approach may be used to improve: tooth brush design (e.g., battery life, layout of bristles, mechanical brushing capabilities); methods of brushing (e.g., time of day, length of time brushing, frequency of brushing, amount of pressure used, etc.); and/or toothpaste design (e.g., amount of grit, whitening agents, decay prevention, plaque prevention, etc.). One of ordinary skill in the art in possession of Gerhardt prior to the time of filing would have looked to Lamb to achieve such improvements. One of ordinary skill in the art would have added to the teaching of Gerhardt, the teaching of Lamb based on this incentive without yielding unexpected results.
As per claim 8,
Gerhardt discloses the limitations of claim 7.
Gerhardt does not explicitly teach wherein the method further comprises uploading the compliance report to a server and storing it at the server in such a way as to be accessible by the secondary user via a computing device communicatively linked to the server.
However, Lamb teaches wherein the method further comprises uploading the compliance report to a server and storing it at the server in such a way as to be accessible by the secondary user via a computing device communicatively linked to the server:
(Paragraphs [0034], [0035] and [0042]-[0050] of Lamb. The teaching describes evaluation of data from smart toothbrushes. It is understood that similar teachings could be applied to other field/types of devices (e.g., renal, cardiothoracic, etc.), a dental example is depicted and described for ease of illustration and simplicity purposes. As indicated in the diagram, this approach may provide dentists, toothbrush users, toothbrush manufacturers, dental practitioners, toothpaste and floss manufacturers, etc., with the analytics reports required to significantly improve tooth brushing. For example, this approach may be used to improve: tooth brush design (e.g., battery life, layout of bristles, mechanical brushing capabilities); methods of brushing (e.g., time of day, length of time brushing, frequency of brushing, amount of pressure used, etc.); and/or toothpaste design (e.g., amount of grit, whitening agents, decay prevention, plaque prevention, etc.). In step P1, data may be collected from a dental provider. Such data may comprise: cavity information (e.g., tooth position and surface); root canal information (e.g., tooth and surface); gum recession information; tooth sensitivity information; whiteness measurement information, etc. In step P2, data may be collected from the sensor-enabled toothbrush. Such data may comprise: brush position (e.g., tooth and surface, angle, etc.); brushing pressure; length of brushing time; battery charge time; battery current charge amount/level; type of brush head installed and when installed (e.g., engine 50 could determine an optimal time to change head); unique unit design identification (e.g., for brush and mechanism design parameters, such as speed, rotary, or back and forth, etc. to be accessed). In step P3, data may be collected from a user of the toothbrush. Such data may comprise: the type of toothpaste being used (e.g., received a scan, or other input such as separate input via a cloud application or the like); times of eating; types of food eaten; flossing times and amount; type of flossing used (string or tape or toothpick, etc.); whether the user is right-handed or left-handed, etc. Still yet, as shown in step P4, data may be collected from the toothbrush and/or toothpaste manufacturer(s). Such data may comprise: information pertaining to a design of the brush head (e.g., bristle material, size of bristles, length of bristles, number of bristles, angle of bristle cut, etc.); and information pertaining to the design of the mechanism (e.g., battery, type of brushing: rotary or back and forth, etc.); information pertaining to any toothpaste whitening agents present; fluoride types and other decay prevention agents; amount of toothpaste grit; plaque prevention agent(s) present; etc. It is understood that since the data collected in step P4 may be collected from a variety of sources, such data may be filtered and/or placed into a standard data format P5 that is recognizable/usable by the system. Regardless, once some or all of this data has been collected (and filtered/standardized), such data may be processed and analyzed in step P6, and potentially stored in step P7, so as to determine a user's dental progress and or hygiene. A set of reports may then be generated in step P8. As shown, such reports may be provided to a variety of recipients such as patient empowerment systems P9A, customer relationship management (CRM) system P9B, toothbrush manufacturers P9C, toothbrush users P9D, dental practitioners P9N, etc. The following steps may be performed: 1. A patient decides to enroll in a toothpaste/toothbrush program; 2. A dentist sends information regarding the patient's cavities (e.g., location and other related data), whiteness factors, enamel factors, etc., to the analytics engine; 3. The engine matches the patient's data to highest aggregate percentages of other patients in a database; 4. The engine analyzes these matched records to find the most effective toothpaste/toothbrush/frequency, pressure, bristle type, etc., for this type of patient; 5. Recommendations are passed back to the patient via the dentist; 6. The sensor-enabled toothbrush may monitor and provide real-time feedback to the patient if they are following the recommendations; 7. Follow up with the dentist by dentist inputting the resulting data from the sensor-enabled toothbrush and any dental exams; and8. The process may be repeated for follow-up care.)
It would have been obvious to one or ordinary skill in the art before the time of filing to add to the tooth brush teachings of Gerhardt, the toothbrush teachings of Lamb. Paragraph [0034] of Lamb teaches that the disclosed methods of its invention significantly improve tooth brushing. For example, this approach may be used to improve: tooth brush design (e.g., battery life, layout of bristles, mechanical brushing capabilities); methods of brushing (e.g., time of day, length of time brushing, frequency of brushing, amount of pressure used, etc.); and/or toothpaste design (e.g., amount of grit, whitening agents, decay prevention, plaque prevention, etc.). One of ordinary skill in the art in possession of Gerhardt prior to the time of filing would have looked to Lamb to achieve such improvements. One of ordinary skill in the art would have added to the teaching of Gerhardt, the teaching of Lamb based on this incentive without yielding unexpected results.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHAD A NEWTON whose telephone number is (313)446-6604. The examiner can normally be reached M-F 8:00AM-4:00PM (EST).
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/CHAD A NEWTON/Primary Examiner, Art Unit 3681
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