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 .
Claim Objections
Claim 10 is objected to because of the following informalities: “haemoglobin” should be changed to “hemoglobin.” Appropriate correction is required.
Claim 19 is objected to because of the following informalities: “computerised” should be changed to “computerized.”
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim 19 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because it is directed to a computer program per se without any structural limitations. See MPEP 2106.03(I). Applicants should amend the claims to specify that the invention is directed to a non-transitory computer readable medium storing instructions which, when executed by a computerized device, cause the computerized device to perform a method of controlling a skincare device.
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.
Claim(s) 1-5 and 7-19 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by US 2023/0233871 A1 to Jafarzadeh.
As to claim 1, Jafarzadeh discloses a skincare device (see Abstract) comprising:
a spectral sensor configured to sense, at a frequency band outside of the visible spectrum (see [0054] – “The example skin care device 102 can also include a camera 126, such as a high-resolution camera, an ultraviolet (“UV”) camera, and/or an infrared camera, and a camera light 128.”), one or more characteristics of a user's skin ([0054] – “The example camera 126 and camera light 128 are configured to operate in cooperation to record images of a user's skin, including lesions, pigments, moles, hair, scars, etc.”); and
a controller configured to:
on the basis of the sensed one or more characteristics, identify one or more metabolic constituents of the user's skin (see [0077]-[0080] – “The example application 108 is configured to receive, from the skin care device 102, sensed biological characteristics of a user's skin. The application 108 is configured to analyse the biological characteristics to determine a diagnosis…The results can include an indication of a skin moisture level, a…collagen level, etc.”);
determine one or more skin features associated with the identified one or more constituents (see id.); and
control the skincare device to perform an action associated with the determined one or more skin features (see [0084] – “For anti-aging and/or skin sensitivity, the routine can specify that red LEDs 130 are to be activated for three minutes. For acne control, the routine can specify that blue LEDs 130 are to be activated for three minutes. After or during, the fluid dispenser module 138 dispenses an acne control fluid. The application 108 can then provide periodic reminders for subsequent acne treatments or application of the acne control lotion. For oily skin, the application 108 may specify that fluid for oily skin should be used and inserted into the device 102. The device 102 may then dispense the fluid. Other routines can be available for cleanser application, toner application, moisturizer application, use of an astringent, exfoliation application, and use of a facial mask.”).
As to claim 2, Jafarzadeh further discloses wherein:
the spectral sensor is configured to sense one or more further characteristics of the user's skin ([0079] – “The results can include an indication of a skin moisture level, a pH level, skin pigment information, collagen level, etc. In some embodiments, the application 108 can perform image analysis to identify wrinkles, blemishes, scars, acne, moles, etc. The application 108 can perform template matching to templates of known wrinkles, blemishes, scars, acne, moles, etc. In other embodiments, the application 108 can determine dimensions, shape, and/or depth of the wrinkles, blemishes, scars, acne, moles, etc. and use a machine learning model for identification.”); and
the controller is configured to determine, on the basis of the sensed one or more further characteristics, topological features associated with the user's skin (see id.);
wherein the one or more skin features are further determined on the basis of the topological features (wrinkles, etc., are topographical features).
As to claim 3, Jafarzadeh further discloses wherein the spectral sensor is configured to sense the one or more further characteristics at a frequency band at least partly within in the visible spectrum (see [0054] – “The example skin care device 102 can also include a camera 126, such as a high-resolution camera, an ultraviolet (“UV”) camera, and/or an infrared camera, and a camera light 128.”).
As to claim 4, Jafarzadeh further discloses wherein the controller is configured to:
process the sensed one or more further characteristics to generate an image of the user's skin ([0069]); and
determine the topological features by performing texture based image processing on the generated image ([0079] – “In some embodiments, the application 108 can perform image analysis to identify wrinkles, blemishes, scars, acne, moles, etc. The application 108 can perform template matching to templates of known wrinkles, blemishes, scars, acne, moles, etc.”).
As to claim 5, Jafarzadeh further discloses wherein the controller is configured to determine the one or more skin features by operating a classifier (see [0079] – such template matching qualifies as a classifier given that it assigns an input to a plurality of known classes, wrinkles, blemishes, etc.).
As to claim 7, Jafarzadeh further discloses wherein the classifier comprises a machine learning agent (see [0079] – “In other embodiments, the application 108 can determine dimensions, shape, and/or depth of the wrinkles, blemishes, scars, acne, moles, etc. and use a machine learning model for identification.”).
As to claim 8, Jafarzadeh further discloses wherein the one or more characteristics comprise reflectance characteristics (the camera necessarily measures reflected light).
As to claim 9, Jafarzadeh further discloses wherein:
the one or more characteristics comprise a plurality of reflectance characteristics; and
a first reflectance characteristic in the plurality is associated with a different wavelength of light to a second reflectance characteristic in the plurality (see [0086] – “The skin quality report 900 includes images of a user's skin recorded at different wavelengths of light 901, 902. The report 900 also includes information regarding skin moisture level in the form of a moisture analysis chart 903 and related information, possible causes for low moisture level, and recommendations for improving skin quality. Additionally, the report 900 can provide expert advice 904 and other useful information/recommendations to the user 905.”.
As to claim 10, Jafarzadeh further discloses wherein the one or more metabolic constituents comprise one or more of: protein, collagen, elastin, melanin, haemoglobin, blood oxygen saturation, water lipid, and sebum (see treatment of claim 1, collagen is specified).
As to claim 11, Jafarzadeh further discloses wherein the determined one or more skin features comprise one or more of: passive skin wrinkles, active skin wrinkles, fine lines, skin roughness, and enlarged pores (see [0078] – wrinkles, texture, and pores are specified) .
As to claim 12, Jafarzadeh further discloses wherein the action comprises adjusting one or more operating settings of the skincare device (see [0084]).
As to claim 13, Jafarzadeh further discloses wherein the action comprises generating an alert, wherein the alert comprises one or more of: a visible alert, an audible alert, and a tactile alert (see [0081]-[0083] – a recommendation is a prompt for the user to take action).
As to claim 14, Jafarzadeh further discloses wherein:
the device comprises a light source configured to emit light onto the user's skin (see [0084]); and
the action comprises controlling one or more parameters of light emission by the light source (see [0084]).
As to claim 15, Jafarzadeh further discloses wherein the action comprises providing an output to a user interface (see [0081]).
As to claim 16, Jafarzadeh further discloses wherein the skincare device comprises the user interface (see Fig 1, element 148 and [0072]-[0073]).
As to claim 17, Jafarzadeh further discloses wherein:
the user interface is provided by a separate computing device (see Fig 1, element 104); and
providing the output comprises transmitting to the separate computing device a signal indicate of the output (see [0069]).
As to claim 18, Jafarzadeh discloses a method of controlling a skincare device, the method comprising:
sensing at a frequency band outside of the visible spectrum, one or more characteristics of a user's skin (see [0054] – “The example skin care device 102 can also include a camera 126, such as a high-resolution camera, an ultraviolet (“UV”) camera, and/or an infrared camera, and a camera light 128.”);
on the basis of the sensed one or more characteristics, identifying one or more metabolic constituents of the user's skin (see [0077]-[0080] – “The example application 108 is configured to receive, from the skin care device 102, sensed biological characteristics of a user's skin. The application 108 is configured to analyse the biological characteristics to determine a diagnosis…The results can include an indication of a skin moisture level, a…collagen level, etc.”);
determining one or more skin features associated with the identified one or more constituents (see id.); and
controlling the skincare device to perform an action associated with the determined one or more skin features (see [0084] – “For anti-aging and/or skin sensitivity, the routine can specify that red LEDs 130 are to be activated for three minutes. For acne control, the routine can specify that blue LEDs 130 are to be activated for three minutes. After or during, the fluid dispenser module 138 dispenses an acne control fluid. The application 108 can then provide periodic reminders for subsequent acne treatments or application of the acne control lotion. For oily skin, the application 108 may specify that fluid for oily skin should be used and inserted into the device 102. The device 102 may then dispense the fluid. Other routines can be available for cleanser application, toner application, moisturizer application, use of an astringent, exfoliation application, and use of a facial mask.”).
As to claim 19, Jafarzadeh discloses a computer program comprising a set of instructions, which, when executed by a computerised device, cause the computerised device to perform a method of controlling a skincare device, the method comprising:
sensing at a frequency band outside of the visible spectrum (see [0054] – “The example skin care device 102 can also include a camera 126, such as a high-resolution camera, an ultraviolet (“UV”) camera, and/or an infrared camera, and a camera light 128.”), one or more characteristics of a user's skin ([0054] – “The example camera 126 and camera light 128 are configured to operate in cooperation to record images of a user's skin, including lesions, pigments, moles, hair, scars, etc.”);
on the basis of the sensed one or more characteristics, identifying one or more metabolic constituents of the user's skin (see [0077]-[0080] – “The example application 108 is configured to receive, from the skin care device 102, sensed biological characteristics of a user's skin. The application 108 is configured to analyse the biological characteristics to determine a diagnosis…The results can include an indication of a skin moisture level, a…collagen level, etc.”);
determining one or more skin features associated with the identified one or more constituents (see id.); and
controlling the skincare device to perform an action associated with the determined one or more skin features (see [0084] – “For anti-aging and/or skin sensitivity, the routine can specify that red LEDs 130 are to be activated for three minutes. For acne control, the routine can specify that blue LEDs 130 are to be activated for three minutes. After or during, the fluid dispenser module 138 dispenses an acne control fluid. The application 108 can then provide periodic reminders for subsequent acne treatments or application of the acne control lotion. For oily skin, the application 108 may specify that fluid for oily skin should be used and inserted into the device 102. The device 102 may then dispense the fluid. Other routines can be available for cleanser application, toner application, moisturizer application, use of an astringent, exfoliation application, and use of a facial mask.”).
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.
Claim(s) 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jafarzadeh in view of US 2020/0280680 A1 to Nichols.
As to claim 6, while Jafarzadeh indicates that features may be determining using machine learning, the reference fails to indicate that the classifier has been trained using:
spectral sensor training data comprising characteristics of a corpus of training users' skin; and indications of known skin features of the corpus of training users.
Examiner believes that such training should be inherent in such machine learning. However, if it is not, in a similar invention Nichols teaches a machine learning tool that utilizes training data comprising characteristics of a corpus of training users' skin; and indications of known skin features of the corpus of training users. Jafarzadeh already discloses gathering data comprising spectral sensor data, as pointed out in the treatment of claim 1. Nichols teaches training data comprising characteristics of a corpus of training users' skin; and indications of known skin features of the corpus of training users (see [0100] – “As one example, training images depicting human faces may be labeled with the locations within the image and associated depths of skin wrinkles within the images, which may be provided to a machine learning model in order to train the model to identify skin wrinkles (such as via one or more classification algorithms or model types) and predict a numeric depth of each identified wrinkle (such as via one or more regression algorithms or model types).”). It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to combine the machine learning of Jafarzadeh with the training techniques of Nichols in order to provide the predictable result of optimizing the performance of such a system.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Eric Messersmith whose telephone number is (571)270-7081. The examiner can normally be reached M-F, 830am-5pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, JACQUELINE CHENG can be reached at 571-272-5596. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ERIC J MESSERSMITH/Primary Examiner, Art Unit 3791