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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 3/21/2025 has been entered.
Status of the Claims
The status of the claims as of the response filed 3/21/2025 is as follows: Claims 2-5, 10-13, and 18-20 are cancelled, and all previously given rejections for these claims are considered moot. Claims 9, 14-17, 21-25 are withdrawn from consideration. Claims 1 and 6-8 are currently amended. Claims 26-29 are new. Claims 1, 6-8, and 26-29 are currently pending in the application.
Election/Restrictions
This application contains claims directed to the following patentably distinct species: the smart coffee machine species of claims 26-27; the smart oven species of claim 28; and the smart closet species of claim 29. The species are independent or distinct because they are directed to nonoverlapping types of smart appliances with different physical architectures and operational functions. For example, the smart coffee machine includes the exclusive characteristics of pouring a cup of coffee and selecting a style of brewing, size of coffee grind, type of coffee roast, coffee bean, or temperature of coffee brew. The smart oven includes the exclusive characteristics of pre-heating the oven. The smart closet includes the exclusive characteristics of identifying a garment and moving the garment to a more accessible location. In addition, these species are not obvious variants of each other based on the current record.
Applicant is required under 35 U.S.C. 121 to elect a single disclosed species, or a single grouping of patentably indistinct species, for prosecution on the merits to which the claims shall be restricted if no generic claim is finally held to be allowable. Currently, claim 1 is generic.
There is a serious search and/or examination burden for the patentably distinct species as set forth above because at least the following reason(s) apply: Separate search strategies will be needed to thoroughly evaluate the prior art for each invention. It is necessary to search for one of the inventions in a manner that is not likely to result in finding art pertinent to the other invention. The coffeemaker species will require, for example, searches related to a smart coffeemaker that can pour a cup of coffee and select a style of brewing, size of coffee grind, type of coffee roast, coffee bean, or temperature of coffee brew. The oven species will require, for example, searches related to a smart oven that can pre-heat the oven. The closet species will require, for example, searches related to a smart closet that can identify a garment and move the garment to a more accessible location.
Applicant is advised that the reply to this requirement to be complete must include (i) an election of a species to be examined even though the requirement may be traversed (37 CFR 1.143) and (ii) identification of the claims encompassing the elected species or grouping of patentably indistinct species, including any claims subsequently added. An argument that a claim is allowable or that all claims are generic is considered nonresponsive unless accompanied by an election.
The election may be made with or without traverse. To preserve a right to petition, the election must be made with traverse. If the reply does not distinctly and specifically point out supposed errors in the election of species requirement, the election shall be treated as an election without traverse. Traversal must be presented at the time of election in order to be considered timely. Failure to timely traverse the requirement will result in the loss of right to petition under 37 CFR 1.144. If claims are added after the election, applicant must indicate which of these claims are readable on the elected species or grouping of patentably indistinct species.
Should applicant traverse on the ground that the species, or groupings of patentably indistinct species from which election is required, are not patentably distinct, applicant should submit evidence or identify such evidence now of record showing them to be obvious variants or clearly admit on the record that this is the case. In either instance, if the examiner finds one of the species unpatentable over the prior art, the evidence or admission may be used in a rejection under 35 U.S.C. 103 or pre-AIA 35 U.S.C. 103(a) of the other species.
Upon the allowance of a generic claim, applicant will be entitled to consideration of claims to additional species which depend from or otherwise require all the limitations of an allowable generic claim as provided by 37 CFR 1.141.
During a telephone conversation with Theodore Mayer (Reg. No. 78910) on 6/5/2025 a provisional election was made without traverse to prosecute the invention of the smart coffee maker species, claims 26-27. Affirmation of this election must be made by applicant in replying to this Office action. Claims 28-29 are withdrawn from further consideration by the examiner, 37 CFR 1.142(b), as being drawn to a non-elected invention.
Applicant is reminded that upon the cancelation of claims to a non-elected invention, the inventorship must be corrected in compliance with 37 CFR 1.48(a) if one or more of the currently named inventors is no longer an inventor of at least one claim remaining in the application. A request to correct inventorship under 37 CFR 1.48(a) must be accompanied by an application data sheet in accordance with 37 CFR 1.76 that identifies each inventor by his or her legal name and by the processing fee required under 37 CFR 1.17(i).
Response to Amendment
Rejection Under 35 USC 101
The claims have been amended but the 35 USC 101 rejections for claims 1 and 6-8 are upheld.
Rejection Under 35 USC 103
The amendments made to the claims introduce limitations that are not fully addressed in the previous office action, and thus the corresponding 35 USC 103 rejections for claims 1 and 6-8 are withdrawn. However, Examiner will consider the amended claims in light of an updated prior art search and address their patentability with respect to prior art below.
Response to Arguments
Rejection Under 35 USC 101
On page 9 of the response filed 3/21/2025 Applicant argues that the amended claims amount to a practical application because they modify physical operation of a smart appliance, e.g. a coffee machine as in claims 26-27. Applicant’s arguments are fully considered, and are partially persuasive. Examiner notes that there is currently no particularity to the type of smart appliance being modified, nor what type of physical operation is being modified or how such a modification is effected in independent claim 1, such that this final limitation amounts to the idea of a solution without details of how a solution to a problem is accomplished and thus amounts to mere instructions to apply the exception (see MPEP 2106.05(f)). Accordingly, claim 1 as a whole is directed to an abstract idea without integration into a practical application, as explained in more detail below. However, Examiner agrees that claims 26 and 27 are patent eligible, because claim 26 specifies that the smart appliance is a smart coffee machine and that modifying physical operation of the smart machine comprises pouring a cup of coffee based on the predicted stressed cognitive state for the user, which shows that the method is achieved with a specific type of machine beyond a generic computer and includes details about what physical operation is modified such that a practical application of the abstract idea (i.e. physically pouring a cup of coffee using a smart coffee machine based on the smart coffee machine’s prediction of a user’s stressed cognitive state) is achieved. Accordingly, claims 26 and 27 are found to be patent eligible.
Examiner notes that arguments directed to claims 28 and 29 are considered moot because they are directed to non-elected claims.
Rejection Under 35 USC 103
On pages 10-11 of the response Applicant argues various deficiencies of the Nudd and Moloney references with respect to the newly added subject matter of amended claim 1. Applicant’s arguments are fully considered, but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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 and 6-8 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
In the instant case, claims 1, 6-8, and 26-27 are directed to a method (i.e. a process) such that each of the claims falls within one of the four statutory categories. Nevertheless, the claims fall within the judicial exception of an abstract idea.
Step 2A – Prong 1
Independent claim 1 recites steps that, under their broadest reasonable interpretations, cover certain methods of organizing human activity, e.g. managing personal behavior, relationships, or interactions between people. Specifically, the claim recites:
obtaining, by a smart appliance, biometric sensor data;
predicting, by the smart appliance, a stressed cognitive state for a user based on the biometric sensor data; and
based on the predicted stressed cognitive state for the user, modifying, by the smart appliance, physical operation of the smart appliance.
But for the recitation of generic computer components like a smart appliance and specifying that the method is “computer implemented,” these functions, when considered as a whole, describe a medical analysis operation that could be achieved by a medical professional managing their personal behavior and interacting with a patient. For example, a patient could provide biometric sensor data about themselves (e.g. heart rate, temperature, etc.) to a medical professional during an appointment or other interaction, and the medical professional could then analyze the received information to predict whether the user is in a stressed cognitive state and make recommendations based on the predicted stressed cognitive state. Thus, the steps recited in this claim describe various interactions and/or management of personal behavior and accordingly claim 1 recites an abstract idea in the form of a certain method of organizing human activity.
Dependent claims 6-8 and 26-27 inherit the limitations that recite an abstract idea from their dependence on claim 1, and thus these claims also recite an abstract idea under the Step 2A – Prong 1 analysis. In addition, claims 6-8 recite limitations that merely further describe the abstract idea identified in the independent claim. Specifically, claim 6 recites receiving a response to one or more conversational prompts and predicting the stressed cognitive state of the user based on content of the received response, which could be achieved as part of a clinician-patient interaction such as verbal conversation and diagnostic analysis. Claim 7 recites receiving second biometric sensor data and updating a cognitive state model based on the second biometric sensor data and the predicted stressed cognitive state for the user, which a clinician could achieve by receiving updated sensor data from a patient and updating their medical expertise for future cases based on the newly-received data in concert with the prediction. Claim 8 specifies receiving a user identifier and only generating the prediction if the user identifier matches the biometric sensor data, which a clinician could achieve by asking a patient for some kind of identifier (e.g. fingerprint, speaking voice, etc.) and only performing the cognitive state analysis when the patient’s identity is successfully verified against known biometric information.
However, recitation of an abstract idea is not the end of the analysis. Each of the claims must be analyzed for additional elements that indicate the abstract idea is integrated into a practical application to determine whether the claim is considered to be “directed to” an abstract idea.
Step 2A – Prong 2
The judicial exception is not integrated into a practical application. In particular, independent claim 1 does not include additional elements that integrate the abstract idea into a practical application. The additional elements of claim 1 include computer implementation of the method, a smart appliance to perform the obtaining and predicting steps, and modifying, by the smart appliance, physical operation of the smart appliance. These additional elements, when considered in the context of the claim as a whole, merely serve to automate interactions that could occur by and among human actors (as described above), and thus amount to instructions to apply the abstract idea via generic computer components (see MPEP 2106.05(f)). For example, various entities of a patient care team can interact to share information, make medical determinations, and make recommendations for modifying operations of devices. The use of a computer and smart appliance to achieve these functions merely digitizes or automates the otherwise-abstract operations of evaluating sensor data and sharing data. Examiner notes that there is currently no particularity to the type of smart appliance being modified, nor what type of physical operation is being modified or how such a modification is effected, such that this final limitation amounts to the idea of a solution without details of how a solution to a problem is accomplished and thus amounts to mere instructions to apply the exception (see MPEP 2106.05(f)). Accordingly, claim 1 as a whole is directed to an abstract idea without integration into a practical application.
The judicial exception recited in dependent claims 6-8 is also not integrated into a practical application under a similar analysis as above. Claims 6 and 8 are performed with the same additional elements introduced in claim 1, without introducing any new additional elements of their own, and accordingly also amount to mere instructions to apply the abstract idea using the same additional elements. Claim 7 recites updating specifically a cognitive state machine learning model, which merely digitizes and/or automates the updating of a clinician’s own medical expertise via a machine learning model recited at a high level of generality (i.e. no specific architecture, training methods, inputs mapped to outputs, weighted parameters, etc. are described) and thus amounts to instructions to apply the abstract idea.
Accordingly, the additional elements of claims 1 and 6-8 do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Claims 1 and 6-8 are directed to an abstract idea.
Examiner notes that claim 26 specifies that the smart appliance is a smart coffee machine and that modifying physical operation of the smart machine comprises pouring a cup of coffee based on the predicted stressed cognitive state for the user, which shows that the method is achieved with a specific type of machine beyond a generic computer and includes details about what physical operation is modified such that a practical application of the abstract idea (i.e. physically pouring a cup of coffee using a smart coffee machine based on the smart coffee machine’s prediction of a user’s stressed cognitive state) is achieved. Accordingly, claims 26 and 27 are found to be patent eligible.
Step 2B
Claims 1 and 6-8 do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of a computer and generic smart appliance for performing the obtaining, predicting, modifying, etc. steps of the invention amount to mere instructions to apply the exception. As evidence of the generic nature of the above recited additional elements, Examiner notes the following portions of Applicant’s specification:
[0036]: “Aspects of the present disclosure can be executed at one or more smart (i.e. network-connected) devices, such as household devices (such as cleaning appliances, smart closets, kitchen appliances such as coffee machines, ovens, or refrigerators, lighting systems, doorbells, TVs, media devices, massage equipment, chairs or couches), industrial devices (e.g. robotic equipment, additive and/or subtractive manufacturing systems), design equipment, personal grooming or hygiene devices (e.g. pools, spas, toothbrush, styling devices, automatic nail paining, hair-cut, make-up devices), mobility devices (e.g. vehicles, scooters, bicycles), networking systems (e.g. transportation systems for selecting transportation, personal/friendship/workplace networking systems), commercial devices (such as vending machines, robotic kitchens, cake decorating machines), workplace devices (such as scheduling systems, collaborative work systems, space planning and/or design systems), and/or educational devices (such as lesson or training planning systems).”
[0039]: “System 100 can include one or more processor 104 coupled with bus 102 for processing information. As such, system 100 can include a computing component. Processor 804 might be implemented using a general-purpose or special-purpose processing engine such as, for example, a microprocessor, controller, or other control logic.”
These disclosures do not indicate that the elements of the invention are particular machines, and instead provide many generic examples of computer hardware and high-level smart appliance types such that one of ordinary skill in the art would understand that generic computer components and smart appliances could be used to implement the invention.
Regarding the use of machine learning as in claim 7, Examiner points to paras. [0051]-[0052] of the specification, where the machine learning is described at a high level via many exemplary types of known machine learning techniques (e.g. feedforward neural network, convolutional neural network, long short-memory network, autoencoder network, deconvolutional network, support vector machine, inference and/or trained neural network, recurrent neural network, classification model, regression model, etc.). Accordingly, one of ordinary skill in the art would understand that many types of high-level machine learning algorithms could be applied in order to automate and/or digitize the otherwise-abstract function of determining a user’s cognitive state in an iterative/updated manner, and thus does not provide “significantly more” than the abstract idea itself.
Further, the combination of these additional elements is not expanded upon in the specification as a unique arrangement and as such relies on the knowledge of one of ordinary skill in the art to understand the combination of components within a computer system as a well-known and generic combination for automating an abstract idea that could otherwise be performed as a certain method of organizing human activity and thus do not provide an inventive concept. Additionally, the combination of a computer and smart appliance utilizing machine learning models to evaluate user data and modify operation of the smart appliance is a well-understood, routine, and conventional combination, as evidenced by at least Boulanger et al. (US 20210309252 A1) Fig. 3, [0023], [0051], & [0072]-[0074]; Nudd et al. (US 11633103 B1) abstract, Fig. 1B, & Col9 L54 – Col10 L54; and Hyman et al. (US 20220240713 A1) Fig. 2 & [0050]-[0052].
Analyzing these additional elements as an ordered combination adds nothing that is not already present when considering the elements individually; the overall effect of the computer and smart appliance implementation and machine learning in combination is to digitize and/or automate a cognitive state prediction operation that could otherwise be achieved as a certain method of organizing human activity. Thus, when considered as a whole and in combination, claims 1 and 6-8 are not patent eligible.
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 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.
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.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 6-8, and 26-27 are rejected under 35 U.S.C. 103 as being unpatentable over Hyman et al. (US 20220240713 A1) in view of Nudd et al. (US 11633103 B1).
Claim 1
Hyman teaches a computer implemented method comprising:
obtaining, by a smart appliance, biometric sensor data (Hyman Fig. 2, [0072], noting a beverage preparation machine (i.e. smart appliance) may receive biometric data from a user);
predicting, by the smart appliance, a stressed cognitive state for a user (Hyman [0050]-[0052], noting the beverage preparation machine can predict when a user is expected to be busy, stressed, tired, etc.);
based on the predicted stressed cognitive state for the user, modifying, by the smart appliance, physical operation of the smart appliance (Hyman [0051]-[0052], noting the beverage preparation machine can identify and automatically dispense (i.e. modify physical operation of the smart appliance) a recommended beverage for the user based on the predicted busy, stressed, tired, etc. state).
In summary, Hyman teaches a smart beverage preparation machine that can obtain biometric user data such as images, voice scans, etc. for user identification purposes (see [0072]-[0073]), and use machine learning techniques to predict a stressed cognitive state for a user (e.g. based on calendar information acquired from the user’s electronic device as in [0051]) and prepare a recommended beverage for the user based on their predicted stressed cognitive state. Though the reference contemplates both obtaining biometric sensor data and predicting a stressed cognitive state for a user, it fails to explicitly disclose predicting a stressed cognitive state for a user specifically based on the received biometric sensor data as required by the instant claim. However, Nudd teaches that a stressed cognitive state may be determined by analyzing biometric sensor data of a user such as voice data (Nudd Col10 L55 – Col11 L19, Col16 L61 – Col17 L4, Col23 L7-9, Col30 L32-54, noting a system that generates conversational prompts to a user and evaluates the user’s cognitive state and stress levels based on voice stress analysis). It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify stressed cognitive state predictions of Hyman to further include analysis of acquired biometric sensor data as in Nudd in order to incorporate additional data types that are known to be predictive of stressed cognitive state (as suggested by Nudd Col11 L16-19) such that the predictive accuracy of the system is improved.
Claim 6
Hyman in view of Nudd teaches the method of claim 1, and the combination further teaches receiving, by the smart appliance, a response to one or more conversational prompts (Hyman Fig. 2, [0035], [0080], noting the beverage preparation machine can provide information to a user via speakers and receive user input from a microphone, considered equivalent to receiving a response to one or more conversational prompts; see also Nudd Col10 L55 – Col11 L7, Col16 L61 – Col17 L4, noting the system can generate conversational prompts to a user, which when considered in the context of the combination with Hyman could be provided at or to the beverage preparation machine), wherein the predicted stressed cognitive state for the user is further predicted based on content of the received response (Nudd Col10 L55 – Col11 L7, Col16 L61 – Col17 L4, noting the system can evaluate the user’s cognitive state and stress levels based on observed conversations and responses to the prompts).
Claim 7
Hyman in view of Nudd teaches the method of claim 6, showing a smart appliance system that can obtain biometric sensor data and determine a user’s stressed cognitive state based on the biometric sensor data using a machine learning model. Though the use of a machine learning model implies that data may be continuously obtained and used to refine the model’s predictions (see Hyman [0052] & [0090]-[0092]), the present combination fails to explicitly disclose obtaining, by the smart appliance, second biometric sensor data, and updating, by the smart appliance, a cognitive state machine learning model based on the second biometric sensor data and the predicted stressed cognitive state for the user. However, Nudd further teaches obtaining second biometric sensor data (Nudd Col26 L60-67, Col30 L26-41, noting sensor data is continually accumulated for event detection, indicating that at least second biometric sensor data is received), and updating a cognitive state machine learning model based on the second biometric sensor data and the predicted stressed cognitive state for the user (Nudd Col25 L55-67, noting a machine learning model is updated based on data received from real-time monitors and results of previously executed strategies for different states (considered equivalent to the continually accumulated second biometric sensor data)). It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the biometric sensing and machine learning model of the combination to include functionality for obtaining additional biometric data and updating the model as in Nudd in order to continuously improve the predictive accuracy of the model based on known outcomes (as suggested by Nudd Col25 L55-67).
Claim 8
Hyman in view of Nudd teaches the method of claim 1, and the combination further teaches receiving, by the smart appliance, a user identifier, and only generating the prediction of the stressed cognitive state for the user if the user identifier matches the biometric sensor data (Hyman [0072]-[0073], noting the beverage preparation machine may recognize a user via biometric sensor data (i.e. by matching the biometric sensor data with an identifier received and stored for the user) and automatically prepares a beverage based on an identity of the user, indicating that a user-specific beverage may only be prepared for the user (e.g. based on stressed cognitive state as in [0050]-[0052]) when the user has been successfully recognized).
Claim 26
Hyman in view of Nudd teaches the method of claim 1, and the combination further teaches wherein: the smart appliance comprises a smart coffee machine (Hyman [0031], noting the beverage preparation machine may prepare many types of beverages, including coffee); and modifying physical operation of the smart coffee machine comprises pouring a cup of coffee based on the predicted stressed cognitive state for the user (Hyman [0051]-[0052], noting the beverage preparation machine may automatically dispense (i.e. pour) a beverage recommended based on a user’s predicted stressed state, including a caffeinated beverage which is considered to include coffee as in [0031]-[0032]).
Claim 27
Hyman in view of Nudd teaches the method of claim 26, and the combination further teaches wherein pouring the cup of coffee based on the predicted stressed cognitive state for the user comprises: based on the predicted stressed cognitive state for the user, determining at least one of: style of brewing, size of coffee grind, type of coffee roast, selection of coffee beans, and temperature of coffee brew; and pouring the cup of coffee based on the determination (Hyman [0051]-[0052], noting the beverage preparation machine may automatically brew a recommended drink (e.g. a caffeinated beverage like coffee) based on a user’s predicted stressed cognitive state; see also [0081], noting drinks may also be selected for preparation in accordance with predicted preferences such as temperature, coffee blend strength, etc., indicating that the system may determine that a user’s stressed cognitive state requires a coffee drink and then brew the coffee drink in accordance with determined parameters like temperature or blend as appropriate).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Knox (US 20200364588 A1) describes an inference recommendation engine coupled to various smart appliances to determine user emotions and cognitive level and accordingly adjust operation of the coupled smart appliances, including a coffee maker. Erickson et al. (US 20170174343 A1) describes systems for determining a user’s cognitive state based on biometric data and delivering a recommended coffee drink to the user based on the cognitive state.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KAREN A HRANEK whose telephone number is (571)272-1679. The examiner can normally be reached M-F 8:00-4:00 ET.
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/KAREN A HRANEK/ Primary Examiner, Art Unit 3684