DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application is being examined under the pre-AIA first to invent provisions.
Amendment Entered
This Office action is responsive to the Amendment filed on May 5th, 2026. The examiner acknowledges the amendments to claims 1, 15, and 18, as well as the cancellation of claims 2, 16, and 19. Claims 1, 3-15, 17-18, and 20 remain pending in the application.
Response to Arguments
Applicant's arguments, filed May 5th, 2026, with respect to the rejections under 35 U.S.C. 101 have been fully considered but they are not persuasive.
At page 1, Applicant argues that the claims are patent eligible because they recite additional elements of a machine learning model specifically trained to perform image denoising to recover swing period information represented on the signal image using a supervised dataset which integrates the judicial exception into a practical application by providing a specific technological improvement to the operation of the machine learning model itself. Examiner respectfully disagrees. The step of processing the signal image using a machine learning model to output one or more health metrics and the machine learning model trained to perform image denoising to recover swing period information represented on the signal image using a supervised dataset comprising ground truth physiological tagging is directed to a mental process (process[ing]) and/or mathematical concepts (including mathematical relationships, mathematical formulas or equations, and mathematical calculations) (image denoising) which are abstract ideas. The improvement cannot be found in the abstract idea itself. “[I]t is important to keep in mind that an improvement in the abstract idea itself ... is not an improvement in technology.” MPEP 2106.05(a) Il. The claims recite steps for denoising of data. The claims do not integrate the processing and the denoising into a practical application. Rather, the alleged improvement lies solely within the processing steps performed by the processor. “Merely adding generic computer components to perform the method is not sufficient. Thus, the claim must include more than mere instructions to perform the method on a generic component or machinery to qualify as an improvement to an existing technology." Id.
Furthermore, the machine learning model is used to generally apply the abstract idea (i.e., perform the mental processes and/or mathematical concepts, i.e. processing, image denoising) without placing any limitations on how machine learning model operates to derive/recover the health metrics and swing period information. That is there is no limitations describing the decisions, computations, or rules performed (emphasis added) on the signal image to derive/recover the health metrics and swing period information and the claim fails to recite how the image denoising and recovered swing period information is related to outputting the one or more health metrics. In addition, the limitations would cover every mode of implementing the recited abstract idea using the machine learning model. The claim omits any details as to how the machine learning model solves a technical problem and instead recites only the idea of a solution or outcome. See MPEP 2106.05(f). Therefore, the limitations “process the signal image using a machine learning model to output one or more health metrics, wherein the machine learning model is trained to perform image denoising to recover swing period information represented on the signal image using a supervised dataset comprising ground truth physiological tagging” represents no more than mere instructions to implement the abstract idea.
Claim Objections
Claim 18 is objected to because of the following informalities:
“A computer program product ... embodied on a computer-readable medium” in claim 18 lines 1-2 should recite “A computer program product ... embodied on a non-transitory computer-readable medium”.
Appropriate correction is required.
Claim Rejections - 35 USC § 101
Claims 1, 3-15, 17-18, and 20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) as a whole, considering all claim elements both individually and in combination, do not amount to significantly more than an abstract idea. A streamlined analysis of claims 1, 15, and 18 follows.
STEP 1
Regarding claims 1, 15, and 18, the claims recite a series of structural elements and/or a series of steps or acts, including a device. Thus, the claims are directed to a machine and/or a process, which is one of the statutory categories of invention.
STEP 2A, PRONG ONE
The claims are then analyzed to determine whether it is directed to any judicial exception. The steps of:
Process[ing] the motion signals using a neural network to determine a motion state of the head-worn device,
in response to the neural network determining the motion state of the head-worn device is in a device on state and a static motion state, extract[ing] features from the motion signals representative of periodic movements of the head-worn device using a transform, the periodic movements including oscillations of the head-worn device related to heart pulses and the features including frequency domain information and time domain information,
generat[ing] a signal image from the features extracted from the motion signals, and
process[ing] the signal image using a machine learning model to output one or more health metrics,
wherein the machine learning model is trained to perform image denoising to recover swing period information represented on the signal image using a supervised dataset comprising ground truth physiological tagging.
set forth a judicial exception.
These steps describe a concept performed in the human mind (including an observation, evaluation, judgment, opinion) (process[ing], determin[ing], extract[ing], generat[ing], process[ing]) and/or mathematical concepts (including mathematical relationships, mathematical formulas or equations, and mathematical calculations) (extract[ing], perform image denoising). Thus, the claim is drawn to a Mental Process and/or a Mathematical Concept, which is an Abstract Idea.
STEP 2A, PRONG TWO
Next, the claim as a whole is analyzed to determine whether the claim recites additional elements that integrate the judicial exception into a practical application. The claim fails to recite an additional element or a combination of additional elements to apply, rely on, or use the judicial exception in a manner that imposes a meaningful limitation on the judicial exception. Claims 1, 15, and 18 recites a motion sensor coupled with a frame and a processor disposed in the frame to communicate with the motion sensor to receive motion signals captured by the motion sensor and output one or more health metrics, which is merely adding insignificant pre-solution activity and insignificant extra-solution activity to the judicial exception (MPEP 2106.05(g)). The receiving motion signals and outputting of the one or more health metrics does not provide an improvement to the technological field, the method does not effect a particular treatment or effect a particular change based on the received motion signals and outputted one or more health metrics, nor does the method use a particular machine to perform the Abstract Idea. The neural network and machine learning model are used to generally apply the abstract idea (i.e., perform the mental processes and/or mathematical concepts) without placing any limitations on how the neural network and machine learning model operates to derive/recover the health metrics and swing period information. In addition, the limitations would cover every mode of implementing the recited abstract idea using the neural network and machine learning model. The claim omits any details as to how neural network and machine learning model solves a technical problem and instead recites only the idea of a solution or outcome. See MPEP 2106.05(f). Therefore, the limitations represent no more than mere instructions to implement the abstract idea.
STEP 2B
Next, the claim as a whole is analyzed to determine whether any element, or combination of elements, is sufficient to ensure that the claim amounts to significantly more than the exception. Besides the Abstract Idea, the claim recites additional steps of:
head-mounted device comprising a frame;
motion sensor coupled to the frame
processor disposed in the frame and in communication with the motion sensor;
receive motion signals captured by the motion sensor
neural network
output one or more health metrics
machine learning model
The receiving steps is a well-understood, routine and conventional activity for those in the field of medical diagnostics. Further, the receiving and outputting steps are each recited at a high level of generality such that it amounts to insignificant pre-solution activity and insignificant extra-solution activity, e.g., mere data gathering and data outputting steps necessary to perform the Abstract Idea. When recited at this high level of generality, there is no meaningful limitation, such as a particular or unconventional step that distinguishes it from well-understood, routine, and conventional data gathering and comparing activity engaged in by medical professionals prior to Applicant's invention. Furthermore, it is well established that the mere physical or tangible nature of additional elements such as the obtaining and comparing steps do not automatically confer eligibility on a claim directed to an abstract idea (see, e.g., Alice Corp. v. CLS Bank Int'l, 134 S.Ct. 2347, 2358-59 (2014)).
Consideration of the additional elements as a combination also adds no other meaningful limitations to the exception not already present when the elements are considered separately. Unlike the eligible claim in Diehr in which the elements limiting the exception are individually conventional, but taken together act in concert to improve a technical field, the claim here does not provide an improvement to the technical field. Even when viewed as a combination, the additional elements fail to transform the exception into a patent-eligible application of that exception. Thus, the claim as a whole does not amount to significantly more than the exception itself. The claim is therefore drawn to non-statutory subject matter.
Regarding claims 1, 15, and 18, the device recited in the claim is a generic device comprising generic components configured to perform the abstract idea (as evidenced by the non-patent literature of record). The recited device and motion sensor are generic sensors configured to perform pre-solutional data gathering activity, the processor is configured to perform insignificant extra-solution activity, and the processor, neural network, and machine learning model is configured to perform the Abstract Idea. According to section 2106.05(f) of the MPEP, merely using a computer as a tool to perform an abstract idea does not integrate the Abstract Idea into a practical application.
The dependent claims also fail to add something more to the abstract independent claims. Claims 3-8, 16-17, and 20 are directed to more abstract ideas. Claims 9-10 are directed to a frame that is well-understood, routine, conventional, and previously known to the pertinent industry. Claims 11-14 are directed to inertial measurement units/accelerometers/gyroscopes that are well-understood, routine, conventional, and previously known to the pertinent industry. The steps recited in the independent claims maintain a high level of generality even when considered in combination with the dependent claims.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure: Aykut (US 20230196567 A1) directed to non-invasive monitoring of a physiological parameter of a patient and discloses a machine learning model to improve (e.g., denoise) the image signal for physiological parameter prediction (para. [0082]).
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ANDREW ELI HOFFPAUIR whose telephone number is (571)272-4522. The examiner can normally be reached Monday-Friday 8:00-5:00.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at
http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Charles Marmor II can be reached at (571) 272-4730. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/A.E.H./Examiner, Art Unit 3791
/AURELIE H TU/Primary Examiner, Art Unit 3791
Prosecution Insights