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 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 1-18 are rejected under 35 USC 101 because the claimed invention is directed to a judicial exception, specifically abstract idea (mathematical concept of preprocessing measured data and mental process of determining a sleep quality metric of a user), without significantly more.
Step 1
The claimed invention in claims 1-18 are directed to statutory subject matter as the claim(s) recite(s) a method and system for preprocessing measured data and determining a sleep quality metric of a user.
Step 2A, Prong 1
Regarding claims 1 and 18, the recited steps are directed to mathematical concepts and mental process of performing concepts in a human mind or by a human using a pen and paper (see MPEP 2106.04(a)(2) subsections (I) and (III)).
Regarding claims 1 and 18, the limitations of "dividing the set of signals into a plurality of pulse segments, each pulse segment comprising an equal number of pulses" and "dividing the set of signals into a first set of input segments, each input segment comprising a plurality of segments" are either or both of mathematical processes (e.g., dividing signals into segments in order to preprocess data) and mental processes (e.g., someone with the signals could draw vertical lines through them to segment them into multiple segments or mentally divide them into a plurality of pulse segments). The limitations of "processing each pulse segment to determine a quality metric for each pulse segment," “dividing the set of signals into a first set of input segments, each input segment comprising a plurality of the pulse segments,” "selecting a second set of input segments from the first set of input segments based on the quality metrics for the pulse segments in each input segment,” and "determining the sleep quality metric for the user using a first prediction model and a second prediction model, wherein the first prediction model determines whether the user is asleep from a first input, and the second prediction model determines occurrences of an apnea event or a hypopnea event using a second input, wherein the first input and the second input are based on the second set of input segments" are processes, as drafted, covers performance of the limitations that can be performed by a human mind (including an observation, evaluation, judgment, opinion) or by a human with pen and paper under the broadest reasonable standard. For example, these limitations are nothing more than a medical professional determining the quality of the signals, selecting only good quality data, determine the sleep status of a patient mentally or by hand calculating with the data one method, and determine the occurrences of abnormal sleep events of patient mentally or by hand calculating the data a different method.
Step 2A, Prong 2
For claims 1 and 18, the judicial exception is not integrated into a practical application. In particular, claim 1 recites additional elements of "one or more processors." The processor is recited at a high-level of generality and amount to nothing more than parts of a generic computer. Merely including instructions to implement an abstract idea on a computer does not integrate a judicial exception into practical application.
In particular, claim 18 recites additional elements of "a memory," "one or more processors," "the set of sensors." The memory, processor(s), sensors are also recited at a high-level of generality and amount to nothing more than parts of a generic computer. Merely including instructions to implement an abstract idea on a computer does not integrate a judicial exception into practical application.
In particular, claims 1 and 18 recites additional elements of "receiving a set of signals
comprising a PPG signal, an Sp02 signal and an accelerometer signal" amount to nothing more than a mere pre-solution activity of data gathering.
Step 2B
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
As discussed about with respect to integration of the abstract idea into a practical application, the additional element of receiving a set of signals amounts to no more than mere pre-solution activity of data gathering, which does not amount to an inventive concept. Furthermore, simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requires no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known to the industry, as discussed in Alice Corp., 573 U.S. at 225, 110 USPQ2d at 1984 (see MPEP § 2106.05(d)). In this case, elements of general computer are being used to implement mathematical concept of preprocessing measured data and mental process of determining a sleep quality metric of a user.
Regarding claims 2-17, the limitations of these claims further define the limitations of claim 1 identified as mental processes and can likewise be performed mentally or by hand.
Response to Arguments
Applicant’s arguments, see “remarks,” filed 4/15/2025, with respect to the rejections under sections 112, 102 and 103 have been fully considered and are persuasive. The rejection of claims 1-18 under sections 112, 102 and 103 have been withdrawn.
Applicant's arguments filed 4/15/2025 with respect to section 101 have been fully considered but they are not persuasive.
Applicant argued that the claims are not directed to an abstract idea because the claims require complexity beyond mental processes because the “set of signals” “received” cannot be processed in the human mind due to the volume and complexity of the data; that the use of “prediction models” that are likely machine learning or artificial intelligence-based algorithms, requiring iterative computations and statistical analysis exceeding capabilities of manual mental or pen-and-paper methods; and rely solely on PPG, SpO2, and accelerometer signals that a medical practitioner could not use to label sleep states and respiratory events with precision. However, much of this is not required in the current claim language. As an example, the examiner’s position is that the “receiving” step can be carried out by a clinician viewing a paper printout or computer display depicting data including a PPG signal, SpO2 signal, and accelerometer signal; the “dividing” step can be carried out by the clinician mentally noting the individual beats/pulses in the conventional PPG tracing; the “processing” step by judging whether the individual pulses looks noisy (e.g., non-physiological spiking or baseline drift or signal dropout); the “dividing” step can be carried out by ignoring the noisy pulses and considering only the non-noisy pulses; the “selecting” step by considering only the non-noisy pulses; and the “determining” step carried out by applying a mental “first prediction model” and “second prediction model” by relying on their clinical training, e.g., that sufficient motion from the accelerometer implies that the patient is not sleeping and a sufficient drop in SpO2 implies that the patient is experiencing an apnea or hypopnea event. With this in mind, the arguments that the claims require complexity beyond mental processes because the “set of signals” “received” cannot be processed in the human mind due to the volume and complexity of the data; that the use of “prediction models” that are likely machine learning or artificial intelligence-based algorithms, requiring iterative computations and statistical analysis exceeding capabilities of manual mental or pen-and-paper methods; and rely solely on PPG, SpO2, and accelerometer signals that a medical practitioner could not use to label sleep states and respiratory events with precision are not commensurate in scope with the requirements of the claims. The claims do not require any sort of volume or complexity of the “set of signals”; the claims do not require that the “prediction models” are machine learning or artificial intelligence-based algorithms, requiring iterative computations and statistical analysis; nor that the method relies solely on PPG, SpO2, and accelerometer signals (they are “comprising” claims with no exclusionary language) to provide any particular level of precision. If the method requires some sort of computer computation that is not performable mentally or manually with pen-and-paper, this step or steps are not currently recited in the claims. Referring specifically to the “determining” step, the claim recites only the idea of a solution or outcome using generic “prediction model” language and does not recite details of how a solution or outcome is accomplished, such as by particular “prediction models” that are beyond the complexity applicable by the human mind.
Applicant further argued that the claims integrate the abstract ideas into a practical application because the invention provides a non-invasive wearable solution for accurately assessing sleep quality that does not require cumbersome PSG equipment. However, this is not reflected in the claims. There is no requirement of a wearable device, and no exclusionary language to indicate that the method is performed exclusively with PPG, SpO2, and accelerometer signals (the claims are “comprising” claims). Applicant further argued that the method improves the field of signal processing and prediction models. However, the broad language in the claims does not require a degree of complexity to the signal processing and prediction models that would require any sort of technological improvement, but instead are performable by the human mind, as set forth above. The additional elements (the generic recitation of “performed via one or more processors”) does not integrate the otherwise mentally-performed steps into a practical application for the reasons set forth above.
Applicant further argued that the claims include additional elements that amount to significantly more than the abstract idea. However, Applicant points to requirements that are either not recited in the claims (exclusive use of PPG, SpO2, and accelerometer sensors -- no sensors are recited in claim 1), or are drawn to the abstract ideas themselves (the “dividing,” “processing,” “dividing,” “selecting,” and “determining” steps).
In regards to the dependent claims, Applicant argued that claim 11 requires the use of generic “neural networks,” but there is no indication of any sort of required complexity and the human mind is strictly-speaking a “neural network.” In regards to claims 13-17, Applicant argued that the claims define a concrete and technical index for the field of signal analysis obtained using machine learning models trained on empirical datasets. Much of this is not recited in the claims and there is no requirement of concrete and technical indicies beyond those obtainable by a user making a “judgment call” of sleep status and sleep events by looking at a tracing of the PPG, SpO2, and accelerometer signals. Again, is there is some sort of complexity or computational steps required by the dual first and second prediction models that cannot be performed mentally or manually by a clinician, these features are not currently recited in the claims.
Accordingly, the examiner respectfully maintains the rejections under section 101.
Claims 1-18 avoid the prior art, but remain rejected under section 101, as set forth above. The previous grounds of rejection was in view of Fox (US 2023/0099622) and Bandyopadhyay (US 2017/0055898). However, neither reference, taken alone or in combination, discloses or fairly renders unpatentable a method that divides the set of signals into a plurality of pulse segments, each pulse segment comprising an equal number of pulses; nor a method that uses both a first prediction model that determines whether the user is asleep from a first input and a second prediction model that determines occurrences of an apnea event or a hypopnea event using a second input, in combination with the remaining limitations of the claims.
Shimol et al. (US 2020/0054289) is another example of a sleep quality monitor that utilizes PPG, SpO2, and an accelerometer signal (pars. 0028, 0029), but does not divide the signals into a plurality of pulse segments, each pulse segment comprising an equal number of pulses, nor a method that uses both a first prediction model that determines whether the user is asleep from a first input and a second distinct prediction model that determines occurrences of an apnea event or a hypopnea event using a second input, in combination with the remaining limitations of the claims.
Carter et al. (US 2017/0181649) is an example of dividing a PPG signal into a plurality of pulse segments, each pulse segment comprising an equal number of pulses, along with processing each pulse segment to determine a quality metric for each pulse segment and dividing the set accordingly (abstract), but this teaching applies to deriving a blood pressure of the patient using the PPG signal alone (and not a set of signals), is not drawn to any sort of sleep quality monitoring, and there does not appear to be any teaching of motivation to apply this concept to sleep quality monitoring using first and second distinct prediction models.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL W KAHELIN whose telephone number is (571)272-8688. The examiner can normally be reached M-F, 8-5.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Benjamin Klein can be reached at (571)270-5213. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MICHAEL W KAHELIN/ Primary Examiner, Art Unit 3792
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