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 .
Status of Claims
This action is in response to the reply filed 12/07/2025.
Claims 1 and 11 were amended12/07/2025.
Claims 1-20 are currently pending and have been examined.
Claim Rejections - 35 USC § 112(a)
Claims 1 and 11 and therefore their dependent claims are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention. The claim limitations of “(ii) applying a trained machine learning model to the frequency domain representation to classify the section as diagnostically usable or not usable based on learned patterns of physiological signal quality, and (iii) determining the usability indicator based on the classification output of the machine learning model” are not recited in the specification. The specification recites that “various machine learning models (such as Support Vector Machine) or other techniques) can be used for determining presence of diagnosis-enabling data” (specification paragraph 307), however is silent on a trained machine learning model that is classifying the data based on whether it is diagnostically usable or not and based on learned patterns of physiological signal quality. The specification mentions that the machine learning techniques are implemented for determining the presence of diagnosis-enabling data and points to the use of the usable identification module (paragraph 552) for classifying the data and finding patterns of physiological signal quality. However, the usable date identification module is silent on its use of machine learning (paragraphs 547-554, Figures 18-19.
Further, the specification is silent on determining the usability indicator based on the classification output of the machine learning model. The specification recites that the usability indicator is determined by physiological data that is identified as usable by the “usable data identification module” (paragraph 552). The usable identification module is based on predetermined parameters during analyzed time periods and does not implement, nor mention the implementation of, machine learning or trained machine learning (paragraphs 547-554). This usable data identification module is shown in Figures 18-19 as the sequence of steps when performing data identification and is silent on the use of machine learning. The claim limitations are not supported by the specification.
Claim Rejections - 35 USC § 112(b)
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1 and 11 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 recites the limitation "the machine learning model" in line 14 of claim 1. There is insufficient antecedent basis for this limitation in the claim.
Claim 11 recite that limitation “the machine learning model” in line 13 of claim 11. There is insufficient antecedent basis for this limitation in the claim.
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 1-20 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.
Claims 1-20 are drawn to a method and a device which are statutory categories of invention (Step 1: YES).
Independent claims 1 and 11 recite receiv[ing] during a non-instantaneous physiological measurement process of a patient, a plurality of continuous sections of physiological data acquired, each of the sections representing a respective time period of the non-instantaneous physiological measurement process; analyz[ing] during the non-instantaneous physiological measurement process each received section of physiological data to determine a usability indicator indicating if the received section is usable for diagnosis of a medical condition of the patient or not, wherein the analysis comprises (i) transforming the section of physiological data into a frequency domain representation (ii) applying to the frequency domain representation to classify the section as diagnostically usable or not usable based on learned patterns of physiological signal quality, and (iii) determining the usability indicator based on the classification output; identify[ing] a subset of the continuous sections, wherein (a) the subset includes at least one of the seconds associated with the respective usability indicator indicating that the received section is usable for diagnosis of the medical condition of the patient, (b) the subset does not include at least one of the sections associated with a respective usability indicator indicating that the received section is not usable for diagnosis of the medical condition of the patient; and send[ing] the identified subset.
The recited limitations, as drafted, under their broadest reasonable interpretation, cover certain methods of organizing human activity by managing interactions between a medical practitioner (user) and patient in order to diagnose the patient as shown in Figure 17. If a claim limitation, under its broadest reasonable interpretation, covers fundamental economic principles or practices and/or managing personal behavior or relationships or interactions between people, then it falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. Accordingly, the claims recite an abstract idea (Step 2A Prong One: YES).
The judicial exception is not integrated into a practical application. The claims are abstract but for the inclusion of the additional elements including “medical data acquisition device”, “processing circuitry”, “sensors”, and “remote practitioner workstation”, “a trained machine learning model“, “the machine learning model” are recited at a high level of generality (e.g., that the calculating and displaying is performed using generic computer components and generic machine learning models with instructions are executed to perform the claimed limitations). Such that they amount to no more than mere instructions to apply the exception using generic computer components. See: MPEP 2106.05(f).
Hence, the additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Accordingly, the claims are directed to an abstract idea (Step 2A Prong Two: NO).
The claims 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, using the additional elements to perform the abstract idea amounts to no more than mere instructions to apply the exception using generic components. Mere instructions to apply an exception using a generic component cannot provide an inventive concept. See MPEP 2106.05(f).
Further, the claimed additional elements, identified above, are not sufficient to amount to significantly more than the judicial exception because they are generic components that are configured to perform well-understood, routine, and conventional activities previously known to the industry. See MPEP 2106.05(d). Said additional elements are recited at a high level of generality and provide conventional functions that do not add meaningful limits to practicing the abstract idea. The originally filed specification supports this conclusion at Figure 1, Figure 17 and
Paragraph 237, where “While not necessarily so1 system 200 may be a portable unit, a mobile unit1 a handheld unit, etc. System 200 may be a user activated mobile device, which is designed to be operated by a user without medical training (also referred to herein as "a non-medical practitioner"). Optionally, system 200 may be a smartphone, or another computer which optionality includes one or more different types of sensors. Optionally, system 200 may be a dedicated portable handheld device which includes one or more sensors and a processor”
Paragraph 496, where “It is to be noted that in some cases, the medical data acquisition device 1704 can be a handheld device, and at least the processing circuitry1705 and the sensors 1706 can be comprised within a housing of the medical data acquisition device 1704, that can optionally be a handheld device. In some cases, the sensors can be comprised within removably attachable units configured to be attached to the medical data acquisition device 1704. In some cases, the sensors can be external to the medical data acquisition device 1704 and in such cases, it may communicate with the medical data acquisition device 1704 via a wired connection and/or via a wireless connection (e.g. a WIFI connection).”
Paragraph 447, where “Providing the diagnosis-enabling data to the diagnosing entity can include transmitting the diagnosis-enabling data, via a network interface (whether wired or wireless), to a separate device (e.g. a computerized workstation, a smartphone, a tablet, etc.), other than system 200, the separate device operated by a medical practitioner.”
Paragraph 307, where “It is to be noted that in some cases, various machine learning models (such as Support Vector Machine (SVM) or other techniques) can be used for determining presence of diagnosis-enabling data (e.g. existence of specific forms in an image (e.g. tonsil, tympanic membrane, body parts) or specific segments in audio (e.g. S1, S2 in heart) within the physiological data.”
Viewing the limitations as an ordered combination, the claims simply instruct the additional elements to implement the concept described above in the identification of abstract idea with route, conventional activity specified at a high level of generality in a particular technological environment.
Hence, the claims as a whole, considering the additional elements individually and as an ordered combination, do not amount to significantly more than the abstract idea (Step 2B: NO).
Dependent claims 2-10 and 12-20 when analyzed as a whole, considering the additional elements individually and/or as an ordered combination, are held to be patent ineligible under 35 U.S.C. 101 because the additional recited limitations fail to establish that the claims are directed to an abstract idea without significantly more. Claims 2, 4-10, 12, 14-20 recite measuring, thresholding, and identifying data and do not provide additional elements that would amount to significantly more than the abstract idea. Claims 3 and 13 further recite a sensor which is generically recited in the specification paragraph 250. Such that they amount to no more than mere instructions to apply the exception using generic computer components. See: MPEP 2106.05(f). These claims fail to remedy the deficiencies of their parent claims above, and therefore rejected for at least the same rationale as applied to their parent claims above, and incorporated herein.
Response to Arguments
The arguments filed 12/7/2025 have been fully considered.
Regarding the arguments pertaining to the 101 rejection, these arguments are not persuasive. Applicant argues that the processing circuitry that “transform the section of physiological data into a frequency-domain representation” is not directed to mental processes. Examiner respectfully disagrees as the claimed invention is directed towards “Certain Methods of Organizing Human Activity” and not mental processes. Further, the processing circuitry is recited generically in the specification without significantly more to the abstract idea as shown in the rejection above. Applicant further argues that the use of a trained machine learning models are recognized by the USPTO as technological tools used to address technological problems. Examiner respectfully disagrees as the trained machine learning model recited in the claim limitations is recited generically in the specification and does not provide a technological improvement of existing generic machine learning models to provide significantly more to the abstract idea (paragraph 307 of specification).
Applicant further argues that the claimed invention is similar to McRo, CardioNet, Enfish and others because it improves the functioning of a device or data-processing system. However, Applicant has not pointed to any technological improvement or improvement of the functioning of a device. The use of generic processing circuitry and generic machine learning models does not provide an improvement to a technology to overcome the abstract idea.
Applicant further argues that a reference must be cited in accordance with Berkheimer, which establishes evidentiary standards for Step 2B only with regard as to what is well-understood, routine, and conventional as per MPEP 2106.05(d). The first criteria set forth in the Berkheimer memo is a “citation to an express statement in the specification or to a statement made by an applicant during prosecution that demonstrates the well-understood, routine, conventional nature of the additional element(s)…” As shown in the 101 rejection as written above, the specification is cited in Figures 1, 17 and their associated citations in the body of the specification as having computer elements that are well-understood, routine, and conventional without significantly more than the abstract idea.
The dependent claims rely on the arguments of the independent claims and are rejected for the reasons stated above.
Regarding the arguments pertaining to the 103 rejection, these arguments are persuasive. The references do not specifically teach the use of a trained machine learning model and the rejection has been withdrawn. A new search was conducted and found the prior art of Allen (US 20180082032 A1) that teaches trained learning models when analyzing diagnostic data, however it did not teach the parsing of data using the trained machine learning model. The 103 rejection has been withdrawn.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Allen (US 20180082032 A1) teaches trained learning models when analyzing diagnostic data, however it did not teach the parsing of data using the trained machine learning model.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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.
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/K.A.S./Examiner, Art Unit 3686
/JASON B DUNHAM/Supervisory Patent Examiner, Art Unit 3686
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