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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 12/02/2025 has been entered.
Response to Amendment
This Office Action is responsive to the amendment filed on 12/02/2025. As directed by the amendment: Claims 1 and 6-7 have been amended, claims 3 and 8-13 have been cancelled, and no claims have been added. Thus, claims 1-2 and 4-7 are presently under consideration in this application.
Response to Arguments
Applicant’s arguments, see page 6, filed 12/02/2025, with respect to claim objections have been fully considered and are persuasive. The objection of the claims has been withdrawn.
Applicant's arguments, see page 6, filed 12/02/2025, regarding 35 U.S.C. 112(b) have been fully considered but they are not persuasive. Applicant has failed to distinguish between the waveforms of the input and trained model. Therefore, the rejections are maintained.
Applicant's arguments, see pages 6-8, filed 12/02/2025, regarding 35 U.S.C. 112(a) have been fully considered but they are not persuasive.
Applicant argues on page 7 that “The Examiner is misapprehending the claims' scope. The claims are not directed to a new way of determining a probability that a measured waveform of a physiological parameter of a subject from a sensor is erroneously calculated due to a technical issue. Instead, the claims are directed to an improvement in that a notification is sent when the probability has a rising trend, before the technical alarm or the physiological alarm is output.” Applicant then asserts that the amendments to the claim have sufficient written description.
Examiner disagrees. Applicant is asserting that there is written description for limitations that the Examiner has not argued to not have written description. Rather, Examiner is arguing that there is a lack of written description for the machine learning model for the inputs of the model, and how the score is calculated based on the model to determine the probability. Specifically, the instant specification fails to detail what features within the ECG waveform are used (e.g. RR intervals, R peaks) and how these features are obtained/determined. ECG features are well-known; however, it is unknown how the model is trained, which specific ECG features observed for a specific output is not disclosed. The instant specification fails to disclose the machine learning model and the equation required for determining the probability. Therefore, the rejection is maintained.
Applicant's arguments, see pages 9-11, filed 12/02/2025, regarding 35 U.S.C. 101 have been fully considered but they are not persuasive.
Applicant argues on page 10 that “As such, the method of claim 1 is directed to a practical application and more than a mere abstract idea. In this way, the claim is directed to a specific improvement to a technical problem and is analogous to the claims found the claims to be patent eligible in CardioNet, LLC V. InfoBionic, Inc., 955 F.3d 1358, 1368-69 (Fed. Cir. 2020), in which the Federal Circuit found the claims were directed to a specific means that improves cardiac monitoring: "In our view, the claims 'focus on a specific means or method that improves' cardiac monitoring technology; they are not 'directed to a result or effect that itself is the abstract idea and merely invoke generic processes and machinery.'” Applicant further asserts on page 11 that “Like the claims in CardioNet, the claims of the present application provide a specific improvement to address a problem in a technical field: determining whether a measured waveform of a physiological parameter of a subject from a sensor is erroneously calculated due to a technical issue. See also Ex Parte Desjardins - September 26, 2025, Appeal No. 2024- 000567 (precedential): (Many advancements in computer technology, "by their very nature, may not be defined by particular physical features but rather by logical structures and processes." citing Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1339 (Fed. Cir. 2016).)”.
Examiner disagrees. The claims for CardioNet are directed to atrial flutter whereas the instant claims are directed to erroneous signal acquisition, which are not analogous art. Furthermore, each case turns on its own facts. The CardioNet case cited by Applicant was found to be eligible due to an unsupported assertion that the claims merely computerize pre-existing techniques for diagnosing atrial fibrillation and atrial flutter (see p. 16 of the decision). No such assertion is made in the present application and thus the facts of that case are not pertinent or related to the fact pattern presented in the present application. Desjardins also is directed to the improvement of storage, and also not pertinent to the fact patterns of the instant case. Therefore, the rejection is maintained.
Applicant’s arguments, see pages 8-9, filed 12/02/2025, with respect to the rejection(s) of the claim(s) under 35 U.S.C. 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Rantala et al. (US 20110291838)(Hereinafter Rantala) in view of Gargiulo et al. (US 20120108989)(Hereinafter Gargiulo).
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are:
“the predictor is configured to output prediction data” in claims 1 and 6-7. Examiner notes that the instant specification fails to recite structure for the phrase “predictor” Examiner will interpret the predictor to be a processor capable of using machine learning for calculating a probability.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112
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 1-2, and 4-7 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.
Regarding claims 1, and 6-7, it is unclear what the predictor may be and how it is possible for the predictor is a learned model, when a model must be implemented on a processor and stored in a memory. It is unclear of the predictor is a processor. It is further unclear how a classifier or a learned model is created by machine learning because classifiers and learned models are a type of machine learning and not “created by” machine learning.
Regarding claims 1, and 6-7, it is unclear in line 8 what is the “…at least one of…” is listing. If the claim is between the value OR the measured waveform, Examiner suggests amending to recite “…at least one of: a value or the measured waveform…”.
Regarding claims 1, and 6-7, it is unclear in lines 17-18 what is the “…at least one of…” is listing. If the claim is between the quality of the waveform data OR the state of the sensor OR an action shall be taken, Examiner suggests amending to recite “…at least one of: the quality of the waveform data, the state of the sensor, or an action shall be taken …”.
Regarding claims 1, and 6-7, it is unclear how it is possible for the notifier to provide a notification of an action “shall be taken by a user”. Examiner requests clarification on how a notification can be an action that “shall be taken”. Furthermore, the phrase “shall be taken” would mean it must be taken, however, the phrase says “to perform a notification of at least one”, and may not picked.
Claim 1 recites the limitation "the input" in line 19. There is insufficient antecedent basis for this limitation in the claim.
Claim 6 recites the limitation "the input" in line 19. There is insufficient antecedent basis for this limitation in the claim.
Claim 7 recites the limitation "the input" in line 19. There is insufficient antecedent basis for this limitation in the claim.
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-2, and 4-7 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.
Similarly, original claims may lack written description when the claims define the invention in functional language specifying a desired result but the specification does not sufficiently describe how the function is performed or the result is achieved. For software, this can occur when the algorithm or steps/procedure for performing the computer function are not explained at all or are not explained in sufficient detail (simply restating the function recited in the claim is not necessarily sufficient). In other words, the algorithm or steps/procedure taken to perform the function must be described with sufficient detail so that one of ordinary skill in the art would understand how the inventor intended the function to be performed. See MPEP §§ 2163.02 and 2181, subsection IV.
When examining computer-implemented functional claims, examiners should determine whether the specification discloses the computer and the algorithm (e.g., the necessary steps and/or flowcharts) that perform the claimed function in sufficient detail such that one of ordinary skill in the art can reasonably conclude that the inventor possessed the claimed subject matter at the time of filing. An algorithm is defined, for example, as "a finite sequence of steps for solving a logical or mathematical problem or performing a task." Microsoft Computer Dictionary (5th ed., 2002). Applicant may “express that algorithm in any understandable terms including as a mathematical formula, in prose, or as a flow chart, or in any other manner that provides sufficient structure." Finisar Corp. v. DirecTV Grp., Inc., 523 F.3d 1323, 1340 (Fed. Cir. 2008) (internal citation omitted).It is not enough that one skilled in the art could write a program to achieve the claimed function because the specification must explain how the inventor intends to achieve the claimed function to satisfy the written description requirement. See, e.g., Vasudevan Software, Inc. v. MicroStrategy, Inc., 782 F.3d 671, 681-683, 114 USPQ2d 1349, 1356, 1357 (Fed. Cir. 2015).
Claims 1, and 6-7 fail to sufficiently describe the usage of the machine learning model in enough detail for one skilled in the art to understand how the inventor intended the function to be performed to show possession of the claimed invention. The mere statement and recitation of the usage of a model in claims 1 and 6-7, and in [0036] of the instant specification provides insufficient detail to the type of machine learning model used in the instant invention, the inputs of the model, and how the score is calculated based on the model to determine the probability. Specifically, the instant specification fails to detail what features within the ECG waveform are used (e.g. RR intervals, R peaks) and how these features are obtained/determined. Further, the instant specification fails to detail the way in the machine learning model is trained to determine erroneous signal and what may be considered high or low erroneous signal. What and how in the training data is viewed to make the determination of the score. Therefore, claims 1 and 6-7 do not provide sufficient detail for one to replicate and understand the intended function that’s being performed to show possession of the claimed invention.
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 1-2, and 4-7 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
MPEP 2106(III) outlines steps for determining whether a claim is directed to statutory subject
matter. The stepwise analysis for the instant claim is provided here.
Step 1 – Statutory categories
Claims 1 and 6 is directed to a system (i.e. machine) and thus meets the step 1 requirements.
Claim 7 is directed to a tangible non-transitory computer-readable medium (i.e. a product), and
thus, meets the step 1 requirements.
Step 2A – Prong 1 – Judicial exception (j.e.)
Regarding claims 1 and 6-7, the following step is an abstract idea:
“a case where it is determined that the physiological parameter is not normally acquired based on the waveform data… a probability that the physiological parameter is erroneously calculated at each of a plurality of points in time of the measured waveform”, which is a mental process when given its broadest reasonable interpretation. As discussed in MPEP 2106.04(a)(2)(II), the mental process grouping includes observations, evaluations, judgements, and opinions. In this case, a human could determine the physiological parameter is not normally acquired based on analyzing the waveform data, which is a judgment that can be made by the human mind.
“a probability that the physiological parameter is erroneously calculated at each of a plurality of points in time of the measured waveform”, which is a mental process when given its broadest reasonable interpretation. As discussed in MPEP 2106.04(a)(2)(II), the mental process grouping includes observations, evaluations, judgements, and opinions. A human can also predict whether or not the physiological parameter is erroneously calculated at different points by doing a probability calculation, which is a evaluation done by the human mind.
Step 2A – Prong 2 – additional elements to integrate j.e. into a practical application
Regarding claims 1 and 6-7, the abstract idea is not integrated into a practical application.
The following claim elements do not add any meaningful limitation to the abstract idea:
- “reception interface”, “predictor”, and “processor” are recited at a high level of generality amounting to generic computer components for implementing abstract idea [MPEP 2106.05(b)];
It is noted that the learning model or classifier and machine learning are by definition automating the human thinking process with a computer.
- “sensor” are data gathering structures for the insignificant extra-solution activity of data gathering [MPEP 2106.05(b)];
- “waveform”, “feature quantity”, “technical alarm”, “physiological alarm”, “waveform data”, “training data”, “measured waveform”, “plurality of points”, “rising trend of the probability”, “prediction data”, “condition”, “predictor”, “physiological parameter”, “quality”, “notification”, and “notifier/alarm” are data (gathering, selecting, and displaying) that is necessary to implement the abstract idea on a computer amounting to insignificant extra-solution activity [MPEP 2106.05(g)].
Step 2B – significantly more/inventive concept
The following claim elements do not add any meaningful limitation to the abstract idea:
- “reception interface”, “predictor”, and “processor” are recited at a high level of generality amounting to generic computer components for implementing abstract idea [MPEP 2106.05(b)];
It is noted that the learning model or classifier and machine learning are by definition automating the human thinking process with a computer.
- “sensor” are data gathering structures for the insignificant extra-solution activity of data gathering [MPEP 2106.05(b)];
- “waveform”, “feature quantity”, “technical alarm”, “physiological alarm”, “waveform data”, “training data”, “measured waveform”, “plurality of points”, “rising trend of the probability”, “prediction data”, “condition”, “predictor”, “physiological parameter”, “quality”, “notification”, and “notifier/alarm” are data (gathering, selecting, and displaying) that is necessary to implement the abstract idea on a computer amounting to insignificant extra-solution activity [MPEP 2106.05(g)].
The additional elements of claims 1 and 6-7, when considered separately and in combination, do not add significantly more (ie. an inventive concept) to the abstract idea. As discussed above with respect to the integration of the abstract idea into a practical application, processor and reception interface, along with their associated functions, are recited at a high level of generality and simply amount to implementing the abstract idea on a computer. The ECG sensor and EKG sensor are claimed very generically and are used only to gather the data they are designed for. These are well-understood, routine and conventional structure since the diagnostic art in Zhao et al (US 20170258356) teaches the use of ECG/EKG sensors to collect ECG signals ([0006]).
Dependent claims 2, and 4-5 do not integrate the abstract idea into a practical application
and do not add significantly more to the abstract idea of claim 1 and 6-7. The dependent claim limitations are directed to extra-solution activity and generic gathering structure (claims 2-5), which are insignificant extra-solution activity and do not amount to more than what is well-understood, routine, and conventional.
In summary, claims 1-2, and 4-7 are directed to an abstract idea without significantly more and, therefore, are patent ineligible.
Claim Interpretation
Regarding claims 1, 6, and 7, the phrase “determined that the physiological parameter is not normally acquired” can be interpreted to mean that an abnormal signal is acquired based relating to a health issue, that the waveform/physiological signal/parameter is poor and unreliable, or that the waveform has too much noise/artifact. In the instant rejection, Examiner interprets the phrase to mean that an abnormal signal was acquired relating to poor health of a patient/user.
Claim Rejections - 35 USC § 103
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.
Claim(s) 1-2, and 4-7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Rantala et al. (US 20110291838)(Hereinafter Rantala) in view of Gargiulo et al. (US 20120108989)(Hereinafter Gargiulo).
Regarding claims 1, and 6-7, Rantala teaches A physiological information acquisition device/processing device/non-transitory computer readable medium (Abstract “a physiological monitoring apparatus, a physiological monitoring apparatus, and a computer program product for a physiological monitoring apparatus are disclosed.”), comprising:
a reception interface configured to receive waveform data corresponding to a measured waveform of a physiological parameter of a subject from a sensor ([0018] “a physiological monitoring apparatus/system 10 for monitoring a subject 100. A monitoring apparatus/system normally acquires a plurality of physiological signals 11 from the subject, where one physiological signal corresponds to one measurement channel… one or more measurement channels, such as heart rate [physiological parameter] derived from an ECG signal or an SPO.sub.2 value [physiological parameter] derived from a plethysmographic signal”);
a notifier (Abstract “A method for generating alarms in a physiological monitoring apparatus,”);
a processor configured to cause the notifier to output an alarm including a technical alarm issued in a case where it is determined that the physiological parameter is not normally acquired based on the waveform data ([0007] “Since the confidence level of the parameter may be lowered due to lowered quality of the respective physiological signal(s) or due to factors lowering the quality of the parameter determination process, the quality measure may be derived from the physiological signal(s) from which the parameter is derived and/or from the parameter determination process…Through quality based control of the alarm escalation the number of alarms caused by such events may be greatly reduced, since the control hampers the escalation of such alarms to higher priority alarms that would be clinically irrelevant.” Examiner notes that the alarm de-escalates during poor quality signals, which means that the alarm is still functioning. Examiner also notes that the claim recites a single alarm, “an alarm”, which supports Examiner’s interpretation of the use of the escalation and de-escalation of the alarm based on the quality of the signal, while also turning on the same alarm when a threshold of abnormality is surpassed.), and a physiological alarm issued in a case where it is determined that at least one of a value and the measured waveform of the physiological parameter is abnormal based on the waveform data ([0024] “Since no alarm is detected before that, no escalation is used until the physiological parameter crosses the first alarm limit (cf. step 21).” [0027] “since the heart rate has not yet reached the first alarm limit (Th1), no alarm escalation is applied, cf. step 32 of FIG. 3. At time instant T1, the heart rate reaches the first alarm limit.”); and
a predictor … in which a feature quantity of training data corresponding to a waveform of a case where the physiological parameter is not normally acquired is learned so that the predictor is configured output prediction data indicating that a probability the physiological parameter is erroneously calculated at each of a plurality of points in time of the measured waveform ([0039] “the confidence index [probability] may be determined based on a first measure indicative of the quality of the physiological signal(s) or based on a second measure indicative of the quality/reliability of the physiological parameter, or based on a combination of the first and second measures [training data]. It is obvious that the quality of a physiological signal affects the confidence level of a parameter derived from the said signal.” [0027] “The signal quality algorithm may be such that the index value maintains at 100 as long as the signal/parameter quality exceeds a predefined level, but begins to drop gradually as the quality drops below the level.” Figs. 4-6 (T1-T6)),
wherein the processor is configured to cause the notifier to perform a notification of at least one of a quality of the waveform data, a state of the sensor, and an action shall be taken by a user, in a case where a probability corresponding to the prediction data outputted from the predictor in response to the input of waveform data satisfies a condition associated with a rising trend of the probability before the alarm is issued (See rising trend before the alarm issued, which is the decrease in CI beginning between before T1 to T1, and then continuing from the start of the alarm to T3 in Fig. 4, in which the time of escalation of the alarm of Fig. 6 still occurs, even during a low CI. Examiner notes that the alarm is not required to be turned on based on the rising trend, as the claim does not require the alarm configured to be turned on based on the rising trend, but only having a rising trend occur prior to the alarm. Furthermore, a “rising trend” does not mean the trend has occurred, but rather, the trend is beginning to occur. [0038] “escalation control unit 85 is configured to control the escalation of the alarm based on a quality measure that may be derived by a confidence determination unit 86…confidence index based on the quality parameters. For example, quality parameters may be determined that are indicative of sensor attachment ("leads-almost-off") [state of sensor],”).
Although Rantala teaches an algorithm, Rantala does not teach a machine learning model used for determining the probability. Gargiulo, in the same field of endeavor, the obtaining of physiological parameters (Abstract) and determining signal quality ([0076]), and further teaches the use of classifiers that analyze signal quality ([0031]) to determine the probability of accuracy of the signal ([0084]). It would have been obvious to one skilled in the art, prior to the effective filing date of the invention, to modify the device of Rantala, with the machine learning model used for determining the probability of Gargiulo, because such a modification would allow to determine the probability of accuracy of the signal.
However, Rantala does not teach the rising trend. Although Rantala may be directed to the escalation of an alarm for good quality signals during a heart rate abnormality and the de-escalation or turning off of an alarm during bad quality, Where Rantala shows a decreasing trend in quality based on the CI (Fig. 4), the rising trend of a probability would also be used to indicate a decrease in quality. It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to use a rising trend of a probability, for the purpose of indicating a decrease in signal quality, since it has been held to be within the general skill of a worker in the art to select a known model on the basis of its suitability for the intended use as a matter of obvious design choice. In re Leshin, 125 USPQ 416.
Regarding claim 2, Rantala teaches wherein the processor is configured to cause the notifier to perform the notification based on a frequency that the probability exceeds a threshold value ([0027] “t time instant T0, the confidence index begins to drop from its normal value, which is 100 in this example…The signal quality algorithm may be such that the index value maintains at 100 as long as the signal/parameter quality exceeds a predefined level, but begins to drop gradually as the quality drops below the level.” Examiner notes that the threshold is 100 which is dropped below the level.).
However, Rantala does not teach the exceeding of the threshold. Although Rantala may be directed to the escalation of an alarm for good quality signals during a heart rate abnormality and the de-escalation or turning off of an alarm during bad quality, Where Rantala shows a decreasing below the threshold in quality based on the CI (Fig. 4), the exceeding the threshold value of a probability would also be used to indicate a decrease in quality. It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to use exceeding threshold value, for the purpose of indicating a decrease in signal quality, since it has been held to be within the general skill of a worker in the art to select a known model on the basis of its suitability for the intended use as a matter of obvious design choice. In re Leshin, 125 USPQ 416.
Regarding claim 4, Rantala teaches wherein the physiological parameter is a heart rate ([0018] “a physiological monitoring apparatus/system 10 for monitoring a subject 100. A monitoring apparatus/system normally acquires a plurality of physiological signals 11 from the subject, where one physiological signal corresponds to one measurement channel… one or more measurement channels, such as heart rate [physiological parameter] derived from an ECG signal or an SPO.sub.2 value [physiological parameter] derived from a plethysmographic signal”).
Regarding claim 5, Rantala and Gargiulo teach the invention of claim 1. Although Rantala teaches the leads off state, meaning electrodes must be used to gather the ECG ([0038]), Rantala does not explicitly teach the sensor includes a plurality of electrodes adapted to be attached to the subject to measure an electrocardiogram and wherein the predictor is configured to calculate the probability for the waveform data associated with each of lead waveforms included in the electrocardiogram received from the plurality of electrodes. Gargiulo, in the same field of endeavor, the obtaining of physiological parameters (Abstract) and determining signal quality ([0076]), and further teaches wherein the sensor includes a plurality of electrodes adapted to be attached to the subject to measure an electrocardiogram ([0058] “The sensors 14 are electrodes able to be placed relative to the animal without any preparatory work being done on the animal's body.” [0078] “This can be identified at the level of individual electrode sensors 14. A further type of loss of quality might be an ECG signal which is swamped by excessive electromyograph (EMG) signals arising from muscle movement in the animal close to the electrode sensors 14.”); and
wherein the predictor is configured to calculate the probability for the waveform data associated with each of lead waveforms included in the electrocardiogram received from the plurality of electrodes ([0084] “The outputs of these parallel diagnostic methods 56 are then combined using a classifier 60 which makes the final decision 46 on diagnosis. This classifier 60, sometimes called a “committee of experts”, uses methods such as Bayesian statistics to allocate a weight or importance to the outcome, based upon the signal quality, the known reliability of the method and a knowledge of prior probabilities of accuracy.” [0025] “The method may include detecting the presence of one or more cardiac signals”) to determine the probability of accuracy of the signal ([0084]). It would have been obvious to one skilled in the art, prior to the effective filing date of the invention, to modify the device of Rantala, with the sensor includes a plurality of electrodes adapted to be attached to the subject to measure an electrocardiogram and wherein the predictor is configured to calculate the probability for the waveform data associated with each of lead waveforms included in the electrocardiogram received from the plurality of electrodes of Gargiulo, because such a modification would allow to determine the probability of accuracy of the signal.
Conclusion
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/MOUSSA HADDAD/Examiner, Art Unit 3796
/Jennifer Pitrak McDonald/Supervisory Patent Examiner, Art Unit 3796