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 Objections
Claim 5 is objected to because of the following informalities: Claim 5 recites “wherein generating the programming recommendations comprises to optimize cardiac capture for the patient,” but should, as a matter of grammar, recite -- wherein generating the programming recommendations comprises optimizing cardiac capture for the patient--. Appropriate correction is required.
Claims 6, 17, 19 and 20 contain a similar recitation and are objected to for the same reason.
Claim Rejections - 35 USC § 112
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 2-4, 10-12 and 16-18, and Claim 14 by dependency, 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.
Regarding Claim 2, Claim 2 recites “wherein to identify the one or more differences between the parameter settings of the ambulatory medical device and the stored model parameter settings comprises to prioritize the identified one or more differences with respect to reduced cardiac pacing or unsuccessful cardiac capture.” The Present Specification does not describe “prioritiz[ing] the identified one or more differences with respect to reduced cardiac pacing or unsuccessful cardiac capture” in sufficient details to enable one of ordinary skill in the art to understand what is contemplated. That is, the Present Specification provides no detail regarding what “prioritizing” entails, does not elaborate on how “one or more differences with respect to reduced cardiac pacing or unsuccessful cardiac capture” may be “identified,” and fails to relate the two in a manner one of ordinary skill in the art would be able to reproduce. Based on the disclosure, one of ordinary skill in the art would be unable to discern whether any particular “identifying” done by a given system “comprises to prioritize the identified one or more differences with respect to reduced cardiac pacing or unsuccessful cardiac capture.”
Regarding Claim 3, Claim 3 recites “receiving cardiac capture information of the patient…” and inputting “the received capture information” into a pre-trained machine learning model. The Present Specification does not define or explain what “cardiac capture information” entails in a manner sufficient to enable a person of ordinary skill in the art to understand what information is received and input.
Regarding Claim 4, Claim 4 recites “determining an indication of cardiac capture of the patient….” The Present Specification does not describe what is contemplated as an “indication of cardiac capture” in a manner sufficient to convey to a person of ordinary skill in the art what is being determined.
Regarding Claim 10, Claim 10 recites “…associated with the following parameter settings: Atrioventricular Delay Fixed and Atrioventricular Dynamic Maximum.” The Present Specification does not describe the settings “Atrioventricular Delay Fixed” and “Atrioventricular Dynamic Maximum” in a manner sufficient to apprise a person of ordinary skill in the art of their meaning. The settings “Atrioventricular Delay Fixed” and “Atrioventricular Dynamic Maximum” are described at Para. [0073] of the Present Specification, which states: “Parameter settings can include, among others: … Atrioventricular Delay Fixed (AVDlyFix or AVDF), which is a fixed atrioventricular delay setting; Atrioventricular Dynamic Maximum (AVDynMax or AVDM), which defines the maximum dynamic atrioventricular delay….” The recited settings are claimed in the context of a computer-implemented function. As the settings “Atrioventricular Delay Fixed” and “Atrioventricular Dynamic Maximum” are not adequately described, the specification does not provide a disclosure of the computer and algorithm in sufficient detail to demonstrate to one of ordinary skill in the art that the inventor possessed the invention.
For purposes of this Office Action, the settings “Atrioventricular Delay Fixed” and “Atrioventricular Dynamic Maximum” are being interpreted to mean that atrioventricular delay is considered.
Regarding Claim 11, Claim 11 recites “implementing at least one of a set of rules associated with at least two of the following parameter settings: Atrial Tachy Response Mode; Biventricular Trigger Enable; Ventricular Tachycardia Zone Rate; Atrial Tachy Response Trigger Rate; Maximum Sensor Rate Interval; Ventricular Tachycardia 1 Zone Rate; Number of Ventricular Zones; Ventricular Fibrillation Zone Rate; Atrial Tachy Response Ventricular Rate Regulation Response; Atrial Tachy Response Biventricular Trigger Enable; Atrial Tachy Response Lower Rate Limit; Tachycardia Mode; Respiration Rate Trend Enable; Atrial Tachy Response Pacing Chamber; and Sensing Mode.” The recited settings are claimed in the context of a computer-implemented function, and – similarly to as explained above with respect to Claim 10 – are not described by the Present Specification in a manner sufficient to apprise a person of ordinary skill in the art of their meaning. Accordingly, the specification does not provide a disclosure of the computer and algorithm in sufficient detail to demonstrate to one of ordinary skill in the art that the inventor possessed the invention.
Regarding Claim 12, Claim 12 recites “implementing at least one of a set of rules associated with at least two of the following parameter settings: Sensed Atrioventricular Delay; Atrioventricular Dynamic Minimum; Atrioventricular Delay Fixed; and Atrioventricular Dynamic Maximum.” The specification does not provide a disclosure of the computer and algorithm in sufficient detail to demonstrate to one of ordinary skill in the art that the inventor possessed the invention for the same reasons as explained above with respect to Claim 10.
Pertinent Claim 12 limitations are being interpreted similarly to similar Claim 10 limitations.
Regarding Claim 13, Claim 13 recites “receiving cardiac capture information of the patient….” The Present Specification does not define or explain what “cardiac capture information” entails in a manner sufficient to enable a person of ordinary skill in the art to understand what information is received and input.
Regarding Claim 16, Claim 16 contains a similar limitation to that addressed above with respect to Claim 2, and does not describe the above-addressed subject matter in a manner sufficient to convey to a person of ordinary skill in the art what is being determined for the same reasons as Claim 2.
Regarding Claim 17, Claim 17 contains a similar limitation to that addressed above with respect to Claim 3, and does not describe the above-addressed subject matter in a manner sufficient to convey to a person of ordinary skill in the art what is information is being received and input for the same reasons as Claim 3.
Regarding Claim 18, Claim 18 contains a similar limitation to that addressed above with respect to Claim 4, and does not describe what is contemplated as an “indication of cardiac capture” in a manner sufficient to convey to a person of ordinary skill in the art what is being determined for the same reasons as Claim 4.
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 2-6, 9 and 16-20 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 Claim 2, Claim 2 recites “wherein to identify the one or more differences between the parameter settings of the ambulatory medical device and the stored model parameter settings comprises to prioritize the identified one or more differences with respect to reduced cardiac pacing or unsuccessful cardiac capture.” It is grammatically unclear in what sense “to identify the one or more differences” can comprise “to prioritize the identified one or more differences,” as the result of the further limited term (i.e., “identified”) is used in its own definition (i.e., “to identify … comprises to prioritize the identified”). The limitation is thus circular, and it is unclear at which point “prioritizing” is done.
For purposes of this Office Action, Claim 2 is being interpreted to mean that “one or more differences with respect to reduced cardiac pacing or unsuccessful cardiac capture” are differences that the system is configured to prioritize.
Regarding Claim 3:
Claim 3 recites “generating the programming recommendations.” There is insufficient antecedent basis for plural “programming recommendations.”
Claim 3 recites “wherein generating the programming recommendations comprises generating a reprogramming recommendation for the ambulatory medical device to optimize cardiac capture for the patient.” Claim 3 further limits the “operations” of Claim 1 (i.e., Claim 3 recites “wherein the operations further comprise,” with reference to the Claim 1 limitation “cause the one or more processors to perform operations comprising:”). It is unclear in what sense “generating the programming recommendations comprises generating a reprogramming recommendation,” in particular relative to “generating the programming recommendation” as recited by Claim 1. For example, it is unclear whether both a “programming recommendation” as recited by Claim 1 and a “reprogramming recommendation” are simultaneously generated (which the Present Specification does not appear to support), whether the “programming recommendation” is instead “a reprogramming recommendation,” or something else.
For purposes of this Office Action, Claim 3 is being interpreted to mean that the “programming recommendation” is instead “a reprogramming recommendation.”
Regarding Claim 4, Claim 4 recites “determining an indication of cardiac capture of the patient during cardiac resynchronization therapy delivered by the ambulatory medical device according to the received parameter settings using the received physiologic information.” It is unclear what is being determined. For example, “determining an indication of cardiac capture…” could mean that it is determined whether a particular set of parameter settings and physiologic information indicates that cardiac capture has occurred in view of an existing (but not unexplained in the Present Specification) set of rules for determining whether cardiac capture has occurred, could mean that a particular set of parameter settings and physiologic information is used to determine an application-unique indication of whether cardiac capture has occurred (i.e., there is no specific existing rule which governs, but data is used to create one), or could mean something else.
For purposes of this Office Action, Claim 4 is being interpreted to mean that it is determined whether a particular set of parameter settings and physiologic information indicates that cardiac capture has occurred in view of an existing set of rules for determining whether cardiac capture has occurred.
Regarding Claim 5, Claim 5 recites “generating the programming recommendations.” There is insufficient antecedent basis for plural “programming recommendations.”
Regarding Claim 6:
Claim 6 recites “the received physiologic information.” There is insufficient antecedent basis for this limitation.
Claim 6 recites “generating the programming recommendations.” There is insufficient antecedent basis for plural “programming recommendations.”
Regarding Claim 9, Claim 9 recites “wherein the operations further comprise: … providing cardiac resynchronization therapy to the patient according to the one or more reprogrammed parameter settings.” The term “the operations draws its antecedent basis from Claim 1, which (in pertinent part) recites “cause the one or more processors to perform operations comprising….” It is unclear in what sense “one or more processors” can “provide cardiac resynchronization therapy.”
For purposes of this Office Action, Claim 9 is being interpreted to require that the one or more processors are configured to output instructions regarding the administration of cardiac resynchronization therapy to the patient according to the one or more reprogrammed parameter settings. Of note, Claim 9 is not being interpreted to affirmatively require actual administration of cardiac resynchronization therapy.
Regarding Claim 16, Claim 16 contains a similar limitation to that addressed above with respect to Claim 2, and is indefinite for the same reasons as Claim 2.
Regarding Claim 17, Claim 17 contains a similar limitation to that addressed above with respect to Claim 3, and is indefinite for the same reasons as Claim 3.
Regarding Claim 18, Claim 18 contains a similar limitation to that addressed above with respect to Claim 4, and is indefinite for the same reasons as Claim 4.
Regarding Claim 19, Claim 19 contains a similar limitation to that addressed above with respect to Claim 5, and is indefinite for the same reasons as Claim 5.
Regarding Claim 20, Claim 20 contains a similar limitation to that addressed above with respect to Claim 6, and is indefinite for the same reasons as Claim 6.
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., an abstract idea) without significantly more. The rejection is maintained.
The Examiner notes that indefiniteness issues in Claim 9 cause the administration of cardiac resynchronization therapy described therein not to sufficiently integrate the recited abstract ideas into a practical application. However, if Claim 9 were amended such that administration of cardiac resynchronization therapy by the ambulatory device in response to the generated programming recommendation was affirmatively required by the claim, Claim 9 might contain additional elements sufficient to integrate the recited abstract idea into a practical application, dependent on phrasing.
Eligibility Step 1 – The Four Categories of Statutory Subject Matter
Claims 1-20 each fall within one of the four categories of statutory subject matter.
Eligibility Step 2A, Prong One
Claims 1-20 recite abstract ideas:
Regarding Independent Claim 1:
“generating the programming recommendation for the ambulatory medical device to improve cardiac capture for the patient based on the identified one or more differences” recites a mental process when afforded its broadest reasonable interpretation. The recited “generating” is practically performable in the human mind. For example, a human could observe the output obtained from the one or more pre-trained machine learning models, and exercise judgment to recommend–based on the observed output–changes that improve cardiac capture.
Significantly, the recited “generating” is done based on output from the recited machine learning model. That is: data is “input” to a “pre-trained” machine learning model, which machine learning model does the entirety of all necessary processing; an “output” is obtained as result of such processing; this output is used for the “generating” addressed above. Broadly recited “generating” is all the claim requires. It is this broad “generating” that is practically performable in the human mind.
Regarding Claims 2-3, Claims 2-3 depend from and further limit Claim 1, and recite a mental process for the same reasons as does Claim 1.
Regarding Claim 4:
“determining an indication of cardiac capture of the patient…” recites a mental process when afforded its broadest reasonable interpretation. Such determining as claimed could practically be performed in the human mind. For example, a human could observe received parameter settings and received physiologic information and exercise judgment to determine whether this information is consistent with cardiac capture.
Regarding Claims 5-12, Claims 5-12 depend from and further limit Claim 1 and recite a mental process for the same reasons as explained above with respect thereto.
Regarding Independent Claim 13:
“generating the programming recommendation for the ambulatory medical device to improve cardiac capture for the patient based on the identified one or more differences” recites a mental process for the same reasons as explained above with respect to the similar limitation addressed above at Claim 1.
Regarding Claim 14:
“prioritizing the one or more differences with respect to a potential or detected loss of cardiac capture or reduced pacing” recites a mental process when afforded its broadest reasonable interpretation. The recited “prioritizing” is practically performable in the human mind. For example, a human could exercise judgment to attribute priority to differences with respect to a potential or detected loss of cardiac capture or reduced pacing.
Regarding Independent Claim 15:
“generating … the programming recommendation for the ambulatory medical device to improve cardiac capture for the patient based on the identified one or more differences” recites a mental process when afforded its broadest reasonable interpretation for the same reasons as explained above with respect to the similar limitation of Claim 1.
Regarding Claims 16-17, Claims 16-17 depend from and further limit Claim 15 and recite a mental process for the same reasons as does Claim 15.
Regarding Claim 18:
“determining … an indication of cardiac capture of the patient…” recites a mental process when afforded its broadest reasonable interpretation for the same reasons as explained above with respect to the similar limitation of Claim 4.
Regarding Claims 19-20, Claims 19-20 depend from and further limit Claim 15, and recite a mental process for the same reasons as does Claim 15.
Eligibility Step 2A, Prong Two: Claims 1-20 do not amount to significantly more than the abstract ideas recited therein.
Regarding Independent Claim 1:
“A computing device for generating a programming recommendation for an ambulatory medical device to improve cardiac capture in a patient during cardiac resynchronization therapy by the ambulatory medical device, one or more processors; and one or more memory devices storing instructions, which when executed by the processor, cause the one or more processors to perform operations comprising” are generic computer structures for performing a generic computer functions, and thus simply amounts to using a computer as a tool to implement the abstract idea. See MPEP 2106.04(a)(2)(III)(C).
“receiving parameter settings of the ambulatory medical device” amounts to mere data gathering in conjunction with implementing the recited abstract idea, and is thus insignificant extra-solution activity insufficient to integrate the judicial exception into a practical application.
“processing the received parameter settings by inputting the received parameter settings into one or more pre-trained machine learning models, each of the one or more pre-trained machine learning models trained to compare the received parameter settings to stored model parameter settings from one or more other ambulatory medical devices corresponding to one or more other patients and to identify one or more differences between the parameter settings of the ambulatory medical device and the stored model parameter settings of the one or more other ambulatory medical devices” amounts to mere data gathering in conjunction with implementing the recited abstract idea, and is thus insignificant extra-solution activity insufficient to integrate the judicial exception into a practical application.
The claimed processing is “inputting” data into a pre-trained machine learning model. The “input” is then processed by the pre-trained machine learning model, creating a new set of data that is subsequently used to “generate” a recommendation (this “generating” is the judicial exception). As the recited “inputting” is to acquire data that is necessary for the abstract idea of “generating,” it amounts to necessary data gathering.
“obtaining an output from the one or more pre-trained machine learning models indicating the identified one or more differences between the parameter settings of the ambulatory medical device and parameter settings of the one or more other ambulatory medical devices” amounts to mere data outputting in conjunction with implementing the recited abstract idea, and is thus insignificant extra-solution activity insufficient to integrate the judicial exception into a practical application.
Regarding Claim 2, Claim 2 does not recite any additional element.
Regarding Claim 3:
“receiving cardiac capture information of the patient during cardiac resynchronization therapy delivered by the ambulatory medical device according to the received parameter settings” amounts to mere data gathering in conjunction with implementing the recited abstract idea, and is thus insignificant extra-solution activity insufficient to integrate the judicial exception into a practical application.
“wherein processing the received parameter settings further comprises inputting the received cardiac capture information of the patient into the one or more pre-trained machine learning model” amounts to mere data gathering in conjunction with implementing the recited abstract idea, and is thus insignificant extra-solution activity insufficient to integrate the judicial exception into a practical application.
Regarding Claim 4:
“receiving physiologic information of the patient obtained by the ambulatory medical device” amounts to mere data gathering in conjunction with implementing the recited abstract idea, and is thus insignificant extra-solution activity insufficient to integrate the judicial exception into a practical application.
Regarding Claim 5:
“receiving physiologic information of the patient obtained by the ambulatory medical device” amounts to mere data gathering in conjunction with implementing the recited abstract idea, and is thus insignificant extra-solution activity insufficient to integrate the judicial exception into a practical application.
“wherein processing the received parameter settings further comprises inputting the received physiologic information of the patient into the one or more pre-trained machine learning models” amounts to mere data gathering in conjunction with implementing the recited abstract idea, and is thus insignificant extra-solution activity insufficient to integrate the judicial exception into a practical application.
Regarding Claim 6:
“wherein the operations further comprise: receiving information about the patient comprising one of demographic information or medical history information separate from sensed physiologic information of the patient,” amounts to mere data gathering in conjunction with implementing the recited abstract idea, and is thus insignificant extra-solution activity insufficient to integrate the judicial exception into a practical application.
“wherein processing the received parameter settings further comprises inputting the received information about the patient into the one or more pre-trained machine learning models,” amounts to mere data gathering in conjunction with implementing the recited abstract idea, and is thus insignificant extra-solution activity insufficient to integrate the judicial exception into a practical application.
Regarding Claim 7:
“providing the generated programming recommendation to a user or process” amounts to mere data outputting in conjunction with implementing the recited abstract idea, and is thus insignificant extra-solution activity insufficient to integrate the judicial exception into a practical application.
Regarding Claim 8, Claim 8 does not recite any additional elements.
Regarding Claim 9:
“reprogramming the ambulatory medical device using the generated programming recommendation including changes to one or more parameter settings” amounts to mere data outputting in conjunction with implementing the recited abstract idea, and is thus insignificant extra-solution activity insufficient to integrate the judicial exception into a practical application.
The “reprogramming” is done by the one or more processors, and appears from the Present Specification to entail providing the programming recommendation to the ambulatory device (see, e.g., Para. [0094] of the Present Specification). This amounts to outputting the result of the abstract idea.
“and providing cardiac resynchronization therapy to the patient according to the one or more reprogrammed parameter settings” amounts to mere data outputting in conjunction with implementing the recited abstract idea, and is thus insignificant extra-solution activity insufficient to integrate the judicial exception into a practical application.
As explained above, Claim 9 is being interpreted to require that the one or more processors are configured to output instructions regarding the administration of cardiac resynchronization therapy to the patient according to the one or more reprogrammed parameter settings. Claim 9 is not being interpreted to affirmatively require actual administration of cardiac resynchronization therapy.
Were the ambulatory medical device to be recited as providing cardiac resynchronization therapy, this interpretation may merit consideration and Claim 9 may integrate the recited abstract idea into a practical application.
Regarding Claims 10-12, Claims 10-12 do not recite any additional elements.
Regarding Independent Claim 13:
“A computing device for generating a programming recommendation for an ambulatory medical device to improve cardiac capture in a patient during cardiac resynchronization therapy by the ambulatory medical device, the computing device comprising: one or more processors; and one or more memory devices storing instructions, which when executed by the processor, cause the one or more processors to perform operations comprising:” are generic computer structures for performing a generic computer functions, and thus simply amounts to using a computer as a tool to implement the abstract idea. See MPEP 2106.04(a)(2)(III)(C).
“receiving physiologic information of the patient obtained by the ambulatory medical device; receiving parameter settings of the ambulatory medical device” amounts to mere data gathering in conjunction with implementing the recited abstract idea, and is thus insignificant extra-solution activity insufficient to integrate the judicial exception into a practical application.
“receiving cardiac capture information of the patient during cardiac resynchronization therapy delivered by the ambulatory medical device according to the received parameter settings” amounts to mere data gathering in conjunction with implementing the recited abstract idea, and is thus insignificant extra-solution activity insufficient to integrate the judicial exception into a practical application.
“… processing the received parameter settings by inputting the received parameter settings into one or more pre-trained machine learning models, each of the one or more pre-trained machine learning models trained to compare the received parameter settings to stored model parameter settings from one or more other ambulatory medical devices corresponding to one or more other patients and to identify one or more differences between the parameter settings of the ambulatory medical device and the stored model parameter settings of the one or more other ambulatory medical devices” is insignificant extra-solution activity insufficient to integrate the judicial exception into a practical application for the same reasons explained above with respect to the similar limitation of Claim 1.
“and upon obtaining an output from the one or more pre-trained machine learning models indicating the identified one or more differences between the parameter settings of the ambulatory medical device and parameter settings of the one or more other ambulatory medical devices” is insignificant extra-solution activity insufficient to integrate the judicial exception into a practical application for the same reasons explained above with respect to the similar limitation of Claim 1.
Regarding Claim 14, Claim 14 does not recite any additional elements.
Regarding Independent Claim 15:
“receiving, over a network, parameter settings of the ambulatory medical device” amounts to mere data gathering in conjunction with implementing the recited abstract idea, and is thus insignificant extra-solution activity insufficient to integrate the judicial exception into a practical application.
“processing, using one or more processors, the received parameter settings by inputting the received parameter settings into one or more pre-trained machine learning models, each of the one or more pre-trained machine learning models trained to compare the received parameter settings to stored model parameter settings from one or more other ambulatory medical devices corresponding to one or more other patients and to identify one or more differences between the parameter settings of the ambulatory medical device and the stored model parameter settings of the one or more other ambulatory medical devices” is insignificant extra-solution activity insufficient to integrate the judicial exception into a practical application for the same reasons explained above with respect to the similar limitation of Claim 1.
“and upon obtaining an output from the one or more pre-trained machine learning models indicating the identified one or more differences between the parameter settings of the ambulatory medical device and parameter settings of the one or more other ambulatory medical devices” is insignificant extra-solution activity insufficient to integrate the judicial exception into a practical application for the same reasons explained above with respect to the similar limitation of Claim 1.
Regarding Claim 16, Claim 16 does not recite any additional elements.
Regarding Claims 17:
“comprising: receiving, over the network, cardiac capture information of the patient during cardiac resynchronization therapy delivered by the ambulatory medical device according to the received parameter settings” amounts to mere data gathering in conjunction with implementing the recited abstract idea, and is thus insignificant extra-solution activity insufficient to integrate the judicial exception into a practical application.
“wherein processing the received parameter settings further comprises inputting the received cardiac capture information of the patient into the one or more pre-trained machine learning models” amounts to mere data gathering in conjunction with implementing the recited abstract idea, and is thus insignificant extra-solution activity insufficient to integrate the judicial exception into a practical application.
Regarding Claim 18:
“receiving, over the network, physiologic information of the patient obtained by the ambulatory medical device” amounts to mere data gathering in conjunction with implementing the recited abstract idea, and is thus insignificant extra-solution activity insufficient to integrate the judicial exception into a practical application.
Regarding Claim 19:
“comprising: receiving, over the network, physiologic information of the patient obtained by the ambulatory medical device” amounts to mere data gathering in conjunction with implementing the recited abstract idea, and is thus insignificant extra-solution activity insufficient to integrate the judicial exception into a practical application.
“wherein processing the received parameter settings further comprises inputting the received physiologic information of the patient into the one or more pre-trained machine learning models” amounts to mere data gathering in conjunction with implementing the recited abstract idea, and is thus insignificant extra-solution activity insufficient to integrate the judicial exception into a practical application.
Regarding Claim 20:
“comprising: receiving information about the patient comprising one of demographic information or medical history information separate from sensed physiologic information of the patient, wherein processing the received parameter settings further comprises inputting the received information about the patient into the one or more pre-trained machine learning models” amounts to mere data gathering in conjunction with implementing the recited abstract idea, and is thus insignificant extra-solution activity insufficient to integrate the judicial exception into a practical application.
Eligibility Step 2B: Claims 1-20 do not recite additional elements that integrate the recited judicial exception into a practical application.
Regarding Independent Claim 1:
“A computing device for generating a programming recommendation for an ambulatory medical device to improve cardiac capture in a patient during cardiac resynchronization therapy by the ambulatory medical device, one or more processors; and one or more memory devices storing instructions, which when executed by the processor, cause the one or more processors to perform operations comprising” does not contribute an inventive concept. Such a computing device is recited at a high level of generality, and is well-understood, routine and conventional. See MPEP 2106.05(d)(II). See, e.g., US 2021/0335457 A1 at Para. [0040].
“receiving parameter settings of the ambulatory medical device” does not contribute an inventive concept. Such receiving is recited at a high level of generality, and is well-understood, routine and conventional. See MPEP 2106.05(d)(II). See, e.g., US 2022/0257949 A1 at Para. [0029], describing transmission of programmed parameters between devices as achievable through well-known techniques.
“processing the received parameter settings by inputting the received parameter settings into one or more pre-trained machine learning models, each of the one or more pre-trained machine learning models trained to compare the received parameter settings to stored model parameter settings from one or more other ambulatory medical devices corresponding to one or more other patients and to identify one or more differences between the parameter settings of the ambulatory medical device and the stored model parameter settings of the one or more other ambulatory medical devices” does not contribute an inventive concept. Such inputting is recited at a high level of generality, and is well-understood, routine and conventional. See MPEP 2106.05(d)(II). See, e.g., US 2022/0343475 A1 at Para. [0015].
“obtaining an output from the one or more pre-trained machine learning models indicating the identified one or more differences between the parameter settings of the ambulatory medical device and parameter settings of the one or more other ambulatory medical devices” does not contribute an inventive concept. Such obtaining output is recited at a high level of generality, and is well-understood, routine and conventional. See MPEP 2106.05(d)(II). See MPEP 2106.05(d)(II). See, e.g., US 2022/0343475 A1 at Para. [0015].
Regarding Claim 2, Claim 2 does not recite any additional element.
Regarding Claim 3:
“receiving cardiac capture information of the patient during cardiac resynchronization therapy delivered by the ambulatory medical device according to the received parameter settings” does not contribute an inventive concept. Such information is recited at a high level of generality, and is well-understood, routine and conventional. See MPEP 2106.05(d)(II). See, e.g., US 2014/0180351 A1 at Para. [0039].
“wherein processing the received parameter settings further comprises inputting the received cardiac capture information of the patient into the one or more pre-trained machine learning model” does not contribute an inventive concept. Such inputting is recited at a high level of generality, and is well-understood, routine and conventional as explained above with respect to the similar inputting of Claim 1.
Regarding Claim 4:
“receiving physiologic information of the patient obtained by the ambulatory medical device” does not contribute an inventive concept. Such information is recited at a high level of generality, and is well-understood, routine and conventional in the context of cardiac capture. See MPEP 2106.05(d)(II). See, e.g., US 2014/0180351 A1 at Para. [0039]; See, e.g., US 2022/0257949 A1 at Para. [0029], describing transmission of programmed parameters between devices as achievable through well-known techniques.
Regarding Claim 5:
“receiving physiologic information of the patient obtained by the ambulatory medical device” does not contribute an inventive concept. Such receiving is recited at a high level of generality, and is well-understood, routine and conventional as explained above with respect to the similar Claim 4 limitation.
“wherein processing the received parameter settings further comprises inputting the received physiologic information of the patient into the one or more pre-trained machine learning models” does not contribute an inventive concept. Such inputting is recited at a high level of generality, and is well-understood, routine and conventional as explained above with respect to the similar inputting of Claim 1.
Regarding Claim 6:
“wherein the operations further comprise: receiving information about the patient comprising one of demographic information or medical history information separate from sensed physiologic information of the patient” does not contribute an inventive concept. Such receiving is recited at a high level of generality, and is well-understood, routine and conventional. See MPEP 2106.05(d)(II). See, e.g., US 2022/0257949 A1 at Para. [0029], describing transmission of programmed parameters between devices as achievable through well-known techniques.
“wherein processing the received parameter settings further comprises inputting the received information about the patient into the one or more pre-trained machine learning models,” does not contribute an inventive concept. Such inputting is recited at a high level of generality, and is well-understood, routine and conventional as explained above with respect to the similar inputting of Claim 1.
Regarding Claim 7:
“providing the generated programming recommendation to a user or process” does not contribute an inventive concept. Such providing is recited at a high level of generality, and is well-understood, routine and conventional. See MPEP 2106.05(d)(II). See, e.g., US 2007/0156194 A1 at Para. [0013].
Regarding Claim 8, Claim 8 does not recite any additional elements.
Regarding Claim 9:
“reprogramming the ambulatory medical device using the generated programming recommendation including changes to one or more parameter settings” does not contribute an inventive concept. Such reprogramming is recited at a high level of generality, and is well-understood, routine and conventional. See MPEP 2106.05(d)(II). See Leyva et al., "20 Years of Cardiac Resynchronization Therapy," Journal of the American College of Cardiology, Volume 64, Issue 10, 9 September 2014, Pages 1047-1058 at Abstract, describing cardiac resynchronization therapy as an accepted treatment, and at Pg. 1051, Left Column, First Paragraph describing programming as part of its administration.
“and providing cardiac resynchronization therapy to the patient according to the one or more reprogrammed parameter settings” does not contribute an inventive concept. Such providing is recited at a high level of generality, and is well-understood, routine and conventional as explained above with respect to the similar Claim 7 limitation.
As explained above, Claim 9 is being interpreted to require that the one or more processors are configured to output instructions regarding the administration of cardiac resynchronization therapy to the patient according to the one or more reprogrammed parameter settings. Of note, Claim 9 is not being interpreted to affirmatively require actual administration of cardiac resynchronization therapy.
Regarding Claims 10-12, Claims 10-12 do not recite any additional elements.
Regarding Independent Claim 13:
“A computing device for generating a programming recommendation for an ambulatory medical device to improve cardiac capture in a patient during cardiac resynchronization therapy by the ambulatory medical device, the computing device comprising: one or more processors; and one or more memory devices storing instructions, which when executed by the processor, cause the one or more processors to perform operations comprising” does contribute an inventive concept for the same reasons as explained above with respect to the similar limitation of Claim 1.
“receiving physiologic information of the patient obtained by the ambulatory medical device; receiving parameter settings of the ambulatory medical device” does contribute an inventive concept for the same reasons as explained above with respect to the similar limitation of Claim 4.
“receiving cardiac capture information of the patient during cardiac resynchronization therapy delivered by the ambulatory medical device according to the received parameter settings” does contribute an inventive concept for the same reasons as explained above with respect to the similar limitation of Claim 3.
“upon receiving or determining an indication of a loss of cardiac capture of a heart using the received physiologic information of the patient obtained by the ambulatory medical device, processing the received parameter settings by inputting the received parameter settings into one or more pre-trained machine learning models, each of the one or more pre-trained machine learning models trained to compare the received parameter settings to stored model parameter settings from one or more other ambulatory medical devices corresponding to one or more other patients and to identify one or more differences between the parameter settings of the ambulatory medical device and the stored model parameter settings of the one or more other ambulatory medical devices” does contribute an inventive concept for the same reasons as explained above with respect to the similar limitation of Claim 1.
“and upon obtaining an output from the one or more pre-trained machine learning models indicating the identified one or more differences between the parameter settings of the ambulatory medical device and parameter settings of the one or more other ambulatory medical devices” does contribute an inventive concept for the same reasons as explained above with respect to the similar limitation of Claim 1.
Regarding Claim 14, Claim 14 does not recite any additional elements.
Regarding Independent Claim 15:
“receiving, over a network, parameter settings of the ambulatory medical device” does contribute an inventive concept for the same reasons as explained above with respect to the similar limitation of Claim 1.
“processing, using one or more processors, the received parameter settings by inputting the received parameter settings into one or more pre-trained machine learning models, each of the one or more pre-trained machine learning models trained to compare the received parameter settings to stored model parameter settings from one or more other ambulatory medical devices corresponding to one or more other patients and to identify one or more differences between the parameter settings of the ambulatory medical device and the stored model parameter settings of the one or more other ambulatory medical devices” does contribute an inventive concept for the same reasons as explained above with respect to the similar limitation of Claim 1.
“and upon obtaining an output from the one or more pre-trained machine learning models indicating the identified one or more differences between the parameter settings of the ambulatory medical device and parameter settings of the one or more other ambulatory medical devices” does contribute an inventive concept for the same reasons as explained above with respect to the similar limitation of Claim 1.
Regarding Claim 16, Claim 16 does not recite any additional elements.
Regarding Claim 17, Claim 17 is similar to Claim 3 and does contribute an inventive concept for the same reasons as explained above with respect to Claim 3.
Regarding Claim 18, Claim 18 is similar to Claim 4 and does contribute an inventive concept for the same reasons as explained above with respect to Claim 4.
Regarding Claim 19, Claim 19 is similar to Claim 5 and does contribute an inventive concept for the same reasons as explained above with respect to Claim 5.
Regarding Claim 20, Claim 20 is similar to Claim 6 and does contribute an inventive concept for the same reasons as explained above with respect to Claim 6.
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.
Claims 1-10 and 12-20 are rejected under 35 U.S.C. 103 as being unpatentable over US 2023/0046704 A1 to Yoder et al. (“Yoder”) in view of US 2006/0287685 A1 to Meyer et al. (“Meyer”).
Regarding Independent Claim 1, Yoder teaches:
A computing device for generating a programming recommendation for an ambulatory medical device to improve to improve [efficacy] in a patient during cardiac resynchronization therapy by the ambulatory medical device, (Fig. 1, “monitoring service 6;” Abstract; Claim 1; Para. [0041], “CRT delivered by IMD 16 may help alleviate heart failure conditions by restoring synchronous depolarization and contraction of one or more chambers of heart 12. … The techniques of this disclosure may allow system 10, e.g., IMD 16, to estimate such measures to determine efficacy of CRT and allow feedback control of CRT parameters.”)
The Examiner notes that Yoder does not disclose improving “cardiac capture” specifically, but instead improves efficacy more generally. This deficiency is addressed below.
The Examiner notes that Yoder’s “monitoring service 6” is “for generating a programming recommendation for an ambulatory medical device” in that it is used in conjunction with “an implantable or wearable monitoring device, a pacemaker/defibrillator, or a ventricular assist device (VAD)” (Yoder at Para. [0025]; compare with Present Specification Paras. [0135] through [0138], detailing similar devices as ambulatory).
the computing device comprising: one or more processors; (Fig. 6, “processing circuitry 250” of “monitoring service 6”);
and one or more memory devices storing instructions, which when executed by the processor, cause the one or more processors to perform operations comprising: (Fig. 6, “storage device 260” of “monitoring service 6;” Para. [0161]; Para. [0009]);
receiving parameter settings of the ambulatory medical device; (Para. [0074], “… monitoring service 6 applies first model 7 to an input dataset comprising the patient cardiac activity data and current or default configurable settings that are programmed into detection logic of IMD 16….”);
Yoder’s “IMD 16” is such an ambulatory medical device as claimed (see Yoder at Para. [0025]; compare with Present Specification Paras. [0135] through [0138]). Yoder’s “monitoring service 6 applies first model 7 to an input dataset comprising … current … configurable settings … of IMD 16” (Para. [0074]). Yoder’s “monitoring service 6” thus “receive[s] parameter settings of the ambulatory medical device.”
processing the received parameter settings by inputting the received parameter settings into one or more pre-trained machine learning models, (Para. [0052], “Monitoring service 6 may be configured to feed, into … the machine learning model, input data identifying setting(s) for IMD 16, and then, generate, … output data indicating parameter values and other settings information … for modifying the device setting(s) and improving IMD 16 operation;” Para. [0053]);
each of the one or more pre-trained machine learning models trained to compare the received parameter settings to stored model parameter settings from one or more other ambulatory medical devices corresponding to one or more other patients (Para. [0053], “This can be accomplished by monitoring service 6 directing the building of … the machine learning model to data from only those similar patients and patient 14 instead of the entire patient population;” Para. [0092], “Another example database stores respective settings information corresponding to a plurality of groups (e.g., patient groupings according to demographics such as by age or gender, reasons for monitoring, physiological characteristics, and/or the like)…. Monitoring service 6 may … retrieve information identifying applicable medical devices for the patent population, and … return appropriate settings for pacing therapy…. Hence, monitoring service 6 may employ the one or more databases to calibrate/update settings for different medical devices;” Para. [0093], “Monitoring service 6 may leverage a machine learning model…”);
Yoder compares current settings to settings found effective in other patients (stored in a database) to “calibrate/update settings.” This is precisely such “compar[ing] as claimed. Yoder accomplishes such comparing using a machine learning model, as discussed at Yoder Para. [0093].
and to identify one or more differences between the parameter settings of the ambulatory medical device and the stored model parameter settings of the one or more other ambulatory medical devices; (Para. [0052]; Para. [0093], “ By comparing the appropriate setting information to the current/default settings, monitoring service 6 may identify one or more settings whose modification should result in improved performance;” Para. [0092]);
Yoder’s “comparing the appropriate setting information to the current/default settings” is such “identify[ing] one or more differences between the parameter settings of the ambulatory medical device and the stored model parameter settings of the one or more other ambulatory medical devices” as claimed (see Para. [0092] elaborating upon such “appropriate settings” as discussed in Para. [0093]).
and upon obtaining an output from the one or more pre-trained machine learning models indicating the identified one or more differences between the parameter settings of the ambulatory medical device and parameter settings of the one or more other ambulatory medical devices, generating the programming recommendation for the ambulatory medical device to improve [efficacy] for the patient based on the identified one or more differences. (Para. [0052], “Monitoring service 6 may be configured to feed, into … the machine learning model, input data identifying setting(s) for IMD 16, and then, generate, … output data indicating parameter values and other settings information … for modifying the device setting(s) and improving IMD 16 operation;” Para. [0053]; Para. [0041]; Para. [0092]; Para. [0093]);
As noted above, Yoder does not disclose improving “cardiac capture” specifically, but instead improves efficacy more generally. This deficiency is addressed below.
Yoder differs from the invention of Claim 1 in that Yoder’s methodology does not improve “cardiac capture” specifically, but instead improves efficacy more generally (albeit in the context of cardiac resynchronization therapy).
Yoder does not disclose:
to improve cardiac capture in a patient during cardiac resynchronization therapy
That is, Yoder does not disclose improving “cardiac capture” specifically, but instead improves efficacy more generally.
Meyer describes “Multi-chamber cardiac capture detection using cross chamber sensing” (Title). Meyer is analogous art.
Meyer remedies the deficiencies of Yoder in that Meyer teaches that such capture detection to which Meyer’s disclosure pertains is useful “in order to ascertain whether capture is being achieved by a pacemaker so that such parameters can be adjusted if needed” (Meyer at Para. [0005]). That is, Yoder describes parameter optimization in the context of cardiac resynchronization therapy more generally, and Meyer teaches the specific optimization (i.e., “wherein cardiac capture is improved”) that Yoder lacks.
Meyer teaches:
to improve cardiac capture in a patient during cardiac resynchronization therapy (Para. [0005], “It is therefore desirable to perform a capture verification test at selected times in order to ascertain whether capture is being achieved by a pacemaker so that such parameters can be adjusted if needed;” Para. [0045]; Para. [0007], “Capture detection allows the cardiac rhythm management system to adjust the energy level of pace pulses to correspond to the optimum energy expenditure that reliably produces a contraction.”).
Meyer’s describes adjusting parameters in the event capture is not achieved. Such adjustment is “improv[ing] cardiac capture” as claimed.
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the device of Yoder with the teachings of Meyer (i.e., to modify the device of Yoder such that its parameter adjustments improve cardiac capture in the manner Meyer suggests) in order to improve device efficiency (Meyer at Para. [0005], “A pacing pulse that does not produce capture wastes energy from the limited energy resources (battery) of pacemaker…”), to improve device safety (Meyer at Para. [0005], “A pacing pulse that does not produce capture … can have deleterious physiological effects….”), and to improve device efficacy by ensuring contraction is produced as desired (Meyer at Para. [0005], “A pace pulse must exceed a … capture threshold, to produce a contraction.”).
Regarding Claim 2, the combination of Yoder and Meyer renders obvious the entirety of Claim 1 as explained above.
Neither Yoder nor Meyer explicitly disclose:
wherein to identify the one or more differences between the parameter settings of the ambulatory medical device and the stored model parameter settings comprises to prioritize the identified one or more differences with respect to reduced cardiac pacing or unsuccessful cardiac capture
As explained above, Claim 2 is being interpreted to mean that “one or more differences with respect to reduced cardiac pacing or unsuccessful cardiac capture” are differences that the system is configured to prioritize.
However, Meyer teaches that “A pace pulse must exceed a … capture threshold, to produce a contraction” (Meyer at Para. [0005]) and that “[c]apture detection allows … to adjust the energy level of pace pulses to … reliably produces a contraction” (Meyer at Para. [0007]).
Meyer determines “unsuccessful cardiac capture” and makes parameter adjustments in response.
In modifying the device of Yoder with the teachings of Meyer such that Yoder’s parameter adjustments improve cardiac capture in accordance with the teachings of Meyer as proposed above at Claim 1, it would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to prioritize “one or more differences with respect to reduced cardiac pacing or unsuccessful cardiac capture” in order to improve device efficiency (Meyer at Para. [0005], “A pacing pulse that does not produce capture wastes energy from the limited energy resources (battery) of pacemaker…”), to improve device safety (Meyer at Para. [0005], “A pacing pulse that does not produce capture … can have deleterious physiological effects….”), and to improve device efficacy by ensuring contraction is produced as desired (Meyer at Para. [0005], “A pace pulse must exceed a … capture threshold, to produce a contraction.”).
That is to say, it would have been obvious to further modify the device of combined Yoder and Meyer such that “one or more differences with respect to reduced cardiac pacing or unsuccessful cardiac capture” are prioritized for the same reasons at it would be obvious to make the initial modification. Meyer determines “unsuccessful cardiac capture” and makes parameter adjustments in response. Prioritizing differences with respect to unsuccessful cardiac capture is precisely the modification one of ordinary skill in the art would read Meyer to suggest.
Regarding Claim 3, the combination of Yoder and Meyer renders obvious the entirety of Claim 1 as explained above.
The Examiner notes that Claim 3 is being interpreted to further limit Claim 1 in the sense that it requires additional information to be considered in the same process of Claim 1. This is in contrast to a potential alternative interpretation wherein a process similar to Claim 1 is run a second time as a different process. This interpretation is based on the term “the operations further comprise,” which derives antecedent basis from the “operations” of Claim 1.
Yoder additionally teaches:
wherein the operations further comprise: receiving [patient cardiac activity data] of the patient during cardiac resynchronization therapy delivered by the ambulatory medical device according to the received parameter settings, (Para. [0106], “…the plurality of pacing devices … may communicate to coordinate sensing and pacing in various chambers of heart 12 to provide CRT according to the techniques described herein;” Para. [0074], “… monitoring service 6 applies first model 7 to an input dataset comprising the patient cardiac activity data and current or default configurable settings that are programmed into detection logic of IMD 16….”);
Yoder teaches receiving [patient cardiac activity data] of the patient, but does not teach “wherein the patient cardiac activity data is cardiac capture information.” Meyer remedies this deficiency.
wherein processing the received parameter settings further comprises inputting the received [patient cardiac activity data] of the patient into the one or more pre-trained machine learning models, (Para. [0081], “…the evaluation by monitoring service 6 may incorporate patient data (e.g., patient physiological data) into the machine learning model…;” Para. [0081] later equates “patient data” to “patient cardiac activity data”);
As noted above, Yoder teaches receiving [patient cardiac activity data] of the patient, but does not teach “wherein the patient cardiac activity data is cardiac capture information.” Meyer remedies this deficiency.
each of the one or more pre-trained machine learning models trained to compare the received parameter settings and the received [patient cardiac activity data] information to stored model parameter settings and stored model [patient cardiac activity data] information from one or more other ambulatory medical devices corresponding to one or more other patients and to identify one or more differences between the parameter settings of the ambulatory medical device and the stored model parameter settings of the one or more other ambulatory medical devices, (Para. [0053]; Para. [0092]; Para. [0093]; Para. [0056], “When given example patient cardiac activity data to evaluate for at least one suspected cardiac episode, monitoring service 6 may return the modified settings that are at least more likely than the default settings or the current settings to accurately detect true episodes;” Claim 1; Abstract);
Yoder’s machine learning entails comparing parameter settings for a given set of cardiac activity data for a particular patient to parameter settings for a given set of cardiac activity data for patients in a database, and adjusting parameters based on that comparison. That is, cardiac activity data is the basis upon which parameter settings are compared. This general methodology is evidenced by, e.g., Yoder’s Para. [0056], Claim 1 and Abstract. Yoder’s machine learning model thus receives and compares both [patient cardiac activity data] and parameter settings in the manner claimed.
As explained above at the rejection of Claim 1 with reference to Paras. [0092] and [0093], Yoder’s “comparing the appropriate setting information to the current/default settings” is such “identify[ing]…” as claimed, and is based on [patient cardiac activity data].
As noted above, Yoder teaches receiving [patient cardiac activity data] of the patient, but does not teach “wherein the patient cardiac activity data is cardiac capture information.” Meyer remedies this deficiency.
wherein generating the programming recommendations comprises generating a reprogramming recommendation for the ambulatory medical device to optimize [efficacy] for the patient, (Para. [0052], “Monitoring service 6 may be configured to feed, into … the machine learning model, input data identifying setting(s) for IMD 16, and then, generate, … output data indicating parameter values and other settings information … for modifying the device setting(s) and improving IMD 16 operation;” Para. [0053]; Para. [0041]; Para. [0092]; Para. [0093]);
As explained above, Claim 3 is being interpreted to mean that the “programming recommendation” is instead “a reprogramming recommendation.”
Yoder does not disclose improving “cardiac capture” specifically, but instead improves efficacy more generally. Meyer remedies this deficiency.
wherein the ambulatory medical device comprises an implantable cardiac resynchronization therapy device implanted in the patient. (Para. [0106], “…the plurality of pacing devices … may communicate to coordinate sensing and pacing in various chambers of heart 12 to provide CRT according to the techniques described herein.”)
Meyer additionally teaches:
cardiac capture information (Para. [0007], “Capture detection allows the cardiac rhythm management system to adjust the energy level of pace pulses to correspond to the optimum energy expenditure that reliably produces a contraction;” Para. [0008], “The present invention involves various methods and devices for detecting capture of one or more heart chambers.”);
cardiac capture (Para. [0005]; Para. [0045]; Para. [0007]).
Regarding Claim 4, the combination of Yoder and Meyer renders obvious the entirety of Claim 1 as explained above.
Yoder additionally teaches:
wherein the operations further comprise: receiving physiologic information of the patient obtained by the ambulatory medical device; (Para. [0074], “… monitoring service 6 applies first model 7 to an input dataset comprising the patient cardiac activity data and current or default configurable settings that are programmed into detection logic of IMD 16….”);
Meyer additionally teaches:
and determining an indication of cardiac capture of the patient during cardiac resynchronization therapy delivered by the ambulatory medical device according to the received parameter settings using the received physiologic information. (Para. [0033], “The right ventricular cardiac signal following the RVP may be sensed by a right ventricular sensing channel.... The left ventricular cardiac signal may be sensed … using a left ventricular sensing channel 240. … The lack of cardiac signal sensed on the left ventricular sensing channel 240 during the cross-chamber sensing window 260 following delivery of the LVP in addition to the evoked response of the right ventricle produced by the RVP indicates capture of the right and the left ventricles.”).
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to further modify the device of combined Yoder and Meyer with the teachings of Meyer (i.e., to use as Yoder’s physiologic information such information as described by Meyer as relevant to determining capture, and to determine using that information such an indication of capture as described by Meyer) in order to improve device efficiency (Meyer at Para. [0005], “A pacing pulse that does not produce capture wastes energy from the limited energy resources (battery) of pacemaker…”), to improve device safety (Meyer at Para. [0005], “A pacing pulse that does not produce capture … can have deleterious physiological effects….”), and to improve device efficacy by ensuring contraction is produced as desired (Meyer at Para. [0005], “A pace pulse must exceed a … capture threshold, to produce a contraction.”).
Regarding Claim 5, the combination of Yoder and Meyer renders obvious the entirety of Claim 1 as explained above.
Yoder additionally teaches:
wherein the operations further comprise: receiving physiologic information of the patient obtained by the ambulatory medical device, (Para. [0074]);
Yoder’s “patient cardiac activity data” is such “physiologic information” as claimed.
wherein processing the received parameter settings further comprises inputting the received physiologic information of the patient into the one or more pre-trained machine learning models, (Para. [0081], “…the evaluation by monitoring service 6 may incorporate patient data (e.g., patient physiological data) into the machine learning model…;” Para. [0081] later equates “patient data” to “patient cardiac activity data”);
each of the one or more pre-trained machine learning models trained to compare the received parameter settings and the received physiologic information of the patient to stored model parameter settings from one or more other ambulatory medical devices corresponding to one or more other patients and stored physiologic information from the one or more other patients and to identify one or more differences between the parameter settings of the ambulatory medical device and the stored model parameter settings of the one or more other ambulatory medical devices, (Para. [0053]; Para. [0092]; Para. [0093]; Para. [0056]; Claim 1; Abstract);
This limitation is being interpreted similarly to the similar Claim 3 limitation addressed above.
Meyer additionally teaches:
wherein generating the programming recommendations comprises optimizing cardiac capture for the patient. (Para. [0005], “It is therefore desirable to perform a capture verification test at selected times in order to ascertain whether capture is being achieved by a pacemaker so that such parameters can be adjusted if needed;” Para. [0045]; Para. [0007], “Capture detection allows the cardiac rhythm management system to adjust the energy level of pace pulses to correspond to the optimum energy expenditure that reliably produces a contraction.”).
Regarding Claim 6, the combination of Yoder and Meyer renders obvious the entirety of Claim 1 as explained above.
Yoder additionally teaches:
wherein the operations further comprise: receiving information about the patient comprising one of demographic information or medical history information separate from sensed physiologic information of the patient, (Para. [0066], “…monitoring service 6 receives a dataset comprising demographic parameters for patient 14…”);
wherein processing the received parameter settings further comprises inputting the received information about the patient into the one or more pre-trained machine learning models, (Para. [0093], “Based on the example service request, monitoring service 6 may apply the machine learning model and/or query the one or more databases and retrieve appropriate settings information for IMD 16. By comparing the appropriate setting information to the current/default settings, monitoring service 6 may identify one or more settings whose modification should result in improved performance;” Para. [0092], “Another example database stores respective settings information corresponding to a plurality of groups (e.g., patient groupings according to demographics such as by age or gender, reasons for monitoring, physiological characteristics, and/or the like)…”);
each of the one or more pre-trained machine learning models trained to compare the received parameter settings and the received physiologic information of the patient to stored model parameter settings from one or more other ambulatory medical devices corresponding to one or more other patients and stored information about the one or more other patients and to identify one or more differences between the parameter settings of the ambulatory medical device and the stored model parameter settings of the one or more other ambulatory medical devices, (Para. [0053]; Para. [0092]; Para. [0093]; Para. [0056]; Claim 1; Abstract);
This limitation is being interpreted similarly to the similar Claim 3 limitation addressed above.
Meyer teaches:
wherein generating the programming recommendations comprises optimizing cardiac capture for the patient. (Para. [0005], “It is therefore desirable to perform a capture verification test at selected times in order to ascertain whether capture is being achieved by a pacemaker so that such parameters can be adjusted if needed;” Para. [0045]; Para. [0007], “Capture detection allows the cardiac rhythm management system to adjust the energy level of pace pulses to correspond to the optimum energy expenditure that reliably produces a contraction.”).
Regarding Claim 7, the combination of Yoder and Meyer renders obvious the entirety of Claim 1 as explained above.
Yoder additionally teaches:
wherein the operations further comprise: providing the generated programming recommendation to a user or process. (Para. [0054], “IMD 16 may generate a user interface (UI) to display the modified device setting(s)…”).
Regarding Claim 8, the combination of Yoder and Meyer renders obvious the entirety of Claim 1 as explained above.
Yoder additionally teaches:
wherein providing the generated programming recommendation to the user or process includes providing an output of the generated programming recommendation to a user interface for display to the user or to a control circuit to control or adjust the process or function of the ambulatory medical device (Para. [0054], “IMD 16 may generate a user interface (UI) to display the modified device setting(s)…”).
Regarding Claim 9, the combination of Yoder and Meyer renders obvious the entirety of Claim 8 as explained above.
Yoder additionally teaches:
wherein the operations further comprise: reprogramming the ambulatory medical device using the generated programming recommendation including changes to one or more parameter settings; (Para. [0060], “IMD 16 may set corresponding parameters to values (e.g., default values or reprogrammed values) … and commence operation.”);
and providing cardiac resynchronization therapy to the patient according to the one or more reprogrammed parameter settings. (Para. [0106], “…the plurality of pacing devices … may communicate to coordinate sensing and pacing in various chambers of heart 12 to provide CRT according to the techniques described herein.”).
Regarding Claim 10, the combination of Yoder and Meyer renders obvious the entirety of Claim 1 as explained above.
Yoder additionally teaches:
wherein generating the programming recommendation for the ambulatory medical device to improve [efficacy] for the patient based on the identified one or more differences includes implementing at least one of a set of rules (Para. [0052], “Monitoring service 6 may define rules for a rules-based engine (or other mathematical model) and/or components (e.g., algorithms) of a machine learning model. Monitoring service 6 may be configured to feed, into the rules-based engine and/or the machine learning model, input data identifying setting(s) for IMD 16, and then, generate, for communication to patient 14, output data indicating parameter values and other settings information (e.g., arrhythmia detection criteria) for modifying the device setting(s) and improving IMD 16 operation.”)
Meyer additionally teaches:
cardiac capture (Para. [0005]; Para. [0007]);
associated with the following parameter settings: Atrioventricular Delay Fixed and Atrioventricular Dynamic Maximum. (Para. [0041], “Cardiac resynchronization therapy may involve pacing one or both ventricles following an atrioventricular delay (AVD);” Paras. [0042] through [0043]).
As explained above, the settings “Atrioventricular Delay Fixed” and “Atrioventricular Dynamic Maximum” are being interpreted to mean that atrioventricular delay is considered.
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to further modify the device of combined Yoder and Meyer with the teachings of Meyer (i.e., improve capture rather than general efficacy and to consider atrioventricular delay in Yoder’s rule set) in order to improve device efficiency (Meyer at Para. [0005], “A pacing pulse that does not produce capture wastes energy from the limited energy resources (battery) of pacemaker…”), to improve device safety (Meyer at Para. [0005], “A pacing pulse that does not produce capture … can have deleterious physiological effects….”), and to improve device efficacy by ensuring contraction is produced as desired (Meyer at Para. [0005], “A pace pulse must exceed a … capture threshold, to produce a contraction.”), and because such cardiac resynchronization therapy to which capture is relevant “involve[s] pacing one or both ventricles following an atrioventricular delay” (Meyer at Para. [0041]).
Regarding Claim 12, the combination of Yoder and Meyer renders obvious the entirety of Claim 1 as explained above.
Yoder additionally teaches:
wherein generating the programming recommendation for the ambulatory medical device to improve [efficacy] for the patient based on the identified one or more differences includes implementing at least one of a set of rules (Para. [0052], “Monitoring service 6 may define rules for a rules-based engine (or other mathematical model) and/or components (e.g., algorithms) of a machine learning model. Monitoring service 6 may be configured to feed, into the rules-based engine and/or the machine learning model, input data identifying setting(s) for IMD 16, and then, generate, for communication to patient 14, output data indicating parameter values and other settings information (e.g., arrhythmia detection criteria) for modifying the device setting(s) and improving IMD 16 operation.”)
Meyer additionally teaches:
cardiac capture (Para. [0005]; Para. [0007]);
associated with at least two of the following parameter settings: Sensed Atrioventricular Delay; Atrioventricular Dynamic Minimum; Atrioventricular Delay Fixed; and Atrioventricular Dynamic Maximum. (Para. [0041], “Cardiac resynchronization therapy may involve pacing one or both ventricles following an atrioventricular delay (AVD);” Paras. [0042] through [0043]).
As explained above, the settings “Atrioventricular Delay Fixed” and “Atrioventricular Dynamic Maximum” are being interpreted to mean that atrioventricular delay is considered.
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to further modify the device of combined Yoder and Meyer with the teachings of Meyer (i.e., improve capture rather than general efficacy and to consider atrioventricular delay in Yoder’s rule set) in order to improve device efficiency (Meyer at Para. [0005], “A pacing pulse that does not produce capture wastes energy from the limited energy resources (battery) of pacemaker…”), to improve device safety (Meyer at Para. [0005], “A pacing pulse that does not produce capture … can have deleterious physiological effects….”), and to improve device efficacy by ensuring contraction is produced as desired (Meyer at Para. [0005], “A pace pulse must exceed a … capture threshold, to produce a contraction.”), and because such cardiac resynchronization therapy to which capture is relevant “involve[s] pacing one or both ventricles following an atrioventricular delay” (Meyer at Para. [0041]).
Regarding Independent Claim 13, Yoder teaches:
A computing device for generating a programming recommendation for an ambulatory medical device to improve [efficacy] in a patient during cardiac resynchronization therapy by the ambulatory medical device, (Fig. 1, “monitoring service 6;” Abstract; Claim 1; Para. [0041]; see Rejection of Claim 1 above, elaborating)
The Examiner notes that Yoder does not disclose improving “cardiac capture” specifically, but instead improves efficacy more generally. This deficiency is addressed below.
the computing device comprising: one or more processors; (Fig. 6, “processing circuitry 250” of “monitoring service 6”);
and one or more memory devices storing instructions, which when executed by the processor, cause the one or more processors to perform operations comprising: (Fig. 6, “storage device 260” of “monitoring service 6;” Para. [0161]; Para. [0009]);
receiving physiologic information of the patient obtained by the ambulatory medical device; (Para. [0074]);
Yoder’s “patient cardiac activity data” is such “physiologic information” as claimed.
receiving parameter settings of the ambulatory medical device; (Para. [0074], “… monitoring service 6 applies first model 7 to an input dataset comprising the patient cardiac activity data and current or default configurable settings that are programmed into detection logic of IMD 16….”);
See Rejection of Claim 1 above, elaborating.
processing the received parameter settings by inputting the received parameter settings into one or more pre-trained machine learning models, each of the one or more pre-trained machine learning models trained to compare the received parameter settings to stored model parameter settings from one or more other ambulatory medical devices corresponding to one or more other patients and to identify one or more differences between the parameter settings of the ambulatory medical device and the stored model parameter settings of the one or more other ambulatory medical devices; (Para. [0052]; Para. [0053]; Para. [0092]; Para. [0093]);
See Rejection of Claim 1 above, elaborating.
and upon obtaining an output from the one or more pre-trained machine learning models indicating the identified one or more differences between the parameter settings of the ambulatory medical device and parameter settings of the one or more other ambulatory medical devices, generating the programming recommendation for the ambulatory medical device based on the identified one or more differences. (Para. [0052]; Para. [0053]; Para. [0041]; Para. [0092]; Para. [0093]);
Yoder differs from the invention of Claim 1 in that Yoder’s methodology does not improve “cardiac capture” specifically, but instead improves efficacy more generally (albeit in the context of cardiac resynchronization therapy).
Yoder does not disclose
to improve cardiac capture in a patient during cardiac resynchronization therapy
That is, Yoder does not disclose improving “cardiac capture” specifically, but instead improves efficacy more generally.
receiving cardiac capture information of the patient during cardiac resynchronization therapy delivered by the ambulatory medical device according to the received parameter settings;
upon receiving or determining an indication of a loss of cardiac capture of a heart using the received physiologic information of the patient obtained by the ambulatory medical device,
That is, Yoder does not consider cardiac capture specifically and thus does not base its timing upon loss of cardiac capture.
Meyer describes “Multi-chamber cardiac capture detection using cross chamber sensing” (Title). Meyer is analogous art.
Meyer remedies the deficiencies of Yoder in that Meyer teaches that such capture detection to which Meyer’s disclosure pertains is useful “in order to ascertain whether capture is being achieved by a pacemaker so that such parameters can be adjusted if needed” (Meyer at Para. [0005]). That is, Yoder describes parameter optimization in the context of cardiac resynchronization therapy more generally, and Meyer teaches the specific optimization (i.e., “wherein cardiac capture is improved”) that Yoder lacks.
to improve cardiac capture in a patient during cardiac resynchronization therapy (Para. [0005], “It is therefore desirable to perform a capture verification test at selected times in order to ascertain whether capture is being achieved by a pacemaker so that such parameters can be adjusted if needed;” Para. [0045]; Para. [0007], “Capture detection allows the cardiac rhythm management system to adjust the energy level of pace pulses to correspond to the optimum energy expenditure that reliably produces a contraction.”).
Meyer’s describes adjusting parameters in the event capture is not achieved. Such adjustment is “improv[ing] cardiac capture” as claimed.
receiving cardiac capture information of the patient during cardiac resynchronization therapy delivered by the ambulatory medical device according to the received parameter settings; (Paras. [0050] through [0053], describing various pacemaker actions in response to capture status as indicated by capture verification test results; Paras. [0005], “It is therefore desirable to perform a capture verification test at selected times in order to ascertain whether capture is being achieved by a pacemaker so that such parameters can be adjusted if needed.”);
Meyer determines whether capture has occurred (see, e.g., Meyer at Paras. [0050] through [0053]), and makes parameter adjustments if not (see, e.g., Meyer at Para. [0005]). Meyer’s determination is such “cardiac capture information” as claimed, and used to make parameter adjustments if necessary. Meyer’s determination must be received alongside the remainder of Meyer’s input for Meyer’s determination to be used in this way.
upon receiving or determining an indication of a loss of cardiac capture of a heart using the received physiologic information of the patient obtained by the ambulatory medical device, (Paras. [0050] through [0053], describing various pacemaker actions in response to capture status as indicated by capture verification test results; Paras. [0005]; Para. [0051], “During delivery of pacing therapy to the patient, the pacemaker may detect loss of capture. …”).
Meyer’s describes loss of cardiac capture at Para. [0051] in the context of describing various pacemaker actions in response to capture status as indicated by capture verification test results. Meyer’s capture is determined using physiologic information similar to Yoder’s (see, e.g., Meyer at Para. [0052]). Meyer’s making parameter adjustments in response to non-capture at Para. [0005]. Meyer thus describes determining parameter adjustments “upon receiving or determining an indication of a loss of cardiac capture” as claimed using such physiologic information as claimed.
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the device of Yoder with the teachings of Meyer (i.e., to modify the device of Yoder such that its parameter adjustments improve cardiac capture in the manner Meyer suggests) in order to improve device efficiency (Meyer at Para. [0005], “A pacing pulse that does not produce capture wastes energy from the limited energy resources (battery) of pacemaker…”), to improve device safety (Meyer at Para. [0005], “A pacing pulse that does not produce capture … can have deleterious physiological effects….”), and to improve device efficacy by ensuring contraction is produced as desired (Meyer at Para. [0005], “A pace pulse must exceed a … capture threshold, to produce a contraction.”).
It would have been obvious for a person of ordinary skill in the art before the effective filing date to modify the device of Yoder with the teachings of Meyer (i.e., to receive cardiac capture information in the manner of Meyer, and to initiate Yoder’s parameter adjustment process in response to loss of cardiac capture in the manner of Meyer) because such further modification is implicit with modifying the device of Yoder such that its parameter adjustments improve cardiac capture in the manner Meyer suggests. Meyer describes determining parameter adjustments in response to non-capture: initiating such adjustment determination “upon receiving or determining an indication of a loss of cardiac capture” is the only logical way to implement modifying the device of Yoder such that its parameter adjustments improve cardiac capture in the manner Meyer suggests.
Regarding Claim 14, the combination of Yoder and Meyer renders obvious the entirety of Claim 13 as explained above.
Yoder additionally teaches:
wherein the operations further comprise: upon obtaining an output from the one or more pre-trained machine learning models indicating differences between the parameter settings of the ambulatory medical device and parameter settings of the one or more other ambulatory medical devices, (Para. [0052]; Para. [0053]; Para. [0041]; Para. [0092]; Para. [0093]);
See rejection of similar Claim 13 limitation, above.
Meyer additionally teaches:
prioritizing the one or more differences with respect to a potential or detected loss of cardiac capture or reduced pacing (Paras. [0050] through [0053], describing various pacemaker actions in response to capture status as indicated by capture verification test results; Paras. [0005]; Para. [0051], “During delivery of pacing therapy to the patient, the pacemaker may detect loss of capture. …”).
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to further modify the device of combined Yoder and Meyer with the teachings of Meyer (i.e., to prioritize differences pertaining to loss of cardiac capture) in order to improve device efficiency (Meyer at Para. [0005], “A pacing pulse that does not produce capture wastes energy from the limited energy resources (battery) of pacemaker…”), to improve device safety (Meyer at Para. [0005], “A pacing pulse that does not produce capture … can have deleterious physiological effects….”), and to improve device efficacy by ensuring contraction is produced as desired (Meyer at Para. [0005], “A pace pulse must exceed a … capture threshold, to produce a contraction.”).
Regarding Independent Claim 15, Yoder teaches:
A method for generating a programming recommendation for an ambulatory medical device to improve [efficacy] in a patient during cardiac resynchronization therapy by the ambulatory medical device, the method comprising: (Title; Fig. 1, “monitoring service 6;” Abstract; Claim 1; Para. [0041], “CRT delivered by IMD 16 may help alleviate heart failure conditions by restoring synchronous depolarization and contraction of one or more chambers of heart 12. … The techniques of this disclosure may allow system 10, e.g., IMD 16, to estimate such measures to determine efficacy of CRT and allow feedback control of CRT parameters.”);
The Examiner notes that Yoder does not disclose improving “cardiac capture” specifically, but instead improves efficacy more generally. This deficiency is addressed below.
receiving, over a network, parameter settings of the ambulatory medical device; (Para. [0074], “… monitoring service 6 applies first model 7 to an input dataset comprising the patient cardiac activity data and current or default configurable settings that are programmed into detection logic of IMD 16….”);
See rejection of similar Claim 1 limitation above, elaborating.
Yoder’s “monitoring service 6” communicates via a network (see Yoder at Para. [0048]).
processing, using one or more processors, the received parameter settings by inputting the received parameter settings into one or more pre-trained machine learning models, (Para. [0052], “Monitoring service 6 may be configured to feed, into … the machine learning model, input data identifying setting(s) for IMD 16, and then, generate, … output data indicating parameter values and other settings information … for modifying the device setting(s) and improving IMD 16 operation;” Para. [0053]);
Yoder’s inputting is done via processor. See Rejection of Claim 1 above.
each of the one or more pre-trained machine learning models trained to compare the received parameter settings to stored model parameter settings from one or more other ambulatory medical devices corresponding to one or more other patients and to identify one or more differences between the parameter settings of the ambulatory medical device and the stored model parameter settings of the one or more other ambulatory medical devices; (Para. [0052]; Para. [0053]; Para. [0092]; Para. [0093]; see rejection of similar Claim 1 limitation above);
and upon obtaining an output from the one or more pre-trained machine learning models indicating the identified one or more differences between the parameter settings of the ambulatory medical device and parameter settings of the one or more other ambulatory medical devices, generating, using the one or more processors, the programming recommendation for the ambulatory medical device to improve [efficacy] for the patient based on the identified one or more differences. (Para. [0052]; Para. [0053]; Para. [0041]; Para. [0092]; Para. [0093]; see rejection of similar Claim 1 limitation above).
As noted above, Yoder does not disclose improving “cardiac capture” specifically, but instead improves efficacy more generally. This deficiency is addressed below.
Yoder does not disclose:
to improve cardiac capture in a patient during cardiac resynchronization therapy
That is, Yoder does not disclose improving “cardiac capture” specifically, but instead improves efficacy more generally.
Meyer describes “Multi-chamber cardiac capture detection using cross chamber sensing” (Title). Meyer is analogous art.
Meyer remedies the deficiencies of Yoder in that Meyer teaches that such capture detection to which Meyer’s disclosure pertains is useful “in order to ascertain whether capture is being achieved by a pacemaker so that such parameters can be adjusted if needed” (Meyer at Para. [0005]). That is, Yoder describes parameter optimization in the context of cardiac resynchronization therapy more generally, and Meyer teaches the specific optimization (i.e., “wherein cardiac capture is improved”) that Yoder lacks.
Meyer teaches:
to improve cardiac capture in a patient during cardiac resynchronization therapy (Para. [0005]; Para. [0045]; Para. [0007]).
Meyer’s describes adjusting parameters in the event capture is not achieved. Such adjustment is “improv[ing] cardiac capture” as claimed.
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the device of Yoder with the teachings of Meyer (i.e., to modify the device of Yoder such that its parameter adjustments improve cardiac capture in the manner Meyer suggests) in order to improve device efficiency (Meyer at Para. [0005], “A pacing pulse that does not produce capture wastes energy from the limited energy resources (battery) of pacemaker…”), to improve device safety (Meyer at Para. [0005], “A pacing pulse that does not produce capture … can have deleterious physiological effects….”), and to improve device efficacy by ensuring contraction is produced as desired (Meyer at Para. [0005], “A pace pulse must exceed a … capture threshold, to produce a contraction.”).
Regarding Claim 16, Claim 16 is similar to Claim 2. The combination of Yoder and Meyer renders obvious the entirety of Claim 16 for the same reasons as explained above with respect to Claim 2.
Regarding Claim 17, Claim 17 is similar to Claim 3. The combination of Yoder and Meyer renders obvious the entirety of Claim 17 for the same reasons as explained above with respect to Claim 3.
Regarding Claim 17, Claim 17 is similar to Claim 3. The combination of Yoder and Meyer renders obvious the entirety of Claim 17 for the same reasons as explained above with respect to Claim 3.
Regarding Claim 18, Claim 18 is similar to Claim 4. The combination of Yoder and Meyer renders obvious the entirety of Claim 18 for the same reasons as explained above with respect to Claim 4.
Regarding Claim 19, Claim 19 is similar to Claim 5. The combination of Yoder and Meyer renders obvious the entirety of Claim 19 for the same reasons as explained above with respect to Claim 5.
Regarding Claim 20, Claim 20 is similar to Claim 6. The combination of Yoder and Meyer renders obvious the entirety of Claim 20 for the same reasons as explained above with respect to Claim 6.
Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over US 2023/0046704 A1 to Yoder et al. (“Yoder”) in view of US 2006/0287685 A1 to Meyer et al. (“Meyer”) as applied to Claim 1 above, and further in view of US 2019/0232065 A1 to Perschbacher et al. (“Perschbacher”).
Regarding Claim 11, the combination of Yoder and Meyer renders obvious the entirety of Claim 1 as explained above.
Yoder additionally teaches:
wherein generating the programming recommendation for the ambulatory medical device to improve [efficacy] for the patient based on the identified one or more differences includes implementing at least one of a set of rules (Para. [0052]).
Meyer additionally teaches:
cardiac capture (Para. [0005]; Para. [0007]);
associated with at least two of the following parameter settings: … and Sensing Mode (Para. [0078] references a sensing mode);
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to further modify the device of combined Yoder and Meyer with the teachings of Meyer (i.e., improve capture rather than general efficacy and to use such a sense mode as taught by Meyer) in order to improve device efficiency (Meyer at Para. [0005], “A pacing pulse that does not produce capture wastes energy from the limited energy resources (battery) of pacemaker…”), to improve device safety (Meyer at Para. [0005], “A pacing pulse that does not produce capture … can have deleterious physiological effects….”), and to improve device efficacy by ensuring contraction is produced as desired (Meyer at Para. [0005], “A pace pulse must exceed a … capture threshold, to produce a contraction.”), and because such sensing modes would facilitate detection (Meyer at Para. [0078]).
The combination of Yoder and Meyer does not disclose:
associated with at least two of the following parameter settings: Atrial Tachy Response Mode; Biventricular Trigger Enable; Ventricular Tachycardia Zone Rate; Atrial Tachy Response Trigger Rate; Maximum Sensor Rate Interval; Ventricular Tachycardia 1 Zone Rate; Number of Ventricular Zones; Ventricular Fibrillation Zone Rate; Atrial Tachy Response Ventricular Rate Regulation Response; Atrial Tachy Response Biventricular Trigger Enable; Atrial Tachy Response Lower Rate Limit; Tachycardia Mode; Respiration Rate Trend Enable; Atrial Tachy Response Pacing Chamber;…
Perschbacher describes “Systems and methods for monitoring chronic over-pacing (COP) to the heart…” (Abstract). Perschbacher is reasonably pertinent to the problem faced by the inventor, and is thus analogous art.
Perschbacher teaches:
associated with at least two of the following parameter settings: Atrial Tachy Response Mode; Biventricular Trigger Enable; Ventricular Tachycardia Zone Rate; Atrial Tachy Response Trigger Rate; Maximum Sensor Rate Interval; Ventricular Tachycardia 1 Zone Rate; Number of Ventricular Zones; Ventricular Fibrillation Zone Rate; Atrial Tachy Response Ventricular Rate Regulation Response; Atrial Tachy Response Biventricular Trigger Enable; Atrial Tachy Response Lower Rate Limit; Tachycardia Mode; Respiration Rate Trend Enable; Atrial Tachy Response Pacing Chamber;… (Para. [0070], “Atrial tachy response (ATR) parameter and mode switch may be used to prevent rapid ventricular pacing in the presence of atrial tachyarrhythmia.”).
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to modify the device of combined Yoder and Meyer with the teachings of Perschbacher (i.e., to employ such an atrial tachy response mode as taught by Perschbacher) in order to “prevent rapid ventricular pacing in the presence of atrial tachyarrhythmia” (Perschbacher at Para. [0070]).
Notice of Art Deemed Relevant Although Not Relied Upon
The Examiner notes the following prior art, which is deemed relevant although not relied upon in any foregoing rejection:
US 2024/0065620 A1 describes “Systems for determining medication-adjusted clinical effects” (Title) and features a machine-learning approach similar to that of Present Claim 1 at Abstract.
Conclusion
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/C.J.M./Examiner, Art Unit 3796
/LYNSEY C Eiseman/Primary Examiner, Art Unit 3796
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