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 .
Response to Amendment
Applicant filed amended claims on Sept-08 2026 and addressed all previous 35 U.S.C. 112(b) rejections set forth in the Non-Final Office Action mailed June-05 2026. These rejections are withdrawn.
Applicant’s amendments re. claims 1, 19 and 20 necessitate a new grounds of rejection.
Response to Arguments
Drawing Objection
Applicant argues that FIG. 5 illustrates the invention and, therefore, should not be labeled prior art. In the specification, for example, Applicant has described many aspects of the invention with specific reference to FIG. 5. In this light, FIG. 5 illustrates an example system embodying the invention. For this reason, "prior art" labels would be inappropriate.
However, Fig 5 of the instant application illustrates the same components, in the same manner and arrangement, with the same reference number as Fig. 1 of Chakravarthy (US 2021/0386312).
These figures are identical, except for the placement of the reference numbers on the figure. (Examiner notes that the design elements to which each reference number refers are in and identical places in each figure, only the position of the number that identifies it and the arrows connecting that number to the element are different).
In the instant application, applicant describes figure 5 noting that “FIG. 5 illustrates the environment of an example medical system 2 in conjunction with a patient 4, in accordance with one or more techniques of this disclosure… In some examples, system 2 may include IMD 10… System 2 may also include external device 12… system 2 may be used to measure subcutaneous impedance to provide to patient 4 other users an early warning for the onset of a heart failure decompensation event. The example techniques may be used with an IMD 10, which may be in wireless communication with at least one of external device 12… In some examples, IMD 10 is implanted outside of a thoracic cavity of patient 4 (e.g., subcutaneously in the pectoral location illustrated in FIG. 5). IMD 10 may be positioned near the sternum near or just below the level of the heart of patient 4, e.g., at least partially within the cardiac silhouette. IMD 10 may include a plurality of electrodes and may be configured for subcutaneous implantation outside of a thorax of patient 4” in [0101]-[0103].
Likewise, Chakravarthy discloses “FIG. 1 illustrates the environment of an example medical device system 2 in conjunction with a patient 4 and a heart 6… The example techniques may be used with an IMD 10, which may be leadless and in wireless communication with external device 12, as illustrated in FIG. 1… In some examples, IMD 10 may be implanted outside of a thoracic cavity of patient 4 (e.g., subcutaneously in the pectoral location illustrated in FIG. 1). IMD 10 may be positioned near the sternum near and/or just below the level of heart 6” in [0026].
As can be seen from the specification, the same elements in the same arrangements are described in both figures. Therefore, what is presented in Fig. 5 of the instant application is already known in the art. This argument is unpersuasive, and the drawing objection is maintained.
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Applicant has amended claim 1 to include some of the subject matter of originally-filed claim 18, which Applicant notes was not rejected under 35 U.S.C. § 101.
Rejection under 35 U.S.C. 101
Applicant has amended claim 1 to include some of the subject matter of originally-filed claim 18, which Applicant notes was not rejected under 35 U.S.C. § 101. Applicant argues that the inclusion of this subject renders the claim as eligible subject matter for at least the same reason as originally-filed claim 18. Specifically, claim 1 has been amended to include a physiological sensor configured to sense at least one parameter wherein the physiological sensor comprises at least one of an electrode and an optical sensor.
However, the use of an electrode and/or the use of an optical sensor to sense a parameter constitutes no more than the insignificant pre-solution activity of data gathering and does not impose meaningful limitation on the abstract ideas of determining and sending a notification. The use of electrodes and optical sensors to collect cardiac data is well-understood, routine, and conventional activity as evidenced by Reilly & Lee (Electrograms (ECG, EEG, EMG, EOG), Pg 3-4, Sec 3.1 Basis of the ECG ) and Park et al. (Photoplethysmogram Analysis and Applications: An Integrative Review, pg 6-7 table 1) respectively.
Rejection under 35 U.S.C. 102
Applicant argues that Chakravarthy in view of Medtronic does not anticipate claims 1-9, 11-3, & 15-17. Applicant argues that because, as laid out in the Double Patenting rejection in the Non-Final Office Action mailed June-05 2026, the claims of US. Patent No. 11,504,048 do not explicitly encompass the limitations “based on at least one comorbidity of the patient” and “send a notification to the patient” that Chakravarthy (US 2021/0386312) fails to disclose or suggest these elements. The examiner notes that while Chakravarthy (US 2021/0386312 A1) is the PG-Pub of patent application 16/897912, which was issued as US. Patent No. 11,504,048 (US 11504048 B2). US 2021/0386312 A1 is a separate document from US 11504048 B2, that qualifies as prior art by virtue of being published before the effective filing date of instant application. As explained in MPEP 1504.06(II) “In determining whether to make a nonstatutory double patenting rejection between designs having differing scope, the examiner should compare the reference claim with the application claim” (emphasis added). US. Patent No. 11,504,048 (US 11504048 B2) does not claim the elements “based on at least one comorbidity of the patient” and “send a notification to the patient”, however Chakravarthy (US 2021/0386312 A1) does DISCLOSE those elements, as laid out in both the obviousness type double patenting rejection and the 35 U.S.C. 102 rejection in [0057] and [0098]. The 35 U.S.C. 102 rejection is based on the entirety of the disclosure of Chakravarthy (US 2021/0386312 A1), not only on what was claimed in the application. This argument is not persuasive.
Applicant further argues that claim 1, as amended, is not anticipated by Chakravarthy as Chakravarthy fails to disclose or suggest "determine an exercise tolerance level for the patient based on values of the set of one or more patient parameters" and that "at least one parameter of a set of one or more patient parameters [is] based on one or more cardiac signals of a patient sensed by the physiological sensor." These arguments are rendered unpersuasive by new grounds of rejection, but are addressed here as they may still be relevant to the new grounds of rejection.
In the Non-Final Office Action mailed June-05 2026, [0040] and [0097] of Chakravarthy are cited. In brief, these paragraphs describe determining an activity level based on motion sensors, and that this activity level is used, in part to determine a heart rate threshold. The examiner notes that the amended claim language “determine an exercise tolerance level for the patient based on values of the set of one or more patient parameters” still reads on the use of a motion as one of the patient parameter, and that the claim language “at least one parameter of a set of one or more patient parameters [is] based on one or more cardiac signals” does not preclude the use of other parameters besides at least one parameter based on one or more cardiac signals to determine an exercise tolerance level. In other words, the claim as drafted does not require that values of every parameter in the set be used, or that the values that are used come from the parameter based on one or more cardiac signals.
Drawings
Figure 5 should be designated by a legend such as --Prior Art-- because only that which is old is illustrated. Specifically, all matter disclosed in Fig. 5 of the instant application is also disclosed in the same way in Fig. 1 of applicant admitted prior art in U.S. PGPUB No. 2021/0386312 to Chakravarthy.
See MPEP § 608.02(g). Corrected drawings in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. The replacement sheet(s) should be labeled “Replacement Sheet” in the page header (as per 37 CFR 1.84(c)) so as not to obstruct any portion of the drawing figures. If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Claim Objections
Claim18, as amended, is objected to because of the following informalities: in line 7 "the physiological sensor comprises a second electrode" would be more appropriately worded "the . Appropriate correction is required.
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 1-17, & 19-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1:
Claims 1-17 recite a medical device system and therefore is a product.
Therefore, the claims fall within the statutory categories.
Step 2A, Prong 1:
Claim 1 recites the following limitations:
determine values of a set of one or more parameters
determine an exercise tolerance level based on values of the set of one or more patient parameters and based on at least one comorbidity of the patient
determine that a present activity level exceeds the exercise tolerance level
send a notification to the patient
The limitations, as drafted, describe a process that, under its broadest reasonable interpretation, includes performance of the limitation in the mind except for the recitation of “an implantable or wearable medical device”, and “processing circuitry”. For the limitation of “an implantable or wearable medical device”, the specification discloses “a device includes a memory and processing circuity” in [0008] of the USPGPub version. Therefore “an implantable or wearable medical device” and “processing circuitry” recited at a high level of generality would be nothing more than a generic computer. That is, other than reciting that “an implantable or wearable medical device” and “processing circuitry” (nothing more than a generic computer) are performing these tasks, nothing in the claim precludes the steps from practically being performed in the human mind or being considered as methods of organizing human activity. MPEP 2106.04(a)(2)(II) states that the sub-grouping "managing personal behavior or relationships or interactions between people" include social activities, teaching, and following rules or instructions and MPEP 2106.04(a)(2)(III) states that the courts consider a mental process (thinking) that "can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. For example, aside from the recitations of “an implantable or wearable medical device” and “processing circuitry” language, the claims encompass the medical professional gathering biological data, determining a safe activity level for a patient, assessing whether the patient has exceeded that activity level, and notifying the patient.
Step 2A, Prong 2:
The claims recite “an implantable or wearable medical device”, and “processing circuitry” to perform the abstract steps. These limitations read on a computer implemented system and method and are recited at a high level of generality, i.e., as a generic processor, performing a generic computer function of processing data. This generic processor limitation is no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional limitation does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
The claims also recite “a physiological sensor configured to sense at least one parameter… wherein the physiological sensor comprises at least one of an electrode and an optical sensor.” These generic at least one of an electrode and an optical sensor perform no more than the insignificant pre-solution activity of data gathering, and act as the source of the parameters upon which the abstract idea is performed. Accordingly, this additional limitation does not integrate the abstract idea into a practical application because it is insignificant extra-solution activity that does not impose any meaningful limits on practicing the abstract idea.
Step 2B:
As discussed with respect to Step 2A Prong Two, the additional elements in the claim amount to no more than mere instructions to apply the exception using a generic computer component. The same analysis applies here in 2B, i.e., mere instructions to apply an exception on a generic computer cannot integrate a judicial except into a practical application at Step 2A or provide an inventive concept in Step 2B.
Under 2019 PEG, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be re-evaluated in Step 2B to determined if it is more than what is well-understood, routine, conventional activity in the field. The specification in [0053] does not provide any indication that the computer processor is anything other than a generic, off-the-shelf computer component. Court decisions cited in MPEP 2106.05(d)(II) indicate that computer‐implemented processes not to be significantly more than an abstract idea (and thus ineligible) where the claim as a whole amounts to nothing more than generic computer functions merely used to implement an abstract idea, such as an idea that could be done by a human analog (i.e., by hand or by merely thinking). Accordingly, a conclusion that the generic computer functions merely being used to implement an abstract idea is well-understood, routine, conventional activity is supported under Berkheimer Option 2.
The use of electrodes and optical sensors to collect cardiac data is well-understood, routing, and conventional activity as evidenced by Reilly & Lee (Electrograms (ECG, EEG, EMG, EOG), Pg 3-4, Sec 3.1 Basis of the ECG ) and Kim & Baek (Photoplethysmography in Wearable Devices: A Comprehensive Review of Technological Advances, Current Challenges, and Future Directions, pg 2 ¶2) respectively.
Dependent claims 2-17 further limit the abstract idea already indicated in independent claim 1 and they are ineligible for the same reasons provided for claim 1 above.
Regarding claims 9 and 17 the additional elements “smartphone” and “cloud computing system” further limits “processing circuitry”. These elements are recited at a high level of generality, as any commercial smartphone, or generic cloud computing system. The generic cloud computing system merely being used to implement an abstract idea is well-understood, routine, conventional activity is supported under Berkheimer Option 2. Furthermore, the use of mobile devices and cloud computing devices in medical device technology is well-understood, routine, conventional activity as evidenced by Krohn and Metcalf (mHealth from Smartphones to Smart Systems, HIMSS, 2012, pp55-64).
For these reasons, there is no inventive concept in the claims and thus they are ineligible.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1-9, 11-12, 15-18 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 10-18 of U.S. Patent No. 11504048 in view of U.S. PGPUB No. 20210386312 to Chakravarthy (herein after referred to as Chakravarthy).
With respect to instant claims 1-4, 6-7, 12, 15-17
Instant Application18/857295
Conflicting Patent
US 11504048 B2
Differences
Claim 1
A medical device system comprising: an implantable or wearable medical device
Claim 10
A medical device comprising: memory; and processing circuitry
comprising a physiological sensor configured to sense at least one parameter
comprising a physiological sensor configured to sense at least one parameter
configured to determine values of a set of one or more patient parameters based on one or more cardiac signals
Claim 13
The medical device of claim 10 configured to: determine whether the heart rate of the patient is less than or equal to the heart rate threshold
of a patient sensed by the physiological sensor, wherein the physiological sensor comprises at least one of an electrode and an optical sensor
of a patient sensed by the physiological sensor, wherein the physiological sensor comprises at least one of an electrode and an optical sensor
and processing circuitry configured to: determine an exercise tolerance level for the patient based on the values of the set of one or more patient parameters and
Claim 11
The medical device of claim 10, configured to: in response to determining that the activity level of the patient meets or exceeds a first activity level, set the heart rate threshold for triggering detection of the arrhythmia episode to a first heart rate threshold
based on at least one comorbidity of the patient
based on at least one comorbidity of the patient
determine that a present activity level for the patient exceeds the exercise tolerance level for the patient;
Claim 10
determine whether the activity level of the patient meets or exceeds an activity level threshold
send a notification to the patient
send a notification to the patient
Claim 2
The system of claim 1,
As claim 1
wherein the processing circuitry is further configured to: determine the exercise tolerance level based on the values of the set of one or more patient parameters and
Claim 11
The medical device of claim 10, configured to: in response to determining that the activity level of the patient meets or exceeds a first activity level, set the heart rate threshold for triggering detection of the arrhythmia episode to a first heart rate threshold
values of one or more additional parameters, wherein the values of the one or more additional parameters are not received from the medical device.
Claim 11
determine the first heart rate threshold based at least in part on an age-predicted maximal heart rate for the patient
Claim 3
The system of claim 2, wherein at least one of the one or more additional parameters includes
as Claim 2
a parameter indicative of the comorbidity of the patient
a parameter indicative of the comorbidity of the patient
Claim 4
The system of claim 1,
As claim 1
wherein the set of one or more patient parameters comprise parameters usable to determine if the patient is engaged in exceeding a risk threshold
Claim 10
where in to determine whether to trigger detection of the arrhythmia episode for the patient based at least in part on comparing a heart rate of the patient with the heart rate threshold
in view of the comorbidity of the patient.
in view of the comorbidity of the patient.
Claim 6
The system of claim 1,
As claim 1
wherein to determine the exercise tolerance level based on the values of the set of one or more patient parameters, the processing circuitry is further configured to apply the values of the set of one or more patient parameters to a patient model that is configured at least in part based on past data of the patient.
Claim 14
The medical device of claim 10, configured to … in response to determining that the activity level for the patient is below the resting threshold for at least the specified period of time, determine the heart rate threshold for triggering detection of the arrhythmia episode.
Claim 7
The system of claim 1,
As claim 1
wherein the processing circuitry is further configured to: determine the present activity level for the patient based on values of a second set of one or more patient parameters.
Claim 10
receive, from one or more motion sensors, one or more sensor values indicative of motion of a patient; determine, based on the one or more sensor values, an activity level of the patient;
Claim 12
The system of claim 1,
(as Claim 1)
wherein the set of one or more patient parameters includes ONE or more of: a heart rate
Claim 10
determine whether to trigger detection of the arrhythmia episode for the patient based at least in part on comparing a heart rate of the patient with the heart rate threshold;
Claim 15
The system of claim 1,
(as Claim 1)
wherein the at least one comorbidity comprises at least one of heart failure, coronary artery disease, or prior myocardial infarction and another health condition.
at least one comorbidity comprises at least one of: heart failure
Claim 16
The system of claim 1,
(as Claim 1)
wherein processing circuitry is configured to: determine a risk level of a cardiac event comprising arrhythmia of the patient based on the values of the set of one or more patient parameters; and determine the exercise tolerance level based on the risk level of the adverse health event.
Claim 15
The medical device of claim 14, wherein to determine whether to trigger detection of the arrhythmia episode for the patient, the processing circuitry is further configured to: determine whether the heart rate of the patient is greater than or equal to the heart rate threshold; and in response to determining that the heart rate of the patient is greater than or equal to the heart rate threshold, trigger detection of the arrhythmia episode
Claim 17
The system of claim 1,
(as Claim 1)
wherein the processing circuitry comprises processing circuitry of at least one of the medical device determine that the present activity level for the patient exceeds the exercise tolerance level for the patient
Claim 10
A medical device comprising: memory; and processing circuitry … configured to: determine whether to trigger detection of the arrhythmia episode for the patient based at least in part on comparing a heart rate of the patient with the heart rate threshold
Therefore, claims in U.S. Patent No. 11504048 anticipate all of instant claims 1-4, excepting for “send a notification to the patient”, “based on at least one comorbidity of the patient”, “a parameter indicative of the comorbidity of the patient”, “in view of the comorbidity of the patient”, “at least one comorbidity comprises at least one of: heart failure”, and “comprising a physiological sensor configured to sense at least one parameter of a patient sensed by the physiological sensor, wherein the physiological sensor comprises at least one of an electrode and an optical sensor”.
Attention is brought to the Chakravarthy reference, which teaches outputting an alert (“send a notification to the patient”) to the patient so that the patient may take action, for example, activating the recording function of a medical monitor device such as a wearable ECG ([0570]). Chakravarthy’s device includes electrode sensors ([0036]) and optical sensors to collect patient data including cardiac electrogram data via these sensors ([0088]) (“comprising a physiological sensor configured to sense at least one parameter of a patient sensed by the physiological sensor, wherein the physiological sensor comprises at least one of an electrode and an optical sensor”).
also teaches that a device may “determine a heart failure tachycardia threshold that is separate from a tachycardia threshold” ([0045]) and that a device may operate in multiple modes such as a heart failure monitoring mode and mobile cardiac telemetry/Holter-type arrhythmia monitoring mode in a patient with atrial fibrillation comorbid with heart failure ([0098]) (“based on at least one comorbidity of the patient”). By operating in multiple modes and adjusting thresholds based on patient morbidity, the device is better able to capture diagnostically relevant arrhythmias for the heart failure patient that might be below the typical heart rate threshold set for patients without heart failure ([0005]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of
the instant application to apply measuring a physiologic parameters through at least one electrode and optical sensor, the use of comorbidity information and outputting an alert as taught by Chakravarthy to the device as claimed in U.S. Patent No. 11504048 so that the device might better capture diagnostically relevant arrhythmias for the heart failure patients.
With respect to instant claim 5
Claim 5
The system of claim 1,
As claim 1
wherein to determine the exercise tolerance level based on the values of the set of one or more patient parameters, the processing circuitry is further configured to apply values of the set of one or more patient parameters to a patient model that is configured at least in part based on data collected from a cohort of patients that have the at least one comorbidity in common with the patient.
the processing circuitry is further configured to apply values of the set of one or more patient parameters to a patient model that is configured at least in part based on data collected from a cohort of patients that have the at least one comorbidity in common with the patient.
Claims of the existing U.S. Patent No. 11504048 do not recite the processing circuitry is further configured to apply values of the set of one or more patient parameters to a patient model that is configured at least in part based on data collected from a cohort of patients that have the at least one comorbidity in common with the patient.
However, attention is brought to the Chakravarthy reference which teaches that for heart failure patients, using the default tachycardia threshold for triggering detection of tachyarrhythmia episodes may cause external device to miss detection of diagnostically relevant tachyarrhythmia episodes of patients when the patients are in a resting state ([0043]). Chakravarthy also teaches modeling of the patient at rest (114 and 116 in Fig. 7 and [0130]) by adjusting the tachycardia threshold for a patient by changing the tachycardia threshold from a preset tachycardia threshold to one more reflective of heart rate for heart failure patients with comorbid tachyarrhythmias ([0044]). In this way IMD may, based on determining that a patient with comorbid heart failure and tachyarrhythmias, is at rest, determine a heart failure tachycardia threshold that is separate from a tachycardia threshold so that the so that external device and/or IMD may capture two types of arrhythmias: typical tachyarrhythmias and heart failure arrhythmias ([0045]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of
the instant application to apply a patient model informed by comorbidity information as taught by Chakravarthy to the device as claimed in U.S. Patent No. 11504048 so that the device might better capture diagnostically relevant arrhythmias for the heart failure patients.
With respect to instant claims 8
Claim 8
The system of claim 7,
As claim 7
wherein the second set of one or more patient parameters are fully distinct from or fully overlap with the set of one or more patient parameters.
wherein the second set of one or more patient parameters are fully distinct from or fully overlap with the set of one or more patient parameters.
Claims of the existing U.S. Patent No. 11504048 do not recite wherein the second set of one or more patient parameters fully overlap with the set of one or more patient parameters. Processing circuitry 20 may be configured to monitor patient 4 for arrhythmia episodes.
However, attention is brought to the Chakravarthy reference which teaches that the processing circuitry may be configured to continually receive sensor values from one or more sensors indicative of the motion of patient and may continually determine the activity level of patient based on the received sensor values. Processing circuitry may therefore also be configured to continually determine heart rate thresholds based on updates to the activity level of patient determined by processing circuitry, and explains that, for example, if processing circuitry determines, after adjusting the tachycardia threshold to 80 BPM based on patient being at rest, that patient is no longer at rest, processing circuitry may be configured to re-raise the tachycardia threshold from 80 BPM to 120 BPM ([0076]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of
the instant application to apply the use of a fully overlapping set of parameters as taught by Chakravarthy by the device as claimed in U.S. Patent No. 11504048 so that data from the device can be easily transmitted to the patient or clinician, and so that the current activity level can inform the heart rate threshold that is considered a tachyarrhythmia.
With respect to instant claims 9
Claim 9
The system of claim 1,
As claim 1
wherein the processing circuitry comprises processing circuitry of at least one of a smartphone of the patient or a cloud computing system configured to determine the exercise tolerance level based on the values of the set of one or more patient parameters.
wherein the processing circuitry comprises processing circuitry of at least one of a smartphone of the patient or a cloud computing system configured to determine the exercise tolerance level based on the values of the set of one or more patient parameters.
Claims of the existing U.S. Patent No. 11504048 do not recite wherein the processing circuitry comprises processing circuitry of at least one of a smartphone of the patient or a cloud computing system configured to determine the exercise tolerance level based on the values of the set of one or more patient parameters. However, attention is brought to the Chakravarthy reference which teaches that a user, such as a physician, technician, surgeon, electro-physiologist, or other clinician, may interact with an external device to retrieve physiological or diagnostic information from the IMD, select or adjust values for operational parameters of the IMD, acts as an access point to facilitate communication with the IMD, and may include a processor configured to evaluate EGM and/or other sensed signals transmitted from the IMD to the external device ([0030-0031]). Chakravarthy teaches that this external device may be “a mobile device, such as a mobile phone, a “smart” phone, a laptop, a tablet computer, a personal digital assistant” ([0028]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of
the instant application to apply the use of a smart phone as part of the processing circuitry as taught by Chakravarthy to the device as claimed in U.S. Patent No. 11504048 so that data from the device can be easily transmitted to the patient or clinician, and so that a clinician can easily alter the parameters used by the device when appropriate.
With respect to instant claims 11
Claim 11
The system of claim 1,
As claim 1
wherein to determine the exercise tolerance level based on the values of the set of one or more patient parameters, the processing circuitry is configured to apply different weightings to different patient parameters of the set of one or more patient parameters.
wherein to determine the exercise tolerance level based on the values of the set of one or more patient parameters, the processing circuitry is configured to apply different weightings to different patient parameters of the set of one or more patient parameters.
Claims of the existing U.S. Patent No. 11504048 do not explicitly recite wherein to determine the exercise tolerance level based on the values of the set of one or more patient parameters, the processing circuitry is configured to apply different weightings to different patient parameters of the set of one or more patient parameters. However, attention is brought to the Chakravarthy reference which teaches the use of an age-predicted maximal heart rate for the patient and the activity level of the patient to determine a heart rate threshold ([0155]) Chakravarthy then discloses that one way of using the age-predicted maximal heart rate for the patient is by multiplying it by a weighting factor associated with the current activity level of the patient to determine a heart rate threshold ([0136]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of
the instant application to apply a weighting factor to a patient parameter, such as age-predicted maximal heart rate, as taught by Chakravarthy to the device as claimed in U.S. Patent No. 11504048 so that a heart rate threshold appropriate to the patient and their current activity level could be determined.
Claims 10, 13-14 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 10-18 of U.S. Patent No. 11504048 in view of Chakravarthy as applied to claim 1 above, and further in view of U.S. PGPUB No. 202000038671 to Schulhauser (herein after referred to as Schulhauser).
With respect to instant claims 13-14
Claim 10
The system of claim 1,
As claim 1
wherein the processing circuitry is configured to determine the exercise tolerance by inputting the values of the set of one or more patient parameters into a Bayesian framework.
wherein the processing circuitry is configured to determine the exercise tolerance by inputting the values of the set of one or more patient parameters into a Bayesian framework.
Claim 13
The system of claim 1,
As claim 1
wherein the set of one or more patient parameters includes three or more of:
a heart rate of the patient;
a respiration rate of the patient; a respiration volume of the patient;
an oxygen saturation level of the patient;
a pulse wave transmit time of the patient;
a measure of muscle activity of the patient;
an ST segment deviation level for the patient;
a level of T-wave alternans for the patient; and
an activity level of the patient.
wherein the set of one or more patient parameters includes three or more of:
a heart rate of the patient;
a respiration rate of the patient; a respiration volume of the patient;
an oxygen saturation level of the patient;
a pulse wave transmit time of the patient;
a measure of muscle activity of the patient;
an ST segment deviation level for the patient;
a level of T-wave alternans for the patient; and
an activity level of the patient.
Claim 14
The system of claim 1,
As claim 1
wherein the set of one or more patient parameters includes five or more of:
a heart rate of the patient;
a respiration rate of the patient; a respiration volume of the patient;
an oxygen saturation level of the patient;
a pulse wave transmit time of the patient;
a measure of muscle activity of the patient;
an ST segment deviation level for the patient;
a level of T-wave alternans for the patient; and
an activity level of the patient.
wherein the set of one or more patient parameters includes five or more of:
a heart rate of the patient;
a respiration rate of the patient; a respiration volume of the patient;
an oxygen saturation level of the patient;
a pulse wave transmit time of the patient;
a measure of muscle activity of the patient;
an ST segment deviation level for the patient;
a level of T-wave alternans for the patient; and
an activity level of the patient.
Claims of the existing U.S. Patent No. 11504048 do not recite wherein the processing circuitry is configured to determine the exercise tolerance by inputting the values of the set of one or more patient parameters into a Bayesian framework, nor do they recite wherein the set of one or more patient parameters includes three or more of: or five or more of: a heart rate of the patient; a respiration rate of the patient; a respiration volume of the patient; an oxygen saturation level of the patient; a pulse wave transmit time of the patient; a measure of muscle activity of the patient; an ST segment deviation level for the patient; a level of T-wave alternans for the patient; and an activity level of the patient.
However, attention is brought to the Schulhauser reference which teaches a wearable defibrillation apparatus configured to apply a machine learning algorithm (title). Based on learning from sets of data, e.g., regarding patient 102, the machine learning algorithm may discover patterns in, and relationships, between several independent and interdependent variables derivable from the data ([0075]). Ongoing consideration of these variables, or other learned variables from continued updating of the algorithm, may allow the machine learning algorithm to probabilistically determine, e.g., classify, diagnose, and/or predict, a state of the patient ([0075]). The machine learning algorithm may be configured to employ any one or more of Bayesian, random forest, decision tree, linear regression, deep learning, neural network and/or dimensionality reduction techniques, as examples ([0075]). In some examples, a result of the application of the machine learning algorithm to the data, e.g., one or more physiological signals from sensing devices 130 or 230 and/or the cardiac signal from sensing circuitry 330 includes classification of the data, e.g., the cardiac signal and physiological signal (individually or collectively) as one of normal or not normal, or indicating one or more other states of the patient, such as whether a treatable tachyarrhythmia is indicated or predicted, or whether one or more comorbidities are indicated or predicted ([0075]). Schulhauser also teaches communication circuitry configured to receive data of at least one physiological signal of the patient from at least one sensing device separate from the apparatus, and applies a machine learning algorithm to that data to probabilistically-determine at least one state of the patient [abstract]. The one or more sensing devices (230A-D in Fig. 2) “provide signals or values for pulse rate, oxygen saturation, and respiration rate” and notes that these parameters may indicate a present or predicted treatable tachyarrhythmia state, or comorbidities, such as heart failure [0058]. The sensing circuitry is also able to monitor cardiac signals to “determine, from the sensed cardiac signal, whether the cardiac signals indicate a normal or not normal state and, if not normal, whether the cardiac signals indicate one of a plurality of not normal sub-classifications, such as bradycardia, treatable tachyarrhythmia, syncope” ([0079]). The machine learning algorithm then incorporates variables from these cardiac signals including morphology characteristics of features such as P-wave, R-wave, QRS-complex, S-T segment, Q-T interval, and T-wave ([0080)].
It would have been obvious to one of ordinary skill in the art before the effective filling date of the instant application to utilize at least 5 of signals taught by Schulhauser (pulse rate, oxygen saturation, respiration rate, S-T segment morphology, and T-wave morphology) to determine parameters used by the system taught by Chakravarthy and to utilize the Bayesian machine learning algorithm as taught by Schulhauser to analyze the parameters used by the system taught by Chakravarthy for the purpose of classifying those parameters as normal or not normal for the purpose of predicting arrhythmias.
Claim 18 is rejected on the ground of nonstatutory double patenting as being unpatentable over claims 10-18 of U.S. Patent No. 11504048 in view of U.S. PGPUB No. 20210386312 to Chakravarthy (herein after referred to as Chakravarthy) as applied to claim 1 above, and further in light of Medtronic (REVEAL LINQTM LNQ11 Insertable Cardiac Monitor and Patient Assistant PA96000 Clinical Manual, 2018, p93).
With respect to instant claims 18
Claim 18
The system of claim 1,
As claim 1
wherein the implantable medical device comprises an insertable cardiac monitor
wherein the implantable medical device comprises an insertable cardiac monitor
comprising: a housing configured for subcutaneous implantation in a patient,
comprising: a housing configured for subcutaneous implantation in a patient,
the housing having a length between 40 millimeters (mm) and 60 mm between a first end and a second end, a width less than the length, and a depth less than the width;
the housing having a length between 40 millimeters (mm) and 60 mm between a first end and a second end, a width less than the length, and a depth less than the width;
wherein the physiological sensor comprises the electrode, the electrode is a first electrode at or proximate to the first end; and the physiological sensor comprises a second electrode at or proximate to the second end,
a first electrode at or proximate to the first end; and a second electrode at or proximate to the second end,
wherein the insertable cardiac monitor is configured to sense at least one of the set of one or more patient parameters via the first electrode and the second electrode.
wherein the insertable cardiac monitor is configured to sense at least one of the set of one or more patient parameters via the first electrode and the second electrode.
Claims of the existing U.S. Patent No. 11504048 do not explicitly recite wherein the implantable medical device comprises an insertable cardiac monitor comprising: a housing configured for subcutaneous implantation in a patient, the housing having a length between 40 millimeters (mm) and 60 mm between a first end and a second end, a width less than the length, and a depth less than the width; wherein the physiological sensor comprises the electrode, the electrode is a first electrode at or proximate to the first end; and the physiological sensor comprises a second electrode at or proximate to the second end, wherein the insertable cardiac monitor is configured to sense at least one of the set of one or more patient parameters via the first electrode and the second electrode.
However, attention is brought to the Chakravarthy reference which teaches the use of an insertable cardiac monitor as the implantable medical device (IMD) for arrhythmia monitoring and diagnosis ([0027]), and that the IMD may be implanted outside of a thoracic cavity of patient, subcutaneously in the pectoral location (as shown in Fig. 1, and in [0026]). Chakravarthy also teaches the use of electrodes positioned on opposite end of a housing of IMD (16A and 16B in Fig. 3) to function as sensors ([0036]) that are connected to circuitry (50, 52 16A and 16B in Fig. 3) that performs the various functions of the device ([0060]) including monitoring electrical activity of a heart of the patient and producing heart-related data for the patient, such as the heart rate, cardiac electrogram data, and the like ([0062]).
Chakravarthy lists the Reveal LINQ™ Insertable Cardiac Monitor as an example device that can be used with their teaching, and while Chakravarthy does not disclose the dimensions of the Reveal LINQ™ Insertable Cardiac Monitor, Medtronic discloses the same device having dimensions as 44.8 mm (H) x 7.2 mm (W) x 4.0 mm (D) on page 93, Table 12, Line 4. Therefore, the IMD of Chakravarthy would necessarily include a housing with a length between 40 mm and 60 mm, a width less than its length, and a depth less than its width as evidenced by Medtronic.
It would have been obvious to one of ordinary skill in the art before the effective filling date of the instant application to utilize the Reveal LINQ™ Insertable Cardiac Monitor as taught by Chakravarthy as the implantable medical device claimed by Chakravarthy in order to monitoring electrical activity of a heart of the patient and producing heart-related data for the patient, such as the heart rate, cardiac electrogram data, and the like.
With respect to instant claims 19-20
Claim 19
The system of claim 1,
As claim 1
wherein the processing circuitry is further configured to: dynamically update the exercise tolerance level over time based on changes in a condition of the patient determined from subsequent values of the set of one or more patient parameters.
Claim 13
The medical device of claim 12, wherein to determine the heart rate threshold for triggering detection of the arrhythmia episode for the patient, the processing circuitry is further configured to: in response to determining that the activity level of the patient meets or exceeds a first activity level, set the heart rate threshold for triggering detection of the arrhythmia episode to a first heart rate threshold; and in response to determining that the activity level of the patient meets or exceeds a second activity level, set the heart rate threshold for triggering detection the arrhythmia episode to a second heart rate threshold.
Claim 20
The system of claim 1,
As claim 1
wherein the set of one or more patient parameters is a first set of patient parameters collected over a first period of time, and wherein to determine the present activity level,
Claim 13
a first activity level, set the heart rate threshold for triggering detection of the arrhythmia episode to a first heart rate threshold;
the processing circuitry is further configured to determine the present activity level based on values of a second set of one or more patient parameters collected over a second period of time
the processing circuitry is further configured to determine the present activity level based on values of a second set of one or more patient parameters collected over a second period of time
the second period of time being shorter than the first period of time and after the first period of time.
the second period of time being shorter than the first period of time and after the first period of time.
Claims of the existing U.S. Patent No. 11504048 do not explicitly recite “the processing circuitry is further configured to determine the present activity level based on values of a second set of one or more patient parameters collected over a second period of time” and “the second period of time being shorter than the first period of time and after the first period of time”.
However, attention is brought to the Chakravarthy reference which teaches a processing circuitry that may be configured to continually receive sensor values from one or more sensors indicative of the motion of patient and may continually determine the activity level of patient based on the received sensor values. Processing circuitry may therefore also be configured to continually determine heart rate thresholds based on updates to the activity level of patient determined by processing circuitry. For example, if processing circuitry determines, after adjusting the tachycardia threshold to 80 BPM based on patient being at rest, that patient is no longer at rest, processing circuitry may be configured to re-raise the tachycardia threshold from 80 BPM to 120 BPM ([0076]). The device may determine that the patient is resting based on whether the patient’s activity level is below a resting threshold for at least a minimum resting duration (e.g., one minute, two minutes, and the like) ([0074]). The process or of the device may then determine the present activity level of patient based at least in part on the magnitude of the sensor values, the average magnitude of the sensor values over a specified time period (e.g., 1 second, 30 seconds, 1 minute, etc.) (“the second period of time being shorter than the first period of time and after the first period of time”) and may compare the average magnitude to one or more threshold values that correspond to different activity levels ([0074]) “the processing circuitry is further configured to determine the present activity level based on values of a second set of one or more patient parameters collected over a second period of time”.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-9, 11-13, 15-17, & 19-20 are rejected under 35 U.S.C. 102(a)(1) and 102(a)(2) as being anticipated by U.S. PGPUB No. 20210386312 to Chakravarthy (herein after referred to as Chakravarthy).
With regard to claim 1, Chakravarthy teaches a medical device system (Fig.s 1-4, 6-7 and “a medical device system” in [0004]) comprising: an implantable or wearable medical device (10 in Fig. 1 and “The example techniques may be used with an IMD 10” in [0026]) comprising a physiological sensor configured to sense at least one parameter of a set of one or more patient parameters based on one or more cardiac signals of a patient sensed by the physiological sensor, (Fig. 5, 102 in Fig. 6, “In some examples, one or more sensors 32 may include heart monitoring circuitry that is operable to monitor electrical activity of a heart of patient 4 of FIG. 1 and produce cardiac electrogram data for patient 4” in [0094], and “processing circuitry 20 may be configured to determine the activity level of patient 4 based at least in part on the magnitude of the sensor values received from one or more sensors 32” in [0102]), wherein the physiological sensor comprises at least one of an electrode and an optical sensor (“IMD 10 collects, via sensing circuitry 50 and/or sensors 58, patient data of patient 4 including cardiac electrogram data. Sensors 58 may include one or more sensors, such as one or more accelerometers, pressure sensors, optical sensors for 02 saturation, etc. In some examples, the patient data includes one or more of an activity level of the patient, a heartrate of the patient, a posture of the patient, a cardiac electrogram of the patient, a blood pressure of the patient, accelerometer data for the patient, or other types of patient parametric data.” in [0088]); and processing circuitry configured to: determine an exercise tolerance level for the patient based on the values of the set of one or more patient parameters (102 and 104 in Fig. 6 and “processing circuitry 20 may be configured to monitor the activity level of patient 4 and to determine one or more heart rate thresholds for triggering detection of arrhythmia episodes based at least in part on the activity level of patient 4” in [0097] and “one or more heart rate sensors” in [0049] and “one or more sensors that are operable… to sense the motion of patient” in [0040]) and based on at least one comorbidity of the patient (“IMD 10 may… determine a heart failure tachycardia threshold that is separate from a tachycardia threshold” in [0045] and “because atrial fibrillation is a co-morbidity with heart failure” in [0098]); determine that a present activity level for the patient exceeds the exercise tolerance level for the patient (108 in Fig. 6, 118 in Fig. 7 and “External device 12 and/or IMD 10 may compare the heart rate of patient 4 with one or more arrhythmia thresholds to determine whether to trigger detection of an arrhythmia episode” in [0050]); and send a notification to the patient in response to determining that the present activity level exceeds the exercise tolerance level for the patient (“in response to triggering detection of a bradyarrhythmia episode for patient 4, external device 12 may output an alert, … to alert patient 4” in [0057]).
With regard to claim 2, Chakravarthy teaches the system of claim 1, wherein the processing circuitry is further configured to: determine the exercise tolerance level based on the values of the set of one or more patient parameters (10 in Fig. 1, 106 in Fig. 6 and “IMD 10 may compare the heart rate of patient 4 with one or more arrhythmia thresholds to determine whether to trigger detection of an arrhythmia episode” in [0050]) and values of one or more additional parameters, wherein the values of the one or more additional parameters are not received from the medical device (“processing circuitry 20 and/or processing circuitry 50 may determine the first heart rate threshold based at least in part on an age-predicted maximal heart rate for the patient 4” in [0123]).
With regard to claim 3, Chakravarthy teaches wherein at least one of the one or more additional parameters includes a parameter indicative of the comorbidity of the patient (“IMD 10 may… determine a heart failure tachycardia threshold that is separate from a tachycardia threshold” in [0045] and “because atrial fibrillation is a co-morbidity with heart failure” in [0098]).
With regard to claim 4, Chakravarthy teaches The system of claim 1, wherein the set of one or more patient parameters comprise parameters usable to determine if the patient is engaged in an activity level exceeding a risk threshold in view of the comorbidity of the patient (104 and 106 in Fig. 6, 130 and 128 in Fig. 8 and “The medical device may, based at least in part on comparing the heart rate of patient 4 with the one or more heart rate thresholds, determine whether to trigger detection of an arrhythmia episode.” in [0037]).
With regard to claim 5, Chakravarthy teaches wherein to determine the exercise tolerance level based on the values of the set of one or more patient parameters, the processing circuitry is further configured to apply values of the set of one or more patient parameters to a patient model (114 and 116 in Fig. 7 and “patient 4 is at rest” in [0130]) that is configured at least in part based on data collected from a cohort of patients that have the at least one comorbidity in common with the patient (“IMD 10 may, based on determining that patient 4 is at rest, determine a heart failure tachycardia threshold that is separate from a tachycardia threshold” in [0045]).
With regard to claim 6, Chakravarthy teaches wherein to determine the exercise tolerance level based on the values of the set of one or more patient parameters, the processing circuitry is further configured to apply the values of the set of one or more patient parameters to a patient model that is configured at least in part based on past data of the patient (114 and 116 in Fig. 7 and “If processing circuitry 50 determines that patient 4 has been at rest for at least the specified amount of time, processing circuitry 50 may be configured to set the tachycardia threshold for patient 4 to a specified heart rate” in [0074]).
With regard to claims 7-8, Chakravarthy teaches wherein the processing circuitry is further configured to: determine the present activity level for the patient based on values of a second set of one or more patient parameters (“Processing circuitry 50 may be configured to determine the activity intensity of patient 4 based at least in part on sensor values received from one or more sensors 58, such as from accelerometer 59, that correspond to the motion of IMD” in [0072]). wherein the second set of one or more patient parameters fully overlap the set of one or more patient parameters (102 and 104 in Fig. 6 and “” determine one or more heart rate thresholds for triggering detection of arrhythmia episodes based at least in part on the activity level of patient 4” in [0097] and “one or more heart rate sensors” in [0049] and “To determine the activity level of patient 4, external device 12 and/or IMD 10 may include one or more sensors that are operable to sense the motion of external device” in [0040]).
With regard to claim 9, Chakravarthy teaches wherein the processing circuitry comprises processing circuitry of a smartphone of the patient configured to determine the exercise tolerance level based on the values of the set of one or more patient parameters (10 and 12 in Fig. 1 and “External device 12 may comprise … a mobile device, such as a mobile phone, a “smart” phone” in [0028]).
With regard to claim 11, Chakravarthy teaches wherein to determine the exercise tolerance level based on the values of the set of one or more patient parameters, the processing circuitry is configured to apply different weightings to different patient parameters of the set of one or more patient parameters 124, 126, 128, and 130 in Fig. 8 and “external device 12 and/or IMD 10 may determine the bradycardia threshold for patient 4 based at least in part on multiplying an age-predicted maximal heart rate for patient 4 by a weight associated with the activity level of patient 4” in [0136]).
With regard to claims 12-13, Chakravarthy teaches wherein the set of one or more patient parameters includes three or more of: a heart rate of the patient (“a heart rate threshold” in [0012]), an oxygen saturation level of the patient (“an optical sensors for 02 saturation” in [0088]), a measure of muscle activity of the patient (cardiac electrogram data in [0088]. Examiner notes that a cardiac electrogram is a type of electo-myogram and therefore an indicator of cardiac muscle activity), and an activity level of the patient (based at least in part on the activity level of the patient” in [0012]).
With regard to claim 15, Chakravarthy teaches wherein the at least one comorbidity comprises at least one of heart failure and another health condition (“because atrial fibrillation is a co-morbidity with heart failure, external device 12 may operate in both heart failure monitoring mode and mobile cardiac telemetry/Holter-type arrhythmia monitoring mode” in [0098]).
With regard to claim 16, Chakravarthy teaches wherein processing circuitry is configured to: determine a risk level of an adverse health event comprising arrhythmia of the patient based on the values of the set of one or more patient parameters (106 in Fig. 6 and “Processing circuitry 20 and/or processing circuitry 50 may determine a heart rate threshold for triggering detection of an arrhythmia episode based at least in part on the activity level of the patient 4 (106)” in [0121]).; and determine the exercise tolerance level based on the risk level of the adverse health event (“Processing circuitry 20 and/or processing circuitry 50 may determine whether to trigger the arrhythmia episode for the patient 4 based at least in part on comparing a heart rate of the patient 4 with the heart rate threshold (108)” in [0125]).
With regard to claim 17, Chakravarthy teaches wherein the processing circuitry comprises processing circuitry of at least one of the medical device or a smartphone of the patient configured to determine that the present activity level for the patient exceeds the exercise tolerance level for the patient (50 in Fig 3 and in [0068] and 12 in Fig. 1 and “the techniques described herein may be performed by an external medical device… device 12 may, in some examples, comprise … a “smart” phone” in [0028]).
With regard to claim 19, Chakravarthy teaches wherein the processing circuitry is further configured to: dynamically update the exercise tolerance level over time based on changes in a condition of the patient determined from subsequent values of the set of one or more patient parameters (“Processing circuitry 50 may be configured to continually receive sensor values from one or more sensors 32 indicative of the motion of patient 4 and may continually determine the activity level of patient 4 based on the received sensor values. Processing circuitry 50 may therefore also be configured to continually determine heart rate thresholds based on updates to the activity level of patient 4 determined by processing circuitry 50.” in [0076]).
With regard to claim 20, Chakravarthy teaches wherein the set of one or more patient parameters is a first set of patient parameters collected over a first period of time, and wherein to determine the present activity level (“Processing circuitry 20 may be configured to determine whether the activity level of patient 4 determined from the sensor values indicate that patient 4 is at rest, and may determine whether patient 4 has been at rest for at least a minimum resting duration (e.g., one minute, two minutes, and the like)” in [0103]), the processing circuitry is further configured to determine the present activity level based on values of a second set of one or more patient parameters collected over a second period of time (“In some examples, processing circuitry 20 may be configured to determine the activity level of patient 4 based at least in part on the magnitude of the sensor values received from one or more sensors 32. For example, processing circuitry 20 may be configured to determine the average magnitude of the sensor values over a specified time period (e.g., 1 second, 30 seconds, 1 minute, etc.) and may compare the average magnitude to one or more threshold values that correspond to different activity levels.” in [0102]), the second period of time being shorter than the first period of time and after the first period of time (first period of time “(e.g., one minute, two minutes, and the like)” in [0103] and second period of time “(e.g., 1 second, 30 seconds, 1 minute, etc.)” in [0102]).
Claim 18 is rejected under 35 U.S.C. 102(a)(1) and 102(a)(2) as being anticipated by Chakravarthy in light of Medtronic.
With regard to claim 18, Chakravarthy teaches wherein the implantable medical device comprises an insertable cardiac monitor (10 in Fig. 1 and in [0027]) comprising: a housing configured for subcutaneous implantation in a patient (14 in Fig. 3), the housing having a length between 40 millimeters (mm) and 60 mm (44.8 mm) between a first end and a second end, a width less than the length (7.2 mm), and a depth less than the width (4.0 mm; “Example IMDs that include electrodes include the Reveal LINQ™“ in [0104]); wherein the physiological sensor comprises the electrode, the electrode is a first electrode at or proximate to the first end; and the physiological sensor comprises a second electrode at or proximate to the second end (16A and 16B in Fig. 3 and “IMD 10 includes … electrodes 16A, 16B, one or more of which may be disposed within a housing of IMD 10” in [0060]), wherein the insertable cardiac monitor is configured to sense at least one of the set of one or more patient parameters via the first electrode and the second electrode (16A, 16B, and 52 in Fig. 2 and “Sensing circuitry 52 may monitor signals from electrodes 16A, 16B in order to monitor electrical activity of a heart of patient 4” in [0062]).
Chakravarthy lists the Reveal LINQ™ Insertable Cardiac Monitor as an example device that can be used with their teaching, and while Chakravarthy does not disclose the dimensions of the Reveal LINQ™ Insertable Cardiac Monitor, Medtronic discloses the same device having dimensions as 44.8 mm (H) x 7.2 mm (W) x 4.0 mm (D) on page 93, Table 12, Line 4. Therefore, the IMD of Chakravarthy would necessarily include a housing with a length between 40 mm and 60 mm, a width less than its length, and a depth less than its width as evidenced by Medtronic.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 10 & 14 are rejected under 35 U.S.C. 103 as being unpatentable over Chakravarthy in view of U.S. PGPUB No. 202000038671 to Schulhauser (herein after referred to as Schulhauser).
With regard to claim 10, Chakravarthy teaches the medical device system of claim 1 as set forth above.
However, Chakravarthy does not teach wherein the processing circuitry is configured to determine the exercise tolerance by inputting the values of the set of one or more patient parameters into a Bayesian framework.
Schulhauser teaches a wearable defibrillation apparatus configured to apply a machine learning algorithm (title). Based on learning from sets of data, e.g., regarding patient 102, the machine learning algorithm may discover patterns in, and relationships, between several independent and interdependent variables derivable from the data ([0075]). Ongoing consideration of these variables, or other learned variables from continued updating of the algorithm, may allow the machine learning algorithm to probabilistically determine, e.g., classify, diagnose, and/or predict, a state of the patient ([0075]). The machine learning algorithm may be configured to employ any one or more of Bayesian, random forest, decision tree, linear regression, deep learning, neural network and/or dimensionality reduction techniques, as examples ([0075]). In some examples, a result of the application of the machine learning algorithm to the data, e.g., one or more physiological signals from sensing devices 130 or 230 and/or the cardiac signal from sensing circuitry 330 includes classification of the data, e.g., the cardiac signal and physiological signal (individually or collectively) as one of normal or not normal, or indicating one or more other states of the patient, such as whether a treatable tachyarrhythmia is indicated or predicted, or whether one or more comorbidities are indicated or predicted ([0075]).
It would have been obvious to one of ordinary skill in the art before the effective filling date of the instant application to utilize the Bayesian machine learning algorithm as taught by Schulhauser to analyze the parameters used by the system taught by Chakravarthy for the purpose of classifying those parameters as normal or not normal for the purpose of predicting arrhythmias.
With regard to claim 14, Chakravarthy teaches the medical device system of claim 1 as set forth above.
However, Chakravarthy does not teach wherein the set of one or more patient parameters includes five or more of: a heart rate of the patient; a respiration rate of the patient; a respiration volume of the patient; an oxygen saturation level of the patient; a pulse wave transmit time of the patient; a measure of muscle activity of the patient; an ST segment deviation level for the patient; a level of T-wave alternans for the patient; and an activity level of the patient.
Schulhauser teaches an apparatus configured to be worn by a patient for cardiac defibrillation that includes communication circuitry configured to receive data of at least one physiological signal of the patient from at least one sensing device separate from the apparatus, and applies a machine learning algorithm to that data to probabilistically-determine at least one state of the patient [abstract]. The one or more sensing devices (230A-D in Fig. 2) “provide signals or values for pulse rate, oxygen saturation, and respiration rate” and notes that these parameters may indicate a present or predicted treatable tachyarrhythmia state, or comorbidities, such as heart failure [0058]. The sensing circuitry is also able to monitor cardiac signals to “determine, from the sensed cardiac signal, whether the cardiac signals indicate a normal or not normal state and, if not normal, whether the cardiac signals indicate one of a plurality of not normal sub-classifications, such as bradycardia, treatable tachyarrhythmia, syncope” ([0079]). The machine learning algorithm then incorporates variables from these cardiac signals including morphology characteristics of features such as P-wave, R-wave, QRS-complex, S-T segment, Q-T interval, and T-wave ([0080)].
It would have been obvious to one of ordinary skill in the art before the effective filling date of the instant application to utilize at least 5 of signals (pulse rate, oxygen saturation, respiration rate, S-T segment morphology, and T-wave morphology) taught by Schulhauser as parameters used in the system of Chakravarthy for the purpose of detecting and monitoring arrhythmias.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to WILLIAM P ADAMS whose telephone number is (571)270-0136. The examiner can normally be reached 9am-6pm M-Th.
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/W.P.A./ Examiner, Art Unit 3792
/AMANDA L STEINBERG/ Examiner, Art Unit 3792
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