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 .
Priority
Claims 1-20 are deemed to have an effective filing date of August 24, 2021.
Drawings
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(5) because they do not include the following reference sign(s) mentioned in the description: 1600, 1700, 1022.
Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). 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 Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 6, 8, 13, and 18 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 6, line 2, refers to a “2H or 3H” (which are mentioned in claim 2). But, claim 6 depends from claims 1 and 5. Thus, it is unclear what “2H” and “3H” are.
Claim 8 refers to a “3H” (which is mentioned in claim 2). But, claim 8 depends from claim 1. Thus, it is unclear if “3H” refers to a third harmonic.
Claim 13, line 3, refers to “FF, 2H and 3H” (which abbreviations are mentioned in claim 2). But, claim 13 depends from claim 1. Thus, it is unclear what “FF”, 2H” and “3H” are.
Claim 18 recites the limitation "the abnormal operational conditions" in line 1. There is insufficient antecedent basis for this limitation in the claim as claim 1 only assesses a condition of the MCSD. The Examiner notes that claim 17 introduces the limitation “normal or abnormal operational conditions of the MCSD”.
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 abstract ideas without significantly more.
Step 1:
Claims 1-18 recite a system, and therefore is a product, and claims 19-20 recite a method for using condition using a device of the system. Therefore, the claims fall within the statutory categories.
Step 2A, Prong 1:
Claims 1 and 19 recite receiving signals indicative of vibrations or acoustics of the device, processing the signals to identify at least one harmonic in the signals, and evaluating the condition of the device using the identified harmonic. 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 "sensor subsystem", and "computer subsystem" (claim 1) and “sensor” (claims 1 and 19). That is, other than reciting that a computerized system is performing these tasks, nothing in the claim precludes the steps from practically being performed in the human mind. 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 recitation of "sensor subsystem", and "computer subsystem", and “sensor”, the claims encompass a user observing vibration/acoustic data to evaluate harmonics of the data for detection of pump thrombosis.
Step 2A, Prong 2:
Claims recite "sensor subsystem", and "computer subsystem", and “sensor” to perform abstract steps. For the limitation of “sensor”, none of the claimed function is being conducted/performed by the sensors. The sensing subsystem is simply receiving sensed data and the actual sensing step is not an active step being performed by the components of the system or method. Therefore, sensors are not part of the system or method claims to performing any of the imitations recited in the claims. The additional limitations, “sensor subsystem", and "computer subsystem", read on computer components as disclosed in [0053] of the specification. These components read on a computer implemented system 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.
Step 2B:
As discussed with respect to Step 2A Prong 2, 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.
The computing subsystem and/or processor are/is recited generically as no details are provided other than receiving the signals indicative of vibrations or acoustics of a device, processing the signals to identify harmonic of vibrations or acoustics, and evaluating the condition of the device using the identified harmonic, which represents no more than mere instructions to apply the judicial exception on a computer. The courts have made it clear that mere physicality or tangibility of an additional element or elements is not a relevant consideration in the eligibility analysis, the physical nature of these computer components does not affect this analysis. See MPEP 2106.05(b) I.
Even when viewed in combination, the additional elements do no more than automate the mental process (e.g., the mental computation of identifying/processing a harmonic), using the computing subsystem as a tool. There is no change to generic computers and other technology recited in the claims, and thus, the claims do not improve computer functionality or other technology (see MPEP 2106.05 I. A. and 2106.05(a)).
Claims 2, 4-8, 13, 15-18, and 20 further limit the abstract idea already indicated in independent claims 1 and 19 and they are ineligible for the same reasons provided for claims 1 and 19 above.
For claims 3 and 9-12, additional sensor limitations are not part of the system or method claims to performing any of the imitations recited in the claims.
For claim 14, the additional limitation of “output…an alert notification…MCSD” is nothing more than insignificant post-solution activity of outing results of performing abstract idea steps as indicated above.
Accordingly, the claims, taken as a whole, do not integrate the recited judicial exception into a practical application. Thus, the above-identified claims are directed to the judicial exception.
Claim Rejections - 35 USC § 102
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.
Claims 1-2, 4-7, 9-11, 14-16, and 18-19 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by US Patent Application Publication No. 2019/0255235 to Sambelashvili et al. (hereinafter referred to as “Sambelashvili”).
Referring to claim 1, Sambelashvili discloses a system for assessing a condition of a mechanical circulatory support device (MCSD) in a mammal (e.g., Abstract and paragraphs [0002] and [0007]: methods for detecting pump thrombosis of an implanted mechanical circulatory support device), the system comprising: a sensing subsystem configured to obtain from one or more sensors signals indicative of at least one of vibrations or acoustics of the MCSD in operation in the mammal (e.g., paragraphs [0020] and [0024]-[0025]: transducer 102 may be sufficiently close to the mechanical circulatory support (MCS), senses a mechanical wave, such as an acoustic wave or a vibration of the pump of the MCS device where the transducer is within or coupled to an IMD; Fig. 1, 102); and a computing subsystem (e.g., paragraph [0026]: transducer 102 is communicatively coupled to computing device 104; Fig. 1, 104) configured to: receive the signals indicative of at least one of the vibrations or the acoustics of the MCSD in operation in the mammal (e.g., paragraphs [0026]-[0028]: transducer 102 generates a signal representative of a mechanical wave from the MCS and transmit the signal to computing device 104; the signal from transducer 102 is received by processing circuitry of computing device 104); process the signals to identify at least one harmonic in the signals (e.g., paragraphs [0007]: The processing circuitry is configured to identify at least one portion of the signal representative of at least one harmonic of the mechanical wave; and [0028]: processing circuitry conditions the received signal); and evaluate the condition of the MCSD (e.g., paragraph [0028]: processing circuitry determines an indication of pump thrombosis based on the signal) using the at least one harmonic identified in the signals indicative of at least one of the vibrations or the acoustics of the MCSD in operation in the mammal (e.g., paragraph [0007]: The processing circuitry is configured to identify at least one portion of the signal representative of at least one harmonic of the mechanical wave and determine an indication of pump thrombosis (condition of the MCSD) based on the at least one portion).
With respect to claim 2, Sambelashvili discloses the system of claim 1, wherein the at least one harmonic is at least one of a fundamental frequency (FF), second harmonic (2H), third harmonic (3H), fourth harmonic (4H), sixth harmonic (6H), or a harmonic of higher-order than 6H (e.g. paragraphs [0058]: Fig. 4 illustrates an example signal 402 of a mechanical wave from an MCS device with pump thrombosis, and features 408, 410, and 412 include, respectively, the second harmonic, the third harmonic, and fourth harmonic of the rotor frequency; and [0066]: in some examples, the selected harmonic is the third harmonic, in other examples, the selected harmonic may be a harmonic different than the third harmonic or a plurality of harmonics).
As to claim 4, Sambelashvili discloses the system of claim 1, wherein processing the signals comprises filtering extraneous noise from the signals (e.g., paragraph [0067]: in some examples, identifying at least one portion of the signal indicative of pump thrombosis may include cancelling noise in the signal).
With respect to claim 5, Sambelashvili discloses the system of claim 1, wherein evaluating the condition of the MCSD comprises determining that an absolute amplitude of the at least one harmonic identified exceeds a threshold level (e.g., paragraphs [0038]: pump thrombosis detection platform may analyze signals to determine threshold signal values indicative of pump thrombosis; [0068]-[0070]: processing circuitry identifies at least one portion of the signal representative of at least one harmonic of the mechanical wave, and normalizes at least one portion of the signal; processing circuitry compares at least one feature of the identified portion of the signal to a threshold value where the threshold values may be a predetermined increase in the amplitude).
As to claim 6, Sambelashvili discloses the system of claim 5, wherein the at least one harmonic is at least one of a 2H or a 3H (e.g., paragraph [0068]: normalizing the amplitude of the third harmonic using a second different harmonic such as a second harmonic).
With respect to claim 7, Sambelashvili discloses the system of claim 1, wherein evaluating the condition of the MCSD comprises determining that a relative amplitude of the signals exceeds a threshold level (e.g., paragraphs [0038]: pump thrombosis detection platform may analyze signals to determine threshold signal values indicative of pump thrombosis; and [0070]: processing circuitry may determine pump thrombosis when the signal and the second signal differ my a predetermined amount (e.g., a threshold value)).
As to claim 9, Sambelashvili discloses the system of claim 1, wherein the one or more sensors are positioned on the mammal's chest at a left lower sternal border (e.g., paragraphs [0024]: transducer 102 may be within or coupled to a wearable device such as an external chest strap; and [0022]: MCS device may sense the left ventricle of the heart – which implies sensors are capable of being positioned on the left lower sternal border using a chest strap).
With respect to claim 10, Sambelashvili discloses the system of claim 1, wherein the one or more sensors are capable of being attached to a handheld surface detection device (e.g., paragraph [0024]: transducer 102 may be within or coupled to a portable device such as a mobile phone).
As to claim 11, Sambelashvili discloses the system of claim 1, wherein the one or more sensors are attached to the MCSD (e.g., paragraph [0026]: transducer 102 is connected to computing device, which includes a wired connection).
With respect to claim 14, Sambelashvili discloses the system of claim 1, wherein the computing subsystem is further configured to: determine, based on evaluating the condition of the MCSD, that the MCSD has pump thrombosis; and output, at a user device, an alert notification identifying the pump thrombosis of the MCSD (e.g., abstract and paragraphs [0008]: processing circuitry determines an indication of pump thrombosis based on the signal, and based on the indication of pump thrombosis, generates an alert or initiate an intervention; [0009]: user interface is communicatively coupled to the processing circuitry and is configured to alert a user of the indication of pump thrombosis; [0033]: user interface may be a mobile device of the user).
As to claim 15, Sambelashvili discloses the system of claim 1, wherein the MCSD is a left ventricular assist device (LVAD) (e.g., paragraphs [0004]: it was known to use a left ventricular assist device as a mechanical circulatory support device; and [0022]: the inflow cannula 114 of the MCS device 106 is attached to the left ventricle of the heart).
With respect to claim 16, Sambelashvili discloses the system of claim 1, wherein the sensing subsystem is further configured to obtain, from the one or more sensors, signals indicative of electromagnetic signals of the MCSD in operation in the mammal (e.g., paragraph [0025]: an electromagnetic transducer can be used to sense the mechanical wave from the MCS device).
As to claim 18, as best understood, Sambelashvili discloses the system of claim 1, wherein the abnormal operational conditions of the MCSD include at least one of a presence of pump thrombosis or a likelihood to develop pump thrombosis at the MCSD (e.g., abstract and paragraph [0039]: pump thrombosis detection system may collect and analyze one or more signals, indications of pump thrombosis … to notify the patient of an indication of pump thrombosis or if the patient is likely to experience pump thrombosis).
Regarding claim 19, Sambelashvili discloses a method for assessing a condition of a mechanical circulatory support device (MCSD) in a mammal, the method comprising: receiving, from one or more sensors, signals indicative of at least one of vibrations or acoustics of the MCSD in operation in the mammal (e.g., paragraphs [0026]-[0028]: transducer 102 generates a signal representative of a mechanical wave from the MCS and transmit the signal to computing device 104; the signal from transducer 102 is received by processing circuitry of computing device 104); processing the signals to identify at least one harmonic in the signals (e.g., paragraphs [0028]: processing circuitry conditions the received signal; [0007]: The processing circuitry is configured to identify at least one portion of the signal representative of at least one harmonic of the mechanical wave); and evaluating the condition of the MCSD using the at least one harmonic identified in the signals indicative of at least one of the vibrations or the acoustics of the MCSD in operation in the mammal (e.g., paragraph [0007]: The processing circuitry is configured to identify at least one portion of the signal representative of at least one harmonic of the mechanical wave and determine an indication of pump thrombosis (condition of the MCSD) based on the at least one portion).
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.
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 3 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over Sambelashvili as applied to claim 1 above, and further in view of US Patent Application Publication No. 2015/0080748 to Hübbert.
With respect to claim 3, Sambelashvili discloses the system of claim 1, but does not expressly disclose that the one or more sensors include at least one of a microphone, a triaxial accelerometer, or a hydrophone. However, Hübbert, in a related art: system for predicting cardiovascular events, teaches that acoustic signals from an assist device can be registered at various time intervals and analyzed using a hydrophone data acquisition system with sensor (e.g., paragraph [0005] of Hübbert). Accordingly, one of ordinary skill in the art would have recognized the benefits of using a hydrophone to sense vibrations or acoustics of a MCSD (assist device) in view of the teachings of Hübbert. Consequently, one of ordinary skill in the art would have modified the system of Sambelashvili to have a hydrophone sensor in view of the teachings of Hübbert that such was a well-known engineering expedient in the sensing acoustics signals of an assist device, and because the combination would have yielded a predictable result.
As to claim 12, Sambelashvili discloses the system of claim 1, but does not expressly disclose that the one or more sensors include at least one of an electronic stethoscope, a hydrophone, an accelerometer, an ECG sensor, or an echocardiographic sensor. However, Hübbert, in a related art: system for predicting cardiovascular events, teaches that acoustic signals from an assist device can be registered at various time intervals and analyzed using a hydrophone data acquisition system with sensor to determine device end-of-life, or an electro-stethoscope system (e.g., paragraph [0005] of Hübbert). Accordingly, one of ordinary skill in the art would have recognized the benefits of using a hydrophone to sense vibrations or acoustics of a MCSD (assist device) in view of the teachings of Hübbert. Consequently, one of ordinary skill in the art would have modified the system of Sambelashvili to have a hydrophone sensor or an electronic stethoscope in view of the teachings of Hübbert that such were well-known engineering expedients in the sensing acoustics signals of an assist device, and because the combination would have yielded a predictable result.
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Sambelashvili as applied to claim 7 above, and further in view of US Patent Application Publication No. 2004/0215050 to Morello.
Sambelashvili discloses the system of claim 7, but does not expressly disclose that the relative amplitude is a ratio of an amplitude of a 3H to an amplitude of a FF in the signals. Sambelashvili does disclose that during operation the MCS devices produce a mechanical wave with frequency peaks (and harmonics thereof) that are produced by structures of the MCS device and by detecting a change in one or more frequency peaks of the mechanical wave, the system detects pump thrombosis of the MCS device (e.g., paragraph [0007]). Morello, in a related art: blood pump system (title of Morello) teaches that to obtain a desired calculation based on a sampled time continuous signal in the frequency domain, the processor may be programmed to validate the integrity of the sampled time continuous signal by calculating the signal to noise plus distortion ratio (e.g., paragraph [0013] of Morello); spectral analysis equations are used to process the frequency domain data and include harmonic distortion, sub-fundamental distortion (distortion below the fundamental frequency), super-fundamental distortion (distortion above the fundamental frequency), the ratio of the super-fundamental distortion to the sub-fundamental distortion, and others (e.g., paragraph [0070] of Morello); and that the harmonic distortion factor measures the ratio of all harmonics about the fundamental frequency with respect to the fundamental frequency (e.g., paragraphs [0073]-[0074] of Morello). Accordingly, one of ordinary skill in the art would have recognized the benefits of processing frequencies of a MCS device including evaluating a relative amplitude such as a ratio of an amplitude of a third harmonic to an amplitude of the fundamental frequency of a signal in view of the teachings of Morello. Consequently, one of ordinary skill in the art would have modified the system of Sambelashvili to evaluate the condition of the MCSD by determining that a ratio of an amplitude of a third harmonic to an amplitude of a fundamental frequency in the signals as taught by Morello that such was a well-known engineering expedient in the blood pump system art, and because the combination would have yielded a predictable result.
Claims 17 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Sambelashvili as applied to claims 1 and 19 above, and further in view of US Patent Application Publication No. 2021/0113099 to Rogers et al. (EFD: 02/15/2019 and hereinafter referred to as “Rogers”).
Sambelashvili discloses the system of claim 1 and the method of claim 19, wherein the computing subsystem is configured to evaluate the condition of the MCSD using the at least one harmonic identified (e.g., paragraphs [0062]-[0063]: processing circuitry identifies a harmonic of the received signal to determine an indication of pump thrombosis) based on: retrieving, from a data store, one or more algorithms (e.g., paragraphs [0012]: computer-readable storage medium comprises instructions that when executed by processing circuitry of the medical device system, cause the processing circuitry to determine an indication of pump thrombosis based on the sensed signal; and [0043]: processing circuitry 263 includes software that sets forth one or more algorithms that are stored within one or more storage components 270); and classifying, based on applying the one or more algorithms, the at least one harmonic as corresponding to normal or abnormal operational conditions of the MCSD (e.g., paragraphs [0006]: pump thrombosis may be classified as suspected pump thrombus or confirmed pump thrombus corresponding to an abnormal condition; and [0058]: the sensed signal may include features that are unique to the mechanical wave from the MCS device having particular operation conditions, such as pump speed and presence of thrombus), but does not expressly disclose that the stored algorithms are machine learning models and that the one or more machine learning models were trained using training datasets that include signals labeled with normal operational conditions and signals labeled with abnormal operational conditions. However, Rogers, in a related art: detection of pump thrombosis, teaches that machine algorithms are particularly useful for further improving device performance (e.g., paragraph [0010] of Rogers), the processor may utilize machine learning to customize the analysis to each user (e.g., paragraph [0015] of Rogers), machine learning algorithms may be employed to improve signal analysis (e.g., paragraph [0122] of Rogers), vibrational acoustics of ventricular assist devices (VADs) or devices used to augment failing myocardial function can be captured and used to detect pump thrombosis or device malfunction (e.g., paragraph [0139] of Rogers), supervised machine learning of labeled signal involves two parts: labeling the signal and multi-class classification methods including but not limited to the Random Forest method (e.g., paragraphs [0175]-[0176]+ of Rogers), and the machine learning classifier is trained at detecting the presence of abnormal movements/features based on ground truth labels provided by a clinician where the model is periodically tested and updated/refined (e.g., paragraph [0235] of Rogers). Accordingly, one of ordinary skill in the art would have recognized the benefits of machine learning for classifying sensed vibrational acoustics of mechanical circulatory support devices in view of the teachings of Rogers. Consequently, one of ordinary skill in the art would have modified the system and method of Sambelashvili so that the algorithms received from the data store is a machine learning model and the classification is based on the machine learning model so that the identified harmonics are classified as normal or abnormal operational conditions of the MCSD, wherein the machine learning model was trained using training datasets that include signals labeled with normal operational conditions and signals labeled with abnormal operational conditions in view of the teachings of Rogers that such were well-known engineering protocol in the detection of thrombosis art, and because the combination would have yielded a predictable result.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US Patent Application Publication No. 2021/0178038 to Kemmerer et al. (EFD: 11/18/2020) is directed to detecting pump suction, pump thrombus, and other adverse VAD events wherein during an adverse event, for example, thrombus or suction, the harmonics in the form of vibrations from the VAD 14 may change and the piezoelectric element 30 can sense those changes in real-time from the driveline 16 and the processing circuitry of the controller 10 can correlate those changes to the presence or absence of an adverse event (e.g., paragraph [0036] of Kemmerer).
US Patent Application Publication 2021/0252275 to Esposti et al. (EFD: 09/13/2019) is directed to a method for determining artificial pump dysfunction where the medical sensor may comprise a processor configured to analyze the output signal, which may utilize machine learning to customize the analysis to each individual user of the medical sensor. The machine learning may comprise one or more supervised learning algorithms and/or unsupervised learning algorithms customizable to the user. The machine learning may improve a sensor performance parameter used for diagnostic sensing or a therapeutic application and/or a personalized user performance parameter, (e.g., paragraph [0015] of Esposti).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CATHERINE M VOORHEES whose telephone number is (571)270-3846. The examiner can normally be reached Monday-Friday 8:30 AM to 4:30 PM.
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/CATHERINE M VOORHEES/Primary Examiner, Art Unit 3792