DETAILED ACTION
This action is responsive to the “AMENDMENT/RESPONSE TO OFFICE ACTION” filed 28 April 2026. The Examiner acknowledges the amendments to claims 1, 4-5, 7, 9-11, 14-16, 24. 26. And 29, as well as the cancelation of claims 6, 8, 12-13, 17-23, 27-28, and 30. Claims 1-5, 7, 9-11, 14-16, 24-26, and 29 are pending.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Interpretation
Examiner Notes: currently, NO limitation invokes interpretation under § 112(f).
Claim Rejections - 35 USC § 112
Examiner’s Note Regarding Machine Learning: the claimed “machine learning model” of claim(s) 26 was considered under § 112(a), wherein the Examiner notes that the disclosure of machine learning models in ¶¶0039 and 0097-0100 of the Applicant’s Specification is considered to provide sufficient written description support for the claimed machine learning model as presently claimed for one of ordinary skill in the art to understand that the Applicant possessed the instant invention at the time of filing.
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.
Claim(s) 9-11, 14-16, 24-26, and 29 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception without significantly more. Each claim has been analyzed to determine whether it is directed to any judicial exceptions.
Representative claim(s) 24 [representing all independent claims] recite(s):
A method of using an implanted ambulatory system for health monitoring, the method comprising:
receiving electrical signal data from an electrical sensor disposed in an anterior mediastinum of a patient, the electrical sensor disposed outside of a heart of the patient and configured to detect electrical signals radiating from an external surface of the heart;
receiving pressure signal data from a pressure sensor disposed in the anterior mediastinum and outside of the heart, the pressure sensor configured to detect pressure signals in the anterior mediastinum;
amplifying and filtering the pressure signal data to define a hemodynamic curve corresponding to pressure signals in a first frequency band, a pulmonary curve corresponding to pressure signals in a second frequency band different from the first frequency band, and a mediastinal curve corresponding to pressure signal in a third frequency band different from the first frequency band and the second frequency band;
defining a change in a heart failure status of the patient over a period of time based on (i) the electrical signal data, the hemodynamic curve, the pulmonary curve, and the mediastinal curve and (ii) a change in at least one of the electrical signal data, the hemodynamic curve, the pulmonary curve, or the mediastinal curve over the period of time; and
executing at least one action associated with the change in the heart failure status.
(Emphasis added: abstract idea, additional element)
Step 2A Prong 1
Representative claim(s) 24 recites the following abstract ideas, which may be performed in the mind or by hand with the assistance of pen and paper:
“receiving electrical signal data from an electrical sensor disposed in an anterior mediastinum of a patient, the electrical sensor disposed outside of a heart of the patient and configured to detect electrical signals radiating from an external surface of the heart” / “receiving pressure signal data from a pressure sensor disposed in the anterior mediastinum and outside of the heart, the pressure sensor configured to detect pressure signals in the anterior mediastinum” – may be performed by merely observing previously collected data [Applicant’s Specification ¶0114]; wherein the Examiner notes that the mere recitation that the data comes from particular sensors disposed in particular locations is not considered to be a positive recitation of the sensor(s) itself/themselves or use of the sensor(s) for data gathering, and merely defines the type of data received
“amplifying and filtering the pressure signal data to define a hemodynamic curve corresponding to pressure signals in a first frequency band, a pulmonary curve corresponding to pressure signals in a second frequency band different from the first frequency band, and a mediastinal curve corresponding to pressure signal in a third frequency band different from the first frequency band and the second frequency band” – may be performed by merely applying known or derived mathematical formulae on at least a limited amount of data [Applicant’s Specification ¶0116]
“defining a change in a heart failure status of the patient over a period of time based on (i) the electrical signal data, the hemodynamic curve, the pulmonary curve, and the mediastinal curve and (ii) a change in at least one of the electrical signal data, the hemodynamic curve, the pulmonary curve, or the mediastinal curve over the period of time” – may be performed by merely observing previously collected or known data and drawing mental conclusions therefrom [Applicant’s Specification ¶0129]
“executing at least one action associated with the change in the heart failure status” – may be performed by merely communicating an alert or notification as a method of organizing human activity [Applicant’s Specification ¶0114; MPEP § 2106.04(a)(2)(II)]
If a claim, under BRI, covers performance of the limitations in the mind but for the mere recitation of extra-solutionary activity (and otherwise generic computer elements) then the claim falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea under Step 2A Prong 1 of the Mayo framework as set forth in the 2019 PEG.
No limitations are provided that would force the complexity of any of the identified evaluation steps to be non-performable by pen-and-paper practice.
Alternatively or additionally, these steps describe the concept of using implicit mathematical formula(s) [i.e., “amplifying and filtering the pressure signal data to define a hemodynamic curve corresponding to pressure signals in a first frequency band, a pulmonary curve corresponding to pressure signals in a second frequency band different from the first frequency band, and a mediastinal curve corresponding to pressure signal in a third frequency band different from the first frequency band and the second frequency band” (graphing data), “defining a change in a heart failure status of the patient over a period of time based on (i) the electrical signal data, the hemodynamic curve, the pulmonary curve, and the mediastinal curve and (ii) a change in at least one of the electrical signal data, the hemodynamic curve, the pulmonary curve, or the mediastinal curve over the period of time” (data correlation)] to derive a conclusion based on input of data, which corresponds to concepts identified as abstract ideas by the courts [Diamond v. Diehr. 450 U.S. 175, 209 U.S.P.Q. 1 (1981), Parker v. Flook. 437 U.S. 584, 19 U.S.P.Q. 193 (1978), and In re Grams. 888 F.2d 835, 12 U.S.P.Q.2d 1824 (Fed. Cir. 1989)]. The concept of the recited limitations identified as mathematical concepts above is not meaningfully different than those mathematical concepts found by the courts to be abstract ideas.
The dependent claims merely include limitations that either further define the abstract idea [e.g. limitations relating to the data gathered or particular steps which are entirely embodied in the mental process] and amount to no more than generally linking the use of the abstract idea to a particular technological environment or field of use because they are merely incidental or token additions to the claims that do not alter or affect how the process steps are performed.
Thus, these concepts are similar to court decisions of abstract ideas of itself: collecting, displaying, and manipulating data [Int. Ventures v. Cap One Financial], collecting information, analyzing it, and displaying certain results of the collection and analysis [Electric Power Group], collection, storage, and recognition of data [Smart Systems Innovations].
Step 2A Prong 2
The judicial exception is not integrated into a practical application.
Representative claim 24 only recites additional elements of extra-solutionary activity – in particular, extra-solution activity [generic computer function] – without further sufficient detail that would tie the abstract portions of the claim into a specific practical application (2019 PEG p. 55 – the instant claim, for example does not tie into a particular machine, a sufficiently particular form of data or signal collection – via the claimed extra-solution activity identified above, or a sufficiently particular form of display or computing architecture/structure).
Dependent claim(s) 10-11, 14-15, and 29 merely add detail to the abstract portions of the claim but do not otherwise encompass any additional elements which tie the claim(s) into a particular application/integration [the dependent claim(s) recite generic ‘units’ or ‘steps’ which encompass mere computer instructions to carry out an otherwise wholly abstract idea].
Dependent claim(s) 16 and 25 encounter substantially the same issues as the independent claim(s) from which they depend in that they encompass further generic extra-solutionary activity [generic data gathering] and/or generic computer elements [storage, memory per se].
Accordingly, the claim(s) are not integrated into a practical application under Step 2A Prong 2.
Step 2B
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Independent claims 9 and 24 as individual wholes fail to amount to significantly more than the judicial exception at Step 2B. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of extra-solutionary activity [i.e., generic computer function] and generic computer elements cannot amount to significantly more than an abstract idea [MPEP § 2106.05(f)] and is further considered to merely implement an abstract idea on a generic computer [MPEP § 2106.05(d)(II) establishes computer-based elements which are considered to be well understood, routine, and conventional when recited at a high level of generality].
For the independent claim portions and dependent claims which provide additional elements of extra-solutionary data gathering, MPEP § 2106.05(g) establishes that mere data gathering for determining a result does not amount to significantly more. The extra-solutionary activity of processor steps [acquiring, amplifying, filtering signals, etc.] as presently recited, cannot provide an inventive concept which amounts to significantly more than the recited abstract idea.
For the independent claims as well as the dependent claims merely reciting generic computer elements and functions [generically recited processor functions], MPEP § 2106.05(d)(II) establishes computer-based elements which are considered to be well understood, routine, and conventional when recited at a high level of generality.
Accordingly, the generic computer elements and functions therein, as presently limited, cannot provide an inventive concept since they fall under a generic structure and/or function that does not add a meaningful additional feature to the judicial exception(s) of the claim(s).
Claim(s) 9 and 24 recite in the preamble that the claimed method is of “using an implanted ambulatory system for health monitoring”. Such an ambulatory system is considered well-understood, routine, and conventional, as known by at least:
Applicant’s disclosure is not particular regarding the particular structure of the generically claimed electrical sensor, and recites the electrical sensor at a high level of generality [Descriptions of well-known components, methods, techniques, etc. may be omitted so as to not obscure the embodiments herein (Applicant’s Specification ¶0050); In some embodiments, the sensing device 110 can be implemented in or as a treatment and/or therapy device such as an implantable cardioverter-defibrillator (ICD), a cardiac resynchronization therapy defibrillator (CRT-D), a pacemaker, and/or any other suitable device (Applicant’s Specification ¶0053)]. This lack of disclosure is acceptable under 35 U.S.C. 112(a) since this hardware performs non-specialized functions known by those of ordinary skill in the medical technology arts. Thus, Applicant's specification essentially admits that this hardware is conventional and performs well understood, routine and conventional activities in the field of the invention. In other words, Applicant’s specification demonstrates the well-understood, routine, conventional nature of the above-identified additional element because it describes such an additional element in a manner that indicates that the additional element is sufficiently well-known that the specification does not need to describe the particulars of such additional elements to satisfy 35 U.S.C. 112(a) [see Berkheimer memo from April 19, 2018, Page 3, (III)(A)(1), not attached]. Adding hardware that performs “well understood, routine, conventional activit[ies]’ previously known to the industry” will not make claims patent-eligible [TLI Communications].
Manicka (US-20220161023-A1) [Other devices implanted in the body can include other implantable medical devices, such as other pacemakers, implantable cardioversion-defibrillators, nerve stimulators, and the like (Manicka ¶0241)]
Ecker (US-5899927-A, previously presented) [It is believed that any of the commonly used leads for pacemakers can perform satisfactorily for this invention (Ecker Col 6:51-53)]
Pramodsingh (US-20200037888-A1, previously presented) [The ambulatory system 105 may include an ambulatory medical device (AMD) 110. In an example, the AMD 110 may be an implantable device subcutaneously implanted in a chest, abdomen, or other parts of the patient 102. Examples of the implantable device may include, but are not limited to, pacemakers, pacemaker/defibrillators, cardiac resynchronization therapy (CRT) devices, cardiac remodeling control therapy (RCT) devices, neuromodulators, drug delivery devices, biological therapy devices, diagnostic devices such as cardiac monitors or loop recorders, or patient monitors, among others. The AMD 110 alternatively or additionally may include a subcutaneous medical device such as a subcutaneous monitor or diagnostic device, external monitoring or therapeutic medical devices such as automatic external defibrillators (AEDs) or Holter monitors, or wearable medical devices such as patch-based devices, smart wearables, or smart accessories (Pramodsingh ¶0042)]
Claim 26 recites a “machine learning model”. Such a machine learning model is considered well-understood, routine, and conventional, as known by at least:
Hu (“Intelligent Sensor Networks”, previously presented) [In supervised learning, the learner is provided with labeled input data. This data contains a sequence of input/output pairs of the form xi, yi, where xi is a possible input and yi is the correctly labeled output associated with it. The aim of the learner in supervised learning is to learn the mapping from inputs to outputs. The learning program is expected to learn a function f that accounts for the input/output pairs seen so far, f (xi) = yi, for all i. This function f is called a classifier if the output is discrete and a regression function if the output is continuous. The job of the classifier/regression function is to correctly predict the outputs of inputs it has not seen before (Hu, Page 5)]
Huang (“Kernel Based Algorithms for Mining Huge Data Sets”, previously presented) [In supervised learning, the learner is provided with labeled input data. This data contains a sequence of input/output pairs of the form xi, yi, where xi is a possible input and yi is the correctly labeled output associated with it. The aim of the learner in supervised learning is to learn the mapping from inputs to outputs. The learning program is expected to learn a function f that accounts for the input/output pairs seen so far, f (xi) = yi, for all i. This function f is called a classifier if the output is discrete and a regression function if the output is continuous. The job of the classifier/regression function is to correctly predict the outputs of inputs it has not seen before (Huang, Page 1)]
Mitchell (“The Discipline of Machine Learning”, previously presented) [For example, we now have a variety of algorithms for supervised learning of classification and regression functions; that is, for learning some initially unknown function f : X [Calibri font/0xE0] Y given a set of labeled training examples {xi; yi} of inputs xi and outputs yi = f(xi) (Mitchell, Pages 3-4)]
Examiner’s Note Regarding Particular Treatment or Prophylaxis: Claim(s) 15-16 and 24-25 recite subject matter regarding “executing at least one action in response to the heart failure status being indicative of worsening heart failure… wherein the at least one action includes sending a signal representing at least one of a notification, a trigger to provide treatment, or an alarm”, which the Examiner notes is not considered to be a particular treatment or prophylaxis, as none of the identified claims positively recite or include language that is considered to be a particular treatment or prophylaxis as an additional element to integrate the judicial exception into a practical application or allow the identified claims to amount to significantly more than the judicial exception [MPEP § 2106.04(d)(2)]. The Examiner notes that the Applicant’s Specification provides written description support for a particular treatment of applying electrical shock therapy via an implantable cardiac treatment device based on the data received from the sensors [In some embodiments, the diagnostic/monitoring systems and/or methods described herein can be at least partially implemented in and/or can otherwise include an implantable cardiac treatment device (e.g., cardiac therapy device, defibrillator, implantable cardioverter defibrillator (ICD), cardiac resynchronization therapy defibrillator (CRT-D), pacemaker, etc.) configured to deliver treatment (shock therapy) based at least in part on one or more characteristics associated with a heart of a patient (Applicant’s Specification ¶0031); For example, in the case of an ICD, the sensing device 110 can be configured to determine whether to provide electric shock therapy (e.g., a defibrillation shock, cardiac pacing, and/or the like) to the heart H of the patient P based at least in part on data received from the set of sensor(s) 120 (Applicant’s Specification ¶0053); In some instances, when ventricular fibrillation is detected and/or confirmed, a defibrillation shock can be delivered as treatment, at 1404 (Applicant’s Specification ¶0161)].
Accordingly, the claim(s) as whole(s) fail amount to significantly more than the judicial exception under Step 2B.
Examiner’s Note Regarding § 101 Analysis: The Examiner notes that claim(s) 1 and those dependent therefrom recite a judicial exception [processor functions of receiving data, defining pressure curves, determining and monitoring at least one health-related parameter, and generating a heart failure status of lines 11-27 of claim 1] at Step 2A Prong 1, which is/are considered to be abstract idea(s) performed in the mind or by hand by merely observing at least a limited amount of previously known or collected data and drawing mental conclusions therefrom based on known or derived mathematical formulas. However, the Examiner further notes that claim(s) 1 recites a particular combination and configuration of additional elements of “an electrical sensor configured to be disposed in an anterior mediastinum of a patient, the electrical sensor configured to be disposed outside of a heart of the patient and to detect an electrical signal radiating from an external surface of the heart”, “a pressure sensor configured to be disposed in the anterior mediastinum and outside the heart, the pressure sensor configured to detect a pressure signal in the anterior mediastinum”, and “a sensing device coupled to the electrical sensor and the pressure sensor” that is considered to integrate the judicial exception into a practical application at Step 2A Prong 2 and allow the invention to amount to significantly more than the judicial exception at Step 2B.
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.
Claim(s) 1-5, 7, 9-11, 14-16, 24-25, and 29 is/are rejected under 35 U.S.C. 103 as being unpatentable over Manicka (US-20220161023-A1) in view of Ecker (US-5899927-A, previously presented) and Nasseri et al. (“Clinical and Radiologic Review of the Normal and Abnormal Thymus: Pearls and Pitfalls”, previously presented).
Regarding claim 1, Manicka teaches
A system for ambulatory health monitoring, the system comprising:
an electrical sensor configured to be disposed in an anterior mediastinum of a patient, the electrical sensor configured to be disposed outside of a heart of the patient and to detect an electrical signal radiating from an external surface of the heart [electrode 172 (Manicka Figs. 5A-B); FIG. 5A is a side view of prong 106 of subcutaneous device 100. FIG. 5B is a top view of prong 106 of subcutaneous device 100. Prong 106 includes proximal end 160, distal end 162, base portion 164, spring portion 166, arm portion 168, contact portion 170, and electrode 172 (Manicka ¶0220)];
a pressure sensor configured to be disposed in the anterior mediastinum and outside the heart, the pressure sensor configured to detect a pressure signal in the anterior mediastinum [Sensor(s) 190 can include any suitable sensor, including, but not limited to, temperature sensors, accelerometers, pressure sensors, proximity sensors, infrared sensors, optical sensors, and ultrasonic sensors. The information from sensor(s) 190 allows subcutaneous device 100 to sense physiological parameters of a patient. For example, the data from the sensors can be used to calculate heart rate, heart rhythm, respiration rate, respiration waveform, activity, movement, posture, oxygen saturation, photoplethysmogram (PPG), blood pressure, core body temperature, pulmonary edema, and pulmonary wetness (Manicka ¶0240)]; and
a sensing device coupled to the electrical sensor and the pressure sensor, the sensing device including a memory and a processor, the processor configured to execute instructions stored in the memory [Further, subcutaneous device 100 can function as a monitoring device, a diagnostic device, a pacemaker device, a defibrillator device, or any combinations thereof (Manicka ¶0289); Controller 182 is configured to implement functionality and/or process instructions for execution within subcutaneous device 100. Controller 182 can process instructions stored in memory 184. Examples of controller 182 can include any one or more of a microcontroller, a microprocessor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other equivalent discrete or integrated logic circuitry (Manicka ¶0235)] operable to cause the processor to:
receive electrical signal data from the electrical sensor and pressure signal data from the pressure sensor [Controller 182 can receive electrical signals from sensing circuitry 180, analyze the electrical signals, and execute instructions stored in memory 184 to determine whether an arrhythmia is present in the heart rate of a patient (Manicka ¶0238); Controller 182 can also receive information from sensor(s) 190 (Manicka ¶0240)];
determine at least one health-related parameter based on the electrical signal data [Controller 182 analyzes the electrical signals and executes instructions stored in memory 184 to determine if there is an arrhythmia in the patient's heart rate. If controller 182 determines that there is an arrhythmia, controller 182 will send instructions to therapy circuitry 186 to send electrical stimulation to the heart to regulate the heart rate of the patient (Manicka ¶0232)];
monitor the at least one health-related parameter over a period of time to determine if a change in the at least one health-related parameter has occurred [Manicka ¶0232]; and
generate a heart failure status of the patient based on the at least one health-related parameter [Manicka ¶0232, wherein a determination of the presence of an arrhythmia resulting in sending instructions to send electrical stimulation to the heart is considered to read on the broadest reasonable interpretation of “generating a heart failure status”].
However, while Manicka discloses using a the pressure sensor to calculate heart rate and rhythm, as well as respiration rate and waveforms [Manicka ¶0240], Manicka fails to explicitly disclose wherein the processor is further configured to define a hemodynamic curve corresponding to the pressure signal data in a first frequency band, a pulmonary curve corresponding to the pressure signal data in a second frequency band different from the first frequency band, and a mediastinal curve corresponding to the pressure signal data in a third frequency band different from the first frequency band and the second frequency band; wherein the determined health-related parameter is further based on the hemodynamic curve, the pulmonary curve, and the mediastinal curve.
Ecker discloses a system for ambulatory health monitoring, wherein the system comprises an electrical sensor configured to be disposed in an anterior mediastinum of a patient, the electrical sensor configured to be disposed outside of a heart of the patient and to detect an electrical signal radiating from an external surface of the heart [an additional sense amplifier 124 is coupled to the lead feedthrough pins 80 and 82 for providing a electrical sense signal to the operating system in a manner well known in the art. In cardiac medical device applications, the electrical sense signal may be the electrogram of the patient's heart detected through the lead 18 (Ecker Col 12:45-51, Fig. 1); the lead distal end segment 16 is typically firmly attached to the heart 14 (and may in fact be alternatively attached to the epicardium) so that good electrical contact is maintained (Ecker Col 8:22-25), wherein being attached to the epicardium is considered to define being positioned in the anterior mediastinum, as the epicardium is understood to define a posterior border of the anterior mediastinum], a pressure sensor configured to be disposed in the anterior mediastinum and outside the heart, the pressure sensor configured to detect a pressure signal in the anterior mediastinum [FIGS. 2 and 3 depict the lead connector module or assembly 20 coupled with a proximal connector end 40 of a lead 18 and the incorporation of a pressure wave transducer 32 and a reference transducer 34 (Ecker Col 8:52-55); In this first embodiment, the transducers 32 and 34 are each formed of a piezoelectric crystal of the type employed as an activity sensor in commercially available MEDTRONIC.RTM. THERA.RTM. DR IPGs for rate-responsive pacing in the DDDR mode and other modes… The resulting capacitive transducer provides an electrical output signal on the sensor lead wires that varies in amplitude in response to minute deflections of the piezoelectric crystal in response to the acoustically or mechanically conducted cardiac and respiratory pressure waves (Ecker Col 8:62-66, Col 9:9-14), see Examiner’s analysis above regarding positioning of the lead], and a sensing device coupled to the electrical sensor and the pressure sensor [The resulting signal is applied to the signal processor 120 of the operating system 122 of interest. The operating system 122 may be microcomputer based IPG, implantable monitor or any other medical equipment that the lead or catheter is coupled to (Ecker Col 12:39-43)] configured to define a hemodynamic curve corresponding to the pressure signal data in a first frequency band and a pulmonary curve corresponding to the pressure signal data in a second frequency band different from the first frequency band, wherein Ecker further discloses determining a health-related parameter based on the electrical signal data, the hemodynamic curve and the pulmonary curve [The pressure wave and reference signals are first amplified in amplifiers 110 and 112, respectively. The amplified pressure wave and reference signals are then bandpass filtered in bandpass filters 114 and 116, respectively (Ecker Col 12:34-38); The bandpass filter characteristics are tailored to pass the range of amplified signal frequencies of interest and to reject frequency components in the signals that are outside that range (Ecker Col 12:52-55); In either case, the frequency range of the bandpass filters for each such channel is selected for the signal to be derived. In sensing cardiac sounds and motion components of the pressure wave, the frequency range of interest is believed to be between about 0.5-7.0 Hz in the atrium and in the ventricle but may be a different range depending on the waveform characteristic to be measured. To sense patient activity related to ambulatory movement, i.e., footfalls the frequency range of interest representing footfalls is between about 0.5-15 Hz. To detect the amplitude and frequency of the respiratory cycle, the frequency range of interest is about 0.05-0.8 Hz. FIG. 7 is a two second waveform diagram depicting the cardiac cycle pressure wave detected by the pressure wave transducer in relation to the preceding intrinsic PQRST complex as detected from the pressure wave transmitted through a conventional pacing lead implanted in the ventricle of a healthy dog… The peaks of FIG. 7 may represent the pressure waveform of the ventricles in forcefully contracting and expelling blood and then relaxing and filling with blood that takes place in closer timed relation to the PQRST complex. A clear correlation between the double signal peaks of the pressure wave and the PQRST complex is observed. This correlation is effective with either an intrinsic depolarization or an evoked depolarization of the heart and in both the atrial and ventricular heart chambers (Ecker Col 13:9-26, 38-47, Fig. 7); FIG. 8 is a 20 second waveform diagram depicting the respiration cycle pressure wave detected by the pressure wave transducer in relation to a series of PQRST complexes in the same dog experiment. The respiration cycle is much longer than the cardiac cycle. Pulmonary minute ventilation may be determined from the amplitude of the peaks of the respiratory cycle and the interval between peaks in a manner well known in the art (Ecker Col 13:48-55, Fig. 8), wherein the pressure waveform of Ecker Fig. 7 (cardiac cycle) is considered to define a hemodynamic curve, and wherein the pressure waveform of Ecker Fig. 8 is considered to define a pulmonary curve].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system of Manicka to employ wherein the processor is further configured to define a hemodynamic curve corresponding to the pressure signal data in a first frequency band, a pulmonary curve corresponding to the pressure signal data in a second frequency band different from the first frequency band, and wherein determining the health-related parameter is further based on the hemodynamic curve and the pulmonary curve, so as to provide visual contextual information regarding hemodynamics and respiration during operation of the system.
However, Manicka in view of Ecker fails to explicitly disclose wherein the processor is further configured to define a mediastinal curve corresponding to the pressure signal data in a third frequency band different from the first frequency band and the second frequency band; and wherein the determined health-related parameter is further based on the mediastinal curve.
Ecker does disclose filtering out pressure signals caused by exterior environmental noise [For example, the piezoelectric transducers as described above are sensitive to heart sound or motion frequencies of interest as well as to footfalls when the patient is ambulatory, muscle artifacts or myopotentials associated with limb movements and exercise, and may be responsive to speech and exterior environmental noise. These may constitute "noise" that are first filtered out to the extent possible and then subtracted in differential amplifier 118 to derive the signal of interest (Ecker Col 12:55-63)] and further suggests identifying particular frequency ranges of interest in order to filter signals outside of the frequency range of interest [In either case, the frequency range of the bandpass filters for each such channel is selected for the signal to be derived. In sensing cardiac sounds and motion components of the pressure wave, the frequency range of interest is believed to be between about 0.5-7.0 Hz in the atrium and in the ventricle but may be a different range depending on the waveform characteristic to be measured (Ecker Col 13:9-15)].
Nasseri discloses assessments of the thymus and thymoma, wherein Nasseri notes that thymoma in the anterior mediastinum can be observed through pressure-induced symptoms [Thymomas represent 20% of all mediastinal neoplasms in adults; they are the most common anterior mediastinal primary neoplasm in adults but account for less than 5% of mediastinal tumors in children (33)… 20%–30% of patients have pressure-induced symptoms such as cough, chest pain, dyspnea, dysphagia, hoarseness, or superior vena cava syndrome (Nasseri p. 421)].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system of Manicka in view of Ecker to employ wherein the processor is further configured to define a mediastinal curve corresponding to the pressure signal data in a third frequency band different from the first frequency band and the second frequency band; and wherein the determined health-related parameter is further based on the mediastinal curve, as thymoma are known to affect pressure in the anterior mediastinum and cause pressure-induced symptoms including cardiac conditions [Nasseri p. 421, wherein the possible presence of a thymoma may be considered to be a cardiac parameter, as a known symptom of a thymoma is superior vena cava syndrome], and as this modification would amount to mere application of a known technique to a known device (method, or product) ready for improvement to yield predictable results [identifying particular frequency ranges of interest in order to filter signals outside of the frequency range of interest] [MPEP § 2143(I)(D)].
Regarding claim 2, Manicka in view of Ecker and Nasseri teaches
The system of claim 1, further comprising: a lead configured to be implanted in the anterior mediastinum of the patient and coupled to the sensing device, wherein the electrical sensor and the pressure sensor are coupled to the lead [Prong 106 includes proximal end 160, distal end 162, base portion 164, spring portion 166, arm portion 168, contact portion 170, and electrode 172 (Manicka ¶0225); Sensor(s) 190 can be positioned in housing 102 and/or prong 106 (Manicka ¶0233)].
Regarding claim 3, Manicka in view of Ecker and Nasseri teaches
The system of claim 2, wherein the sensing device is at least one of a pacemaker, an implantable cardioverter defibrillator (ICD), a cardiac resynchronization therapy defibrillator (CRT-D), or a ventricular assist device (VAD) [Manicka ¶0289].
Regarding claim 4, Manicka in view of Ecker and Nasseri teaches
The system of claim 1, wherein the processor is further configured to execute instructions stored in the memory that cause the processor to: amplify and filter the pressure signal data to separate the pressure signal data into the first frequency band, the second frequency band, and the third frequency band [See § 103 modification of claim 1 above; Ecker Col 12:52-55].
Regarding claim 5, Manicka in view of Ecker and Nasseri teaches
The system of claim 4, wherein the monitoring of the at least one health-related parameter over the period of time includes monitoring a change in each of the electrical signal data, the hemodynamic curve, the pulmonary curve, and the mediastinal curve [See § 103 modification of claim 1 above; Manicka ¶0207; Ecker Col 13:38-47, Fig. 7; Nasseri p. 421].
Regarding claim 7, Manicka in view of Ecker and Nasseri teaches
The system of claim 5, wherein the change in the at least one health-related parameter is associated with at least one of a change in a central venous pressure, a right atrial pressure, a pulmonary capillary wedge pressure, a tidal volume, a respiratory rate [See § 103 modification of claim 1 above; Manicka ¶0240; Ecker Col 13:48-55, Fig. 8], a stroke volume, a fluid load in the anterior mediastinum, or a mediastinal neoplasm [See § 103 modification of claim 1 above; Nasseri p. 421].
Regarding claim 9, Manicka teaches
A method of using an implanted ambulatory system for health monitoring, the method comprising:
receiving electrical signal data from an electrical sensor disposed in an anterior mediastinum of a patient, the electrical sensor disposed outside of a heart of the patient and configured to detect electrical signals radiating from an external surface of the heart [electrode 172 (Manicka Figs. 5A-B); FIG. 5A is a side view of prong 106 of subcutaneous device 100. FIG. 5B is a top view of prong 106 of subcutaneous device 100. Prong 106 includes proximal end 160, distal end 162, base portion 164, spring portion 166, arm portion 168, contact portion 170, and electrode 172 (Manicka ¶0220); Controller 182 can receive electrical signals from sensing circuitry 180, analyze the electrical signals, and execute instructions stored in memory 184 to determine whether an arrhythmia is present in the heart rate of a patient (Manicka ¶0238)];
receiving pressure signal data from a pressure sensor disposed in the anterior mediastinum and outside of the heart, the pressure sensor configured to detect a pressure signal in the anterior mediastinum [Controller 182 can also receive information from sensor(s) 190. Sensor(s) 190 can include any suitable sensor, including, but not limited to, temperature sensors, accelerometers, pressure sensors, proximity sensors, infrared sensors, optical sensors, and ultrasonic sensors. The information from sensor(s) 190 allows subcutaneous device 100 to sense physiological parameters of a patient. For example, the data from the sensors can be used to calculate heart rate, heart rhythm, respiration rate, respiration waveform, activity, movement, posture, oxygen saturation, photoplethysmogram (PPG), blood pressure, core body temperature, pulmonary edema, and pulmonary wetness (Manicka ¶0240)];
determining at least one health-related parameter based on the electrical signal data [Controller 182 analyzes the electrical signals and executes instructions stored in memory 184 to determine if there is an arrhythmia in the patient's heart rate. If controller 182 determines that there is an arrhythmia, controller 182 will send instructions to therapy circuitry 186 to send electrical stimulation to the heart to regulate the heart rate of the patient (Manicka ¶0232)];
monitoring the at least one health-related parameter over a period of time to determine if a change in the at least one health-related parameter has occurred [Manicka ¶0232]; and
generating a heart failure status of the patient based on the at least one health-related parameter [Manicka ¶0232, wherein a determination of the presence of an arrhythmia resulting in sending instructions to send electrical stimulation to the heart is considered to read on the broadest reasonable interpretation of “generating a heart failure status”].
However, while Manicka discloses using a the pressure sensor to calculate heart rate and rhythm, as well as respiration rate and waveforms [Manicka ¶0240], Manicka fails to explicitly disclose defining a hemodynamic curve corresponding to the pressure signal data in a first frequency band, a pulmonary curve corresponding to the pressure signal data in a second frequency band different from the first frequency band, and a mediastinal curve corresponding to the pressure signal data in a third frequency band different from the first frequency band and the second frequency band; wherein the at least one health-related parameter is further determined based on the hemodynamic curve, the pulmonary curve, and the mediastinal curve.
Ecker discloses a method for using an implanted ambulatory system for health monitoring, wherein the method comprises receiving electrical signal data from an electrical sensor disposed in an anterior mediastinum of a patient, the electrical sensor disposed outside of a heart of the patient and configured to detect electrical signals radiating from an external surface of the heart [an additional sense amplifier 124 is coupled to the lead feedthrough pins 80 and 82 for providing a electrical sense signal to the operating system in a manner well known in the art. In cardiac medical device applications, the electrical sense signal may be the electrogram of the patient's heart detected through the lead 18 (Ecker Col 12:45-51, Fig. 1); the lead distal end segment 16 is typically firmly attached to the heart 14 (and may in fact be alternatively attached to the epicardium) so that good electrical contact is maintained (Ecker Col 8:22-25), wherein being attached to the epicardium is considered to define being positioned in the anterior mediastinum, as the epicardium is understood to define a posterior border of the anterior mediastinum], receiving pressure signal data from a pressure sensor disposed in the anterior mediastinum and outside of the heart, the pressure sensor configured to detect a pressure signal in the anterior mediastinum [FIGS. 2 and 3 depict the lead connector module or assembly 20 coupled with a proximal connector end 40 of a lead 18 and the incorporation of a pressure wave transducer 32 and a reference transducer 34 (Ecker Col 8:52-55); In this first embodiment, the transducers 32 and 34 are each formed of a piezoelectric crystal of the type employed as an activity sensor in commercially available MEDTRONIC.RTM. THERA.RTM. DR IPGs for rate-responsive pacing in the DDDR mode and other modes… The resulting capacitive transducer provides an electrical output signal on the sensor lead wires that varies in amplitude in response to minute deflections of the piezoelectric crystal in response to the acoustically or mechanically conducted cardiac and respiratory pressure waves (Ecker Col 8:62-66, Col 9:9-14), see Examiner’s analysis above regarding positioning of the lead], and defining a hemodynamic curve corresponding to the pressure signal data in a first frequency band and a pulmonary curve corresponding to the pressure signal data in a second frequency band different from the first frequency band, wherein Ecker further discloses determining a health-related parameter based on the electrical signal data, the hemodynamic curve and the pulmonary curve [The pressure wave and reference signals are first amplified in amplifiers 110 and 112, respectively. The amplified pressure wave and reference signals are then bandpass filtered in bandpass filters 114 and 116, respectively (Ecker Col 12:34-38); The bandpass filter characteristics are tailored to pass the range of amplified signal frequencies of interest and to reject frequency components in the signals that are outside that range (Ecker Col 12:52-55); In either case, the frequency range of the bandpass filters for each such channel is selected for the signal to be derived. In sensing cardiac sounds and motion components of the pressure wave, the frequency range of interest is believed to be between about 0.5-7.0 Hz in the atrium and in the ventricle but may be a different range depending on the waveform characteristic to be measured. To sense patient activity related to ambulatory movement, i.e., footfalls the frequency range of interest representing footfalls is between about 0.5-15 Hz. To detect the amplitude and frequency of the respiratory cycle, the frequency range of interest is about 0.05-0.8 Hz. FIG. 7 is a two second waveform diagram depicting the cardiac cycle pressure wave detected by the pressure wave transducer in relation to the preceding intrinsic PQRST complex as detected from the pressure wave transmitted through a conventional pacing lead implanted in the ventricle of a healthy dog… The peaks of FIG. 7 may represent the pressure waveform of the ventricles in forcefully contracting and expelling blood and then relaxing and filling with blood that takes place in closer timed relation to the PQRST complex. A clear correlation between the double signal peaks of the pressure wave and the PQRST complex is observed. This correlation is effective with either an intrinsic depolarization or an evoked depolarization of the heart and in both the atrial and ventricular heart chambers (Ecker Col 13:9-26, 38-47, Fig. 7); FIG. 8 is a 20 second waveform diagram depicting the respiration cycle pressure wave detected by the pressure wave transducer in relation to a series of PQRST complexes in the same dog experiment. The respiration cycle is much longer than the cardiac cycle. Pulmonary minute ventilation may be determined from the amplitude of the peaks of the respiratory cycle and the interval between peaks in a manner well known in the art (Ecker Col 13:48-55, Fig. 8), wherein the pressure waveform of Ecker Fig. 7 (cardiac cycle) is considered to define a hemodynamic curve, and wherein the pressure waveform of Ecker Fig. 8 is considered to define a pulmonary curve].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of Manicka to employ defining a hemodynamic curve corresponding to the pressure signal data in a first frequency band and a pulmonary curve corresponding to the pressure signal data in a second frequency band different from the first frequency band, and wherein determining the health-related parameter is further based on the hemodynamic curve and the pulmonary curve, so as to provide visual contextual information regarding hemodynamics and respiration during operation of the system.
However, Manicka in view of Ecker fails to explicitly disclose defining a mediastinal curve corresponding to the pressure signal data in a third frequency band different from the first frequency band and the second frequency band; and wherein the determined health-related parameter is further based on the mediastinal curve.
Ecker does disclose filtering out pressure signals caused by exterior environmental noise [For example, the piezoelectric transducers as described above are sensitive to heart sound or motion frequencies of interest as well as to footfalls when the patient is ambulatory, muscle artifacts or myopotentials associated with limb movements and exercise, and may be responsive to speech and exterior environmental noise. These may constitute "noise" that are first filtered out to the extent possible and then subtracted in differential amplifier 118 to derive the signal of interest (Ecker Col 12:55-63)] and further suggests identifying particular frequency ranges of interest in order to filter signals outside of the frequency range of interest [In either case, the frequency range of the bandpass filters for each such channel is selected for the signal to be derived. In sensing cardiac sounds and motion components of the pressure wave, the frequency range of interest is believed to be between about 0.5-7.0 Hz in the atrium and in the ventricle but may be a different range depending on the waveform characteristic to be measured (Ecker Col 13:9-15)].
Nasseri discloses assessments of the thymus and thymoma, wherein Nasseri notes that thymoma in the anterior mediastinum can be observed through pressure-induced symptoms [Thymomas represent 20% of all mediastinal neoplasms in adults; they are the most common anterior mediastinal primary neoplasm in adults but account for less than 5% of mediastinal tumors in children (33)… 20%–30% of patients have pressure-induced symptoms such as cough, chest pain, dyspnea, dysphagia, hoarseness, or superior vena cava syndrome (Nasseri p. 421)].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of Manicka in view of Ecker to employ defining a mediastinal curve corresponding to the pressure signal data in a third frequency band different from the first frequency band and the second frequency band; and wherein the determined health-related parameter is further based on the mediastinal curve, as thymoma are known to affect pressure in the anterior mediastinum and cause pressure-induced symptoms including cardiac conditions [Nasseri p. 421, wherein the possible presence of a thymoma may be considered to be a cardiac parameter, as a known symptom of a thymoma is superior vena cava syndrome], and as this modification would amount to mere application of a known technique to a known device (method, or product) ready for improvement to yield predictable results [identifying particular frequency ranges of interest in order to filter signals outside of the frequency range of interest] [MPEP § 2143(I)(D)].
Regarding claim 10, Manicka in view of Ecker and Nasseri teaches
The method of claim 9, further comprising:
amplifying and filtering the pressure signal data to separate the pressure signal data into the first frequency band, the second frequency band, and the third frequency band [See § 103 modification of claim 9 above; Ecker Col 12:52-55].
Regarding claim 11, Manicka in view of Ecker and Nasseri teaches
The method of claim 10, wherein the monitoring of the at least one health-related parameter over the period of time includes monitoring a change in each of the electrical signal data, the hemodynamic curve, the pulmonary curve, and the mediastinal curve [See § 103 modification of claim 1 above; Manicka ¶0207; Ecker Col 13:38-47, Fig. 7; Nasseri p. 421].
Regarding claim 14, Manicka in view of Ecker and Nasseri teaches
The method of claim 11, wherein the change in the at least one health-related parameter is indicative of at least one of a change in a central venous pressure, right atrial pressure, a pulmonary capillary wedge pressure, a tidal volume, a respiratory rate [See § 103 modification of claim 1 above; Manicka ¶0240; Ecker Col 13:48-55, Fig. 8], a stroke volume, a fluid load, or a mediastinal neoplasm [See § 103 modification of claim 1 above; Nasseri p. 421].
Regarding claim 15, Manicka in view of Ecker and Nasseri teaches
The method of claim 9, further comprising: executing at least one action in response to the heart failure status being indicative of worsening heart failure [Manicka ¶0232].
Regarding claim 16, Manicka in view of Ecker and Nasseri teaches
The method of claim 15, wherein the at least one action includes sending a signal representing at least one of a notification, a trigger to provide treatment [Manicka ¶0232], or an alarm.
Regarding claim 24, Manicka teaches
A method of using an implanted ambulatory system for health monitoring, the method comprising:
receiving electrical signal data from an electrical sensor disposed in an anterior mediastinum of a patient, the electrical sensor disposed outside of a heart of the patient and configured to detect electrical signals radiating from an external surface of the heart [electrode 172 (Manicka Figs. 5A-B); FIG. 5A is a side view of prong 106 of subcutaneous device 100. FIG. 5B is a top view of prong 106 of subcutaneous device 100. Prong 106 includes proximal end 160, distal end 162, base portion 164, spring portion 166, arm portion 168, contact portion 170, and electrode 172 (Manicka ¶0220); Controller 182 can receive electrical signals from sensing circuitry 180, analyze the electrical signals, and execute instructions stored in memory 184 to determine whether an arrhythmia is present in the heart rate of a patient (Manicka ¶0238)];
receiving pressure signal data from a pressure sensor disposed in the anterior mediastinum and outside of the heart, the pressure sensor configured to detect pressure signals in the anterior mediastinum [Controller 182 can also receive information from sensor(s) 190. Sensor(s) 190 can include any suitable sensor, including, but not limited to, temperature sensors, accelerometers, pressure sensors, proximity sensors, infrared sensors, optical sensors, and ultrasonic sensors. The information from sensor(s) 190 allows subcutaneous device 100 to sense physiological parameters of a patient. For example, the data from the sensors can be used to calculate heart rate, heart rhythm, respiration rate, respiration waveform, activity, movement, posture, oxygen saturation, photoplethysmogram (PPG), blood pressure, core body temperature, pulmonary edema, and pulmonary wetness (Manicka ¶0240)];
defining a change in a heart failure status of the patient over a period of time based on (i) the electrical signal data, and (ii) a change in the electrical signal data over the period of time [Controller 182 analyzes the electrical signals and executes instructions stored in memory 184 to determine if there is an arrhythmia in the patient's heart rate. If controller 182 determines that there is an arrhythmia, controller 182 will send instructions to therapy circuitry 186 to send electrical stimulation to the heart to regulate the heart rate of the patient (Manicka ¶0232)]; and
executing at least one action associated with the change in the heart failure status [Manicka ¶0232].
However, while Manicka discloses using a the pressure sensor to calculate heart rate and rhythm, as well as respiration rate and waveforms [Manicka ¶0240], Manicka fails to explicitly disclose amplifying and filtering the pressure signal data to define a hemodynamic curve corresponding to pressure signals in a first frequency band, a pulmonary curve corresponding to pressure signals in a second frequency band different from the first frequency band, and a mediastinal curve corresponding to pressure signal in a third frequency band different from the first frequency band and the second frequency band; wherein defining the change in the heart failure status of the patient over the period of time is further based on the hemodynamic curve, the pulmonary curve, and the mediastinal curve, and a change in at least one of the electrical signal data, the hemodynamic curve, the pulmonary curve, or the mediastinal curve over the period of time.
Ecker discloses a method for using an implanted ambulatory system for health monitoring, wherein the method comprises receiving electrical signal data from an electrical sensor disposed in an anterior mediastinum of a patient, the electrical sensor disposed outside of a heart of the patient and configured to detect electrical signals radiating from an external surface of the heart [an additional sense amplifier 124 is coupled to the lead feedthrough pins 80 and 82 for providing a electrical sense signal to the operating system in a manner well known in the art. In cardiac medical device applications, the electrical sense signal may be the electrogram of the patient's heart detected through the lead 18 (Ecker Col 12:45-51, Fig. 1); the lead distal end segment 16 is typically firmly attached to the heart 14 (and may in fact be alternatively attached to the epicardium) so that good electrical contact is maintained (Ecker Col 8:22-25), wherein being attached to the epicardium is considered to define being positioned in the anterior mediastinum, as the epicardium is understood to define a posterior border of the anterior mediastinum], receiving pressure signal data from a pressure sensor disposed in the anterior mediastinum and outside of the heart, the pressure sensor configured to detect a pressure signal in the anterior mediastinum [FIGS. 2 and 3 depict the lead connector module or assembly 20 coupled with a proximal connector end 40 of a lead 18 and the incorporation of a pressure wave transducer 32 and a reference transducer 34 (Ecker Col 8:52-55); In this first embodiment, the transducers 32 and 34 are each formed of a piezoelectric crystal of the type employed as an activity sensor in commercially available MEDTRONIC.RTM. THERA.RTM. DR IPGs for rate-responsive pacing in the DDDR mode and other modes… The resulting capacitive transducer provides an electrical output signal on the sensor lead wires that varies in amplitude in response to minute deflections of the piezoelectric crystal in response to the acoustically or mechanically conducted cardiac and respiratory pressure waves (Ecker Col 8:62-66, Col 9:9-14), see Examiner’s analysis above regarding positioning of the lead], and amplifying and filtering the pressure signal data to define a hemodynamic curve corresponding to the pressure signal data in a first frequency band and a pulmonary curve corresponding to the pressure signal data in a second frequency band different from the first frequency band, wherein Ecker further discloses determining a health-related parameter based on changes in the electrical signal data, the hemodynamic curve and the pulmonary curve [The pressure wave and reference signals are first amplified in amplifiers 110 and 112, respectively. The amplified pressure wave and reference signals are then bandpass filtered in bandpass filters 114 and 116, respectively (Ecker Col 12:34-38); The bandpass filter characteristics are tailored to pass the range of amplified signal frequencies of interest and to reject frequency components in the signals that are outside that range (Ecker Col 12:52-55); In either case, the frequency range of the bandpass filters for each such channel is selected for the signal to be derived. In sensing cardiac sounds and motion components of the pressure wave, the frequency range of interest is believed to be between about 0.5-7.0 Hz in the atrium and in the ventricle but may be a different range depending on the waveform characteristic to be measured. To sense patient activity related to ambulatory movement, i.e., footfalls the frequency range of interest representing footfalls is between about 0.5-15 Hz. To detect the amplitude and frequency of the respiratory cycle, the frequency range of interest is about 0.05-0.8 Hz. FIG. 7 is a two second waveform diagram depicting the cardiac cycle pressure wave detected by the pressure wave transducer in relation to the preceding intrinsic PQRST complex as detected from the pressure wave transmitted through a conventional pacing lead implanted in the ventricle of a healthy dog… The peaks of FIG. 7 may represent the pressure waveform of the ventricles in forcefully contracting and expelling blood and then relaxing and filling with blood that takes place in closer timed relation to the PQRST complex. A clear correlation between the double signal peaks of the pressure wave and the PQRST complex is observed. This correlation is effective with either an intrinsic depolarization or an evoked depolarization of the heart and in both the atrial and ventricular heart chambers (Ecker Col 13:9-26, 38-47, Fig. 7); FIG. 8 is a 20 second waveform diagram depicting the respiration cycle pressure wave detected by the pressure wave transducer in relation to a series of PQRST complexes in the same dog experiment. The respiration cycle is much longer than the cardiac cycle. Pulmonary minute ventilation may be determined from the amplitude of the peaks of the respiratory cycle and the interval between peaks in a manner well known in the art (Ecker Col 13:48-55, Fig. 8), wherein the pressure waveform of Ecker Fig. 7 (cardiac cycle) is considered to define a hemodynamic curve, and wherein the pressure waveform of Ecker Fig. 8 is considered to define a pulmonary curve].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of Manicka to employ amplifying and filtering the pressure signal data to define a hemodynamic curve corresponding to pressure signals in a first frequency band and a pulmonary curve corresponding to pressure signals in a second frequency band different from the first frequency band; wherein defining the change in the heart failure status of the patient over the period of time is further based on the hemodynamic curve and the pulmonary curve, and a change in at least one of the electrical signal data, the hemodynamic curve, and the pulmonary curve over the period of time, so as to provide visual contextual information regarding hemodynamics and respiration.
However, Manicka in view of Ecker fails to explicitly disclose defining a mediastinal curve corresponding to pressure signal in a third frequency band different from the first frequency band and the second frequency band; and wherein defining the change in the heart failure status of the patient over the period of time is further based on the mediastinal curve, and a change in at least one of the electrical signal data, the hemodynamic curve, the pulmonary curve, or the mediastinal curve over the period of time.
Ecker does disclose filtering out pressure signals caused by exterior environmental noise [For example, the piezoelectric transducers as described above are sensitive to heart sound or motion frequencies of interest as well as to footfalls when the patient is ambulatory, muscle artifacts or myopotentials associated with limb movements and exercise, and may be responsive to speech and exterior environmental noise. These may constitute "noise" that are first filtered out to the extent possible and then subtracted in differential amplifier 118 to derive the signal of interest (Ecker Col 12:55-63)] and further suggests identifying particular frequency ranges of interest in order to filter signals outside of the frequency range of interest [In either case, the frequency range of the bandpass filters for each such channel is selected for the signal to be derived. In sensing cardiac sounds and motion components of the pressure wave, the frequency range of interest is believed to be between about 0.5-7.0 Hz in the atrium and in the ventricle but may be a different range depending on the waveform characteristic to be measured (Ecker Col 13:9-15)].
Nasseri discloses assessments of the thymus and thymoma, wherein Nasseri notes that thymoma in the anterior mediastinum can be observed through pressure-induced symptoms [Thymomas represent 20% of all mediastinal neoplasms in adults; they are the most common anterior mediastinal primary neoplasm in adults but account for less than 5% of mediastinal tumors in children (33)… 20%–30% of patients have pressure-induced symptoms such as cough, chest pain, dyspnea, dysphagia, hoarseness, or superior vena cava syndrome (Nasseri p. 421)].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of Manicka in view of Ecker to employ defining a mediastinal curve corresponding to pressure signal in a third frequency band different from the first frequency band and the second frequency band; and wherein defining the change in the heart failure status of the patient over the period of time is further based on the mediastinal curve, and a change in at least one of the electrical signal data, the hemodynamic curve, the pulmonary curve, or the mediastinal curve over the period of time, as thymoma are known to affect pressure in the anterior mediastinum and cause pressure-induced symptoms including cardiac conditions [Nasseri p. 421, wherein the possible presence of a thymoma may be considered to be a cardiac parameter, as a known symptom of a thymoma is superior vena cava syndrome], and as this modification would amount to mere application of a known technique to a known device (method, or product) ready for improvement to yield predictable results [identifying particular frequency ranges of interest in order to filter signals outside of the frequency range of interest] [MPEP § 2143(I)(D)].
Regarding claim 25, Manicka in view of Ecker and Nasseri teaches
The method of claim 24, wherein the at least one action includes sending a signal representing at least one a notification, a trigger to provide treatment [Manicka ¶0232], or an alarm.
Regarding claim 29, Manicka in view of Ecker and Nasseri teaches
The method of claim 24, wherein the change in at least one of the electrical signal data, the hemodynamic curve, the pulmonary curve, or the mediastinal curve over the period of time is associated with at least one of a change in a central venous pressure, right atrial pressure, a pulmonary capillary wedge pressure, a tidal volume, a respiratory rate [See § 103 modification of claim 1 above; Manicka ¶0240; Ecker Col 13:48-55, Fig. 8], a stroke volume, a fluid load, or a mediastinal neoplasm [See § 103 modification of claim 1 above; Nasseri p. 421].
Claim(s) 26 is/are rejected under 35 U.S.C. 103 as being unpatentable over Manicka in view of Ecker and Nasseri, as applied to claim 24 above, in further view of Pramodsingh (US-20200037888-A1, previously presented).
Regarding claim 26, Manicka in view of Ecker and Nasseri teaches
The method of claim 24.
However, Manicka in view of Ecker and Nasseri as presently modified fails to explicitly disclose further comprising: executing a machine learning model to correlate the electrical signal data, the hemodynamic curve, the pulmonary curve, and the mediastinal curve.
Pramodsingh discloses systems for ambulatory health monitoring using implanted devices, wherein Pramodsingh discloses the use of machine learning algorithms to correlate vasoactivity detection based on sensor measurements [Computationally intensive algorithms, such as machine-learning algorithms, may be implemented in the remote device 124 to process the data retrospectively to confirm, reject, or modify the vasoactivity detection provided by the AMD 110 (Pramodsingh ¶0049)].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of Manicka in view of Ecker and Nasseri to employ executing a machine learning model to correlate the electrical signal data, the hemodynamic curve, the pulmonary curve, and the mediastinal curve, in order to confirm or deny measurements indicative of cardiac parameters and conclusions drawn therefrom, and as this modification would amount to mere application of a known technique to a known device (method, or product) ready for improvement to yield predictable results [use of machine learning for data correlation] [MPEP § 2143(I)(D)].
Response to Arguments
Applicant’s arguments, see Applicant’s Remarks p. 10, filed 28 April 2026, with respect to the previously presented claim objections have been fully considered and are persuasive. The claim objections have been withdrawn.
Applicant’s arguments, see Applicant’s Remarks p. 10, with respect to the previously presented claim objections have been fully considered and are persuasive. The objections to claims 1, 7-9, 14-17, 19, 24, and 29 been withdrawn.
Applicant's arguments, see Applicant’s Remarks p. 11-14, with respect to the previously applied rejections under § 101 have been fully considered but they are not entirely persuasive.
The Examiner notes that the Applicant’s arguments with respect to claim 1 and those dependent therefrom are considered persuasive. However, the Applicant’s arguments are not considered persuasive with respect to claims 9 and 24 as outlined below.
The Applicant asserts that the specification “provides sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement in the functioning of a computer, or an improvement to other technology or a technical field” [Applicant’s Specification ¶¶0003-0007, 0034], wherein the Applicant further notes that amended independent claims 9 and 24 recite “the components or steps of the invention that provide the improvement described in the specification” as required by MPEP § 2106.04(d)(1), such that the claims are directed to patent eligible subject matter for at least the reason that the claims recite an improvement to the technical field of health monitoring and/or detecting cardiac function, and integrate the judicial exception into a practical application at Step 2A Prong 2. The claimed invention is not considered to be patent eligible under 35 U.S.C. 101, as while the Applicant asserts that the claimed invention is for improving “other technology or technical field”, the improvement is recited within limitations that have been identified as being abstract ideas implemented on a generic computer with additional elements that are considered to be well-understood, routine, and conventional. The “improvements” are not considered to be additional elements, as the processor functions/steps to receive signal data, define a hemodynamic, pulmonary, and mediastinal curve, determine and monitor at least one health-related parameter, and generate a heart failure status, are identified as being abstract ideas. As such, under MPEP 2106.05(a), "an improvement in the abstract idea itself (e.g. a recited fundamental economic concept) is not an improvement in technology". Specifically, the "improvements" analysis in Step 2A determines whether the claim pertains to an improvement to the functioning of a computer or to another technology without reference to what is well-understood, routine, conventional activity [MPEP § 2106.04(d)(1)]. It is important to note, the judicial exception alone cannot provide the improvement. The improvement can be provided by one or more additional elements. See the discussion of Diamond v. Diehr, 450 U.S. 175, 187 and 191-92, 209 USPQ 1, 10 (1981)) in subsection II, below. In addition, the improvement can be provided by the additional element(s) in combination with the recited judicial exception [MPEP § 2106.05(a)]. It is important to note that in order for a method claim to improve computer functionality, the broadest reasonable interpretation of the claim must be limited to computer implementation. That is, a claim whose entire scope can be performed mentally, cannot be said to improve computer technology. Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 120 USPQ2d 1473 (Fed. Cir. 2016) (a method of translating a logic circuit into a hardware component description of a logic circuit was found to be ineligible because the method did not employ a computer and a skilled artisan could perform all the steps mentally) [MPEP § 2106.05(a)(I)]. As such, the claims do not recite additional elements that may integrate the abstract ideas into a practical application of the abstract ideas, and thus the claimed invention is not considered to improve other technology or technical field.
The Applicant further asserts that the pending claims are also patent eligible under Step 2B, as the independent claims, as amended, recite sensors implanted in the anterior mediastinum and use of signals from those sensors to “define a hemodynamic curve… a pulmonary curve… and a mediastinal curve…”, which the Applicant notes is/are part of the improvement made to the technical field and therefore amount to more than just mere generic computer elements performing data gathering for determining a result. However, as noted above, the processor function/step to “define a hemodynamic curve… a pulmonary curve… and a mediastinal curve…” itself is not considered to be an improvement to computer technology or a technical field, as the identified processor function/step is considered to be directed towards an abstract idea.
The Applicant also cites the December Memorandum with respect to dismissing additional elements as mere “generic computer components” without considering whether such elements confer a technological improvement to a technical problem and the August Memorandum regarding a “close call” as to whether a claim is eligible. In light of the December 5, 2025 memo, the Examiner notes that revised MPEP § 2106.04(d)(1) recites “In short, first the specification should be evaluated to determine if the disclosure provides sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement in the functioning of a computer, or an improvement to other technology or a technical field… Conversely, if the specification explicitly sets forth an improvement but only in a conclusory manner (i.e., a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art), the examiner should not determine that the claim improves technology or a technical field. Second, if the specification sets forth an improvement in technology or a technical field, the claim must be evaluated to ensure that the claim itself reflects the disclosed improvement… See, e.g., Ex Parte Desjardins, Appeal No. 2024-000567 (PTAB September 26, 2025, Appeals Review Panel Decision) (precedential), in which the specification identified the improvement to machine learning technology by explaining how the machine learning model is trained to learn new tasks while protecting knowledge about 2 previous tasks to overcome the problem of “catastrophic forgetting,” and that the claims reflected the improvement identified in the specification. Indeed, enumerated improvements identified in the Desjardins specification included disclosures of the effective learning of new tasks in succession in connection with specifically protecting knowledge concerning previously accomplished tasks; allowing the system to reduce use of storage capacity; and the enablement of reduced complexity in the system. Such improvements were tantamount to how the machine learning model itself would function in operation and therefore not subsumed in the identified mathematical calculation.” As such, the Examiner notes that the Applicant’s arguments related to the Applicant’s noted improvements with respect to claims 9, 24, and those dependent therefrom [“In some implementations, inputs from the pressure sensor (and/or any other sensor) can be used and/or correlated with inputs of the ECG sensor to detect and/or determine a cardiac status and/or the occurrence of health events, such as arrhythmia, tachycardia, bradycardia, specific pressure measurements associated with hemodynamics, respiratory signals, and/or the like. The cardiac status determined using the methods described herein can be more specific than determining cardiac status using cardiac electrical signal measurements alone, hemodynamic status measurements alone, and/or other cardiac characteristics individually. Using a combination of cardiac signal measurements such as cardiac electrical signal measurements, cardiac mechanical signal measurements (e.g., hemodynamic rate, status, and/or output measurements), and/or other bio-signal measurements (e.g., pressure changes in the substernal space) can increase sensitivity and specificity, thereby reducing false results (false positives and false negatives). Additionally, detecting, sensing, and/or determining hemodynamic status can further confirm arrythmias, ventricular fibrillation, atrial fibrillation, ventricular tachycardias, heart failure status, COPD status, and/or other cardiac states. This results in specificity in diagnostic decisions that is more beneficial to patients and supported by clinical evidence” (Applicant’s Specification ¶0034)] are not considered to be directed towards the functioning of a computer or technology and are considered conclusory, as the Applicant fails to provide necessary details as to how the alleged improvement improves the functioning of a computer or technology. In light of the August 4, 2025 memo, the Examiner has analyzed claims 9 and 24 at Step 2A Prong 1 to determine whether the claim sets for or describes an abstract idea, wherein the Examiner notes that claim 1 is considered to recite several limitations [the entirety of claim 1 is considered to recite limitations directed towards abstract ideas with the exception of the limitations directed towards the electrical sensor, pressure sensor, and sensing device; see Step 2A Prong 1 analysis above], wherein the Examiner notes that the recited abstract ideas may be performed in the mind or by hand with the assistance of pen and paper and alternatively or additionally, describe the concept of using implicit mathematical formula(s) to derive a conclusion based on input of data. Next, at Step 2A Prong 2, the additional elements identified [electrical sensor, pressure sensor, sensing device] are analyzed to assess whether the additional elements use or interact with the recited exception to integrate the judicial exception into a practical application, wherein the Examiner notes that the identified additional elements in light of the judicial exception fail to interact and impact each other in such a way to integrate the judicial exception into a practical application, as the claim fails to reflect an improvement to the functioning of a computer or to another technology or technical field, as the alleged improvement to “define a hemodynamic curve… a pulmonary curve… and a mediastinal curve…” is considered to be recited within limitations identified as being directed towards abstract ideas implemented on a generic computer [see improvements analysis above]; and the additional elements fail to amount to more than a recitation of “apply it” (or equivalent) or mere instructions to implement the judicial exception on a computer merely as a tool to perform the limitations directed towards steps that may be performed in the mind or by hand with the assistance of pen and paper and using implicit mathematical formula(s) to derive a conclusion based on input of data, wherein a display recited at a high level of generality modified to display output data. Finally, at Step 2B, the Examiner notes the recitation of a processor and functionality therein at a high level of generality and the combination of an electrical sensor, pressure sensor, and sensing device as claimed are considered well-understood, routine, and conventional, such that the claim as a whole fails to amount to significantly more than the judicial exception.
The Applicant additionally notes that an “inventive concept may be found in the non-conventional and non-generic arrangement of components that are individually well-known and conventional” [MPEP § 2106.05]. The Examiner agrees with respect to claim 1 and those dependent therefrom, as claim 1 is considered to positively recite each of the argued components of an electrical sensor, pressure sensor, and sensing device. However, the Examiner notes that claims 9, 24, and those dependent therefrom fail to positively recite such a non-conventional and non-generic arrangement of components.
Applicant’s arguments, see Applicant’s Remarks p. 14-17, with respect to the rejection(s) of claim(s) 1, 9, and 24 under § 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Manicka (US-20220161023-A1) in view of Ecker (US-5899927-A, previously presented) and Nasseri et al. (“Clinical and Radiologic Review of the Normal and Abnormal Thymus: Pearls and Pitfalls”, previously presented).
The Applicant asserts that Ecker, alone or in combination with Pramodsingh and/or Nasseri fails to teach, suggest, or render obvious the amended subject matter of claims 1, 9, and 24; wherein the Applicant particularly notes that Ecker and Pramodsingh alone or in combination fail to disclose an electrical sensor and a pressure sensor disposed in an anterior mediastinum of a patient and outside of a heart of the patient, and that Ecker, Pramodsingh, and Nasseri alone or in combination fail to teach a processor configured to “define a hemodynamic curve corresponding to the pressure signal data in a first frequency band, a pulmonary curve corresponding to the pressure signal data in a second frequency band different from the first frequency band, and a mediastinal curve corresponding to the pressure signal data in a third frequency band different from the first frequency band and the second frequency band”. However, the Examiner notes that Applicant’s arguments with respect to claim(s) 1, 9, and 24 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. Claims 1, 9, and 24 are presently rejected as being obvious over Manicka (US-20220161023-A1) in view of Ecker (US-5899927-A, previously presented) and Nasseri et al. (“Clinical and Radiologic Review of the Normal and Abnormal Thymus: Pearls and Pitfalls”, previously presented), wherein Manicka is considered to disclose an electrical sensor and a pressure sensor disposed in an anterior mediastinum of a patient and outside of a heart of the patient [Manicka ¶¶0220, 0240, Figs. 5A-B]; wherein the Examiner further notes that Ecker teaches disposing sensors on the epicardium of the heart [Ecker Col 8:22-25, wherein being attached to the epicardium is considered to define being positioned in the anterior mediastinum, as the epicardium is understood to define a posterior border of the anterior mediastinum]. Furthermore, the Examiner notes that Applicant’s argument that Ecker, Pramodsingh, and Nasseri alone or in combination fail to teach a processor configured to “define a hemodynamic curve corresponding to the pressure signal data in a first frequency band, a pulmonary curve corresponding to the pressure signal data in a second frequency band different from the first frequency band, and a mediastinal curve corresponding to the pressure signal data in a third frequency band different from the first frequency band and the second frequency band” fail to comply with 37 CFR 1.111(b) because they amount to a general allegation that the claims define a patentable invention without specifically pointing out how the language of the claims patentably distinguishes them from the references. The modification of Manicka in view of Ecker and Nasseri is considered to teach the argued limitation regarding defining the hemodynamic, pulmonary, and mediastinal curves [Ecker Col 12:34-38, 52-55; Ecker 13:9-26, 38-55, Figs. 7-8; Nasseri p. 421].
Applicant’s arguments, see Applicant’s Remarks p. 17-18, with respect to the previously applied rejections under Non-Statutory Double Patenting have been fully considered and are persuasive. The Non-Statutory Double Patenting Rejections of claims 1-3 and 9 have been withdrawn.
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.
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/SEVERO ANTONIO P LOPEZ/Examiner, Art Unit 3791
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