DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim 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.
Claim 33 recites the limitation "blanking durations" in lines 2 and 5. It is unclear in both the claims and the specification what qualifies as a blanking duration. Therefore, the claim is rendered indefinite.
Claim 34 recites the limitation "blanking durations" in line 2. It is unclear in both the claims and the specification what qualifies as a blanking duration. Therefore, the claim is rendered indefinite.
Claim 35 recites the limitation "blanking durations" in line 3. It is unclear in both the claims and the specification what qualifies as a blanking duration. Therefore, the claim is rendered indefinite.
Claim 46 recites the limitation "blanking durations" in lines 1 and 2. It is unclear in both the claims and the specification what qualifies as a blanking duration. Therefore, the claim is rendered indefinite.
Claim 47 recites the limitation "blanking durations" in lines 1 and 2. It is unclear in both the claims and the specification what qualifies as a blanking duration. Therefore, the claim is rendered indefinite.
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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 27-34, 36, 37, 39-44, and 46-47 are rejected under 35 U.S.C. 102(a)(1) and 102(a)(2) as being unpatentable by Thorp(AU 2022288632 A1).
Regarding claim 27, Thorp discloses a method for controlling delivery of a neurostimulation therapy, the method comprising: receiving an acceleration signal from an accelerometer, wherein the accelerometer is configured for implantation in a submandibular region or cervical region of a patient(Device 10A includes a sensor 12A and a control portion 14A electrically coupled to the sensor 12A. The sensor 12A is securable to a patient to provide a sensor signal indicative of respiration of the patient. In one example, sensor 12A includes an implantable accelerometer to sense changes in acceleration indicative of respiration of the patient. The control portion 14A may extract features from the sensor signal to determine each respiratory phase of the patient.[0046]. ] As further shown in FIG. 15, device 611 comprises a lead 617 including a lead body 618 for chronic subcutaneous implantation (e.g., via tunneling) and extends to a position adjacent a nerve, such as a hypoglossal nerve 605, an ansa cervicalis-related nerve (as one example of nerve 606) and/or phrenic nerve (as one example of nerve 606). The lead 617 may comprise a stimulation electrode to engage the nerve (e.g., 605, 606) for stimulating the nerve to treat a physiologic condition, such as sleep disordered breathing like obstructive sleep apnea, central sleep apnea, multiple-type sleep apneas, etc.[0181]); determining a moving average of the acceleration signal over a first duration; determining a moving standard deviation based on the moving average; determining a first specified threshold based on the moving standard deviation; identifying respiration phase transitions based on a relationship between the first specified threshold and the acceleration signal; determining a respiration rate based on the identified respiration phase transitions; determining a therapy withholding duration based on the respiration rate; and providing neurostimulation therapy in coordination with an onset of an inspiration phase of a respiratory cycle of the patient, wherein the onset of the inspiration phase follows a first respiration phase transition of the identified respiration phase transitions by the therapy withholding duration(In some examples in which the sensor signal enables determining at least respiratory phase information, the closed loop parameter may be implemented to initiate, maintain, pause, adjust, and/or terminate stimulation therapy based on (at least) the determined respiratory phase information. In some examples, the stimulation is started prior to an onset of the inspiratory phase and the stimulation is stopped exactly at the end of the inspiratory phase or stopped just after the end of the inspiratory phase[0073]. For example, the quality assessment block 780 may calculate the total variance V: where Ax is the average of the Ax Ay is the average of the Ay and Az is the average of the Az.sub.t. If V falls below some threshold, then the signals are considered to be adequate. The threshold may be a parameter that is programmed into the device, or the threshold may be determined adaptively from a patient’s signals[0234]. In some examples, more than two previous midpoints may be used, such as 4, 6, 8, etc. In other examples, many (e.g., 11 or more) previous midpoints may be used to determine the median, and deviation from a multiple N of two previous midpoints corresponding to N complete respiratory cycles is acceptable (i.e. , an odd number of half cycles may be used)[0137]. The DC component of the acceleration signal may be determined using a low-pass filter (e.g., MR, FIR, other low-pass type), a moving average (e.g., mean, median, other average type), or another suitable process. The AC component of the acceleration signal may be determined using a high-pass filter (e.g., MR, FIR, other high-pass type), by subtracting the moving average from the signal average (mean, median, other average type), or another suitable process.[0102]).
Regarding claim 28, Thorp discloses the method of claim 27, wherein the first specified threshold is based on a product of the moving standard deviation and a specified sensitivity scalar(In other examples, many (e.g., 11 or more) previous midpoints may be used to determine the median, and deviation from a multiple N of two previous midpoints corresponding to N complete respiratory cycles is acceptable (i.e. , an odd number of half cycles may be used)[0137]. As shown via parameter 854 at 850 in FIG. 16C, in some examples a sensitivity factor may be applied by a user or clinician to adjust thresholds used in performing feature extraction of the inspiratory phase 752 (e.g., inhalation sensitivity), of the expiratory active phase 754 (e.g., exhalation sensitivity), and/or of the expiratory pause phase 756 (e.g., exhalation sensitivity)[0222]).
Regarding claim 29, Thorp discloses the method of claim 27, wherein identifying the respiration phase transitions includes identifying respective times when a value of the acceleration signal meets or exceeds the first specified threshold(In yet other examples, the feature of relative peak-to- trough timing and/or peak-to-trough slope may be used to identify each inspiratory phase and/or each expiratory phase since the inspiratory phase is typically shorter than the expiratory phase, such that relative phase may be determined. In yet other examples, the features of relative slope of the sensor signal(s) between peak and trough versus between trough and peak may be used to identify each inspiratory phase and/or each expiratory phase since the slope of the expiratory phase (e.g., 144B of FIG. 4) is typically smaller than the slope of the inspiratory phase (e.g., 144A of FIG. 4).In yet other examples, the feature of a non-midpoint threshold crossing (e.g., 149 of FIGS. 5C and 5D) may be used to identify each inspiratory phase and/or each expiratory phase since the time between the non-midpoint threshold crossing of an expiratory phase followed by the non-midpoint threshold crossing of an inspiratory phase is typically longer than the time between the non-midpoint threshold crossing of an inspiratory phase followed by the non-midpoint threshold crossing of an expiratory phase (e.g., due to an expiratory pause of each expiratory phase)[0053]).
Regarding claim 30, Thorp discloses the method of claim 29, wherein identifying the respiration phase transitions includes identifying respective times corresponding to an onset of exhalation(In other examples, the feature of curvature of peak versus trough may be used to identify each inspiratory phase and/or each expiratory phase since the peak at an inspiratory phase to expiratory phase transition (e.g., 148 of FIG. 4) will typically have a sharper peak than the peak at an expiratory phase to inspiratory phase transition (e.g., 146 of FIG. 4)[0053]).
Regarding claim 31, Thorp discloses the method of claim 27, comprising: monitoring the respiration rate over time; and in response to a detected change in the respiration rate, changing the therapy withholding duration(In some examples in which the sensor signal enables determining at least respiratory phase information, the closed loop parameter may be implemented to initiate, maintain, pause, adjust, and/or terminate stimulation therapy based on (at least) the determined respiratory phase information. In some examples, the stimulation is started prior to an onset of the inspiratory phase and the stimulation is stopped exactly at the end of the inspiratory phase or stopped just after the end of the inspiratory phase[0073]).
Regarding claim 32, Thorp discloses the method of claim 27, wherein identifying the respiration phase transitions includes changing the first specified threshold to increase a likelihood that a value of the acceleration signal meets or exceeds the first specified threshold(In yet other examples, the feature of a non-midpoint threshold crossing (e.g., 149 of FIGS. 5C and 5D) may be used to identify each inspiratory phase and/or each expiratory phase since the time between the non-midpoint threshold crossing of an expiratory phase followed by the non-midpoint threshold crossing of an inspiratory phase is typically longer than the time between the non-midpoint threshold crossing of an inspiratory phase followed by the non-midpoint threshold crossing of an expiratory phase (e.g., due to an expiratory pause of each expiratory phase)[0053]).
Regarding claim 33, Thorp discloses the method of claim 27, wherein determining the moving average of the acceleration signal includes identifying one or more blanking durations corresponding to one or more portions of the acceleration signal over the first duration, and determining the moving average without using the one or more portions of the acceleration signal that correspond to the one or more blanking durations(The DC component of the acceleration signal may be determined using a low-pass filter (e.g., MR, FIR, other low-pass type), a moving average (e.g., mean, median, other average type), or another suitable process. The AC component of the acceleration signal may be determined using a high-pass filter (e.g., MR, FIR, other high-pass type), by subtracting the moving average from the signal average (mean, median, other average type), or another suitable process. [0102]. At least some example methods may use such identification of feature- based phase differences to determine a respiratory phase, a respiratory rate, and durations of inspiration/expiration, among other useful respiratory parameters, therapy parameters, etc.[0056]).
Regarding claim 34, Thorp discloses the method of claim 33, comprising: determining likely values of the acceleration signal for the one or more blanking durations; and wherein determining the moving average of the acceleration signal includes using the determined likely values(The respiratory information relates to breathing frequency and phase, which can be used to predict the time of the next start of inspiration, when simulation may be applied. This may combine short-term predictions, e.g., based on the shape of bit) over a short time window, and long-term predictions, e.g., based on the average frequency and phase of b(t) over the last few breaths. The short-term predictions and the long-term predictions may be combined[0246]).
Regarding claim 36, Thorp discloses a system comprising: a first housing configured for implantation in a submandibular region or cervical region of a patient; a first electrode lead coupled to the first housing and configured to be disposed in the submandibular region, wherein at least one electrode on the first electrode lead is configured to be disposed at or near a cranial nerve of the patient to provide a first neurostimulation therapy that is configured to treat a sleep disorder or breathing disorder of the patient; an accelerometer configured to provide an acceleration signal that includes information about a respiration cycle of the patient(FIG. 13 is a diagram 400 including an isometric view schematically representing an implantable device 402 comprising an accelerometer-based sensor 304, which may comprise at least some of substantially the same features and attributes as the sensors, sensing elements, and related example methods as previously described in association with FIGS. 1A-12. It will be understood that the sensor (and sensing elements) described in FIGS. 1A-12 may be implemented as being on or within device 402. In some examples, sensor 304 is enclosed within a sealed housing (e.g., can) of the device 402. However, the sensor 304 may be external to the housing 405 of device 402, whether located on the housing or extending from the housing 405 on a lead[0168]); and a processor circuit configured to: receive the acceleration signal; determine a moving average of the acceleration signal over a first duration; determine a moving standard deviation based on the moving average; determine a first specified threshold based on the moving standard deviation; identify respiration phase transitions based on a relationship between the first specified threshold and the acceleration signal; determine a respiration rate based on the identified respiration phase transitions; determine a therapy withholding duration based on the respiration rate; and provide a control signal to a signal generator circuit to provide the first neurostimulation therapy in coordination with an onset of an inspiration phase of a respiratory cycle of the patient, wherein the onset of the inspiration phase follows a first respiration phase transition, of the identified respiration phase transitions, by the therapy withholding duration(Device 10A includes a sensor 12A and a control portion 14A electrically coupled to the sensor 12A. The sensor 12A is securable to a patient to provide a sensor signal indicative of respiration of the patient. In one example, sensor 12A includes an implantable accelerometer to sense changes in acceleration indicative of respiration of the patient. The control portion 14A may extract features from the sensor signal to determine each respiratory phase of the patient[0046]. As further shown in FIG. 15, device 611 comprises a lead 617 including a lead body 618 for chronic subcutaneous implantation (e.g., via tunneling) and extends to a position adjacent a nerve, such as a hypoglossal nerve 605, an ansa cervicalis-related nerve (as one example of nerve 606) and/or phrenic nerve (as one example of nerve 606). The lead 617 may comprise a stimulation electrode to engage the nerve (e.g., 605, 606) for stimulating the nerve to treat a physiologic condition, such as sleep disordered breathing like obstructive sleep apnea, central sleep apnea, multiple-type sleep apneas, etc. [0181]. In some examples in which the sensor signal enables determining at least respiratory phase information, the closed loop parameter may be implemented to initiate, maintain, pause, adjust, and/or terminate stimulation therapy based on (at least) the determined respiratory phase information. In some examples, the stimulation is started prior to an onset of the inspiratory phase and the stimulation is stopped exactly at the end of the inspiratory phase or stopped just after the end of the inspiratory phase[0073]. For example, the quality assessment block 780 may calculate the total variance V: where Ax is the average of the Ax Ay is the average of the Ay and Az is the average of the Az.sub.t. If V falls below some threshold, then the signals are considered to be adequate. The threshold may be a parameter that is programmed into the device, or the threshold may be determined adaptively from a patient’s signals[0234]. In some examples, more than two previous midpoints may be used, such as 4, 6, 8, etc. In other examples, many (e.g., 11 or more) previous midpoints may be used to determine the median, and deviation from a multiple N of two previous midpoints corresponding to N complete respiratory cycles is acceptable (i.e. , an odd number of half cycles may be used)[0137]. The DC component of the acceleration signal may be determined using a low-pass filter (e.g., MR, FIR, other low-pass type), a moving average (e.g., mean, median, other average type), or another suitable process. The AC component of the acceleration signal may be determined using a high-pass filter (e.g., MR, FIR, other high-pass type), by subtracting the moving average from the signal average (mean, median, other average type), or another suitable process[0102]).
Regarding claim 37, Thorp discloses the system of claim 36, wherein the processor circuit comprises a processor in communication with memory, the memory configured to store instructions that are executable by the processor and cause the processor circuit to perform one or more functions(For purposes of this application, in reference to the controller 902, the term “processor” shall mean a presently developed or future developed processor (or processing resources) that executes machine readable instructions contained in a memory. In some examples, execution of the machine readable instructions, such as those provided via memory 910 of control portion 900 cause the processor to perform the above-identified actions, such as operating controller 902 to implement the sensing, monitoring, determining respiration information, stimulation, treatment, etc. as generally described in (or consistent with) at least some examples of the present disclosure[0256]).
Regarding claim 39, Thorp discloses the system of claim 36, wherein the processor circuit is further configured to determine a number of the identified respiration phase transitions exceeds a respiration phase transition threshold within a specified time window, and, in response to determining the number of the identified respiration phase transitions exceeds the respiration phase transition threshold, provide a control signal to the signal generator circuit to provide neurostimulation therapy synchronous with respiration(In some examples, the closed loop parameter may be implemented using the sensed information to control the particular timing of the stimulation according to respiratory information, in which the stimulation pulses are triggered by or synchronized with specific portions (e.g., inspiratory phase) of the patient’s respiratory cycle(s). In some such examples and as previously described, this respiratory information may be determined via the sensor 12A or 12B[0072]. As shown via parameter 852 at 850 in FIG. 16C, in some examples a threshold factor may be applied by a user or clinician to adjust thresholds used in performing feature extraction of the inspiratory phase 752 (e.g., inhalation threshold), of the expiratory active phase 754 (e.g., exhalation threshold), and/or of the expiratory pause phase 756 (e.g., exhalation threshold). As shown via parameter 854 at 850 in FIG. 16C, in some examples a sensitivity factor may be applied by a user or clinician to adjust thresholds used in performing feature extraction of the inspiratory phase 752 (e.g., inhalation sensitivity), of the expiratory active phase 754 (e.g., exhalation sensitivity), and/or of the expiratory pause phase 756 (e.g., exhalation sensitivity)[0223] In some examples, in determining the respiratory phase information (790) example method 700 also may comprise predicting an inspiratory phase (e.g., 752 in FIG. 16A), as shown at 860 in FIG. 16D. The prediction of the inspiratory phase may be used to increase a likelihood of implementing actions (e.g., start of stimulation, etc.) which are to be synchronized with a start of the inspiratory phase 752[0222]).
Regarding claim 40, Thorp discloses the system of claim 36, wherein the processor circuit is further configured to: monitor the respiration rate over time; and in response to detecting a change in the respiration rate, changing the therapy withholding duration(FIG. 1 B is a block diagram illustrating one example of a device 10B for detecting respiration and applying stimulation based on the detected respiration. Device 10B includes a sensor 12B and a control portion 14B. Sensor 12B may comprise one example implementation of sensor 12A (FIG. 1A) and/or control portion 14B may comprise one example implementation of control portion 14A (FIG. 1A). In this example, sensor 12B senses changes in acceleration indicative of respiration of the patient as indicated at 16[0049]).
Regarding claim 41, Thorp discloses the system of claim 36, wherein the first electrode lead is configured to be disposed at or near a first branch of a hypoglossal nerve of the patient(As further shown in FIG. 15, device 611 comprises a lead 617 including a lead body 618 for chronic subcutaneous implantation (e.g., via tunneling) and extends to a position adjacent a nerve, such as a hypoglossal nerve 605, an ansa cervicalis-related nerve (as one example of nerve 606) and/or phrenic nerve (as one example of nerve 606)[0181]).
Regarding claim 42, Thorp discloses the method of claim 27, wherein identifying respiration phase transitions comprises identifying a first set of respiration phase transitions, and further comprising: determining a second moving average of the acceleration signal over a second duration; determining a second moving standard deviation based on the second moving average; determining a second specified threshold based on the second moving standard deviation; identifying a second set of respiration phase transitions based on a relationship between the second specified threshold and the acceleration signal, the second set of respiration phase transitions being subsequent to the first set of respiration phase transitions; determining an updated respiration rate based on the identified second set of respiration phase transitions; determining an updated therapy withholding duration based on the updated respiration rate; and providing updated neurostimulation therapy in coordination with the onset of the inspiration phase of a subsequent respiratory cycle of the patient, wherein the onset of the inspiration phase follows a first respiration phase transition of the identified second set of respiratory phase transitions by the updated therapy withholding duration(For example, the control portion 14B may apply the electrical stimulation starting relative to the predicted midpoint by a first predetermined interval (e.g., first time period) and ending after the predicted midpoint by a second predetermined interval (e.g., second time period). The first predetermined interval may be selected based on a preselected, or computed, relative position (e.g., 20% or 30%) within the mean or median of previous inspiratory phase durations plus optionally an absolute additional amount (e.g., 200 ms or 300 ms) to ensure the stimulation is started just prior to the inspiratory phase. The second predetermined interval may be selected based on a preselected, or computed, relative position within the mean or median of previous inspiratory phase durations plus optionally an absolute additional amount to ensure the stimulation is ended at or just after the inspiratory phase. The relative position may be responsive to optimize therapy based on detected sleep disordered breathing like obstructive sleep apnea, central sleep apnea, multiple-type sleep apneas, etc., and may be moved forwards or backwards from the relative position to optimize the efficacy of the stimulation[0070]. For example, the quality assessment block 780 may calculate the total variance V: where Ax is the average of the Ax Ay is the average of the Ay and Az is the average of the Az.sub.t. If V falls below some threshold, then the signals are considered to be adequate. The threshold may be a parameter that is programmed into the device, or the threshold may be determined adaptively from a patient’s signals[0234]).
Regarding claim 43, Thorp discloses the method of claim 27, wherein the therapy withholding duration comprises a specified percentage of the respiration rate(The device of claim 22, wherein the control portion is to apply the electrical stimulation starting an amount of time prior to the predicted midpoint computed as a percentage of a respiratory rate and ending after the predicted midpoint[claim 24]).
Regarding claim 44, Thorp discloses the method of claim 27, further comprising determining a number of the identified respiration phase transitions exceeds a respiration phase transition threshold within a specified time window, and, in response to determining the number of the identified respiration phase transitions exceeds the respiration phase transition threshold, providing neuromodulation therapy synchronous with respiration(The respiratory information relates to breathing frequency and phase, which can be used to predict the time of the next start of inspiration, when simulation may be applied. This may combine short-term predictions, e.g., based on the shape of bit) over a short time window, and long-term predictions, e.g., based on the average frequency and phase of b(t) over the last few breaths. The short-term predictions and the long-term predictions may be combined[0246]. The extracted features (e.g., midpoints) may be used by control portion 14A to control (e.g., synchronize, trigger, etc.) the delivery of therapy relative to the appropriate respiratory phase of the patient, for diagnostic storage and/or display, and/or for other purposes[0046]. In some examples, the identified respiration morphology comprises identifying (within the respiratory waveform morphology) a start of the inspiratory phase, i.e., onset of inspiration. In some examples, this start of the inspiratory phase also may at least partially correspond to an expiration-to-inspiration transition. In some examples, a method of identifying the start of the inspiratory phase within the identified respiratory waveform morphology further comprises performing the identification (of the start of the inspiratory phase) without identifying an end (e.g., offset) of the inspiratory phase, which may enhance the accuracy of identification (of the start of the inspiratory phase) in the presence of noise, in contrast to identification of more than one phase transition (e.g., inspiratory-to-expiratory or expiratory-to-inspiratory) per respiratory cycle where each transition is subject to mis-identification due to noise[0090]).
Regarding claim 46, Thorp discloses the method of claim 33, wherein identifying the one or more blanking durations comprises determining the one or more blanking durations based on an intensity or duration of the neurostimulation therapy(As further shown in FIG. 16A, from the determined respiratory phases (752, 754, 754), additional respiratory parameters 760 may be determined. For example, an (overall) expiratory phase may comprise a sum or combination of the expiratory active phase (754) and the expiratory pause phase (756). In addition, a respiratory period may be determined from a sum of duration of the inspiratory phase 752 and a duration of the (overall) expiratory phase, including both the active and pause phases 754, 756. Meanwhile, the respiratory rate (RR) may be computed as 1 /respiratory period. Additional parameters may comprise a computed l/E ratio, such as inspiratory phase duration (Ti in FIG. 4) divided by an expiratory phase duration (TEA plus TEP in FIG. 4)[0211]).
Regarding claim 47, Thorp discloses the method of claim 33, wherein identifying the one or more blanking durations comprises determining the one or more blanking durations based on the determined respiration rate(In some examples, the midpoint of a future inspiratory phase may be predicted based on one or more previous respiratory cycles and the respiratory rate of one or more previous respiratory cycles[0068]).
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.
Claim(s) 35 and 45 are rejected under 35 U.S.C. 103 as being unpatentable over Thorp in view of Shute(US 20190223839 A1).
Regarding claim 35, Thorp discloses the method of claim 33, but fails to disclose wherein determining the likely values of the acceleration signal includes using an interpolation function based on values of the acceleration signal outside of the one or more blanking durations.
However, Shute teaches “In embodiments, the HS component 240 may be configured to perform a data interpolation process on the acceleration data to generate standardized acceleration data. The interpolation may be configured to generate standardized acceleration data based on templates, internal characteristics of the acceleration data, known information, and/or the like[0101]”.
It would be obvious to one of ordinary skill in the art before the effective filing date to configure the respiration sensing of Thorp with the interpolation of the values of the acceleration measurements of Shute. Doing so would specify estimation method used to calculate values for the acceleration signal.
Regarding claim 45, Thorp discloses the method of claim 34, but fails to disclose wherein determining the likely values of the acceleration signal includes using one or more a forecasting model, a regression model, or a pattern-matching model.
However, Shute teaches “As the terms are used herein with respect to measurements (e.g., dimensions, characteristics, attributes, components, etc.), and ranges thereof, of tangible things (e.g., products, inventory, etc.) and/or intangible things (e.g., data, electronic representations of currency, accounts, information, portions of things (e.g., percentages, fractions), calculations, data models, dynamic system models, algorithms, parameters, etc.), “about” and “approximately” may be used, interchangeably, to refer to a measurement that includes the stated measurement and that also includes any measurements that are reasonably close to the stated measurement, but that may differ by a reasonably small amount such as will be understood, and readily ascertained, by individuals having ordinary skill in the relevant arts to be attributable to measurement error; differences in measurement and/or manufacturing equipment calibration; human error in reading and/or setting measurements; adjustments made to optimize performance and/or structural parameters in view of other measurements (e.g., measurements associated with other things); particular implementation scenarios; imprecise adjustment and/or manipulation of things, settings, and/or measurements by a person, a computing device, and/or a machine; system tolerances; control loops; machine-learning; foreseeable variations (e.g., statistically insignificant variations, chaotic variations, system and/or model instabilities, etc.); preferences; and/or the like[0046]”.
It would be obvious to one of ordinary skill in the art before the effective filing date to configure the respiration sensing of Thorp with the modeling of the values of the acceleration measurements of Shute. Doing so would specify models used with the acceleration values in order to generate specific data.
Claim(s) 38 is rejected under 35 U.S.C. 103 as being unpatentable over Thorp in view of Stahmann(EP 1670547 B1).
Regarding claim 38, Thorp discloses the system of claim 36, but fails to disclose further comprising an antenna configured to exchange power and/or data between the system and an external device.
However, Stahmann teaches “The communications circuitry 518 may allow the ITCS device 500 to communicate with an external programmer. In one configuration, the communications circuitry 518 and the programmer unit (not shown) use a wire loop antenna and a radio frequency telemetric link, as is known in the art, to receive and transmit signals and data between the programmer unit and communications circuitry 518(see attached translation, page 26, paragraph 4)”.
It would be obvious to one of ordinary skill in the art before the effective filing date to configure the respiration sensing of Thorp with the antenna and external communication of the monitoring system of Stahmann. Doing so would specify the external communications system mechanics used between the main implantable body and external device.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MARIA CATHERINE ANTHONY whose telephone number is (703)756-4514. The examiner can normally be reached 7:30 am - 4:30 pm, EST, M-F.
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/MARIA CATHERINE ANTHONY/Examiner, Art Unit 3796
/CARL H LAYNO/Supervisory Patent Examiner, Art Unit 3796
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