DETAILED ACTION
Election/Restrictions
Claims 19-41 are withdrawn from further consideration pursuant to 37 CFR 1.142(b) as being drawn to a nonelected Groups II-III, there being no allowable generic or linking claim. Election was made without traverse in the reply filed on November 17th, 2025.
Applicant’s election without traverse of Group I (Claims 1-18) in the reply filed on November 17th, 2025 is acknowledged.
Amendment Entered
In response to the amendment filed on November 17th, 2025, amended claims 1, 10, and 13 are entered. Claims 19-41 are withdrawn.
Claim Objections
Claims 1 and 7 are objected to because of the following informalities:
Claim 1 recites “from the at least a portion” in line 6, but should read “from the portion”
Claim 7 recites “the at least a portion” in line 2, but should read “the portion”
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 5 and 10-16 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 5 recites “at least one of” in line 2. Further in line 2, Claim 5 recites “and”. These two terms conflict one another. Examiner cannot definitively ascertain whether this is an alternative limitation or both limitations are required. The Examiner will interpret the claim as in the alternative.
Claim 10 recites “an estimated respiratory rate (RR)” in line 7. It is unclear as to whether this is referring to the previously introduced “respiration rate (RR)” from Claim 1, or a separate element. Clarification is requested.
Claim 13 recites “a respiratory rate (RR)” in line 5. It is unclear as to whether this is referring to the previously introduced “respiration rate (RR)” from Claim 1, or a separate element. Clarification is requested.
Claim 13 recites “a tidal volume (TV)” in line 6. It is unclear as to whether this is referring to the previously introduced “tidal volume (TV)” from Claim 1, or a separate element. Clarification is requested.
Claim 14 recites “a RR” in line 2. It is unclear as to whether this is referring to the previously introduced “respiration rate (RR)” from Claim 1, “respiratory rate (RR)” from Claim 13, or a separate element. Clarification is requested.
Claim 14 recites “a TV” in line 2. It is unclear as to whether this is referring to the previously introduced “tidal volume (TV)” from Claim 1, “tidal volume (TV)” from Claim 13, or a separate element. Clarification is requested.
Claim 15 recites “at least one of” in line 2. Further in line 2, Claim 15 recites “and”. These two terms conflict one another. Examiner cannot definitively ascertain whether this is an alternative limitation or both limitations are required. The Examiner will interpret the claim as in the alternative.
Claim 16 recites “at least one of” in line 2. Further in line 2, Claim 16 recites “and”. These two terms conflict one another. Examiner cannot definitively ascertain whether this is an alternative limitation or both limitations are required. The Examiner will interpret the claim as in the alternative.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-18 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Each of Claims 1-18 has been analyzed to determine whether it is directed to any judicial exceptions.
Step 1
Claims 1-18 recites a series of steps or acts for extracting respiratory parameters for a human subject. Thus, the claims are directed to a process, which is one of the statutory categories of invention.
Step 2A, Prong 1
Each of Claims 1-18 recites at least one step or instruction for extracting respiratory parameters for a human subject from a thoracic impedance (TI) measurement signal, which is grouped as a mental process under the 2019 PEG or a certain method of organizing human activity under the 2019 PEG. Accordingly, each of Claims 1-18 recites an abstract idea.
Specifically, Claim 1 recites:
performing a signal quality check on the TI measurement signal; and
executing at least one of an autocorrelation algorithm or a time-domain zero-crossing algorithm on at least a portion of the TI measurement signal to extract at least one respiratory parameter for the human subject from the at least a portion of the TI measurement signal, wherein the at least one respiratory parameter comprises at least one of respiration rate (RR) or tidal volume (TV).
The claimed steps of performing signal quality checks and extracting a respiratory parameter from signal data can be practically performed in the human mind using mental steps or basic critical thinking, which are types of activities that have been found by the courts to represent abstract ideas.
Further, dependent Claims 2-18 merely include limitations that either further define the abstract idea (and thus don’t make the abstract idea any less abstract) or amount to no more than generally linking the use of the abstract idea to a particular technological environment or field of use because they’re merely incidental or token additions to the claims that do not alter or affect how the process steps are performed.
Accordingly, as indicated above, each of the above-identified claims recites an abstract idea.
Step 2A, Prong 2
The above-identified abstract idea in each of independent Claim 1 (and its dependent Claims) is not integrated into a practical application under 2019 PEG because the additional elements (identified above in independent Claim 1), either alone or in combination, generally link the use of the above-identified abstract idea to a particular technological environment or field of use. More specifically, the claims fail to recite any additional elements, although a computer is implied, which would serve to execute the autocorrelation algorithm or time-domain zero-crossing algorithm. Therefore, there is no improvement to the functioning of a computer, or any other technology or technical field. Nor do these above-identified additional elements serve to apply the above-identified abstract idea with, or by use of, a particular machine, effect a transformation or apply or use the above-identified abstract idea in some other meaningful way beyond generally linking the use thereof to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception. Furthermore, the above-identified additional elements do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer. For at least these reasons, the abstract idea identified above in independent Claim 1 (and its respective dependent claims) is not integrated into a practical application under 2019 PEG.
Moreover, the above-identified abstract idea is not integrated into a practical application under 2019 PEG because the claimed method and system merely implements the above-identified abstract idea (e.g., mental process and certain method of organizing human activity) using rules (e.g., computer instructions) executed by a computer. In other words, these claims are merely directed to an abstract idea with additional generic computer elements which do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer. Additionally, Applicant’s specification does not include any discussion of how the claimed invention provides a technical improvement realized by these claims over the prior art or any explanation of a technical problem having an unconventional technical solution that is expressed in these claims. That is, like Affinity Labs of Tex. v. DirecTV, LLC, the specification fails to provide sufficient details regarding the manner in which the claimed invention accomplishes any technical improvement or solution. Thus, for these additional reasons, the abstract idea identified above in independent Claim 1 (and its dependent claims) is not integrated into a practical application under the 2019 PEG.
Accordingly, independent Claim 1 (and its dependent claims) are each directed to an abstract idea under 2019 PEG.
Step 2B
None of Claims 1-18 include additional elements that are sufficient to amount to significantly more than the abstract idea for at least the following reasons.
The claims fail to recite any additional elements, although a computer is implied, which would serve to execute the autocorrelation algorithm or time-domain zero-crossing algorithm. The above-identified additional elements are generically claimed computer components which enable the above-identified abstract idea(s) to be conducted by performing the basic functions of automating mental tasks. The courts have recognized such computer functions as well understood, routine, and conventional functions when claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity. See, Versata Dev. Group, Inc. v. SAP Am., Inc. , 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); and OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93.
Those in the relevant field of art would recognize the above-identified additional elements as being well-understood, routine, and conventional means for data-gathering and computing, as demonstrated by
Applicant’s specification (e.g. paragraphs [0025-0030]) which discloses that the processor(s) comprise generic computer components that are configured to perform the generic computer functions (e.g. performing and extracting) that are well-understood, routine, and conventional activities previously known to the pertinent industry.
Applicant’s Background in the specification; and
The non-patent literature of record in the application.
Accordingly, in light of Applicant’s specification, the processor is reasonably construed as a generic computing device. Like SAP America vs Investpic, LLC (Federal Circuit 2018), it is clear, from the claims themselves and the specification, that these limitations require no improved computer resources, just already available computers, with their already available basic functions, to use as tools in executing the claimed process.
Furthermore, Applicant’s specification does not describe any special programming or algorithms required for the processor. 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 computer arts. By omitting any specialized programming or algorithms, Applicant's specification essentially admits that this hardware is conventional and performs well understood, routine and conventional activities in the computer industry or arts. In other words, Applicant’s specification demonstrates the well-understood, routine, conventional nature of the above-identified additional elements because it describes these additional elements in a manner that indicates that the additional elements are 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, (III)(A)(1) on page 3). Adding hardware that performs “‘well understood, routine, conventional activit[ies]’ previously known to the industry” will not make claims patent-eligible (TLI Communications).
The recitation of the above-identified additional limitations in Claims 1-18 amounts to mere instructions to implement the abstract idea on a computer. Simply using a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); and TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Moreover, implementing an abstract idea on a generic computer, does not add significantly more, similar to how the recitation of the computer in the claim in Alice amounted to mere instructions to apply the abstract idea of intermediated settlement on a generic computer.
A claim that purports to improve computer capabilities or to improve an existing technology may provide significantly more. McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314-15, 120 USPQ2d 1091, 1101-02 (Fed. Cir. 2016); and Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335-36, 118 USPQ2d 1684, 1688-89 (Fed. Cir. 2016). However, a technical explanation as to how to implement the invention should be present in the specification for any assertion that the invention improves upon conventional functioning of a computer, or upon conventional technology or technological processes. That is, the disclosure must provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. Here, Applicant’s specification does not include any discussion of how the claimed invention provides a technical improvement realized by these claims over the prior art or any explanation of a technical problem having an unconventional technical solution that is expressed in these claims. Instead, as in Affinity Labs of Tex. v. DirecTV, LLC 838 F.3d 1253, 1263-64, 120 USPQ2d 1201, 1207-08 (Fed. Cir. 2016), the specification fails to provide sufficient details regarding the manner in which the claimed invention accomplishes any technical improvement or solution.
For at least the above reasons, the methods of Claims 1-18 are directed to applying an abstract idea as identified above on a general purpose computer without (i) improving the performance of the computer itself, or (ii) providing a technical solution to a problem in a technical field. None of Claims 1-18 provides meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that these claims amount to significantly more than the abstract idea itself.
Taking the additional elements individually and in combination, the additional elements do not provide significantly more. Specifically, when viewed individually, the above-identified additional elements in independent Claim 1 (and its dependent claims) do not add significantly more because they are simply an attempt to limit the abstract idea to a particular technological environment. That is, neither the general computer elements nor any other additional element adds meaningful limitations to the abstract idea because these additional elements represent insignificant extra-solution activity. When viewed as a combination, these above-identified additional elements simply instruct the practitioner to implement the claimed functions with well-understood, routine and conventional activity specified at a high level of generality in a particular technological environment. As such, there is no inventive concept sufficient to transform the claimed subject matter into a patent-eligible application. When viewed as whole, the above-identified additional elements do not provide meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that the claims amount to significantly more than the abstract idea itself. Thus, Claims 1-18 merely apply an abstract idea to a computer and do not (i) improve the performance of the computer itself (as in Bascom and Enfish), or (ii) provide a technical solution to a problem in a technical field (as in DDR).
Therefore, none of the Claims 1-18 amounts to significantly more than the abstract idea itself. Accordingly, Claims 1-18 are not patent eligible and rejected under 35 U.S.C. 101.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-2, 4, 6-12, and 15-16 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Wen et al (U.S. Publication No. US 2019/0223782 A1; cited by Applicant).
Regarding Claim 1, Wen discloses a method of extracting respiratory parameter
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s for a human subject from a thoracic impedance (TI) measurement signal (Systems and methods for sensing respiration from a subject; Abstract), the method comprising:
performing a signal quality check (the selection may be based on a signal characteristic, such as signal quality measure; [0067]) on the TI measurement signal (one of the respiratory sensor circuits (e.g., respiratory sensor circuit 210A) is configured to sense impedance via electrodes attached to or implanted in the patient. An example of the sensed impedance includes a thoracic impedance representing an electrical property of the chest and varies during inspiration expiration phases, such that the impedance increases during inspiration and decreases during expiration. Electrical current may be injected into a body part (e.g., the chest) between two stimulation electrodes to establish an electric field that covers at least a portion of the chest, and voltage drop may be measured between a pair of sensing electrodes. The impedance may be determined using Ohm's law; [0059]); and
executing at least one of an autocorrelation algorithm or a time-domain zero- crossing algorithm on at least a portion of the TI measurement signal to extract at least one respiratory parameter for the human subject from the at least a portion of the TI measurement signal, wherein the at least one respiratory parameter comprises at least one of respiration rate (RR) or tidal volume (TV) (respirator rate may be detected using one of a plurality of candidate algorithms including, for example, a peak detector, a zero-crossing detector, a correlator, or a frequency analyzer…The zero-crossing detector detects when a physiologic signal indicative of respiration crosses signal baseline (denoted by “zero”) representing a DC component of the physiologic signal during the inspiration phase and the expiration phase of a respiratory cycle. The respiratory rate may be determined using the timing of the zero-crossings. The correlator detects respiratory rate using an autocorrelation of a physiologic signal indicative of respiration…The respiratory parameter generator 233 may compute one or more respiration parameters from the selected one or more physiologic signals. The respiration parameters may be generated using a plurality of detection algorithms; [0068-0069]).
Regarding Claim 2, Wen discloses prior to the performing and executing, low-pass filtering the TI measurement signal (The respiratory signal can be obtained from the R-wave amplitude signal using demodulation method, such as by filtering an R-wave amplitude trend through a low-pass filter or a bandpass filter; [0063]).
Regarding Claim 4, Wen discloses wherein the signal quality check comprises an impedance-specific signal quality check (the signal quality analyzer 350 may determine signal strength of an impedance-based respiration parameter, such a peak-to-peak impedance value. The peak-to-peak impedance represents a maximum impedance change within a respiratory cycle, which correlates to a tidal volume. If the impedance signal strength (e.g., peak-to-peak value) falls below a threshold indicating a reduced tidal volume, then the sensor signal selector 332 may dynamically switch to a different physiologic signal, such as a chest wall motion signal or an abdomen motion signal; [0075]).
Regarding Claim 6, Wen discloses wherein the signal quality check comprises identifying at least one signal artifact in the TI measurement signal (The signal quality analyzer 350 may be coupled to the respiratory parameter generator 233, and generate an indication of signal quality of the respiration parameter…the signal quality analyzer 350 may determine the SNR of a respiration parameter (e.g., a ventilation period, which represents duration of a respiratory cycle) using a root-mean-squared (RMS) value of impedance-based respiration parameter estimates and a RMS value of the noise presented in the impedance signal. If the SNR falls below a threshold, or if the RMS of the noise exceeds a noise threshold, then the sensor signal selector 332 may switch to a different physiologic signal, such as a chest wall motion or abdomen motion signal sensed by an accelerometer; [0075]).
Regarding Claim 7, Wen discloses removing the at least one artifact from the TI measurement signal to produce the at least a portion of the TI measurement signal (For example, motion sensed by an accelerometer may be more susceptible to interferences when the patient is physically active than an impedance signal. The sensor signal selector 432 may select the impedance signal if the physical activity intensity or duration exceeds a respective threshold, or when a particular activity pattern such as one indicating repetitive body motion is detected…the sensor signal selector 432 may switch to the impedance signal when the clock 414 indicates daytime or a specified time period during a day when the patient is likely physically active, in a sitting or supine position, or in a sleep state; [0078]; [0089]).
Regarding Claim 8, Wen discloses wherein the at least one artifact comprises noise (The signal quality analyzer 350 may be coupled to the respiratory parameter generator 233, and generate an indication of signal quality of the respiration parameter…the signal quality analyzer 350 may determine the SNR of a respiration parameter (e.g., a ventilation period, which represents duration of a respiratory cycle) using a root-mean-squared (RMS) value of impedance-based respiration parameter estimates and a RMS value of the noise presented in the impedance signal. If the SNR falls below a threshold, or if the RMS of the noise exceeds a noise threshold, then the sensor signal selector 332 may switch to a different physiologic signal, such as a chest wall motion or abdomen motion signal sensed by an accelerometer; [0075]).
Regarding Claim 9, Wen discloses wherein the at least one artifact is a result of movement of the human subject (For example, motion sensed by an accelerometer may be more susceptible to interferences when the patient is physically active than an impedance signal. The sensor signal selector 432 may select the impedance signal if the physical activity intensity or duration exceeds a respective threshold, or when a particular activity pattern such as one indicating repetitive body motion is detected…the sensor signal selector 432 may switch to the impedance signal when the clock 414 indicates daytime or a specified time period during a day when the patient is likely physically active, in a sitting or supine position, or in a sleep state; [0078]; [0089]).
Regarding Claim 10, Wen discloses wherein the executing at least one of the autocorrelation algorithm or the time-domain zero-crossing algorithm on the TI measurement signal further comprises: autocorrelating the TI measurement signal to determine a second order average of the TI measurement signal (The correlator detects respiratory rate using an autocorrelation of a physiologic signal indicative of respiration. As the peaks of the autocorrelation signal represent periodicity of respiration, the respiratory rate may be determined based on a time interval between adjacent autocorrelation peaks. The correlator may alternatively detect respiratory rate using a cross-correlation between a physiologic signal indicative of respiration and a respiration template that includes one or more respiratory cycles under a controlled condition, such as when the subject is physically inactive or maintains at a specific posture. Respiratory cycles may be detected such as based on the peak of cross-correlation, and the respiratory rate may be derived from the detected respiratory cycles; [0068]); and
calculating an expected value based on time lags between peaks in the autocorrelated TI measurement signal to derive an estimated respiratory rate (RR) (respirator rate may be detected using one of a plurality of candidate algorithms including, for example, a peak detector, a zero-crossing detector, a correlator, or a frequency analyzer. The peak detector detects positive or negative peaks in a physiologic signal indicative of respiration, and determines the respiratory rate using time intervals between the detected peaks…respiratory rate may be derived from the frequency at which the signal peak or spectral peak occurs; [0068]).
Regarding Claim 11, Wen discloses deriving a signal to noise ratio (SNR) for the TI measurement signal from the autocorrelated TI measurement signal (a physiologic signal may initially be selected based on signal quality, such that a physiologic signal with stronger signal intensity or a higher signal-to-noise ratio (SNR) may be selected; [0072]).
Regarding Claim 12, Wen discloses calculating a confidence metric for the estimated RR (The sensing configuration selector 232 may select or adjust a respiration detection algorithm for detecting respiration. The selection of the respiration detection algorithm may be based on a signal characteristic such as signal qualities, patient conditions, sensor configurations, environmental conditions, or a computational cost, among others…the sensing configuration selector 232 may quantify both the signal changes caused by respiration and noise levels on the signal and select a respiration detection algorithm based on both the signal changes and the noise levels; [0068]; the algorithm selector 335 may dynamically switch to a different detection algorithm than the originally selected detection algorithm based on the signal quality indication. In an example, if the respirator rate detected using the zero-crossing detector or peak detector has a poor quality (e.g., large variability of the respiratory rate estimates, or substantial failure rate in detecting the peaks or zero-crossings such as due to high physical activity level), then the algorithm selector 335 may switch to a different detection algorithm, such as correlator or a frequency analyzer or other computationally more intensive algorithm; [0076]).
Regarding Claim 15, Wen discloses choosing estimates produced by at least one of the autocorrelation algorithm and the time-domain zero-crossing algorithm based on a confidence metric associated with the autocorrelation algorithm (The sensing configuration selector 232 may select or adjust a respiration detection algorithm for detecting respiration. The selection of the respiration detection algorithm may be based on a signal characteristic such as signal qualities, patient conditions, sensor configurations, environmental conditions, or a computational cost, among others…the sensing configuration selector 232 may quantify both the signal changes caused by respiration and noise levels on the signal and select a respiration detection algorithm based on both the signal changes and the noise levels; [0068]; the algorithm selector 335 may dynamically switch to a different detection algorithm than the originally selected detection algorithm based on the signal quality indication. In an example, if the respirator rate detected using the zero-crossing detector or peak detector has a poor quality (e.g., large variability of the respiratory rate estimates, or substantial failure rate in detecting the peaks or zero-crossings such as due to high physical activity level), then the algorithm selector 335 may switch to a different detection algorithm, such as correlator or a frequency analyzer or other computationally more intensive algorithm; [0076]).
Regarding Claim 16, Wen discloses choosing estimates produced by at least one of the autocorrelation algorithm and the time-domain zero-crossing algorithm based on a signal signature indicative of a clinical condition (The respiration detector circuit 160 may select at least one signal from a plurality of physiologic signals of distinct types, such as sensed by various sensors, based on signal qualities, patient conditions, sensor configurations, or environmental conditions, among others. The respiration detector circuit 160 may detect respiration and compute one or more respiration parameters using the selected signal. The respiration detector may select or adjust a respiration detection algorithm for detecting the respiration parameters. The detection algorithm may be selected or adjusted according to a signal characteristic such as signal quality measure or computational complexity measure, or a patient condition. The AMD 110 may include circuitry that detect a cardiopulmonary event using the detected respiration parameters, such as a WHF event, a sleep apnea event, or other medical conditions presented with breathing disturbances or disordered breathing; [0049]).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 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.
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Wen in view of Wang et al (U.S. Publication No. 2019/0021633).
Regarding Claim 3, Wen fails to disclose wherein a cutoff frequency of a filter used to perform the low-pass filtering is 0.65 Hertz.
In a similar technical field, Wang teaches detecting respiratory rates in audio using an adaptive low-pass filter (Abstract), wherein a cutoff frequency of a filter used to perform the low-pass filtering is 0.65 Hertz (The bandwidth updater 114 can update the bandwidth of the adaptive low-pass filter 108. For example, the bandwidth updater 114 can update the bandwidth of the adaptive low-pass filter 108 in real-time. In some examples, if the breathing rate of a user is much higher or lower than 0.65 Hz, or the breathing rate of a user moves up or down, then the bandwidth of the adaptive low-pass filter 108 may be updated; [0025]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have incorporated the cutoff frequency teachings of Wang into those of Wen because the bandwidth initializer can set an initial bandwidth for the adaptive low-pass filter, and the initial bandwidth set by the bandwidth initializer is based on an average breathing rate, which may be 0.65 Hz (Wang [0021]).
Claims 5 and 17-18 are rejected under 35 U.S.C. 103 as being unpatentable over Wen in view of Kearns (U.S. Patent No. 4,289,142).
Regarding Claim 5, Wen fails to disclose wherein the signal quality check comprises checking at least one of electrode contact impedance and total body impedance with reference to thresholds based on physiological limits.
In a similar technical field, Kearns teaches a respiration monitor (Abstract), wherein the signal quality check comprises checking at least one of electrode contact impedance and total body impedance with reference to thresholds based on physiological limits (Similarly, where transthoracic impedances over 1000 ohms are encountered, an improper electrode connection to the subject or a system malfunction exists. A truth table for decoder 312 is provided in Table 1; Column 16 Lines 22-25).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have incorporated the signal quality check teachings of Kearns into those of Wen in order to implement a threshold to indicate inaccurate readings due to improper electrode connection (Kearns Column 16 Lines 22-25).
Regarding Claim 17, Wen fails to disclose wherein the TI measurement signal is less than 60 seconds in duration.
In a similar technical field, Kearns teaches a respiration monitor (Abstract), wherein the TI measurement signal is less than 60 seconds in duration (A 25 msec. sample period is chosen in accordance with Shannon sampling therorum; Column 19 Lines 35-36).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have incorporated the duration teachings of Kearns into those of Wen in order to ensure that the sampling duration is at most half the period of the highest frequency to capture enough information and avoid aliasing (Kearns Column 19 Lines 35-36).
Regarding Claim 18, Wen fails to disclose wherein the TI measurement signal is less than 30 seconds in duration.
In a similar technical field, Kearns teaches a respiration monitor (Abstract), wherein the TI measurement signal is less than 30 seconds in duration (A 25 msec. sample period is chosen in accordance with Shannon sampling therorum; Column 19 Lines 35-36).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have incorporated the duration teachings of Kearns into those of Wen in order to ensure that the sampling duration is at most half the period of the highest frequency to capture enough information and avoid aliasing (Kearns Column 19 Lines 35-36).
Claims 13-14 are rejected under 35 U.S.C. 103 as being unpatentable over Wen in view of Koh (U.S. Patent No. 7,070,568).
Regarding Claim 13, Wen discloses wherein the executing at least one of the autocorrelation algorithm or the time-domain zero-crossing algorithm on the TI measurement signal further comprises: counting zero-crossings to calculate a respiratory rate (RR) (respirator rate may be detected using one of a plurality of candidate algorithms including, for example, a peak detector, a zero-crossing detector, a correlator, or a frequency analyzer…the zero-crossing detector detects when a physiologic signal indicative of respiration crosses signal baseline (denoted by “zero”) representing a DC component of the physiologic signal during the inspiration phase and the expiration phase of a respiratory cycle. The respiratory rate may be determined using the timing of the zero-crossings. The correlator detects respiratory rate using an autocorrelation of a physiologic signal indicative of respiration. As the peaks of the autocorrelation signal represent periodicity of respiration, the respiratory rate may be determined based on a time interval between adjacent autocorrelation peaks; [0068]); and
calculating a tidal volume (TV) from a median of peak TI values (the signal quality analyzer 350 may determine signal strength of an impedance-based respiration parameter, such a peak-to-peak impedance value. The peak-to-peak impedance represents a maximum impedance change within a respiratory cycle, which correlates to a tidal volume. If the impedance signal strength (e.g., peak-to-peak value) falls below a threshold indicating a reduced tidal volume, then the sensor signal selector 332 may dynamically switch to a different physiologic signal, such as a chest wall motion signal or an abdomen motion signal; [0075]).
Wen fails to specifically teach counting zero-crossings on a first order derivative of the TI measurement signal to divide the TI signal into inhalation and exhalation cycles.
In a similar technical field, Koh teaches a system and method for diagnosing and tracking congestive heart failure based on the periodicity of Cheyne-Stokes Respiration using an implantable medical device (Abstract), comprising counting zero-crossings on a first order derivative of the TI measurement signal to divide the TI signal into inhalation and exhalation cycles (Signals representative of thoracic impedance sensed using leads implanted within the heart are low-pass filtered. The derivative of the filtered impedance signal is calculated and then zero-crossing points are identified. The derivative of the filtered impedance signal is then integrated between each pair of consecutive zero-crossing points to generate a set of integral values, which effectively restore valley-top-peak amplitudes. A moving average of the integrated values is then periodically updated for use as the discrimination threshold; Column 4 Lines 47-56).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have incorporated the processing teachings of Koh into those of Wen in order to calculate the discrimination threshold based on the thoracic impedance signal (Koh Column 4 Lines 45-46).
Regarding Claim 14, Wen discloses applying a shallow breath threshold to the first order derivative prior to the calculating a RR and the calculating a TV (the generated respiration parameters may include a respiratory pattern, such as a rapid-shallow breathing index (RSBI) (represented by a ratio of a respiratory rate measurement to a tidal volume measurement), Cheyne-Stokes pattern, cluster breathing, Kussmaul's breathing, apneustic breathing, or ataxic breathing, among other patterns; [0069]).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Cho et al (U.S. Publication No. 2004/0134496) teaches a method and apparatus for detecting respiratory disturbances (Abstract), wherein the patient's respiration rate is derived from the physiological signal. Generally, by filtering a sensed signal to remove higher frequency components and pass low frequencies associated with the respiration cycle, a respiration rate may be determined. A preferred method for deriving the respiration rate comprises a simple peak detection algorithm. In this case, an input impedance signal measures the thoracic excursion due to respiration (e.g., herein "respiration"). By detecting individual breaths and related peaks and valleys of the input impedance signals, respiration rate can be derived (by measuring interval between peaks) or tidal volume (by measuring peak to peak amplitude change from a peak to the corresponding valley) ([0035]).
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/CHANEL J JHIN/Examiner, Art Unit 3791