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 .
Applicant' s arguments, filed 10/24/2024, have been fully considered. The following rejections and/or objections are either reiterated or newly applied. They constitute the complete set presently being applied to the instant application.
Applicants have amended their claims, filed 10/24/2024, and therefore rejections newly made in the instant office action have been necessitated by amendment.
Claims 1-20 are the current claims hereby under examination.
Claims 1, 3, 12, and 13 are the claims that have been amended on 10/24/2024.
Claim Objections
Claims 1, 8, and 12 are objected to because of the following informalities:
In claim 1, lines 8-9: “the” should be inserted before “patient respiration”.
In claim 1, line 13: “inspiration and expiration” should be “the inspiration and the expiration”.
In claim 1, line 15: “the” should be inserted before “respiratory vibration information”.
In claim 8, lines 1-2: “a transition between inspiration and expiration” should be “the transition between the inspiration and the expiration”.
In claim 12, line 9: “the” should be inserted before “patient respiration”.
In claim 12, line 15: “the” should be inserted before “respiratory vibration information”.
Appropriate correction is required.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 of the subject matter eligibility test (see MPEP 2106.03).
Claims 1-11 are directed to a “system”, and claims 12-20 to a “method” which describes one of the four statutory categories of patentable subject matter, i.e., a machine, a process, a manufacture, or a composition of matter.
Step 2A of the subject matter eligibility test (see MPEP 2106.04)
Prong one: abstract ideas of a mental process are recited, as follows:
Claim 1 recites the following:
identify a first set of respiratory cycles of the plurality of respiratory cycles having a duration within a threshold using the received physiologic information cyclic with patient respiration;
align segments of the vibration information corresponding to the first set of respiratory cycles, the segments associated with a desired portion of the respiratory cycle using a feature of the respiratory cycle including at least one of a beginning of inspiration, a beginning of expiration, or a transition between inspiration and expiration;
determine a composite respiratory vibration using the aligned segments;
detect respiratory vibration information of the patient based on the determined composite respiratory vibration.
Claim 12 the following:
identifying, using an assessment circuit, a first set of respiratory cycles of the plurality of respiratory cycles having a duration within a threshold using the received physiologic information cyclic with patient respiration;
aligning, using the assessment circuit, segments of the vibration information corresponding to the first set of respiratory cycles, the segments associated with a desired portion of the respiratory cycle using a feature of the respiratory cycle;
determining, using the assessment circuit, a composite respiratory vibration using the aligned segments;
detecting respiratory vibration information of the patient based on the determined composite respiratory vibration.
Based on the broadest reasonable interpretation, determining a composite respiratory vibration can be done mentally. If a person is given physiologic information and vibration information, the person can determine the first set of respiratory cycles by looking at the received data, such as a waveform of ECG or breath vibrations, and determine the inspiration and expiration of a patient by observing the curves of the breath waveform, aligning the waveforms, determine a composite of the two via any number of simple mathematical methods (e.g., averaging) to produce a composite respiratory vibration, and then the composite can be analyzed to identify respiratory vibration information of the patient.
Prong two: Claims include additional elements that does not integrate the judicial exception into practical application.
The additional elements found in Claim 1 and 12 are: a signal receiver circuit and an assessment circuit.
The above additional elements, taken individually and in combination, do not integrate the judicial exceptions into a practical application, but generally links the above-identified abstract idea into a particular technological environment or field of use. More specifically, receiving a signal by a signal receiver circuit and processing the judicial exception by using an assessment circuit that performs the mental process does not integrate the mental process in a meaningful way; it is merely applying the judicial exception to a technological environment of a computer. Additionally, there is no improvements to the functioning of a computer, or to any other technology or technical field, nor is there a transformation of a particular article to a different state or thing 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.
Therefore, claim 1 and 12 are ineligible at step 2A, prong two. See MPEP 2106.04(d) and (h). Additionally see Alice Corp. v. CLS Bank, 573 U.S. 208, 221, 110 USPQ2d 1976, 1982-83 (2014).
Step 2B of the subject matter eligibility test (see MPEP 2106.05)
Receiving physiologic and vibration information from a patient is an insignificant extra-solution activity that uses conventional, routine, and well-known elements. The element is well known, routine, and conventional because receiving a signal from a signal receiving circuit has been widely used and known in the art, as evidenced by the applicant’s lack of detailed description of signal received by a signal receiving circuit so as to satisfy requirements under 35 U.S.C. 112(a).
As such, a well-known, routine, and conventional activity does not amount to significantly more than the judicial exception - see MPEP 2106.05(g).
Dependent Claims
The dependent claims 2-11 and 13-20 do not remedy the abstract idea, but merely further define the abstract idea of the parent claims and are therefore directed to an abstract idea without amounting to significantly more.
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.
Claims 1-6, 8, 10-15, 17, and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Zhang et al. (US20150038854A1), hereto referred as Zhang, in view of Spina et al. (US10898160B2), hereto referred as Spina, and in view of Cobb et al. (US20040249299A1), hereto referred to as Cobb, and citing to Reichert et al. (Reichert S, Gass R, Brandt C, Andrès E. Analysis of respiratory sounds: state of the art. Clin Med Circ Respirat Pulm Med. 2008 May 16;2:45-58. doi: 10.4137/ccrpm.s530. PMID: 21157521; PMCID: PMC2990233), as evidence.
Regarding Claims 1 and 12, Zhang teaches a system to improve detection of respiratory vibration information by a medical device (Zhang, Figure 3 and ¶[0045], “medical device 310 may be incorporated into a medical system”; ¶[0027] “Information developed from respiratory data in accordance with various embodiments provides for enhanced patient monitoring and therapy management, particularly when the status of a patient is in decline”, showing a system that improves respiratory information), comprising: a signal receiver circuit configured to receive physiologic information cyclic with patient respiration and vibration information indicative of patient respiratory vibrations… for a plurality of respiratory cycles of a patient where the “respiration circuitry 318 may be configured to receive the signals generated by the one or more respiration sensors” (Zhang, ¶[0048]) and the sensors such as a “ventilation sensor, transthoracic impedance sensor, accelerometer, pressure, air flow, or other sensor capable of producing a respiratory waveform” (Zhang, ¶[0042]) can include physiologic and vibration information that is cyclic with a patients respiration such as “acoustic information…of the respiratory cycle” (Zhang, ¶[0038]). Additionally, Zhang teaches an assessment circuit (Zhang, Figure 3, “Processor 314”) configured to: identify a first set of respiratory cycles of the plurality of respiratory cycles having a duration (Zhang, ¶[0072], “first respiration related parameter aggregate determined over a first time window”).
Zhang does not explicitly describe capturing vibrations greater than 20 Hz. Spina, who investigates an acoustic monitoring system for respiration and cardiology, discusses adventitious sound recognition including detecting coughing (where a cough is “between 50 and 3000 Hz”, Reichert et al., Definition of terms, Cough sound), showing that the system is capable of capturing higher frequency components, such as respiratory vibrations greater than 20 Hz (Spina, Col. 3, Lines 5-17). Therefore, it is reasonable to infer that the combined system of Zhang and Spina is capable of capturing such high-frequency vibrations. It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Zhang in view of Spina to capture vibration information indicative of patient respiratory vibrations greater than 20 Hz. This has the benefit of capturing a wider range of breathing sounds and not just those associated with lower frequencies such as respiration rate, allowing advanced diagnostics on different breathing syndromes and conditions.
Zhang does not fully teach a duration within a threshold using the received physiologic information cyclic with patient respiration. Zhang describes identifying respiratory cycles and physiologic parameters such as “respiration rate…tidal volume…and RSBI values” and investigates those values “over a first time window” (Zhang, ¶[0072]), but does not provide detailed threshold identification. Spina describes how phase duration of the respiratory cycle (inspiration and expiration) can be estimated from the chest expansion data, which aligns with the claim’s focus on identifying respiratory cycles with a duration within a threshold using physiologic information (Spina, Col 18, Lines 41-67). It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Zhang in view of Spina to have a duration within a threshold using the cyclic physiologic information. Such a combination would have the benefit of both quantifying the phase durations and monitoring respiratory parameters, allowing it to precisely identify respiratory cycles that meet the specific duration requirements. This combination enhances the system’s capability to detect abnormal respiratory patterns or changes that may require clinical attention, providing a more comprehensive and accurate assessment of patient respiration.
While Zhang does not expressly teach align segments of the vibration information corresponding to the first set of respiratory cycles, the segments associated with a desired portion of the respiratory cycle using a feature of the respiratory cycle including at least one of a beginning of inspiration, a beginning of expiration, or a transition between inspiration and expiration, it is implied and well understood that in order to properly combine multiple signals, the signals must be aligned. Cobb, who investigates processing and analyzing cardio-pulmonary signals, teaches segmenting respiratory cycles into specific phases and recognizing features of the respiratory cycle. Cobb explains that since a primary event is a pattern or group of component primitive events, it may be recognized when the proper primitive events arranged in the defining pattern or group have been found in an input signal (Cobb, ¶[0010]). In the case of respiratory measurements, primary events are the complete breaths that actually move air for pulmonary gas exchange and may be recognized as a proper sequence of primitive inspiratory and expiratory phases recognized in input lung volume data (Cobb, ¶[0011]). Furthermore, Cobb details that each normal breath includes sequential primitive events such as begin inspiration ('BI') and end expiration ('EE') (Cobb, ¶[0046]). This demonstrates that Cobb's system aligns segments of vibration information corresponding to desired portions of the respiratory cycle using features like the beginning of inspiration and expiration. Aligning physiological signals based on identifiable events within the signal is a common practice in signal processing. Respiratory signals often exhibit characteristic features such as the onset of inspiration and expiration, which are used as reference points for segmenting and analyzing the data. Both Zhang and Cobb deal with respiratory signals and their analysis. Incorporating Cobb's alignment method does not require fundamental changes to Zhang's system but enhances its functionality. Aligning data segments using physiological markers is a well-known technique in signal processing. Applying this method to Zhang's system would have been predictable and within the expected skill set of someone in the field. There are no technical obstacles or unexpected results associated with combining these teachings and the benefits of improved synchronization and analysis are direct and foreseeable. It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combined Zhang and Spina in view of Cobb to align segments of the respiratory vibration information using features of the respiratory cycle including things like beginning of inspiration, expiration, or a transition between them. By aligning segments at consistent physiological markers, variations due to timing differences are minimized, leading to more reliable composite signals for enhanced analysis.
Zhang does not teach determining a composite respiration using the aligned segments. Zhang does combine “aggregates” through subtraction (Zhang, Claim 3, “subtracting the first RSBI aggregate determined for the first time window from the second RSBI aggregate”), as well as create a “representative respiration rate value” (Zhang, ¶[0049]) by using components of the received signals. Cobb teaches combining primitive events to form primary events, effectively determining a composite respiratory vibration. Cobb states that representations of primary events preferably include their component primitive events along with further information characterizing the type and quality of the primary event itself and that “these events are grouped or associated into the primary (or composite)” (Cobb, ¶[0010]). According to Cobb, the structured information resulting from input-signal analysis may be subject to higher-level physiological analysis (Cobb, ¶[0012]). Additionally, Cobb mentions that it is advantageous to compute and store summary status information generally concerning the breath's quality or type during primary event recognition (Cobb, ¶[0076]). These teachings indicate that Cobb's system determines composite respiratory vibrations from aligned segments for advanced analysis. One of ordinary skill in the art would have recognized the benefits of combining aligned segments to create a composite respiratory vibration. In signal processing, constructing composite signals from multiple aligned segments is a standard method to enhance signal quality and extract meaningful patterns. Combining segments allows for more comprehensive analysis by emphasizing common features and suppressing random variations. Implementing composite signal determination in Zhang's system would not require significant modifications but would enhance its analytical capabilities. It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combined Zhang, Spina, and Cobb to determine a composite respiration using the aligned segments. Averaging or otherwise combining the aligned segments has the benefit of reducing random noise, and recurring signal components become more prominent allowing more advanced analysis and diagnosis using the respiratory signals.
Zhang does not teach to detect respiratory vibration information of the patient based on the determined composite respiratory vibration. Cobb teaches detecting respiratory vibration information by processing structured representations (composite events) of respiratory cycles. Cobb explains that primary events are the complete breaths and may be recognized as a proper sequence of primitive inspiratory and expiratory phases recognized in input lung volume data (Cobb, ¶[0011]). Cobb further describes that higher-level analysis examines the physiologically structured representations created by input signal processing (Cobb, ¶[0013]). As such, Cobb emphasizes that the invention recognizes “primitive and primary physiological events in an input signal, represents these events in a structured manner, and performs further processing in a 'physiological domain' of these events” (Cobb, ¶[0016]) and that “input signal analysis may function alone… data analysis may function alone… or an embodiment may include both functions acting in coordination” (Cobb, ¶[0017]). These teachings demonstrate that Cobb's system detects respiratory vibration information based on composite respiratory vibrations. A person of ordinary skill in the art would have found it natural to detect respiratory vibration information based on the composite respiratory vibration determined from aligned segments. Processing composite signals for detection purposes is a standard method in various biomedical signal processing applications. Since the system already aligns segments and determines a composite signal (as per Elements above), using the composite for detection is a logical and straightforward extension. It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combined Zhang, Spina, and Cobb to detect respiratory vibration information of the patient based on the determined composite respiratory vibration. This approach enhances the reliability and accuracy of detection by utilizing the improved signal quality of the composite and as the benefit of facilitating more precise detection of physiological events.
Regarding Claims 2 and 13, Zhang teaches an implantable housing (Zhang, Figure 2, 207, “Patient-Implantable Medical Device”) comprising a vibration sensor configured to sense the vibration information indicative of patient respiratory vibrations (Zhang, ¶[0042], “PIMD 207 may incorporate… sensors 209 may include one or more of a minute ventilation sensor, transthoracic impedance sensor, accelerometer, pressure, air flow, or other sensor capable of producing a respiratory waveform representative of the patient's breathing”). Zhang also teaches storing the determined composite respiratory vibration in a memory in the implantable housing (Zhang, [0063], "respiration related parameter data may be collected… as the data storage capabilities of the medical device (e.g. medical device 310) permit.")
Regarding Claim 3, Zhang does not teach that the composite respiratory vibration has a signal-to-noise ratio (SNR) greater than the vibration information for the plurality of respiratory cycles of the patient. Cobb teaches that filtering and combining signals result in composite signals with improved SNR. Cobb mentions that such pre-processing may serve to filter noise and other non-physiological signals, or physiological signals that are not of interest, or other artifacts (Cobb, ¶[0009]). After the primitive physiological event recognition and characterization, these events are grouped or associated into the primary (or composite), basic physiological events (Cobb, ¶[0010]). These teachings indicate that Cobb's methods enhance the SNR of the composite respiratory vibration compared to individual cycles. Applying filtering and combining techniques to improve SNR is a routine optimization step in the development of biomedical signal processing systems. One of ordinary skill in the art would recognize that combining aligned segments into a composite signal inherently improves the SNR. This is due to the averaging effect, where random noise components tend to cancel out while the consistent signal components reinforce each other. It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the combined Zhang, Spina, and Cobb to ensure that the composite respiratory vibration has a signal-to-noise ratio (SNR) greater than the vibration information for the plurality of respiratory cycles of the patient. The modification utilizes basic principles of signal processing to enhance system performance, motivated by the predictable benefits of improved signal quality without introducing complexity or unforeseen issues. A higher SNR has the benefit of a more reliable interpretation of the data and can reveal features that are otherwise obscured by noise.
Regarding Claims 4 and 14, Zhang teaches that the physiologic information (Zhang, ¶[0042], “sensors 205”) and the vibration information (Zhang, ¶[0042], “sensors 209”) comprise different types of information, where the vibration information from a patient’s breathing can come from “sensors 209… accelerometer, pressure, air flow, or other sensor capable of producing a respiratory waveform” (Zhang, ¶[0042]) and the physiologic information comprises at least of electrocardiogram information of the patient, accelerometer information of the patient, impedance information of the patient, acoustic information of the patient, or blood flow information of the patient (Zhang, ¶[0042], “sensors 205 may also be used to sense various physiological parameters of the patient… pulse oximetry sensor, blood pressure sensor, patient temperature sensor, EKG sensor arrangement, weight scale, biomarkers, among others").
Regarding Claims 5 and 15, Zhang also teaches that the assessment circuit is configured to determine a change in patient status (Zhang, ¶[0029], “Analysis of the patient's respiration… in combination with other physiological information, may trigger an alert indicating a change in the patient's status”), to detect a physiological condition of the patient (Zhang, ¶[0029], “In particular… change in the patient's heart failure status.”), or to determine a patient therapy parameter using the determined composite respiratory vibration (Zhang, ¶[0027], “Information developed from respiratory data in accordance with various embodiments provides for enhanced patient monitoring and therapy management”, such as: (Zhang, ¶[0032], “bi-ventricular pacing/therapy, cardiac resynchronization therapy”)).
Regarding Claim 6, Zhang indirectly, implicitly, or inherently teaches that the first set of respiratory cycles of the patient comprises at least 3 respiratory cycles by having their processor configured to function over a 24 hour period of respiration cycles (Zhang, ¶[0057], “The processor 314 may be configured to determine a representative respiration rate value, a tidal volume value, and/or an RSBI value, as discussed herein, for each twenty-four hour period”). This amount of time would be more than enough to have at least three respiratory cycles as a first set. Spina also teaches a system that is “configured to monitor a subject over a time period of at least one hour” (Spina, Col 4, Line 22-27), which once again is ample amount of time to capture at least the first three respiratory cycles.
Regarding Claims 8 and 17, Zhang does not teach that the feature of the respiratory cycle comprises a transition between inspiration and expiration of the patient. However, Spina specifically points out this feature: "end of an inspiration phase (and start of an expiration phase) is indicated by reference signal maximum 1152" (Spina, Figure 11, Col 18, Line 41-55) and, in Figure 11, depicts an example reconstructed physiological signal together with an acoustic signal and a reference signal where the selected segment of the vibration information is aligned with the transition between inspiration and expiration. It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Zhang to use the inspiration/expiration transition as the selected feature. This would have the benefit of facilitating the alignment of the signals based on the easily identifiable nature of this particular parameter.
Regarding Claims 10 and 19, Zhang does not teach that the segments of the vibration information associated with the desired portion of the respiratory cycle comprise segments associated with two or more of: a wheeze segment of the respiratory cycle; a stridor segment of the respiratory cycle; a squawk segment of the respiratory cycle; a rhonchus segment of the respiratory cycle; a snore segment of the respiratory cycle; a fine crackle segment of the respiratory cycle; a course crackle segment of the respiratory cycle; a crackle segment of the respiratory cycle; and a pleural friction rub segment of the respiratory cycle. Spina does account for these kinds of breathing sounds as part of their signal processing and are included as physiological variables of interest (Spina Col 16, Line 4-25, "The audio signal extracted can be modeled” using “lung sounds” and “the noise components related to biological interferences (as wheezes, crackles, swallowing sounds, etc.)”) It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Zhang to include analysis using these breathing sounds to reduce “interference from biological sounds such as the heart beats, abnormal lung sounds, swallowing, coughing, speech” (Spina, Col 2, Line 29-39) to better diagnose the condition of the patient.
Regarding Claims 11 and 20, Zhang teaches that the assessment circuit is configured to: determine trends of the determined composite respiratory vibrations for each of the two or more segments (Zhang, ¶[0049] “The processor 314… configured to execute one or more software applications stored in the memory 322 for monitoring and/or trending one or more respiration related parameters”); and determine a change in patient condition using the determined trends, wherein the change in patient condition includes an indication of at least one of: chronic obstructive pulmonary disorder (COPD); asthma; heart failure (HF); pneumonia; bronchitis; or sleep apnea of the patient (Zhang, ¶[0027], “patient's heart failure status may be detected based, at least in part, on a trend”).
Claims 7 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over the combined Zhang, Spina, and Cobb, and citing to Reichert et al. as evidence, and further in view of US20100160992A1 (Andreas Blomqvist), hereto referred as Blomqvist.
The combined Zhang, Spina, and Cobb teach Claims 1 and 12 as described above.
Regarding Claims 7 and 16, Zhang-Spina-Cobb does not teach that the threshold comprises a range within N% of the duration a first respiratory cycle or of the inspiration/expiration (I/E) ratio of the first respiratory cycle. Blomqvist teaches a similar art of monitoring respiration phase (Blomqvist, abstract). Blomqvist teaches determining inspiration to expiration (I/E) ratio from a respiration phase which could be a first respiration cycle (Blomqvist, claim 26, “circuit is configured to monitor, as said relationship, a ratio between a duration of the expiratory phase and a duration of the inspiratory phase.”). It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Zhang-Spina-Cobb to have included determining I/E ratio from the composite respiratory cycle of Zhang-Spina-Cobb because doing so would allow monitoring a patient condition based on the I/E ratio.
Claims 9 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over the combined Zhang, Spina, and Cobb, and citing to Reichert et al. as evidence, and further in view of US20180214090A1 (Al-Ali et al.), hereto referred as Al-Ali.
The combined Zhang, Spina, and Cobb teach Claims 1 and 12 as described above.
Regarding Claims 9 and 18, Zhang-Spina-Cobb do not directly teach that the composite respiratory vibration comprises an average of the aligned vibration information, but instead combine signals in other ways for determining physiological parameters and diagnostics. Al-Ali teaches a similar art of detecting respiratory rate (Al-Ali, abstract). Al-Ali teaches the creating of a composite signal using averages (Al-Ali, ¶[0104], “Or, the respiratory rate analyzer 650 could average, perform a weighted average (e.g., based on respective single parameter confidences), or otherwise combine the respiratory rate measurements to determine the respiratory rate output RROUT.”). It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Zhang-Spina-Cobb to include a simple average of the aligned vibration signals as a method to further analyze the respiration cycle in order more clearly define signal components for diagnostic purposes.
Response to Arguments
101 Rejections
Applicant's arguments filed 10/24/2024, pages 8-10, regarding the previous 101 rejection, have been fully considered but they are not persuasive.
Applicant asserts that claim 3 has been canceled, page 8. Under 37 CFR § 1.121, any canceled claims must be explicitly made by the applicant. Claims that are not formally canceled remain part of the application. A review of the record indicates no formal cancelation of claim 3. Therefore, the argument that claim 3 has been canceled is not persuasive as the claim remains in the application.
Applicant assert their arguments and amendments to Claims 1 and 12 overcome the § 101 rejection by demonstrating that the claims are directed to patent-eligible subject matter. Under the Alice/Mayo framework, claims must pass a two-step analysis to determine eligibility under § 101:
1. Determine whether the claims are directed to a judicial exception, such as an abstract idea.
2. If so, determine whether the claims recite an “inventive concept” sufficient to transform the abstract idea into a patent-eligible application. Merely reciting improved results or intended benefits, without an improvement to the underlying technology or functionality, is insufficient to satisfy the second step.
Applicants have amended Claims 1 and 12, as filed on 10-24-2024, arguing that the amendments demonstrate an improvement to the claimed invention. However, the amendments and accompanying arguments focus solely on achieving an improved result, rather than specifying how the claims improve the functioning of technology or computer-related operations. An improved result alone—without identifying a specific technological solution or enhancement—does not satisfy the requirement for an inventive concept as outlined in Alice. The amended claims still recite an abstract idea of achieving the result, rather than any technological means of achieving it.
For example, the amendments describe “using the received physiologic information cyclic with patient respiration”, “including at least one of a beginning of inspiration, a beginning of expiration, or a transition between inspiration and expiration”, and “detect respiratory vibration information of the patient based on the determined composite respiratory vibration”, but these elements merely restate the desired outcome without detailing a technological implementation that goes beyond the abstract idea itself. As a result, the amendments do not sufficiently address the concerns raised in the § 101 rejection.
The applicants' arguments and amendments to Claims 1 and 12 do not overcome the § 101 rejection. The claims remain directed to an abstract idea without the requisite inventive concept to transform the claims into patent-eligible subject matter. Therefore, the § 101 rejection is maintained.
Applicant argues that the claims, as amended, overcome the § 101 rejection by demonstrating that they are directed to a patent-eligible improvement in respiratory vibration monitoring technology, as argued by the applicant with reference to CardioNet LLC v. Infobionic, Inc.
The Applicant analogizes the present application with Cardionet, LLC v. Infobionic, Inc., 955 F.3d 1358 (Fed. Cir. 2020), hereinafter Cardionet 2020 (I).1
The Cardionet 2020 (I) court concluded that the claim at issue was directed to an improved cardiac monitoring device. The court indicated that, “At the heart of the district court’s erroneous step one analysis is the incorrect assumption that the claims are directed to automating known techniques.” (See the Cardionet 2020 (I) slip opinion at page 16). The Cardionet 2020 (I) court reasoned that (1) the written description of the patent at issue did not disclose that doctors performed the same techniques as the claimed device in diagnosing atrial fibrillation or atrial flutter; (2) nothing in the record supports the district court’s fact finding that doctors long used the claimed diagnostic processes; and (3) it is difficult to fathom how doctors mentally or manually used “logic to identify the relevance of the variability [in the beat-to-beat timing] using a non-linear function of a beat-to-beat interval” as required by claim 10 (See the Cardionet 2020 (I) slip opinion at pages 16-17).
However, Cardionet 2020 (I) is not on point with respect to the 101 rejection of the present case since:
(1) the rejection does not rely upon the assumption that the claims are directed to the automation of known techniques;
(2) the rejection rests on a mental process that can be practically performed in the human mind; and
(3) one of ordinary skill in the art can mentally or manually execute the mental processes of claim 1 and claim 12.
Indeed, the present case is more like the subsequent Federal Circuit cases:
Cardionet, LLC v. Infobionic, Inc., Case 20-2123 (Fed. Cir. 2021)(nonprecedential), hereinafter Cardionet 2021,2 and
Cardionet, LLC v. InfoBionic, Inc., Case 2020-1018 (Fed. Cir. 2020) (nonprecedential), hereinafter Cardionet 2020 (II).3
The patent at issue in Cardionet 2021 was also drawn to a cardiac monitoring system, but the invention was deemed to be directed to the abstract idea of filtering patient heartbeat signals to increase accuracy (See the Cardionet 2021 slip opinion at page 8). The filtering only required basic mathematical calculations, such as decomposing a T wave into its constituent frequencies and multiplying them by a filter frequency response. (See the Cardionet 2021 slip opinion at pages 8-9). Even if these calculations were groundbreaking, they were still directed to an abstract idea. (See the Cardionet 2021 slip opinion at page 9).
In contrast, the claims in Cardionet 2020 (I) were found to be patent eligible by focusing on the claimed aspect of “identify[ing] a relevance of the variability in the beat-to-beat timing to at least one of atrial fibrillation and atrial flutter”. (See the Cardionet 2020 (I) slip opinion at pages 15-17). This is a more sophisticated aspect such that it results in a focus on a specific means or method that improves cardiac monitoring technology.
The calculations of the present case (identify a first set of respiratory cycles of the plurality of respiratory cycles having a duration within a threshold using the received physiologic information cyclic with patient respiration; align segments of the vibration information corresponding to the first set of respiratory cycles, the segments associated with a desired portion of the respiratory cycle using a feature of the respiratory cycle including at least one of a beginning of inspiration, a beginning of expiration, or a transition between inspiration and expiration; determine a composite respiratory vibration using the aligned segments; detect respiratory vibration information of the patient based on the determined composite respiratory vibration of claim 1 and identifying a first set of respiratory cycles of the plurality of respiratory cycles having a duration within a threshold using the received physiologic information cyclic with patient respiration; aligning segments of the vibration information corresponding to the first set of respiratory cycles, the segments associated with a desired portion of the respiratory cycle using a feature of the respiratory cycle; determining a composite respiratory vibration using the aligned segments; detecting respiratory vibration information of the patient based on the determined composite respiratory vibration) are basic mathematical calculations of claim 12) are like the claims in Cardionet 2021, and are dissimilar to the sophisticated logic of identifying the relevance of the variability in the beat-to-beat timing using a non-linear function of a beat-to-beat interval, like the claims in Cardionet 2020 (I).
In Cardionet 2020 (II), the court looked at a claim drawn to a system for reporting information related to arrhythmia events comprising: a monitoring system configured to process and report physiological data, including heart rate data, for a living being and configured to identify arrhythmia events from the physiological data; a monitoring station for receiving the physiological data from the monitoring system; a processing system configured to receive arrhythmia information from the monitoring system and configured to receive human-assessed arrhythmia information from the monitoring station wherein the human-assessed arrhythmia information derives from at least a portion of the physiological data and wherein the processing system is capable of pictographically presenting, using a common time scale, information regarding the heart rate data during a defined time period and regarding duration of arrhythmia event activity, according to the identified arrhythmia events, during the defined time period such that heart rate trend is presented with arrhythmia event burden. (Cardionet 2020 (II) at page 473). The Cardionet 2020 (II) court concluded that the claims are directed to collecting, analyzing, and displaying data, which are abstract concepts (see Cardionet 2020 (II) at 475).
The calculations of the present case (identify a first set of respiratory cycles of the plurality of respiratory cycles having a duration within a threshold using the received physiologic information cyclic with patient respiration; align segments of the vibration information corresponding to the first set of respiratory cycles, the segments associated with a desired portion of the respiratory cycle using a feature of the respiratory cycle including at least one of a beginning of inspiration, a beginning of expiration, or a transition between inspiration and expiration; determine a composite respiratory vibration using the aligned segments; detect respiratory vibration information of the patient based on the determined composite respiratory vibration of claim 1 and identifying a first set of respiratory cycles of the plurality of respiratory cycles having a duration within a threshold using the received physiologic information cyclic with patient respiration; aligning segments of the vibration information corresponding to the first set of respiratory cycles, the segments associated with a desired portion of the respiratory cycle using a feature of the respiratory cycle; determining a composite respiratory vibration using the aligned segments; detecting respiratory vibration information of the patient based on the determined composite respiratory vibration) are basic mathematical calculations of claim 12) are analyzing data, like the claims in Cardionet 2020 (II), and are dissimilar to the sophisticated logic to identify the relevance of the variability in the beat-to-beat timing using a non-linear function of a beat-to-beat interval, like the claims in Cardionet 2020 (I).
Also, the analysis undergone in the claims of the present application are similar to the type of analysis in the claims found ineligible in Electric Power Group, 119 USPQ2d 1739 (Fed. Cir. 2016). For example, the calculations of the present case (identify a first set of respiratory cycles of the plurality of respiratory cycles having a duration within a threshold using the received physiologic information cyclic with patient respiration; align segments of the vibration information corresponding to the first set of respiratory cycles, the segments associated with a desired portion of the respiratory cycle using a feature of the respiratory cycle including at least one of a beginning of inspiration, a beginning of expiration, or a transition between inspiration and expiration; determine a composite respiratory vibration using the aligned segments; detect respiratory vibration information of the patient based on the determined composite respiratory vibration of claim 1 and identifying a first set of respiratory cycles of the plurality of respiratory cycles having a duration within a threshold using the received physiologic information cyclic with patient respiration; aligning segments of the vibration information corresponding to the first set of respiratory cycles, the segments associated with a desired portion of the respiratory cycle using a feature of the respiratory cycle; determining a composite respiratory vibration using the aligned segments; detecting respiratory vibration information of the patient based on the determined composite respiratory vibration) are basic mathematical calculations of claim 12) are like the analysis of “detecting and analyzing events in real-time from the plurality of data streams from the wide area based on at least one of limits, sensitivities and rates of change for one or more measurements from the data streams and dynamic stability metrics derived from analysis of the measurements from the data streams including at least one of frequency instability, voltages, power flows, phase angles, damping, and oscillation modes, derived from the phasor measurements and the other power system data sources in which the metrics are indicative of events, grid stress, and/or grid instability, over the wide area” of claim 12 of the patent at issue in Electric Power Group. (Electric Power Group at 1740). In this case and in Electric Power Group, “the claims are clearly focused on the combination of those abstract-idea processes. The advance they purport to make is a process of gathering and analyzing information of a specified content, then displaying the results, and not any particular assertedly inventive technology for performing those functions. They are therefore directed to an abstract idea.” (Electric Power Group at 1742). In this case and in Electric Power Group, the claims are simply drawn to abstract-idea processes for determining events. Id.
The applicant further contends that Claim 1 and 12 demonstrates a practical application. However, the practical application of an abstract idea alone does not satisfy § 101 unless it embodies a specific, inventive concept. Here, the claims still rely on abstract data processing techniques applied to physiological signals, which do not amount to an inventive concept sufficient to transform the abstract idea into patent-eligible subject matter.
While the applicant’s reference to CardioNet is noted, the claims in the present application differ significantly as they fail to recite specific technological improvements to respiratory vibration monitoring. Instead, they describe a desired result without demonstrating how the claimed invention improves the underlying technology. Therefore, the arguments and amendments presented are not persuasive, and the § 101 rejection is maintained.
112 Rejections
Applicant’s arguments, see page 10, filed 10/24/2024, with respect to the rejections of claims 3 and 13 under 35 U.S.C. 112(a) have been fully considered and are persuasive. Therefore, the rejections have been withdrawn.
103 Rejections
Applicant’s arguments, see pages 10-13, filed 10/24/2024, with respect to claims 1-6, 8, 10-15, 17, and 19-20 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. That is, there are new grounds of rejection that were necessitated by the claim amendments filed on 10/24/2024.
Applicant’s argument that, Claims 1 and 12 as amended, see pages 12-13 filed on 10/24/2024, distinguishes over the prior art by requiring both physiologic information cyclic with patient respiration and vibration information at higher frequencies.
Under 35 U.S.C. § 103, a claim is unpatentable if the differences between the claimed subject matter and the prior art are such that the subject matter as a whole would have been obvious to a person of ordinary skill in the art at the time of the invention. A combination of prior art references can demonstrate obviousness when the combined teachings disclose all claim limitations and there is a reasonable motivation to combine them.
The applicant argues that Claims 1 and 12 requires vibration information at frequency ranges distinct from those of physiologic information cyclic with patient respiration, implying that this limitation is not disclosed in the prior art. However, the prior art already discloses vibration information at higher frequencies, including those associated with coughing, as evidenced by Spina, Col. 3, Lines 5-17.
For example, Spina explicitly describes monitoring vibration frequencies both cyclic with respiration and at higher ranges associated with events such as coughing or other respiratory conditions. These higher frequency ranges overlap with the ranges recited in amended Claims 1 and 12. Additionally, the evidentiary reference Reichert et al., further supports this, specifying that the frequency ranges of coughing vibrations (50-3000 Hz, Reichert et al., Definition of terms, Cough sound) fall within the amended frequency range of Claims 1 and 12 (greater than 20 Hz). A person of ordinary skill in the art would have understood that monitoring both respiratory and higher frequency vibrations is an established practice in the field, and combining these teachings to achieve the claimed result would have been obvious.
The applicant’s argument fails to demonstrate how the amended claim introduces a novel or non-obvious distinction over the prior art. The claimed invention merely combines known practices—monitoring respiration and higher-frequency vibrations—without presenting a unique or inventive technological improvement.
The applicant's arguments regarding Claims 1 and 12 and their dependent claims are moot in light of the new grounds of rejection provided in the present Office action. The new rejection demonstrates that the cited prior art, in combination, discloses or renders obvious all limitations of Claims 1 and 12 and their dependents, including the claimed physiologic information cyclic with patient respiration and vibration information at higher frequencies.
Accordingly, the rejections of Claim 1 and 12 and its dependent claims are proper.
Applicant’s arguments, see pages 13-14, filed 10/24/2024, with respect to claims 7 and 16 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. That is, there are new grounds of rejection that were necessitated by the claim amendments filed on 10/24/2024.
Applicant’s arguments, see pages 13-14, filed 10/24/2024, with respect to claims 9 and 18 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. That is, there are new grounds of rejection that were necessitated by the claim amendments filed on 10/24/2024.
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 extension fee 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 date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to AARON R MERRIAM whose telephone number is (703) 756-5938. The examiner can normally be reached M-F 8:00 am - 5:00 pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jason Sims can be reached on (571)272-4867. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/AARON MERRIAM/Examiner, Art Unit 3791
/MATTHEW KREMER/Primary Examiner, Art Unit 3791
1 The slip opinion for this decision accompanies this Office Action.
2 The slip opinion for this decision accompanies this Office Action.
3 This decision accompanies this Office Action.
Prosecution Insights