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 .
Status of Claims
Claims 1-11 are currently pending and under consideration.
Priority
Should applicant desire to obtain the benefit of foreign priority under 35 U.S.C. 119(a)-(d) prior to declaration of an interference, a certified English translation of the foreign application must be submitted in reply to this action. 37 CFR 41.154(b) and 41.202(e).
Failure to provide a certified translation may result in no benefit being accorded for the non-English application.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on March 7, 2024 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Drawings
The drawings are objected to because:
The spec refers to element 110 as “a processor” starting in ¶[0020]. In Fig. 1, element 130 points to a box that reads “processor” however element 110 points to a box that reads “storage medium”.
The spec refers to element 120 as “a storage medium” starting in ¶[0020]. In Fig. 1, element 110 points to a box that reads “storage medium” however element 120 points to a box that contains the two modules.
The spec refers to element 130 as “a transceiver” starting in ¶[0020]. In Fig. 1, element 130 points to a box that reads “processor” not “transceiver” as the spec defines.
Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
In addition to Replacement Sheets containing the corrected drawing figure(s), applicant is required to submit a marked-up copy of each Replacement Sheet including annotations indicating the changes made to the previous version. The marked-up copy must be clearly labeled as “Annotated Sheets” and must be presented in the amendment or remarks section that explains the change(s) to the drawings. See 37 CFR 1.121(d)(1). Failure to timely submit the proposed drawing and marked-up copy will result in the abandonment of the application.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: “a data collection module” and “a computation module” in claim 1. MPEP 2181(I)(A) states the Federal Circuit determined that "the word 'module' does not provide any indication of structure because it sets forth the same black box recitation of structure for providing the same specified function as if the term ‘means’ had been used.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
“Data collection module” and “computation module” in ¶[0022] are interpreted as applications that can be executed by the processor, which is a computer application or a code.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 10 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 10 recites the limitation "the sampled signals" in lines 3-4. There is insufficient antecedent basis for this limitation in the claim. Earlier, claim 10 recited “the first sampled signals” therefore failing to provide adequate antecedent basis for “the sampled signals”. For the purposes of examination “the sampled signals” will be interpreted as “the first sampled signals”.
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 1-11 are rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract ideas of “decomposing the first cerebrovascular flow signal to obtain a first decomposed signal”; “sampling a plurality of first sampled signals from the first decomposed signal according to the respiration signal”; “generating a first characteristic signal according to an average of the first sampled signals”; and “determining whether to output a warning message according to the first characteristic signal” without significantly more.
Step 1
Claims 1 and 11 recite a device and a method, and therefore, they are a product and a method, and therefore fall within the statutory categories.
Step 2A, Prong 1
Claim 1 and 11 recite the limitations of decomposing the first cerebrovascular flow signal to obtain a first decomposed signal; sampling a plurality of first sampled signals from the first decomposed signal according to the respiration signal; generating a first characteristic signal according to an average of the first sampled signals; and determining whether to output a warning message according to the first characteristic signal. The limitations, as drafted, are a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind and as a mathematical calculation but for the recitation of “a transceiver”, “a storage medium storing a plurality of modules”, “a processor”, which is a computer processor, “a data collection module”, “obtaining a first cerebrovascular flow signal and a respiration signal”, and “a computation module”. That is, other than reciting “a transceiver”, “a storage medium storing a plurality of modules”, “a processor”, “a data collection module”, ”obtaining a first cerebrovascular flow signal and a respiration signal”, and “a computation module”, nothing in the claim precludes the steps from practically being performed in the human mind or as a mathematical concept. MPEP 2106.04(a)(2)(III) states that the courts consider a mental process (thinking) that "can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. MPEP 2106.04(a)(2)(I) states that claims to a ‘‘series of mathematical calculations based on selected information’’ are directed to abstract ideas. For example, aside from the “transceiver”, “storage medium storing a plurality of modules”, “processor”, “data collection module”, “obtaining a first cerebrovascular flow signal and a respiration signal”, and “computation module” language, the claim encompasses the user visually inspecting waveforms, using a mathematical decomposition to decompose the waveforms, lining up the decomposed signals with the respiratory waveform and sampling based on it, taking a mathematical average of the data, and mentally deciding if this average poses the need for warning the patient. These limitations are a mental process and mathematical calculations.
Step 2A, Prong 2
Claim 1 and 11 recite the additional element “obtaining a first cerebrovascular flow signal and a respiration signal”. Claim 1 recites additional elements “an electronic device”, “a transceiver”, “a storage medium storing a plurality of modules”, “a processor”, “a data collection module”, and “a computation module” to perform the abstract steps.
The system for evaluating a risk assessment of cerebrovascular disease consisting of the “transceiver”, “storage medium storing a plurality of modules”, “processor”, “data collection module”, and “computation module” read on a computer implemented system and are recited at a high level of generality, i.e., as a generic processor, performing a generic computer function of processing data. This generic processor limitation is no more than mere instructions to apply the exception using a generic computer component (see ¶[0021]). Accordingly, this additional limitation does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
The step of “obtaining a first cerebrovascular flow signal and a respiration signal” is recited at a high level of generality (i.e., The cerebrovascular flow signal may include but is not limited to signals such as a blood pressure (BP) signal, a blood flow velocity (BFV) signal, a maximum systolic flow velocity signal (i.e., a maximum blood flow velocity signal), or a minimum diastolic flow velocity signal (i.e., a minimum blood flow velocity signal). The blood flow velocity signal may include a BFV left (BFVL) signal or a BFV right (BFVR) signal. The respiration signal may include but is not limited to signals such as a carbon dioxide concentration signal in ¶[0025]) and amounts to no more than pre-solution activity gathering by the system.
Step 2B
As discussed with respect to Step 2A Prong Two, the additional elements in the claim amount to no more than mere instructions to apply the exception using a generic computer component and pre-solution activity gathering. The same analysis applies here in 2B, i.e., mere instructions to apply an exception on a generic computer cannot integrate a judicial except into a practical application at Step 2A or provide an inventive concept in Step 2B.
Under 2019 PEG, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be re-evaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The specification in ¶[0021] does not provide any indication that the computer is anything other than a generic, off-the-shelf computer component. Court decisions cited in MPEP 2106.05(d)(II) indicate that computer‐implemented processes not to be significantly more than an abstract idea (and thus ineligible) where the claim, as a whole, amounts to nothing more than generic computer functions merely used to implement an abstract idea, such as an idea that could be done by a human analog (i.e., by hand or by merely thinking). Accordingly, a conclusion that the generic computer functions merely being used to implement an abstract idea is well-understood, routine, conventional activity is supported under Berkheimer Option 2.
As discussed with respect to Step 2A Prong Two, “obtaining a first cerebrovascular flow signal and a respiration signal” is recited at a high level of generality (see ¶[0025]) which amounts to no more than pre-solution activity of data gathering by the system. This pre-solution activity of gathering cerebrovascular flow signals and respiration signals is well understood, routine, and conventional technology in the field: “The four universally recognized vital signs (body temperature, blood pressure, pulse, and respiratory rate) are regularly used to measure the body’s basic functions to help assess the general physical health of a person, give clues to possible diseases, and show progress toward recovery… Doppler technology displays velocity of blood flow” (Eymann, S. “Blood Flow: Life’s Quintessential Vital Sign?”. Transonic. 23 Sep 2015. https://blog.transonic.com/cardiothoracic-surgery/blood-flow-life-s-quintessential-vital-sign#:~:text=By%20Susan%20Eymann%2C%20MS23,EKG%2C%20CO%2C%20and%20BP., hereinafter referred to as “Eymann”). All uses of the recited abstract idea require the pre-solution of data gathering.
Dependent claims 2-10 further limit the process of decomposing the first cerebrovascular flow signal to obtain a first decomposed signal; sampling a plurality of first sampled signals from the first decomposed signal according to the respiration signal; generating a first characteristic signal according to an average of the first sampled signals; and determining whether to output a warning message according to the first characteristic signal without adding significantly more.
Claim 2 adds the limitation “wherein the respiration signal corresponds to carbon dioxide concentration”. This pre-solution activity of gathering carbon dioxide concentration signals is well understood, routine, and conventional technology in the field: “The response of CBF to changes in Pa CO 2 is defined as cerebrovascular reactivity to CO 2 (CVR) and is widely measured or analyzed in related research fields as one of the regulatory functions of cerebral circulation” (Ogoh, S. “Interaction between the respiratory system and cerebral blood flow regulation”. Journal of Applied Physiology. Vol.125:5; Nov. 2019; doi:10.1152/japplphysiol.00057.2019 pg 1198; hereinafter referred to as “Ogoh”). All uses of the recited abstract idea require the pre-solution of data gathering.
Claim 7 and 8 further limits “obtaining a first cerebrovascular flow signal and a respiration signal” with the limitations of “a blood pressure signal” and “a blood flow velocity signal”. This pre-solution activity of gathering blood pressure signals and blood flow velocity signals is well understood, routine, and conventional technology in the field: “The four universally recognized vital signs (body temperature, blood pressure, pulse, and respiratory rate) are regularly used to measure the body’s basic functions to help assess the general physical health of a person… Doppler technology displays velocity of blood flow” (Eymann). Further, “In many studies on CBF regulation, blood flow velocity in the middle cerebral artery (MCA V) has been measured as an index of anterior CBF by transcranial Doppler (TCD), commercial measurement equipment used worldwide” (Ogoh). All uses of the recited abstract idea require the pre-solution of data gathering.
Claim 9 further limits “obtaining a first cerebrovascular flow signal and a respiration signal” with the limitation of “wherein the first cerebrovascular flow signal comprises a pulsatility index signal, and the second cerebrovascular flow signal comprises a blood flow velocity signal”. This pre-solution activity of gathering pulsatility index and blood flow velocity signals is well understood, routine, and conventional technology in the field: “In many studies on CBF regulation, blood flow velocity in the middle cerebral artery (MCA V) has been measured as an index of anterior CBF by transcranial Doppler (TCD), commercial measurement equipment used worldwide” (Ogoh). Further, “The pulsatility index (PI) (also known as the Gosling index) is a calculated flow parameter in ultrasound, derived from the maximum, minimum, and mean Doppler frequency shifts during a defined cardiac cycle. Along with the resistive index (RI), it is typically used to assess the resistance in a pulsatile vascular system.” (Bell, D. “Pulsatility index (ultrasound)” Radiopaedia. 16 Jun 2020. https://radiopaedia.org/articles/pulsatility-index-ultrasound?lang=us). All uses of the recited abstract idea require the pre-solution of data gathering.
Therefore, claims 2-10 further limit the abstract idea already indicated in independent claim 1 without adding significantly more and they are ineligible for the same reasons provided for claim 1 above.
For these reasons, there is no inventive concept in the claims and thus they are ineligible.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 3-4, and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Hsu et al. (US 20220354437 A1, published Nov. 10, 2022, hereinafter referred to as “Hsu”) in view of Goodman (US 20030036685 A1, published Feb. 20, 2003, hereinafter referred to as “Goodman”).
Applicant cannot rely upon the certified copy of the foreign priority application to overcome this rejection because a translation of said application has not been made of record in accordance with 37 CFR 1.55. When an English language translation of a non-English language foreign application is required, the translation must be that of the certified copy (of the foreign application as filed) submitted together with a statement that the translation of the certified copy is accurate. See MPEP §§ 215 and 216.
Regarding claims 1 and 11, Hsu discloses an electronic device and a method of evaluating a risk assessment of cerebrovascular disease (“method for risk assessment of neurological disorders and an electronic device using the same method” in ¶[0002]), comprising: a transceiver (“transmitter” for collecting data in ¶[0005] and “transceiver” in claim 1); a storage medium storing a plurality of modules (“storage medium stores multiple modules” in ¶[0005]); and a processor coupled to the storage medium and the transceiver, and accessing and executing the modules (“the processor is coupled to the storage medium and the transformer, and assesses and performs multiple modules” in ¶[0005]), wherein the modules comprise: a data collection module obtaining a first cerebrovascular flow signal through the transceiver (“the data collection module obtains blood flow signal through the transmitter” in ¶[0005]); and a computation module decomposing the first cerebrovascular flow signal to obtain a first decomposed signal (“the calculation module performs signal decomposition on the blood flow signal to generate a first signal and a second signal” in ¶[0005]), generating a first characteristic signal according to an average of the first sampled signals (“generates a statistical parameter according to the correlation signal” in ¶[0005] and “the statistical parameter … is, for example, a mean” in ¶[0031]), and determining whether to output a warning message according to the first characteristic signal (“determines whether to output a warning message through the transmitter according to the statistical parameter” in ¶[0005]).
Hsu discloses generating “a correlation signal according to the modulation signal and the second signal” in ¶[0005], but does not explicitly disclose a data collection module obtains a respiration signal through the transceiver, and sampling a plurality of first sampled signal from the first decomposed signal according to the respiration signal.
Goodman’s invention relates to a physiological signal monitoring system and more particularly to a system which allows a user to determine various types of physiological information and which allows a user to electronically access this information over a communication network (¶[0002]). FIG. 9 is a flowchart showing the general process steps to obtain cardiovascular and respiratory data which are executed by the microcontroller of the user input device and the CPU of the processing device (¶[0086]). The rise and fall of blood pressure, on a beat to beat basis, in association with respiration is the simplest way to measure blood pressure and pulse wave velocity over a small range of values. Raising an arm and rising from a sitting position are ways to provoke larger changes in blood pressure at the wrist. In this way, it is possible to simultaneously sample blood pressure and pulse wave velocity enabling the derivation of the nonlinear relationship between these parameters for a particular user (¶[0220]).
Therefore, it would have been obvious to a person having ordinary skill in the art at the time of filing to sample the plurality of first sampled signals according to the respiration signal as taught by Goodman in the device of Hsu since Hsu’s device is capable of the sampling blood pressure and velocity in association with the respiratory signal is the simplest way to measure over a small range.
Regarding claim 3, Hsu discloses wherein the computation module decomposes the first cerebrovascular flow signal into a plurality of intrinsic mode function signals according to empirical mode decomposition, and selects one of the intrinsic mode function signals as the first decomposed signal (“the calculation module may perform empirical mode decomposition method of the blood flow signal S0 to generate the signal S1 and the signal S2. The signal S1 is an intrinsic mode signal” in ¶[0027]).
Regarding claim 4, Hsu does not teach wherein the computation module obtains a respiration frequency according to the respiration signal, and selecting the one of the intrinsic mode function signals that matches the respiration frequency as the first decomposed signal.
Goodman also teaches it is preferable to use the respiration frequency extraction technique to obtain an accurate estimate of the entire signal contour shape of the reflected wave components originating in the abdominal aorta (¶[0176]). It is possible to use signal extraction techniques to remove the components which do not vary with breathing. This information can then be used for calculation of cardiovascular parameters such as aortic pulse wave velocity (¶[0178]).
Therefore, it would have been obvious to a person having ordinary skill in the art at the time of filing to obtain a respiration frequency and select the IMF that matches the respiration frequency as taught by Goodman in the device of Hsu and Goodman in order to remove components that do not vary with breathing.
Claims 1, 3-4, and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Lo et al. (US 8211022 B2, published Jul. 3, 2012, hereinafter referred to as “Lo”) in view of van Drongelen (van Drongelen. W. "4 - Signal Averaging", Signal Processing for Neuroscientists, Academic Press, 2007, P. 55-70, ISBN 9780123708670, https://doi.org/10.1016/B978-012370867-0/50004-8. (https://www.sciencedirect.com/science/article/pii/B9780123708670500048) , hereinafter referred to as “van Drongelen”), and further in view of Goodman (US 20030036685 A1, published Feb. 20, 2003, hereinafter referred to as “Goodman”).
Regarding claims 1 and 11, Lo discloses an electronic device and a method of evaluating a risk assessment of cerebrovascular disease (“method for dynamic cerebral autoregulation assessment” in Col. 1 ln. 40-41 and Fig. 1 “dynamic cerebral autoregulation assessment system 100” in Col. 3 ln. 47-48), comprising: a transceiver (Fig. 1 “probes 120, 130 can send sensing signals to the analyzer 110” in Col. 3 ln. 57-58); a storage medium storing a plurality of modules (“algorithm can be pre-stored in a computer memory” in Col. 3 ln. 64-65) and a processor coupled to the storage medium and the transceiver, and accessing and executing the modules (Fig. 1 “The analyzer 110 also includes a computer processor that is configured to process and analyze the sensing signals” in Col. 1 ln. 61-63), wherein the modules comprise: a data collection module obtaining a first cerebrovascular flow signal through the transceiver (“acquiring a blood pressure signal ” in Col. 1 ln. 42); and a computation module decomposing the first cerebrovascular flow signal to obtain a first decomposed signal (“decomposing the BP signal into a first group of intrinsic mode functions (IMFs)” in Col. 1 ln. 45-46), and determining whether to output a warning message (“a pathological condition can be determined when a CA index exceeds or falls below a predetermined condition” in Col. 6 ln. 4-5).
Lo does not disclose generating a first characteristic signal according to an average of the first sampled signals and determining whether to output a warning message according to the first characteristic signal.
van Drongelen discloses that signal averaging is an important technique that allows estimation of small amplitude signals that are buried in noise (page 55).
Therefore, it would have been obvious to a person having ordinary skill in the art at the time of filing to average the first sampled signals and issue a warning according to the averaged signal as taught by van Drongelen in the device and method of Lo because averaging a signal improves it by further reduce noise from the signal.
Lo does not disclose a data collection module obtains a respiration signal through the transceiver, and sampling a plurality of first sampled signal from the first decomposed signal according to the respiration signal.
Goodman’s invention relates to a physiological signal monitoring system and more particularly to a system which allows a user to determine various types of physiological information and which allows a user to electronically access this information over a communication network (¶[0002]). FIG. 9 is a flowchart showing the general process steps to obtain cardiovascular and respiratory data which are executed by the microcontroller of the user input device and the CPU of the processing device (¶[0086]). The rise and fall of blood pressure, on a beat to beat basis, in association with respiration is the simplest way to measure blood pressure and pulse wave velocity over a small range of values. Raising an arm and rising from a sitting position are ways to provoke larger changes in blood pressure at the wrist. In this way, it is possible to simultaneously sample blood pressure and pulse wave velocity enabling the derivation of the nonlinear relationship between these parameters for a particular user (¶[0220]).
Therefore, it would have been obvious to a person having ordinary skill in the art at the time of filing to sample the plurality of first sampled signals according to the respiration signal as taught by Goodman in the device of Lo since Lo’s device is capable of sampling the blood pressure and velocity in association with the respiratory signal is the simplest way to measure over a small range.
Regarding claim 3, Lo discloses wherein the computation module decomposes the first cerebrovascular flow signal into a plurality of intrinsic mode function signals according to empirical mode decomposition (“physiological signals can be decomposed into intrinsic mode functions (IMFs) by the ensemble empirical mode decomposition technique” in Col. 4 ln. 30-32), and selects one of the intrinsic mode function signals as the first decomposed signal (“A characteristic BP, BFVL or BFVR IMF having characteristic frequency in the interesting frequency range can be selected for CA assessment” in Col. 5 ln. 1-3).
Regarding claim 4, Lo does not teach wherein the computation module obtains a respiration frequency according to the respiration signal, and selecting the one of the intrinsic mode function signals that matches the respiration frequency as the first decomposed signal.
Goodman also teaches it is preferable to use the respiration frequency extraction technique to obtain an accurate estimate of the entire signal contour shape of the reflected wave components originating in the abdominal aorta (¶[0176]). It is possible to use signal extraction techniques to remove the components which do not vary with breathing. This information can then be used for calculation of cardiovascular parameters such as aortic pulse wave velocity (¶[0178]).
Therefore, it would have been obvious to a person having ordinary skill in the art at the time of filing to obtain a respiration frequency and select the IMF that matches the respiration frequency as taught by Goodman in the device of Lo in view of van Drongelen in further view of Goodman in order to remove components that do not vary with breathing.
Claim 2 is rejected under 35 U.S.C. 103 as being unpatentable over Hsu in view of Goodman (hereinafter referred to as “modified Hsu”) as applied to claim 1 above, and further in view of Zhang (US 20140180037 A1, published Jun. 26, 2014, hereinafter referred to as “Zhang”).
Regarding claim 2, modified Hsu teaches the electronic device of evaluating a risk assessment of cerebrovascular disease of claim 1.
Modified Hsu does not disclose wherein the respiration signal corresponds to carbon dioxide concentration and comprises a first trough and a second trough adjacent to the first trough, and the computation module samples one of the first sampled signals from the first decomposed signal according to the first trough and the second trough.
Zhang’s invention relates to systems and methods for analyzing biological tissue functions. The device includes a patient monitor with a respiratory monitor for monitoring respiration signal waveforms associated with the patient. For example, it may include a capnograph for measuring the carbon dioxide content in inspired and expired air from the patient. Respiration signal waveforms may be derived from such respiration measurements (¶[0032]). The invention detects windows where waves are expected and peaks and/or valleys within the windows may be identified. The segmentation may be performed by synchronizing a detection window with respect to detected cycle start or end points. Referring to FIG. 4, for instance, a cycle start point 410 may be defined by a maximum peak of the signal and the cycle end point 412 may be defined by the next consecutive maximum peak of the signal. Alternatively, the cycle start and end points may be the minimum valleys (troughs) of the signal, the points where the signal crosses the baseline value (in a predetermined wave window, for example) or any other pre-defined points (¶[0046]). Signal data analysis unit may segment, analyze and use ECG and blood pressure signals in determining synchronized signal time durations and using the ECG and blood pressure signal parameters in combination with the SPO2 data in evaluating patient health status. The received ECG and blood pressure signals may also be analyzed to determine variations in signal parameters indicative of substantial change (¶[0059]). In Fig. 3, the analysis unit determines whether there is an abnormality. The abnormality may be, for example, a cardiac medical condition such as cardiac arrhythmia, cardiac tissue and electrophysiological-hemodynamic malfunctions, etc. In some implementations, the abnormality is identified based on baseline values and threshold values (¶[0061]).
Therefore, it would have been obvious to a person having ordinary skill in the art at the time of filing to use carbon dioxide concentration with first and second troughs and sample the decomposed samples according to the troughs as taught by Zhang in the device of modified Hsu because it can be analyzed to determine variations with substantial change which can be used to determine cardiac medical conditions.
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over modified Hsu as applied to claim 1 above, and further in view of Thrane et al. (Thrane, N. et al. “Application Note: Practical use of the “Hilbert transform”.” Internet Archive. 30 Aug 2017. https://web.archive.org/web/20170830051255/https://www.bksv.com/media/doc/bo0437.pdf , hereinafter referred to as “Thrane”).
Regarding claim 5, modified Hsu teaches the electronic device of evaluating a risk assessment of cerebrovascular disease of claim 1.
Modified Hsu does not teach wherein the computation module performs Hilbert transform on the average of the first sampled signals to generate the first characteristic signal.
Thrane teaches that by using the Hilbert transform, the rapid oscillations can be removed from the signal to produce a direct representation of the envelope alone (pg. 1).
Therefore, it would have been obvious to a person having ordinary skill in the art at the time of filing to perform a Hilbert transform as taught by Thrane on the first sampled signals to generate the first characteristic signals of modified Hsu in order to remove oscillations in the signal.
Claims 6-7 are rejected under 35 U.S.C. 103 as being unpatentable over modified Hsu as applied to claim 1 above, and further in view of Lo.
Regarding claim 6, modified Hsu teaches the electronic device for evaluating a risk assessment of cerebrovascular disease of claim 1.
Modified Hsu does not disclose wherein the data collection module obtains a second cerebrovascular flow signal through the transceiver, wherein the computation module generates a second characteristic signal according to the second cerebrovascular flow signal, and determines whether to output the warning message according to the first characteristic signal and the second characteristic signal.
Lo’s invention relates to assessment of dynamic cerebral autoregulation, specifically, the assessment of dynamic cerebral autoregulation function by analyzing multiple physiological signals (Col. 1, ln. 6-9). The method includes acquiring a blood pressure signal (first cerebrovascular signal); acquiring a blood flow velocity signal (second cerebrovascular signal); decomposing the BP signal into a first group of intrinsic mode functions (IMFs); decomposing the BFV signal into a second group of IMFs; selecting a second characteristic IMF from the second group of IMFs; calculating a time sequence of instantaneous phase difference between the first characteristic IMF and the second characteristic IMF; computing an average of the instantaneous phase difference in the time sequence; and identifying a pathological condition in the individual if the average of the instantaneous phase difference satisfies a predetermined criterion (Col. 1, ln. 41-59).
Therefore, it would have been obvious to a person having ordinary skill in the art at the time of filing to obtain a second cerebrovascular flow signal, generate a second characteristic signal, and determine whether to output the warning message according to the two signals as taught by Lo in the device of modified Hsu because the method provides more reliable, accurate assessment of cerebral autoregulation and enables accurate diagnosis while being non-invasive and less expensive than other techniques (Col. 2, ln. 56-62).
Regarding claim 7, Hsu does not disclose wherein the first cerebrovascular flow signal comprises a blood pressure signal and the second cerebrovascular flow signal comprises a blood flow velocity signal, wherein the computation module calculates a phase difference between the first characteristic signal and the second characteristic signal, and determines to output the warning message in response to an absolute difference between the phase difference and a reference phase difference being greater than a threshold.
Lo teaches acquiring a blood pressure signal (first cerebrovascular signal) and acquiring a blood flow velocity signal (second cerebrovascular signal) (Col. 1, ln. 42-44). The system involves calculating a time sequence of instantaneous phase difference between the first characteristic IMF and the second characteristic IMF; computing an average of the instantaneous phase difference in the time sequence; and identifying a pathological condition in the individual if the average of the instantaneous phase difference satisfies a predetermined criterion (Col. 1, ln. 53-59). The phases of BFV oscillations follow BP oscillations more closely for patients under pathological conditions compared to healthy individuals. In other words, the BFV oscillations have smaller phase shift behind the BP oscillations for these pathological conditions (Col. 5, ln. 50-54). In general, a pathological condition can be determined when a cerebral autoregulatory index exceeds or falls below a predetermined condition (Col. 6, ln. 3-5).
Therefore, it would have been obvious to a person having ordinary skill in the art at the time of filing to obtain a blood pressure signal and a blood flow velocity signal, calculate the phase difference between their characteristic signals, and issue a warning based on the absolute difference being greater than a threshold as taught by Lo in the device of modified Hsu in order to diagnose a cerebral autoregulatory condition.
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Hsu in view of Goodman in further view of Lo as applied to claim 6 above (hereinafter referred to as “modified Hsu”), and even further in view of De Haan (US 20200121262 A1, published Apr. 23, 2020, hereinafter referred to as “De Haan”).
Regarding claim 8, modified Hsu teaches the electronic device of evaluating a risk assessment of cerebrovascular disease of claim 6. Lo also teaches wherein the first cerebrovascular flow signal comprises a blood flow velocity signal (acquiring a blood flow velocity signal in Col. 1, ln. 43-44) and the second cerebrovascular flow signal comprises a difference between a maximum blood flow velocity and a minimum blood flow velocity (“IMFs can be obtained by decomposing the BFVL and BFVR signals” in Col. 4 ln 54-55 the same way the inventors obtain blood pressure signals which are “obtained by tracing the envelope of local maxima and local minima in the blood pressure waveform” in Col. 4 ln. 38-40).
Modified Hsu fails to disclose wherein the computation module determines to output the warning message in response to a correlation coefficient between a mean of the first characteristic signal and the second characteristic signal being less than zero.
De Haan’s invention relates to a device for processing physiological signals of a subject as well as a corresponding method and computer program, further to a system for monitoring a health parameter of a subject (¶[0001]). In the device, relative weights are assigned to individual cardiac cycles based on a trust metric or trust score derived from correlation with neighboring cycles (¶[0100]). In an embodiment, it is thus proposed to define trust weights w as the positive Pearson correlation coefficients between a window of cardiac correlation coefficients between a window of cardiac cycles and the median cycle of the DCA signal (¶[0123]) where DCA is measured and ensemble-averaged waveform for a given image data (¶[0101]). Referring to Fig. 14, in step 1403 a correlation coefficient between the template obtained from step 1402 and the respective individual cycles obtained from step 1401 can be estimated. As indicated by the decision step 1404 the trust weight w for sample n is set to zero in step 1405 if the correlation coefficient is negative (less than zero) (¶[0124]).
Therefore, it would have been obvious to a person having ordinary skill in the art at the time of filing to output a warning message when the correlation coefficient between the mean of the first signal and the second signal is less than zero as taught by De Haan in the device of modified Hsu since a value less than zero is not preferred.
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over modified Hsu as applied to claim 6 above, and further in view of Frost (Frost, J. “Coefficient of Variation in Statistics”. Statistics By Jim. Internet Archive. 24 Nov 2020. https://web.archive.org/web/20201124033225/https://statisticsbyjim.com/basics/coefficient-variation/ , hereinafter referred to as “Frost”) and Wijnhoud et al. (Wijnhoud, A. et al. “The prognostic value of pulsatility index, flow velocity, and their ratio, measured with TCD ultrasound, in patients with a recent TIA or ischemic stroke.” Acta Neurologica Scandinavica. Vol.124 Issue 4. Abstract. 4 Jan 2011. https://doi.org/10.1111/j.1600-0404.2010.01462.x , hereinafter referred to as “Wijnhoud”).
Regarding claim 9, modified Hsu teaches the electronic device of evaluating a risk assessment of cerebrovascular disease of claim 6. Lo also teaches wherein the second cerebrovascular flow signal comprises a blood flow velocity signal (acquiring a blood flow velocity signal in Col. 1, ln. 43-44).
Modified Hsu does not disclose wherein the first cerebrovascular flow signal comprises a pulsatility index signal, wherein the computation module determines to output the warning message in response to a ratio between a first coefficient of variation of the first characteristic signal and a second coefficient of variation of the second characteristic signal being less than one.
Frost teaches that a coefficient of variation is a standardized, unitless measure that allows you to compare variability between disparate groups and characteristics. When measurements use different scales, you can’t compare them directly and any time you want to assess the variability of inherently different characteristics, you’ll need to use a relative measure of variability, such as the coefficient of variability.
Wijnhoud discloses the prognostic value of pulsatility index, flow velocity, and their ratio, measured with TCD ultrasound, in patients with a recent TIA or ischemic stroke (abstract). Increased flow velocities, and combinations of low mean flow velocity (MFV) and a high pulsatility index (PI) (one value is therefore less than the other and the ratio is less than one) are associated with intracranial arterial disease (background). MFV and the PI–MFV ratio in the MCA are independent prognostic factors for recurrent vascular events (conclusion).
Therefore, it would have been obvious to a person having ordinary skill in the art at the time of filing to issue a warning message in response to a ratio between the first coefficient of variation (CV) (in this case based on pulsatility index) and the second CV being less than one as taught by Wijnhoud and Frost in the device of modified Hsu in order to prognose vascular events in patients with recent ischemic stroke using a relative measure of variability.
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over modified Hsu as applied to claim 1 above, and further in view of ScienceDirect (“Interpolation”. ScienceDirect. https://www.sciencedirect.com/topics/earth-and-planetary-sciences/interpolation) and MathWorks (“Measuring Signal Similarities”. MathWorks. Internet Archive. 02 May 2015. https://web.archive.org/web/20150502193133/https://www.mathworks.com/help/signal/ug/measuring-signal-similarities.html ).
Regarding claim 10, modified Hsu teaches the electronic device of evaluating a risk assessment of cerebrovascular disease of claim 1.
Modified Hsu does not disclose wherein before the average of the first sampled signals is calculated, the computation module performs interpolation computation on at least one of the first sampled signals, so that each of the first sampled signals have a same length.
ScienceDirect defines interpolation as a method for estimating the value of a signal or function at points where it is not directly measured, often used to address unreliable data points.
MathWorks teaches that different signal lengths prevent you from calculating the difference between two signals but this can easily be remedied by extracting the common part of signals. Furthermore, it is not always necessary to equalize lengths. Cross-correlation can be performed between signals with different lengths, but it is essential to ensure that they have identical sampling rates.
Therefore, it would have been obvious to a person having ordinary skill in the art at the time of filing to have used interpolation to make the signals the same length in the device of modified Hsu since it is a known method of addressing unreliable data points and having the same length signals allows the comparison of two signals as taught by ScienceDirect and MathWorks.
Conclusion
The following prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Schaafsma (US 20070293760 A1, published Dec. 20, 2007) - device for risk assessment of cerebrovascular disease; measures velocity and blood pressure and normalizes them; includes averaging and comparisons
Brady (CA 2677257 A1, published Aug. 14, 2008) - oxygen measurements correlated to bp for brain diagnosis; includes sampling bp and venous oxygen content
Schneider et al. (US 20090177102 A1, published Jul. 9, 2009) – collection of respiration and blood pressure
Ferren et al. (US 20090292222 A1, published Nov. 26, 2009) - sending a warning message based on respiration
Osorio (US 20150080670 A1, published Mar. 19, 2015) – system related to risk of death for epilepsy obtaining cardiac data and issuing a warning based on indices
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/E.N.C./ Patent Examiner, Art Unit 3792
/AMANDA L STEINBERG/ Examiner, Art Unit 3792