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 .
Priority
The following claimed benefit is acknowledged: The instant application, filed on 15 March 2023, claims foreign priority to JP Application No. 2020-155516, filed on 16 September 2020.
Information Disclosure Statement
The Information Disclosure Statement (lDS) submitted on 03/15/2023 is in compliance with the provisions of 37 CFR 1.97 and has been considered.
Claim Objections
Applicant is advised that should claim 1 be found allowable, claim 10 will be objected to under 37 CFR 1.75 as being a substantial duplicate thereof. When two claims in an application are duplicates or else are so close in content that they both cover the same thing, despite a slight difference in wording, it is proper after allowing one claim to object to the other as being a substantial duplicate of the allowed claim. See MPEP § 608.01(m).
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 1-3 and 7-13 are rejected under 35 U.S.C. 103 as being unpatentable over Perchoux (“Current Developments on Optical Feedback Interferometry as an All-Optical Sensor for Biomedical Applications,” published 2016)1 in view of Scalise (“Self-mixing feedback in a laser diode for intra-arterial optical blood velocimetry,” published 2001)2.
Regarding claim 1, Perchoux discloses a measurement device (Fig. 9), comprising:
a light emitter configured to irradiate, with light, an irradiation target having a fluid flowing in an internal space of the irradiation target (p. 10, § 3.1.2, “laser diode” irradiating “fluid flow” in a “PDMS fluidic channel”; Fig. 9);
a light receiver (p. 10, § 3.1.2, “photodiode”) configured to receive coherent light including light scattered by the irradiation target and output a signal corresponding to an intensity of the coherent light (pp. 2 & 9, §§ 1 & 3.1.1, employing “coherent detection” based on “single scattering or multiple scattering” feedback from fluid “causing significant change in signal power”); and
a computation processor (p. 10, § 3.1.2, “A/D card connected to a PC”) configured to generate a frequency spectrum for a temporal change in a signal strength of the signal output from the light receiver and calculate (Fig. 12b, frequency spectrum of detected signal),
based on the frequency spectrum, a calculation value for a flow state of the fluid flowing in the internal space of the irradiation target (p. 12, § 3.2.1, Equation 6, M), wherein
the computation processor generates a first frequency spectrum of the signal output from the light receiver with the fluid in a first flow state (p. 12, § 3.2.1, Equation 6, OFIflow),
generates a second frequency spectrum of the signal output from the light receiver with the fluid in a second flow state in which the fluid has a flow rate lower than in the first flow state (p. 12, § 3.2.1, Equation 6, OFInoflow), and
calculates a usable frequency range to calculate the calculation value […] (p. 12, § 3.2.1, Equation 6, usable frequency range from f = 0 to f = Fs/2, where maximum frequency is determine based on calculating the Nyquist frequency Fs/2 as naturally recognized by the skilled artisan (see, e.g., Wolfram (2019)3).
Although Perchoux discloses determining a usable frequency range based on the ADC sampling Nyquist frequency, Perchoux does not disclose: [calculating a usable frequency range] “based on a comparison between the first frequency spectrum and the second frequency spectrum.” However, Scalise teaches calculating a usable frequency based on the frequency spectra difference between a first flow state and a second no-flow state in Fig. 13 & p. 4613. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the calculation of usable frequency range of Perchoux with the teachings of Scalise with a reasonable expectation for success in order to isolate the frequency at which flow-induced Doppler components become indistinguishable from a no-flow baseline, enabling the capture of the full band of meaningful Doppler information while excluding noise-dominant background, thereby yielding an optical measurement device with improved measurement robustness and accuracy (Scalise, p. 4613, col. 2).
Regarding claim 2, Perchoux in view of Scalise teaches the measurement device of claim 1, and further teaches: wherein the first flow state is a state in which the flow rate of the fluid is set to a maximum value in a controllable range (Perchoux, p. 13, § 3.2.2 and Figs. 14d & 15, M measured for flow rate of 8 mL/min, representing the highest flow rate in a controllable range scaled from zero to eight).
Regarding claim 3, Perchoux in view of Scalise teaches the measurement device of claim 1, and further teaches: wherein the second flow state is a state in which the flow rate of the fluid is set to zero (Perchoux, Fig. 12b, “absence of flow (green)”; and similarly, Scalise, p. 4613, col. 2, “with no flow”).
Regarding claim 7, Perchoux in view of Scalise teaches the measurement device of claim 1, and further teaches: further comprising: an output device configured to visually output the calculation value calculated by the computation processor (Perchoux, Fig. 16; p. 15, § 3.2.3, “front panel” display).
Regarding claim 8, Perchoux in view of Scalise teaches the measurement device of claim 1, and further teaches: wherein the computation processor calculates a flow quantitative value quantitatively indicating the flow state of the fluid based on the calculation value (Perchoux, p. 15, § 3.2.3, M used for “real-time monitoring of time-dependent flows”).
Regarding claim 9, Perchoux in view of Scalise teaches the measurement device of claim 8, and further teaches:an output device configured to visually output the flow quantitative value calculated by the computation processor (Perchoux, Fig. 16; p. 15, § 3.2.3, “front panel” display).
Regarding claim 10, Perchoux discloses a measurement system (Fig. 9), comprising:
a light emitter configured to irradiate, with light, an irradiation target having a fluid flowing in an internal space of the irradiation target (p. 10, § 3.1.2, “laser diode” irradiating “fluid flow” in a “PDMS fluidic channel”; Fig. 9);
a light receiver (p. 10, § 3.1.2, “photodiode”) configured to receive coherent light including light scattered by the irradiation target and output a signal corresponding to an intensity of the coherent light (pp. 2 & 9, §§ 1 & 3.1.1, employing “coherent detection” based on “single scattering or multiple scattering” feedback from fluid “causing significant change in signal power”); and
a computation processor (p. 10, § 3.1.2, “A/D card connected to a PC”) configured to generate a frequency spectrum for a temporal change in a signal strength of the signal output from the light receiver and calculate (Fig. 12b, frequency spectrum of detected signal),
based on the frequency spectrum, a calculation value for a flow state of the fluid flowing in the internal space of the irradiation target (p. 12, § 3.2.1, Equation 6, M), wherein
the computation processor generates a first frequency spectrum of the signal output from the light receiver with the fluid in a first flow state (p. 12, § 3.2.1, Equation 6, OFIflow),
generates a second frequency spectrum of the signal output from the light receiver with the fluid in a second flow state in which the fluid has a flow rate lower than in the first flow state (p. 12, § 3.2.1, Equation 6, OFInoflow), and
calculates a usable frequency range to calculate the calculation value […] (p. 12, § 3.2.1, Equation 6, usable frequency range from f = 0 to f = Fs/2, where maximum frequency is determine based on calculating the Nyquist frequency Fs/2 as naturally recognized by the skilled artisan (see, e.g., Wolfram (2019)4).
Although Perchoux discloses determining a usable frequency range based on the ADC sampling Nyquist frequency, Perchoux does not disclose: [calculating a usable frequency range] “based on a comparison between the first frequency spectrum and the second frequency spectrum.” However, Scalise teaches calculating a usable frequency based on the frequency spectra difference between a first flow state and a second no-flow state in Fig. 13 & p. 4613. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the calculation of usable frequency range of Perchoux with the teachings of Scalise with a reasonable expectation for success in order to isolate the frequency at which flow-induced Doppler components become indistinguishable from a no-flow baseline, enabling the capture of the full band of meaningful Doppler information while excluding noise-dominant background, thereby yielding an optical measurement system with improved measurement robustness and accuracy (Scalise, p. 4613, col. 2).
Regarding claim 11, Perchoux in view of Scalise teaches the measurement device of claim 1, and further teaches: a non-transitory computer-readable recording medium storing a program executable by a processor included in a measurement device to cause the measurement device to function as the measurement device according to claim 1 (Perchoux, p. 15, § 3.2.3, MATLAB software as implemented on an A/D card connected to a PC; p. 10, § 3.1.2).
Regarding claim 12, Perchoux discloses a calibration method for a measurement device, the method comprising:
receiving, with a light receiver (p. 10, § 3.1.2, “photodiode”), coherent light including light scattered by an irradiation target (pp. 2 & 9, §§ 1 & 3.1.1, employing “coherent detection” based on “single scattering or multiple scattering” feedback from fluid “causing significant change in signal power”) while irradiating, with a light emitter, the irradiation target having a fluid flowing in an internal space of the irradiation target (p 10, § 3.1.2, “laser diode” irradiating “fluid flow” in a “PDMS fluidic channel”; Fig. 9) in a first flow state with light (Fig. 12b, “circulating fluid (blue)”),
generating, with a computation processor (p. 10, § 3.1.2, “A/D card connected to a PC”), a first frequency spectrum for a temporal change in a signal strength of a signal corresponding to an intensity of the coherent light (p. 12, § 3.2.1, Equation 6, OFIflow; see further Fig. 12b, first frequency spectrum plotted in blue),
receiving, with the light receiver (p. 10, § 3.1.2, “photodiode”), coherent light including light scattered by the irradiation target (pp. 2 & 9, §§ 1 & 3.1.1, employing “coherent detection” based on “single scattering or multiple scattering” feedback from fluid “causing significant change in signal power”) while irradiating, with the light emitter, the irradiation target having the fluid in the internal space of the irradiation target (p 10, § 3.1.2, “laser diode” irradiating “fluid flow” in a “PDMS fluidic channel”; Fig. 9) in a second flow state with light, the second state being a state in which the fluid has a flow rate lower than in the first flow state (Fig. 12b, “absence of flow (green)”), and
generating, with the computation processor (p. 10, § 3.1.2, “A/D card connected to a PC”), a second frequency spectrum for a temporal change in a signal strength of a signal corresponding to an intensity of the coherent light (p. 12, § 3.2.1, Equation 6, OFInoflow measured in situ; Fig. 12b, second frequency spectrum plotted in green); and
calculating, with the computation processor (p. 10, § 3.1.2, “A/D card connected to a PC”), a usable frequency range (p. 12, § 3.2.1, Equation 6, usable frequency range from f = 0 to f = Fs/2, where maximum frequency is determine based on calculating the Nyquist frequency Fs/2 as naturally recognized by the skilled artisan (see, e.g., Wolfram (2019)5) to calculate a calculation value for a flow state of the fluid flowing in the internal space of the irradiation target (p. 12, § 3.2.1, Equation 6, M) […].
Although Perchoux discloses determining a usable frequency range based on the ADC sampling Nyquist frequency, Perchoux does not disclose: [calculating a usable frequency range] “based on a comparison between the first frequency spectrum and the second frequency spectrum.” However, Scalise teaches calculating a usable frequency based on the frequency spectra difference between a first flow state and a second no-flow state in Fig. 13 & p. 4613. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the calculation of usable frequency range of Perchoux with the teachings of Scalise with a reasonable expectation for success in order to isolate the frequency at which flow-induced Doppler components become indistinguishable from a no-flow baseline, enabling the capture of the full band of meaningful Doppler information while excluding noise-dominant background, thereby yielding a method with improved measurement robustness and accuracy (Scalise, p. 4613, col. 2).
Regarding claim 13, Perchoux in view of Scalise teaches the measurement device of claim 2, and further teaches: wherein the second flow state is a state in which the flow rate of the fluid is set to zero (Perchoux, Fig. 12b, “absence of flow (green)”; and similarly, Scalise, p. 4613, col. 2, “with no flow”).
Claims 4 and 14-16 are rejected under 35 U.S.C. 103 as being unpatentable over Perchoux in view of Scalise further in view of Christian (US20130215410A1).
Regarding claim 4, Perchoux in view of Scalise teaches the measurement device of claim 1, and further teaches: a converter configured to convert the signal output from the light receiver from an analog signal to a digital signal (Perchoux, p. 4, § 2.1.2, “oscilloscope digitizes the analog signal from the photodiode and sends the digitized signal to a computer, where further processing is performed”), […]. Perchoux in view of Scalise does not teach: “wherein the computation processor calculates a sampling rate in the converter based on the usable frequency range.” However, Christian teaches in ¶¶ 40 and 90 the selection of a sampling rate based on the maximum usable Doppler frequency range. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the converter of Perchoux in view of Scalise such that its sampling rate was based on the maximum usable Doppler frequency range as taught by Christian with a reasonable expectation for success in order to satisfy the Nyquist criterion for the full range of relevant Doppler frequencies so that the digitized signal preserves the entire Doppler spectrum without aliasing, thereby providing more accurate spectral processing and flow measurements across the full operating range of flow rates (Christian, ¶¶ 40 and 90).
Regarding claim 14, Perchoux in view of Scalise teaches the measurement device of claim 2, and further teaches: a converter configured to convert the signal output from the light receiver from an analog signal to a digital signal (Perchoux, p. 4, § 2.1.2, “oscilloscope digitizes the analog signal from the photodiode and sends the digitized signal to a computer, where further processing is performed”), […]. Perchoux in view of Scalise does not teach: “wherein the computation processor calculates a sampling rate in the converter based on the usable frequency range.” However, Christian teaches in ¶¶ 40 and 90 the selection of a sampling rate based on the maximum usable Doppler frequency range. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the converter of Perchoux in view of Scalise such that its sampling rate was based on the maximum usable Doppler frequency range as taught by Christian with a reasonable expectation for success in order to satisfy the Nyquist criterion for the full range of relevant Doppler frequencies so that the digitized signal preserves the entire Doppler spectrum without aliasing, thereby providing more accurate spectral processing and flow measurements across the full operating range of flow rates (Christian, ¶¶ 40 and 90).
Regarding claim 15, Perchoux in view of Scalise teaches the measurement device of claim 3, and further teaches: a converter configured to convert the signal output from the light receiver from an analog signal to a digital signal (Perchoux, p. 4, § 2.1.2, “oscilloscope digitizes the analog signal from the photodiode and sends the digitized signal to a computer, where further processing is performed”), […]. Perchoux in view of Scalise does not teach: “wherein the computation processor calculates a sampling rate in the converter based on the usable frequency range.” However, Christian teaches in ¶¶ 40 and 90 the selection of a sampling rate based on the maximum usable Doppler frequency range. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the converter of Perchoux in view of Scalise such that its sampling rate was based on the maximum usable Doppler frequency range as taught by Christian with a reasonable expectation for success in order to satisfy the Nyquist criterion for the full range of relevant Doppler frequencies so that the digitized signal preserves the entire Doppler spectrum without aliasing, thereby providing more accurate spectral processing and flow measurements across the full operating range of flow rates (Christian, ¶¶ 40 and 90).
Regarding claim 16, Perchoux in view of Scalise teaches the measurement device of claim 13, and further teaches: a converter configured to convert the signal output from the light receiver from an analog signal to a digital signal (Perchoux, p. 4, § 2.1.2, “oscilloscope digitizes the analog signal from the photodiode and sends the digitized signal to a computer, where further processing is performed”), […]. Perchoux in view of Scalise does not teach: “wherein the computation processor calculates a sampling rate in the converter based on the usable frequency range.” However, Christian teaches in ¶¶ 40 and 90 the selection of a sampling rate based on the maximum usable Doppler frequency range. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the converter of Perchoux in view of Scalise such that its sampling rate was based on the maximum usable Doppler frequency range as taught by Christian with a reasonable expectation for success in order to satisfy the Nyquist criterion for the full range of relevant Doppler frequencies so that the digitized signal preserves the entire Doppler spectrum without aliasing, thereby providing more accurate spectral processing and flow measurements across the full operating range of flow rates (Christian, ¶¶ 40 and 90).
Allowable Subject Matter
Claims 5-6 and 17-20 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. A statement of reasons for the indication of allowable subject matter are as follows.
Regarding claims 5 and 17-20, Perchoux fails to disclose: “wherein the computation processor converts the first frequency spectrum into a form of an approximation and calculates the usable frequency range based on a comparison between the first frequency spectrum converted into the form of the approximation and the second frequency spectrum.” Neither Scalise nor Christian remedies the deficiencies of Perchoux.
Regarding claim 6, Perchoux fails to disclose: “wherein the computation processor converts the second frequency spectrum into a form of an approximation and calculates the usable frequency range based on a comparison between the second frequency spectrum converted into the form of the approximation and the first frequency spectrum.” Neither Scalise nor Christian remedies the deficiencies of Perchoux.
The remaining prior art made of record and not relied upon is considered pertinent to applicant’s disclosure, as noted in the attached PTO 892, include:
Presura (US20080188726A1) discloses converting “the first frequency spectrum into a form of an approximation” (¶¶ 5, 11, 35-37), and further discloses obtaining a lower flow rate “second frequency spectrum” (¶ 34); however, does not disclose “the computation processor … calculates the usable frequency range based on a comparison between the first frequency spectrum converted into the form of the approximation and the second frequency spectrum” of claims 5 and 17-20, nor “the computation processor converts the second frequency spectrum into a form of an approximation and calculates the usable frequency range based on a comparison between the second frequency spectrum converted into the form of the approximation and the first frequency spectrum” of claim 6.
Zhao (“Optical feedback interferometry for microscale-flow sensing study: numerical simulation and experimental validation,” published 2016)6 discloses converting “the first frequency spectrum into a form of an approximation” (p. 23860, Gaussian curve-fitting employed) and converting the lower flow rate “second frequency spectrum into a form of an approximation” (p. 23860, curve-fitting applied to different flow rates from 0 uL/min to 50 uL/min); however, does not disclose “the computation processor … calculates the usable frequency range based on a comparison between the first frequency spectrum converted into the form of the approximation and the second frequency spectrum” of claims 5 and 17-20, nor “the computation processor … calculates the usable frequency range based on a comparison between the second frequency spectrum converted into the form of the approximation and the first frequency spectrum” of claim 6.
Chen (US20030208326A1) discloses “the computation processor converts the first frequency spectrum into a form of an approximation” (Fig. 9, Lorentzian fit); however, does not disclose “the computation processor … calculates the usable frequency range based on a comparison between the first frequency spectrum converted into the form of the approximation and the second frequency spectrum” of claims 5 and 17-20, nor “the computation processor converts the second frequency spectrum into a form of an approximation and calculates the usable frequency range based on a comparison between the second frequency spectrum converted into the form of the approximation and the first frequency spectrum” of claim 6.
Byrd (US5821427A) which discloses a method for measuring velocity of liquid flowing where the measured frequency spectrum is fitted in order to approximate the maximum velocity of the flowing liquid. Specifically, Byrd discloses “the computation processor converts the first frequency spectrum into a form of an approximation” (Fig. 2, step 40m, application of a least squats curve fit); however, does not disclose “the computation processor … calculates the usable frequency range based on a comparison between the first frequency spectrum converted into the form of the approximation and the second frequency spectrum” of claims 5 and 17-20, nor “the computation processor converts the second frequency spectrum into a form of an approximation and calculates the usable frequency range based on a comparison between the second frequency spectrum converted into the form of the approximation and the first frequency spectrum” of claim 6.
In sum, the cited prior art lacks any teaching or motivation that would lead a person of ordinary skill in the art to implement the features of claims 5-6 and 17-20, thereby failing to render the claimed invention anticipated or obvious. Accordingly, claims 5-6 and 17-20 would be allowable if rewritten in independent form, including all limitations of its base claim and any intervening claims.
Conclusion
Prior art made of record though not relied upon in the present basis of rejection are noted in the attached PTO 892 further include: Wolfram (“Nyquist Frequency,” published 2019)7 which discloses the established relationship of the highest signal frequency that can be reconstruction without aliasing, i.e., Nyquist frequency, as half the sampling rate.
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/ZHENGQING QI/Examiner, Art Unit 3645
1 Perchoux, J.; Quotb, A.; Atashkhooei, R.; Azcona, F.J.; Ramírez-Miquet, E.E.; Bernal, O.; Jha, A.; Luna-Arriaga, A.; Yanez, C.; Caum, J.; et al. Current Developments on Optical Feedback Interferometry as an All-Optical Sensor for Biomedical Applications. Sensors 2016, 16, 694.
2 Lorenzo Scalise, Wiendelt Steenbergen, and Frits de Mul, "Self-mixing feedback in a laser diode for intra-arterial optical blood velocimetry," Appl. Opt. 40, 4608-4615 (2001).
3 Accessed from “mathworld.wolfram.com/NyquistFrequency.html” with Wayback Machine dated December 17, 2019.
4 Accessed from “mathworld.wolfram.com/NyquistFrequency.html” with Wayback Machine dated December 17, 2019.
5 Accessed from “mathworld.wolfram.com/NyquistFrequency.html” with Wayback Machine dated December 17, 2019.
6 Zhao Y, Perchoux J, Campagnolo L, Camps T, Atashkhooei R, Bardinal V. Optical feedback interferometry for microscale-flow sensing study: numerical simulation and experimental validation. Opt Express. 2016 Oct 17;24(21):23849-23862.
7 Accessed from “mathworld.wolfram.com/NyquistFrequency.html” with Wayback Machine dated December 17, 2019.