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 .
Response to Arguments
Applicant's arguments filed 07/09/2025 in view of the amendments have been fully considered and are persuasive in light of the previous rejection. However, the added limitations are not successful in overcoming the main reference since the limitations as considered obvious as described below.
For this reason, the rejection is updated to reflect the claim amendments below.
Claim Rejections - 35 USC § 112
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claims 1, 2, 3, 6, 7, 10 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
With respect to claim 1, the limitations are drawn to an apparatus. However, the newly added limitations include “wherein based on the one or more reference particles being trapped in the plurality of traps” the processor is configured to perform some steps related to calibration. However, there is not indication that reference particles are trapped in the plurality of traps. The traps are configured “to trap the fine particles” with no mention of reference particles therein. Either there are missing components in the claimed apparatus or the limitation is an intended use. Either way, the limitation adds confusion as whether the apparatus is infringed upon when the structure of the claim is met or only if certain method steps are also performed. Clarification is required.
With respect to claim 1, the limitation “the processor is further configured to control the measurer to obtain a plurality of calibration spectra” however “the measurer” is only described as a light source and detector to emit light to a plurality of traps and measure a spectrum. No calibration is disclosed. There seems to be missing components. Correction is required.
The balance of claims are likewise rejected for failing to correct the deficiencies in the claims upon which they depend.
Claim Rejections - 35 USC § 103
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claim(s) 1, 2, 3, 6, 7, 8, 9, 10, 11, 12, 13, 14, 17, 18, 19, 20 are rejected under 35 U.S.C. 103 as being unpatentable over Jung U.S. Publication 2023/0302447.
With respect to claim 1, Jung discloses an apparatus and method for bio particle detection comprising:
A fine particle trap comprising a plurality of traps that are configured to trap the fine particles (Figure 2A, 2B,
A measurer comprising: a light source configured to emit light to the plurality of traps (P.0007)
A detector configured to detect light scattered, reflected, transmitted through the plurality of traps and measure a spectrum (P.0007)
A processor configured to estimate a concentration of the fine particles trapped in the plurality of traps based on of the measured spectrum (P.0008)
Wherein the plurality of traps have a diameter equal to or less than 10 micrometers (P.0069, 10 nm is less than 1 µm)
Wherein processor is further configured to extract one or more features from the spectrum and estimate the number of the fine particles based on the extracted features using a fine particle estimation model (P.0071, P.0097-101, fine particle estimation model = predetermined equation matching peaks and points and other values in the spectrum to the number of through holes with target material)
However, Jung fails to disclose a processor configured for estimating a number of fine particles trapped in the plurality of traps and determining whether to perform calibration based on a present calibration period being reached, and then performing calibration with one or more reference particles. Additionally, Jung fails to disclose the processor is further configured to control the measurer to obtain a plurality of calibration spectra and train the fine particle estimation model based on the obtained calibration spectra, the fine particle estimation model being a neural network model, and the processor is configured to extract one or more features from the spectrum using a principal component analysis.
It would have been obvious to one of ordinary skill in the art at the time of the invention to calculate the number of particles from the concentration of particles since the two measurements are physically linked and are obvious variations of knowing the amount of particles in a sample. Moving from concentration to number of particles involves routine skill in the art and which one is more desirable to know would be based on the intended application.
Additionally, it would have been obvious to one of ordinary skill in the art at the time of the invention to consider if a measurement system needs calibration based on a preset calibration period and then to perform that calibration if it does need calibration, updating the fine particle estimation model based on the calibration. Measurement systems generally have specified calibration periods as set by manufacturers and measurement functions and data sets have useful lifetimes that the information is pertinent to the current measurements. Performing calibration, updating the model used to perform measurements, makes sense such that the measurements are being performed with the most recent information, leading to greater accuracy.
It would have been obvious to one of ordinary skill in the art at the time of the invention that the fine particle estimation model is a neural network model since neural network models are more and more common as a quick manner of analyzing data and updating the functions used to analyze that data as opposed to the predefined function disclosed by Jung. Neural networks are known in the art to be able to handle complex data in an adaptable way that can improve over time.
Finally, it would have been obvious to one of ordinary skill in the art at the time of the invention to use principal component analysis for data analysis since principal component analysis is a well-known data analysis and one of ordinary skill in the art would use it when appropriate for finding a plurality of features through a plurality of extracted components in large amounts of data.
With respect to claim 13, Jung discloses an method for bio particle detection comprising:
Trapping fine particles in a plurality of traps (Figure 2A, 2B,
Emitting, by a light source, light to the plurality of traps (P.0007)
Detecting, by a detector, light scattered, reflected, or transmitted through the plurality of traps (P.0007)
Measuring, by the detector, a spectrum based on the detected light (P.0007)
Estimating, by a processor, a concentration of the fine particles trapped in the plurality of traps based on the measured spectrum (P.0008)
Wherein the plurality of traps have a diameter equal to or less than 10 micrometers (P.0069, 10 nm is less than 1 µm)
Wherein estimating concentration comprises extracting one or more features from the spectrum and estimate the number of the fine particles based on the extracted features using a fine particle estimation model (P.0071, P.0097-101)
However, Jung fails to disclose estimating a number of fine particles trapped in the plurality of traps and determining whether to perform calibration based on a present calibration period being reached, and then performing calibration with one or more reference particles. Additionally, Jung fails to disclose obtaining a plurality of calibration spectra and training the fine particle estimation model, the fine particle estimation model being a neural network model and extracting the one or more features comprises using a principal component analysis.
It would have been obvious to one of ordinary skill in the art at the time of the invention to calculate the number of particles from the concentration of particles since the two measurements are physically linked and are obvious variations of knowing the amount of particles in a sample. Moving from concentration to number of particles involves routine skill in the art and which one is more desirable to know would be based on the intended application.
Additionally, it would have been obvious to one of ordinary skill in the art at the time of the invention to consider if a measurement system needs calibration based on a preset calibration period and then to perform that calibration if it does need calibration, updating the fine particle estimation model based on the calibration. Measurement systems generally have specified calibration periods as set by manufacturers and measurement functions and data sets have useful lifetimes that the information is pertinent to the current measurements. Performing calibration and then updating the model used to perform measurements, makes sense such that the measurements are being performed with the most recent information, leading to greater accuracy.
It would have been obvious to one of ordinary skill in the art at the time of the invention that the fine particle estimation model is a neural network model since neural network models are more and more common as a quick manner of analyzing data and updating the functions used to analyze that data as opposed to the predefined function disclosed by Jung. Neural networks are known in the art to be able to handle complex data in an adaptable way that can improve over time.
Finally, it would have been obvious to one of ordinary skill in the art at the time of the invention to use principal component analysis for data analysis since principal component analysis is a well-known data analysis and one of ordinary skill in the art would use it when appropriate for finding a plurality of features through a plurality of extracted components in large amounts of data.
With respect to claims 2, 3, 6, 7, 14, Jung discloses all of the limitations as applied to claim 1 above. In addition, Jung discloses:
2- The fine particle trap further comprises an inlet through which the sample is injected, a channel through which the injected sample moves, and an outlet through which the sample is discharged (Figure 5B, P.0108, inlet = left side where arrow is indicated, outlet = right most side, channel = pathway above structures 510,520,530)
2- The plurality of traps are formed to penetrate in a direction perpendicular to a length direction of the channel such that the sample moving along the channel is trapped (Figure 5B, P.0108)
3, 14 -The fine particles are trapped in the traps by capillarity or dielectrophoresis (P.0023, P.0130)
6- the plurality of traps are provided to have photonic crystals (P.0051)
7- a shape of each of the plurality of traps and a size of each of the plurality of traps are determined based on at least one of each of a shape of each target fine particles (P.0068, P.0072, P.0049)
It should be noted that for the limitation of claim 7, the reason or manner in which the structure of the traps is selected does not affect the structure itself and is not limiting on the apparatus nor can it differentiate from prior art.
With respect to claim 10, Jung discloses all of the limitations as applied to claims 1 and 8. However, Jung fails to disclose using principal component analysis for feature extraction.
It would have been obvious to one of ordinary skill in the art at the time of the invention to use principal component analysis for data analysis since principal component analysis is a well-known data analysis as described above. Additionally, having a first principal component and a second principal component of a PCA is inherent and setting those components as the features of interest or variables of the data is by definition how PCA is used.
Claim(s) 4, 5, 15, and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Jung et al. U.S. Publication 2023/0302447 in view of Stakenborg et al. U.S. Publication 2019/0346358.
With respect to claims 4, 5, 15, and 16, Jung discloses all of the limitations as applied to claims 1 and 13 above. However, Jung fails to disclose the fine particle trap comprises an alternating current electrode configured to induce the dielectrophoresis.
Stakenborg discloses a micro sieve method and device comprising:
A fine particle trap comprising a plurality of traps that are configured to trap fine particles (Figure 3A)
The particle trap further comprises an alternating current electrode configured to induce the dielectrophoresis based on control of a processor (Figure 2, P.0098)
It would have been obvious to one of ordinary skill in the art at the time of the invention to use the dielectrophoresis from an alternating current in order to draw the particles into the trap as in Stakenborg since dielectrophoresis is an art recognized equivalent to capillary action and photothermal effect for drawing particles. All three are known methods of controlling very small particles and one of ordinary skill in the art would know to select one of the known methods for particle manipulation based on the size and space constraints as well as budget and accuracy.
Conclusion
THIS ACTION IS MADE FINAL. 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 nonprovisional extension fee (37 CFR 1.17(a)) 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 mailing date of this final action.
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/REBECCA C BRYANT/Primary Examiner, Art Unit 2877