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 .
DETAILED ACTION
Status of Claims
The present Office Action is pursuant to Applicant’s communication on 07-11-2023; current application filed on 07-11-2023; This application is a 371 of PCT/JP2021/046169 12-15-2021 and claims foreign priority to Japan 2021-005751 01-182021.
Information Disclosure Statement
The information disclosure statements (IDS) filed on 07-11-2023, 07-18-2023, 07-19-2024, have been acknowledged. The submissions are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Examiner’s Note
The rejections below group claims that may not be identical, but whose language and scope are so substantively similar as to lend themselves to grouping, in the interests of clarity and conciseness.
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 1-12 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception without significantly more.
Step 1: Statutory Category
Claims 1, 11, and 12 are directed to a biological information processing device, system, and method, respectively. These fall within the statutory categories of machine/system and process/method. Therefore, claims 1-12 pass Step 1.
Step 2A Prong One: Abstract Idea
Representative Claim1 recites: “A biological information processing device comprising:
an extraction unit that extracts a component signal corresponding to a physiological index from signals detected from a living body; and
a variation emphasizing unit that changes the value of the component signal, based on a time constant when the value of the component signal varies,
wherein the variation emphasizing unit changes a value of a first component signal in accordance with a value of a second component signal having a time constant shorter than that of the first component signal of which the value is changed.”.
The claims recite limitations that amount to an abstract idea and mathematical concepts. Specifically, the independent claims focus on extracting physiological signals, calculating time constants, and adjusting signal values using weighting coefficients to derive emotional/psychological states. This corresponds to mathematical formulas and mental processes of observing, analyzing, and correlating biological data.
As disclosed in the specification: “The present technology provides a biological information processing device including an extraction unit that extracts a component signal corresponding to a physiological index from signals detected from a living body, and a variation emphasizing unit that changes the value of the component signal, based on a time constant when the value of the component signal varies”. The claims themselves recite: “an extraction unit that extracts a component signal corresponding to a physiological index from signals detected from a living body; and a variation emphasizing unit that changes the value of the component signal, based on a time constant when the value of the component signal varies, wherein the variation emphasizing unit changes a value of a first component signal in accordance with a value of a second component signal having a time constant shorter than that of the first component signal of which the value is changed”. These limitations are directed to mathematical relationships (time constants, saturation indexes, weighting coefficients) and mental processes of monitoring physiological states, which fall squarely within judicial exceptions.
Step 2A Prong Two: Practical Application
The additional elements in the claims do not integrate the abstract idea into a practical application. The claims merely recite generic functional units (“extraction unit,” “variation emphasizing unit,” “storage unit”) that perform data gathering, mathematical calculation, and output generation. These are conventional computing components applied to biological signals without improving the functioning of the computer itself or applying the exception in a meaningful way beyond linking it to a particular technological environment.
The specification confirms these units are implemented by standard processing hardware: “The processor 301 can function as, for example, the extraction unit 11, the variation emphasizing unit 13, the storage unit 14, the index calculation unit 12, and the like”. Because the claims only use generic computer components to perform the mathematical/mental process, they fail Step 2A Prong Two.
Step 2B: Significantly More
The claims do not recite an inventive concept that amounts to “significantly more” than the judicial exception. The additional elements are well-known, routine, and conventional activities in the fields of signal processing and machine learning. The specification explicitly notes that standard algorithms and neural networks may be employed: “A learning model can be modeled, for example, with a neural network... Alternatively, various types of neural networks such as an artificial neural network (ANN), a deep neural network (DNN)... may be used”. Using conventional processors to extract signals, apply mathematical weighting based on time constants, and run standard machine learning models does not transform the abstract idea into patent-eligible subject matter. Thus, the claims fail Step 2B.
Dependent Claims Analysis (Claims 2-10)
Claims 2-10 depend from independent claim 1 and add further limitations that do not overcome the § 101 rejection:
Claims 2 & 3 recite an index calculation unit and storage unit for correspondence relationship information. These merely formalize the mathematical saturation index calculations and lookup tables, which are conventional data processing steps.
Claims 4-6 further define how weighting coefficients change based on threshold values. These are additional mathematical relationships that refine the abstract idea but do not add practical application or inventive concept.
Claim 7 adds a resting state determination unit based on body motion information. This is a conventional sensor data filtering step routinely used in wearable device signal processing.
Claims 8-10 introduce an estimation unit and machine learning unit to correlate signals with emotional states. As noted above, applying standard machine learning models to physiological data is a well-known, routine application that does not provide significantly more than the abstract idea itself.
Because these dependent claims merely append conventional computing steps, mathematical refinements, or standard machine learning implementations to the underlying abstract idea, they remain directed to patent-ineligible subject matter under 35 U.S.C. § 101.
Claims 1-12 are rejected under 35 U.S.C. § 101 as being directed to an abstract idea and mathematical concepts without significantly more. The claims recite generic functional units performing conventional data extraction, mathematical weighting based on time constants, and standard machine learning estimation, which do not integrate the judicial exception into a practical application nor provide an inventive concept beyond well-known computer implementations.
Thus, taken alone, the additional elements do not amount to significantly more than the abstract idea identified above. Furthermore, looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually, and there is no indication that the combination of elements improves the functioning of a computer or improves any other technology, and their collective functions merely provide conventional computer implementation.
Therefore, whether taken individually or as an ordered combination, claim(s) 1-12 is/are nonetheless rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Claim Interpretation - 35 USC § 112 sixth paragraph
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.
Claim limitation(s) 1-12 has/have been interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because it uses/they use a generic placeholder “means for” coupled with functional language without reciting sufficient structure to achieve the function. Furthermore, the generic placeholder is not preceded by a structural modifier.
Since the claim limitation(s) invokes 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, claim(s) 1-12 has/have been interpreted to cover the corresponding structure described in the specification that achieves the claimed function, and equivalents thereof.
A review of the specification shows that the following appears to be the corresponding structure described in the specification for the 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph limitation:
Claims 1-12:
“extraction unit”; [Applicant specification, ¶88: encapsulated within a processor]
“variation unit”; [Applicant specification, ¶88: encapsulated within a processor]
“index calculation unit”; [Applicant specification, ¶88: instantiated by a processor]
“storage unit”; [Applicant specification, ¶89: encapsulated within a device such as a hard drive]
“estimation unit”; [Applicant specification, Fig 13, encapsulated within “10”, a processor as depicted in ¶87 ]
“machine learning unit”; [Applicant specification, Fig 13, encapsulated within “10”, a processor as depicted in ¶87 ]
If applicant wishes to provide further explanation or dispute the examiner’s interpretation of the corresponding structure, applicant must identify the corresponding structure with reference to the specification by page and line number, and to the drawing, if any, by reference characters in response to this Office action.
If applicant does not intend to have the claim limitation(s) treated under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112 , sixth paragraph, applicant may amend the claim(s) so that it/they will clearly not invoke 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, or present a sufficient showing that the claim recites/recite sufficient structure, material, or acts for performing the claimed function to preclude application of 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
For more information, see MPEP § 2173 et seq. and Supplementary Examination Guidelines for Determining Compliance With 35 U.S.C. 112 and for Treatment of Related Issues in Patent Applications, 76 FR 7162, 7167 (Feb. 9, 2011).
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 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 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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1-6 and 8-12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Fabiano1 in view of Matsumoto2.
Regarding claim(s) 1, 11, 12, Fabiano discloses: A biological information processing device comprising, A biological information processing system comprising, A biological information processing method comprising:
an extraction unit that extracts a component signal corresponding to a physiological index from signals detected from a living body; [Fabiano extracts multiple physiological signals corresponding to physiological indices from a living body: “There is a total of 8 physiological signals that include blood pressure (diastolic, systolic, mean, and raw), respiration (rate and volts), heart rate, and electrodermal /EDA) [Section IV]”] and
a variation emphasizing unit that changes the value of the component signal, based on a time constant when the value of the component signal varies, [Fabiano uses signal variance to emphasize or dampen signals based on how much they vary over time: “we use the variance to weight each signal during fusion [Section III]” Variance inherently relates to the time constant of signal variation (high variance indicates rapid/large changes, i.e., shorter time constant)]
wherein the variation emphasizing unit changes a value of a first component signal in accordance with a value of a second component signal having a time constant shorter than that of the first component signal of which the value is changed. [The system adjusts signal values based on their variance characteristics. “This weighted fusion effectively boosts the high variance signals while dampening the low variance signals [Section III]”. High-variance signals (shorter time constant) are emphasized, while low-variance signals are de-emphasized, thereby changing the first component signal's value in accordance with the second.]
Regarding [b]-[c], Fabiano, while Fabiano discloses weighting physiological signals based on variance (which relates to time-based variation), it does not explicitly disclose as disclosed by Matsumoto: changing signal values based on time constants between different component signals. Matsumoto teaches generating multiple delayed versions of biological signals with different timing characteristics, which would suggest to one of ordinary skill in the art that varying signal processing based on temporal characteristics (time constants) is known in the field; [In a case where a signal detected from a living body is subjected to signal processing and analyzed, a delay generation part 1 creates biological signals at a plurality of different timings for one biological signal for improving deterioration due to an unknown delay of the biological signal".
"The delay generating unit generates a signal with a plurality of (for example, N) delay times for each signal of the signals related to the biological signal".
"The analysis unit 20 analyzes each delayed signal and outputs a detailed analysis signal"]
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to have modified Fabiano, including mechanism(s) [b]-[c] as taught by Matsumoto. One of ordinary skill would have been so motivated to employ said mechanism(s) to process physiological signals based on temporal characteristics. [Section III]
Regarding claim 2, Fabiano-Matsumoto as a combination discloses: The biological information processing device according to claim 1, Fabiano disclosing: further comprising:
an index calculation unit that calculates a saturation index indicating a degree of saturation when the value of the component signal varies from a reference value to a maximum value, based on the value of the component signal. [Fabiano normalizes the variance of each signal to a specific range, representing the degree of variation relative to minimum and maximum bounds: “we then normalize these values be in the range [min, max], which are the final variance values used to weight each signals importance [Section III]” This normalized value functions as a saturation index indicating how far the signal's variation extends from a reference (min) toward a maximum.]
Regarding claim 3, Fabiano-Matsumoto as a combination discloses: The biological information processing device according to claim 2, Fabiano disclosing: further comprising:
a storage unit that stores correspondence relationship information indicating a correspondence relationship between the saturation index related to the first component signal and the saturation index related to the second component signal, [Fabiano stores/uses the normalized variance as a weight. Quote: “Where nsi2 is the normalized variance (i.e., weight) [Section III]”]
wherein the variation emphasizing unit changes the value of the first component signal by multiplying the value of the first component signal by a weighting coefficient obtained from the correspondence relationship information. [“Each signal frame is multiplied by the weight, and then each signal is summed together [Section III]”]
Regarding claim 4, Fabiano-Matsumoto as a combination discloses: The biological information processing device according to claim 3, Fabiano disclosing: wherein the storage unit stores the correspondence relationship information in which the weighting coefficient becomes large as the value of the saturation index related to the second component signal increases when the value of the saturation index related to the first component signal is equal to or greater than the reference value and equal to or less than a threshold value. [The normalization process inherently creates a direct correspondence where higher variance (higher saturation index) results in a larger weight, and lower variance results in a smaller weight: “This weighted fusion effectively boosts the high variance signals while dampening the low variance signals Section III]”. Thus, as the saturation index related to the second component signal increases/decreases, the weighting coefficient correspondingly becomes large/small]
Regarding claim 5, Fabiano-Matsumoto as a combination discloses: The biological information processing device according to claim 3, Fabiano disclosing: wherein the storage unit stores the correspondence relationship information in which the weighting coefficient becomes small as the value of the saturation index related to the second component signal decreases when the value of the saturation index related to the first component signal is equal to or greater than a threshold value and equal to or less than the maximum value. [The normalization process inherently creates a direct correspondence where higher variance (higher saturation index) results in a larger weight, and lower variance results in a smaller weight: “This weighted fusion effectively boosts the high variance signals while dampening the low variance signals Section III]”. Thus, as the saturation index related to the second component signal increases/decreases, the weighting coefficient correspondingly becomes large/small]
Regarding claim 6, Fabiano-Matsumoto as a combination discloses: The biological information processing device according to claim 3, Fabiano disclosing: wherein the storage unit stores the correspondence relationship information in which the weighting coefficient becomes large as the value of the saturation index related to the second component signal increases when the value of the saturation index related to the first component signal is equal to or greater than the reference value and equal to or less than a first threshold value, and the weighting coefficient becomes small as the value of the saturation index related to the second component signal decreases when the value of the saturation index related to the first component signal is equal to or greater than a second threshold value and equal to or less than the maximum value. [The normalization process inherently creates a direct correspondence where higher variance (higher saturation index) results in a larger weight, and lower variance results in a smaller weight: “This weighted fusion effectively boosts the high variance signals while dampening the low variance signals Section III]”. Thus, as the saturation index related to the second component signal increases/decreases, the weighting coefficient correspondingly becomes large/small]
Regarding claim 8, Fabiano-Matsumoto as a combination discloses: The biological information processing device according to claim 1, Fabiano disclosing: further comprising: an estimation unit that estimates an emotional state, based on the value of the first component signal changed by the variation emphasizing unit, and the value of the second component signal. [Both the fused and non-fused signals are used to train feedforward neural networks to recognize a range of emotion”]
Regarding claim 9, Fabiano-Matsumoto as a combination discloses: The biological information processing device according to claim 8, Fabiano disclosing: further comprising: a machine learning unit that correlates the value of the first component signal changed by the variation emphasizing unit, the value of the second component signal, and an estimation result of the emotional state, to causes a learning model to perform machine learning. [“Both the fused and non-fused signals are used to train feedforward neural networks to recognize a range of emotion [Abstract]”.
The system trains a model using the variance-weighted (changed) physiological signals and their corresponding emotional labels: “The proposed method increases the influence of high-variance signals and decreases the influence of low-variance signals on emotion recognition [Section IV]” The neural network learns the correlation between the emphasized component signals and the estimated emotional states]
Regarding claim 10, Fabiano-Matsumoto as a combination discloses: The biological information processing device according to claim 8, Fabiano disclosing: wherein the estimation unit estimates the emotional state by using the value of the first component signal, the value of the second component signal, and the learning model having been subjected to machine learning by the machine learning unit. [“Both the fused and non-fused signals are used to train feedforward neural networks to recognize a range of emotion [Abstract]”.
The system trains a model using the variance-weighted (changed) physiological signals and their corresponding emotional labels: “The proposed method increases the influence of high-variance signals and decreases the influence of low-variance signals on emotion recognition [Section IV]” The neural network learns the correlation between the emphasized component signals and the estimated emotional states]
Claim(s) 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Fabiano in view of Matsumoto and further in view of Murphy3.
Regarding claim 7, Fabiano-Matsumoto as a combination discloses: The biological information processing device according to claim 1; however, aforementioned combination does not disclose as disclosed by Murphy: wherein
the value of the component signal extracted in accordance with the physiological index is a difference from the component signal in a resting state (i.e., performing a subtraction to remove physiological variance), [Page 353] and
the biological information processing device further comprises a resting state determination unit that determines the resting state, based on body motion information obtained from a sensor and/or the signal detected from the living body. [Murphy et al. explicitly discloses determining a resting state and using motion information: "Motion artefacts are problematic for all types of fMRI including resting-state fMRI [Page 350]... The goal of resting-state fMRI is to use the common variance of the fMRI blood oxygenation level dependent (BOLD) signals in different regions of the brain as an indicator of synchronous neural activity [Page 349]”. Furthermore, Murphy et al. states: "Recent studies have demonstrated that functional connectivity conclusions may be erroneous when motion artefacts have a differential effect on resting BOLD signals for between group comparisons [Page 351]”. This teaches determining a resting state based on body motion information to extract component signals (difference from resting state).]
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to have modified Fabiano, including mechanism(s) [a]-[b] as taught by Murphy. One of ordinary skill would have been so motivated to employ said mechanism(s) to cleanse variance from process physiological signals. [Pages 349-353]
Conclusion
The prior art made of record4 and NOT relied upon is considered pertinent to applicant's disclosure:
Boynton:
Early fMRI studies comparing results from fMRI and electrophysiological experiments support the notion that the blood oxygen level-dependent (BOLD) signal reliably follows the spiking activity of an underlying neuronal population averaged across a small region in space and a brief period in time. However, more recent studies focusing on higher level cognitive factors such as attention and visual awareness report striking discrepancies between the fMRI response in humans and electrophysiological signals in macaque early visual areas. Four hypotheses are discussed that can explain the discrepancies between the two methods: (1) the BOLD signal follows local field potential (LFP) signals closer than spikes, and only the LFP is modulated by top-down factors, (2) the BOLD signal is reflecting electrophysiological signals that are occurring later in time due to feedback delay, (3) the BOLD signal is more sensitive than traditional electrophysiological methods due to massive pooling by the hemodynamic coupling process, and finally (4) there is no real discrepancy, and instead, weak but reliable effects on firing rates may be obscured by differences in experimental design and interpretation of results across methods.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL EZEWOKO whose telephone number is 571 272 7850. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Fonya Long can be reached on 571 270 5096. The fax phone number for the organization where this application or proceeding is assigned is 571-273-7850.
Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/MICHAEL I EZEWOKO/Primary Examiner, Art Unit 3682
1 Form 892: Non-Patent Literature
2 Form 892: JP2017144200A
3 Form 892: Non-Patent Literature
4Please see Form 892 for complete listing
Prosecution Insights