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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on December 19, 2024 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
As an initial matter, Applicant is reminded of the continuing obligation under 37 CFR 1.56, to timely apprise the Office of any information which is material to patentability of the claims under consideration in this application.
Drawings
The drawings filed on December 19, 2024 are accepted.
Claim Objections
Claims 1, 3, 4, 9, 10 and 15 are objected to because of the following informalities:
Claim 1, page 2, line 2: “the thermal image data” should be corrected to –the preprocessed thermal image data--.
Claim 1, page 2, line 7: “the physiological data” should be corrected to –the preprocessed physiological data--.
Claim 1, page 2, line 9: “the user-provided contextual data” should be corrected to –the preprocessed user-provided contextual data--.
Claim 1, page 2, line 25: after the punctuation comma, the word “wherein” should be added.
Claim 3, page 4, line 3: after the punctuation semi-colon, the word “and” should be added.
Claim 4, line 3: after the punctuation comma, the word “wherein” should be added.
Claim 9, lines 1-4: “wherein generating the one or more multi-modal features using one or more convolutional neural networks (CNNs) as the one or more machine learning (ML) models, generating at least one of:…” should be corrected to –wherein generating the one or more multi-modal features uses wherein the one or more multi-modal features comprises
Claim 10, page 6, line 1: “integrating” should be corrected to –integrate--; and “assigning” should be corrected to –assign--.
Claim 15, line 10: after the punctuation semi-colon, the word “and” should be added.
Appropriate correction is required.
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:
Claims 1, 12, 14 and 18: the claim limitations of “obtaining multi modal data through a data-obtaining subsystem”; “preprocessing the obtained multi-modal data through a data preprocessing subsystem”; “generating one or more multi-modal features through a feature engineering subsystem”; generating unified features through a feature fusion subsystem”; “analyzing the unified features through a data analysis subsystem”; “the data analysis subsystem is configured to select the one or more machine learning models” have been interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because it uses a generic placeholder “subsystem” coupled with functional language “obtaining/preprocessing/generating/analyzing/to select” without reciting sufficient structure to achieve the function. Furthermore, the generic placeholder is not preceded by a structural modifier that has a known structural meaning before the phrase “subsystem”.
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.
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 and 14: “a data-obtaining subsystem”, “a data preprocessing subsystem”, “a feature engineering subsystem”, “a feature fusion subsystem”, and “a data analysis subsystem” refer to the specification, PG Pub US 2025/0204794 A1, [0046]: a “module” or “subsystem” may also comprise programmable logic or circuitry (as encompassed within a general purpose processor or other programmable processor) that is temporarily configured by software to perform certain operations.
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.
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 § 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.
Claims 1-20 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 pre-AIA the applicant regards as the invention.
Claim 1 recites in lines 3-6 that the multi-model data is obtained from a plurality of sources comprise at least one of one or more image-capturing units, one or more thermal imaging sensors, one or more physiological sensing peripherals, and one or more users; and further in lines 7-8 recites that the multi-modal data comprises at least one of colored image data, thermal image data, physiological data, speech signals, and user-provided contextual data. Based on the above recitation, claim 1 requires only at least one of the type of data obtained from its corresponding source, for example, colored image data obtained from one or more image-capturing units, or thermal image data obtained from one or more thermal imaging sensors...etc.
However, in lines 9-23, all of the colored image data, the thermal image data, the physiological data, and the user-provided contextual data are preprocessed (preprocessing,…the obtained multi-modal data comprises: preprocessing the colored image data…; preprocessing the thermal image data…; preprocessing the physiological data…; and preprocessing the user-provided contextual data…), and in lines 24 to line 10 of page 2, all the above preprocessed data are used to generate one or more multi-modal features (generating,…one or more multi-modal features based on: extracting…in the preprocessed colored image data; extracting…from the thermal image data…; generating…from the physiological data…; and determining…from the user-provided contextual data).
Hence, since all 4 types of data and preprocessed and being based upon for generating the multi-modal features, it would require to have all 4 types of data to be obtained from their corresponding sources. Yet as underlined above, claim 1 requires only at least one of the type of data obtained from its corresponding source. The scope of the claim hence is indefinite and unclear. It is unclear how all 4 types of data may be available for preprocessing if they have not all been obtained from their corresponding sources.
For examination purpose, claim 1 is interpreted such that in lines 3-6, the multi-modal data is obtained from a plurality of sources comprises
The above consideration and interpretation apply to claim 14 and claim 20 for the substantially identical limitations recited in the claims.
The dependent claims of the above rejected claims are rejected due to their dependency.
Conclusion
Shouldice et al., US 2024/0173499 A1. This reference discloses systems and methods for managing blood pressure conditions of a user by controlling operational parameters of a respiratory therapy associated. It uses transdermal optical imaging to capture reflected light from the red blood cells in the skin. It uses a machine learning model trained to modify the operational parameter associated with the respiratory therapy system. The systems and methods may be used in concert with cognitive behavioral therapy, breathing exercises or blood pressure management medications.
Corso et al., US 2023/0253119 A1. This reference teaches a computer implemented method for deriving a physiological rank indicative of a physiological status of a user. It carries applications in lifestyle management such as cognitive performance. It uses optical sensing module configured to receive light backscattered from the skin of the user. The user input information includes body temperature information from a temperature sensor, heart rate information from a heart rate sensor, motion information from a motion sensor. It uses an index model and a status model as machine learning models.
Jain et al., US 11,322,260 B1. This reference discloses methods, systems and apparatus for collecting monitoring data and predicting outcomes for communities. The system can collect and analyze data regarding physiological, behavioral, and cognitive patterns indicative of the onset of diseases. The data collected includes cardiac related biodata, respiration related biodata, sleep data such as motion, heart rate, and body temperature. It uses machine learning model trained to predict likelihood that different medications regimens are appropriate for different individuals.
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/YI-SHAN YANG/Primary Examiner, Art Unit 3798
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