CTNF 19/211,666 CTNF 98092 DETAILED ACTION Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. This is a non-final office action on the merits. Claims 1-7 are currently pending and are addressed below. The examiner notes that the fundamentals of the rejection are based on the broadest reasonable interpretation of the claim language. Applicant is kindly invited to consider the reference as a whole. References are to be interpreted as by one of ordinary skill in the art rather than as by a novice. See MPEP 2141. Therefore, the relevant inquiry when interpreting a reference is not what the reference expressly discloses on its face but what the reference would teach or suggest to one of ordinary skill in the art. Information Disclosure Statement The information disclosure statement (IDS) submitted on May 19, 2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner. 07-30-03-h AIA Claim Interpretation 07-30-03 AIA 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. 07-30-05 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. 07-30-06 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: “biometric information recognition portion ” in claims 1-3 and 7 “driving behavior recognition portion ” in claims 1-2 “predicted risk score calculation portion ” in claim 1-2 and 4-5 “health level recognition portion ” in claim 2 “moving body position recognition portion ” in claim 4 “moving route guidance portion” in claim 5 Because these claim limitations are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, they are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof. 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 § 101 07-04-01 AIA 07-04 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 1-7 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Step 1 Claims 1 and 6-7 are directed towards a device, method, and non-transitory storage medium which fall within at least one of the statutory categories. STEP 2A (Prong 1) Claim 1 A driver monitoring device comprising: a biometric information recognition portion that recognizes biometric information of a driver of a moving body a driving behavior recognition portion that recognizes driving behavior of the driver, who is driving the moving body a predicted risk score calculation portion that calculates, based on driving behavior of the driver recognized by the driving behavior recognition portion at a predetermined time point while the driver is driving the moving body and on-driving biometric information, which is biometric information of the driver, recognized by the biometric information recognition portion at the predetermined time point, a predicted risk score indicating a risk level regarding movement of the moving body due to driving of the driver after the predetermined time point The examiner submits that the foregoing bolded limitations constitute a mental process because under its broadest reasonable interpretation, the claim covers performance of limitations in the human mind. The “calculate” step in the context of the claims, encompasses a person looking at the biometric data collected (obtained, received, acquired, recognized by the system etc.) and forming a simple judgement (determination, analysis, comparison, etc.) regarding a predicted risk score indicating a risk level regarding movement of the moving body due to driving of the driver after the predetermined time point. Thus, claim 1 recites at least one mental process. Claim 6 A driver monitoring method to be executed by a computer, the driver monitoring method comprising: a biometric information recognition step of recognizing biometric information of a driver of a moving body a driving behavior recognition step of recognizing driving behavior of the driver, who is driving the moving body a predicted risk score calculation step of calculating, based on driving behavior of the driver recognized in the driving behavior recognition step at a predetermined time point while the driver is driving the moving body and on-driving biometric information, which is biometric information of the driver, recognized in the biometric information recognition step at the predetermined time point, a predicted risk score indicating a risk level regarding movement of the moving body due to driving of the driver after the predetermined time point The examiner submits that the foregoing bolded limitations constitute a mental process because under its broadest reasonable interpretation, the claim covers performance of limitations in the human mind. The “calculating” step in the context of the claims, encompasses a person looking at the biometric data collected (obtained, received, acquired, recognized by the system etc.) and forming a simple judgement (determination, analysis, comparison, etc.) regarding a predicted risk score indicating a risk level regarding movement of the moving body due to driving of the driver after the predetermined time point. Thus, claim 1 recites at least one mental process. Claim 7 A non-transitory computer-readable storage medium storing a program causing a computer to function as: a biometric information recognition portion that recognizes biometric information of a driver of a moving body a driving behavior recognition portion that recognizes driving behavior of the driver, who is driving the moving body a predicted risk score calculation portion that calculates, based on driving behavior of the driver recognized by the driving behavior recognition portion at a predetermined time point while the driver is driving the moving body and on-driving biometric information, which is biometric information of the driver, recognized by the biometric information recognition portion at the predetermined time point, a predicted risk score indicating a risk level regarding movement of the moving body due to driving of the driver after the predetermined time point. The examiner submits that the foregoing bolded limitations constitute a mental process because under its broadest reasonable interpretation, the claim covers performance of limitations in the human mind. The “calculate” step in the context of the claims, encompasses a person looking at the biometric data collected (obtained, received, acquired, recognized by the system etc.) and forming a simple judgement (determination, analysis, comparison, etc.) regarding a predicted risk score indicating a risk level regarding movement of the moving body due to driving of the driver after the predetermined time point. Thus, claim 1 recites at least one mental process. STEP 2A (Prong 2) Claim 1 A driver monitoring device comprising: a biometric information recognition portion that recognizes biometric information of a driver of a moving body a driving behavior recognition portion that recognizes driving behavior of the driver, who is driving the moving body a predicted risk score calculation portion that calculates, based on driving behavior of the driver recognized by the driving behavior recognition portion at a predetermined time point while the driver is driving the moving body and on-driving biometric information, which is biometric information of the driver, recognized by the biometric information recognition portion at the predetermined time point, a predicted risk score indicating a risk level regarding movement of the moving body due to driving of the driver after the predetermined time point The examiner submits that the identified additional limitations do not integrate the previously discussed abstract ideas into practical applications. Regarding the additional limitations of, “recognizing,” is a form of insignificant extra- solution activity. The “recognizing” step in the context of the claims is recited at a high level of generality (i.e. as a general means of receiving, obtaining etc., sensor data regarding an environment associated with a moving body) and amounts to mere data gathering which is a form of insignificant extra-solution activity. As such, the additional elements of claim 1 do not integrate the abstract idea into practical application. Additionally, the examiner submits that the identified additional limitations do not integrate the previously discussed abstract ideas into practical applications. The recited facilities such as the “biometric information recognition portion,” “driving behavior recognition portion,” are generic computer components meant to implement the abstract ideas into a computer and merely “apply” the mental judgements in a general-purpose vehicle controls environment. Claim 6 A driver monitoring method to be executed by a computer, the driver monitoring method comprising: a biometric information recognition step of recognizing biometric information of a driver of a moving body a driving behavior recognition step of recognizing driving behavior of the driver, who is driving the moving body a predicted risk score calculation step of calculating, based on driving behavior of the driver recognized in the driving behavior recognition step at a predetermined time point while the driver is driving the moving body and on-driving biometric information, which is biometric information of the driver, recognized in the biometric information recognition step at the predetermined time point, a predicted risk score indicating a risk level regarding movement of the moving body due to driving of the driver after the predetermined time point The examiner submits that the identified additional limitations do not integrate the previously discussed abstract ideas into practical applications. Regarding the additional limitations of, “recognizing,” is a form of insignificant extra- solution activity. The “recognizing” step in the context of the claims is recited at a high level of generality (i.e. as a general means of receiving, obtaining etc., sensor data regarding an environment associated with a moving body) and amounts to mere data gathering which is a form of insignificant extra-solution activity. As such, the additional elements of claim 1 do not integrate the abstract idea into practical application. Additionally, the examiner submits that the identified additional limitations do not integrate the previously discussed abstract ideas into practical applications. The recited facilities such as the “biometric information recognition portion,” “driving behavior recognition portion,” are generic computer components meant to implement the abstract ideas into a computer and merely “apply” the mental judgements in a general-purpose vehicle controls environment. Claim 7 A non-transitory computer-readable storage medium storing a program causing a computer to function as: a biometric information recognition portion that recognizes biometric information of a driver of a moving body a driving behavior recognition portion that recognizes driving behavior of the driver, who is driving the moving body a predicted risk score calculation portion that calculates, based on driving behavior of the driver recognized by the driving behavior recognition portion at a predetermined time point while the driver is driving the moving body and on-driving biometric information, which is biometric information of the driver, recognized by the biometric information recognition portion at the predetermined time point, a predicted risk score indicating a risk level regarding movement of the moving body due to driving of the driver after the predetermined time point. The examiner submits that the identified additional limitations do not integrate the previously discussed abstract ideas into practical applications. Regarding the additional limitations of, “recognizing,” is a form of insignificant extra- solution activity. The “recognizing” step in the context of the claims is recited at a high level of generality (i.e. as a general means of receiving, obtaining etc., sensor data regarding an environment associated with a moving body) and amounts to mere data gathering which is a form of insignificant extra-solution activity. As such, the additional elements of claim 1 do not integrate the abstract idea into practical application. Additionally, the examiner submits that the identified additional limitations do not integrate the previously discussed abstract ideas into practical applications. The recited facilities such as the “biometric information recognition portion,” “driving behavior recognition portion,” are generic computer components meant to implement the abstract ideas into a computer and merely “apply” the mental judgements in a general-purpose vehicle controls environment. STEP 2B Claims 1 and 6-7 do not include additional elements (considered individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above. The additional elements such as a u “biometric information recognition portion,” “driving behavior recognition portion,” and “predicted risk score calculation portion,” to perform the steps amounts to nothing more than applying the exception using generic computer components. General application of an exception using a generic computer component cannot provide an inventive concept. Thus, since claims 1 and 6-7 are: (a) directed towards abstract ideas, (b) do not recite additional elements that integrate the judicial exception into a practical application, and (c) do not recite additional elements that amount to significantly more than the judicial exception, it is clear that claims 1 and 6-7 are directed towards non-statutory subject matter. Dependent claims 2-5 do not recite any further limitations that cause the claims to be patent eligible. The limitations of the dependent claims are directed towards additional aspects of the judicial exception and/or additional elements that do not integrate the judicial exception into a practical application. As such, claims 1-7 are rejected under 35 U.S.C 101 as being drawn to an abstract idea without significantly more, and thus are ineligible. Claim Rejections - 35 USC § 102 07-06 AIA 15-10-15 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. 07-07-aia AIA 07-07 The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – 07-08-aia AIA (a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention. 07-15 AIA Claim 1-2 and 4-7 are rejected under 35 U.S.C. 102( a)(1 ) as being anticipated by Iwase Koji et al. (JP20210077141A), hereinafter referred to as Koji . Regarding claim 1, Koji discloses: a driver monitoring device (see at least Koji, ¶¶ [0001]-[0005], [0040], which discloses a driver monitoring method and device) comprising: a biometric information recognition portion that recognizes biometric information of a driver of a moving body (see at least Koji, Fig.3, Item 29, “biometric information sensor,” ¶¶ [0049]-[0051], which discloses a sensor capable of recognizing biological information of the driver) a driving behavior recognition portion that recognizes driving behavior of the driver, who is driving the moving body (see at least Koji Fig.3, Item 35, “driver behavior recognition unit,” ¶¶ [0063]-[0065] which discloses examples of the unit identifying driver behavior such as, their health condition, emotion, and physical behavior based on the output of the driver state sensor) a predicted risk score calculation portion that calculates, based on driving behavior of the driver recognized by the driving behavior recognition portion at a predetermined time point while the driver is driving the moving body and on-driving biometric information, which is biometric information of the driver, recognized by the biometric information recognition portion at the predetermined time point (see at least Koji [0084]-[0086], discloses the concept of a degree of risk, which may be associated with a predicted risk score calculated based on measured components of sensor data such as, the vehicle and driver recognition units; a specific example presented is calculating a level of risk based on detecting the gaze point (biometric data of the driver) of a driver of a vehicle and vehicle behavior indicative of speed, position, etc., to determine the degree of danger of a traveling scene as a result of the input information; [0102]-[0105], discloses a risk level indicative of driver abnormality against a predetermined threshold incorporated in the predicted score at a time of travel, this means a predicted risk score calculation portion that calculates, based on driving behavior of the driver recognized by the driving behavior recognition portion at a predetermined time point while the driver is driving the moving body and on-driving biometric information, which is biometric information of the driver, recognized by the biometric information recognition portion at the predetermined time point) a predicted risk score indicating a risk level regarding movement of the moving body due to driving of the driver after the predetermined time point (see at least Koji, ¶¶ [0060]-[0063], which discloses a predicted degree of risk indicative of vehicle behavior related to movement such as, speed, acceleration, yaw rate, etc., this means a predicted risk score indicating a risk level regarding movement of the moving body due to driving of the driver after a little time has passed from the first running scene) Regarding claim 2, Koji discloses: the driver monitoring device according to claim 1, further comprising: a health level recognition portion that recognizes a health level of the driver, based on pre-driving biometric information, which is the biometric information of the driver, recognized by the biometric information (see at least Koji, Fig.3, Item 29, “biometric information sensor,” ¶¶ [0049]-[0051], which discloses a sensor capable of recognizing biological information of the driver such as the driver’s health status) recognition portion before the driver starts driving the moving body, wherein the predicted risk score calculation portion calculates the predicted risk score, based on the driving behavior of the driver recognized by the driving behavior recognition portion at the predetermined time point, and the on-driving biometric information recognized by the biometric information recognition portion at the predetermined time point, and the health level of the driver recognized by the health level recognition portion. (see at least Koji [0084]-[0086], discloses the concept of a degree of risk, which may be associated with a predicted risk score calculated based on measured components of sensor data such as, the vehicle and driver recognition units; a specific example presented is calculating a level of risk based on detecting the gaze point (biometric data of the driver) of a driver of a vehicle and vehicle behavior indicative of speed, position, etc., to determine the degree of danger of a traveling scene as a result of the input information; [0102]-[0105], discloses a risk level indicative of driver abnormality against a predetermined threshold incorporated in the predicted score before a time of travel, recognition portion before the driver starts driving the moving body, wherein the predicted risk score calculation portion calculates the predicted risk score, based on the driving behavior of the driver recognized by the driving behavior recognition portion at the predetermined time point) Regarding claim 4, Koji discloses: the driver monitoring device according to claim 1, further comprising: a moving body position recognition portion that recognizes a position of the moving body (see at least Koji, ¶¶ [0040] which discloses a position sensor that recognizes the position of the vehicle) a moving environment recognition portion that recognizes a moving environment of the moving body after the predetermined time point, based on the position of the moving body at the predetermined time point recognized by the moving body position recognition portion (see at least Koji, ¶¶ [0040], [0045] which discloses recognizes a moving environment of the moving body after the predetermined time point, based on the position of the moving body at the predetermined time point of travel) wherein the predicted risk score calculation portion compensates the predicted risk score based on the moving environment estimated by a moving environment estimation portion (see at least Koji [0084]-[0086], discloses the concept of a degree of risk, which may be associated with a predicted risk score calculated based on measured components of sensor data such as, the vehicle and driver recognition units; a specific example presented is calculating a level of risk based on detecting the gaze point (biometric data of the driver) of a driver of a vehicle and vehicle behavior indicative of speed, position, etc., to determine the degree of danger of a traveling scene as a result of the input information; [0102]-[0105], discloses a risk level indicative of driver abnormality against a predetermined threshold incorporated in the predicted score before a time of travel, recognition portion before the driver starts driving the moving body, wherein the predicted risk score calculation portion calculates the predicted risk score, based on the driving behavior of the driver recognized by the driving behavior recognition portion at the predetermined time point) Regarding claim 5, Koji discloses: the driver monitoring device according to claim 4, further comprising: a moving route guidance portion that guides a moving route that is a moving environment recognized by the moving environment recognition portion to reduce a driving load of the driver when the predicted risk score calculation portion calculates the predicted risk score that is equal to or greater than a predetermined value (see at least Koji, ¶¶ [0052]-[0053], [0060]-[0062] which discloses a candidate route generation unit that guides a particular route recognized by the moving environment recognition portion to reduce a driving load of the driver when the predicted risk score calculation portion calculates the predicted risk score that is equal to or greater than a predetermined threshold) Regarding claim 6, Koji discloses: a driver monitoring method to be executed by a computer (see at least Koji, ¶¶ [0001]-[0005], [0040], which discloses a driver monitoring method and device), the driver monitoring method comprising: a biometric information recognition step of recognizing biometric information of a driver of a moving body (see at least Koji, Fig.3, Item 29, “biometric information sensor,” ¶¶ [0049]-[0051], which discloses a sensor capable of recognizing biological information of the driver) a driving behavior recognition step of recognizing driving behavior of the driver, who is driving the moving body (see at least Koji Fig.3, Item 35, “driver behavior recognition unit,” ¶¶ [0063]-[0065] which discloses examples of the unit identifying driver behavior such as, their health condition, emotion, and physical behavior based on the output of the driver state sensor) a predicted risk score calculation step of calculating, based on driving behavior of the driver recognized in the driving behavior recognition step at a predetermined time point while the driver is driving the moving body and on-driving biometric information, which is biometric information of the driver, recognized in the biometric information recognition step at the predetermined time point (see at least Koji [0084]-[0086], discloses the concept of a degree of risk, which may be associated with a predicted risk score calculated based on measured components of sensor data such as, the vehicle and driver recognition units; a specific example presented is calculating a level of risk based on detecting the gaze point (biometric data of the driver) of a driver of a vehicle and vehicle behavior indicative of speed, position, etc., to determine the degree of danger of a traveling scene as a result of the input information; [0102]-[0105], discloses a risk level indicative of driver abnormality against a predetermined threshold incorporated in the predicted score at a time of travel, this means a predicted risk score calculation portion that calculates, based on driving behavior of the driver recognized by the driving behavior recognition portion at a predetermined time point while the driver is driving the moving body and on-driving biometric information, which is biometric information of the driver, recognized by the biometric information recognition portion at the predetermined time point) a predicted risk score indicating a risk level regarding movement of the moving body due to driving of the driver after the predetermined time point (see at least Koji, ¶¶ [0060]-[0063], which discloses a predicted degree of risk indicative of vehicle behavior related to movement such as, speed, acceleration, yaw rate, etc., this means a predicted risk score indicating a risk level regarding movement of the moving body due to driving of the driver after a little time has passed from the first running scene) Regarding claim 7, Koji discloses: a non-transitory computer-readable storage medium storing a program (see at least Koji, ¶¶ [0001]-[0005], [0040] causing a computer to function as: a biometric information recognition portion that recognizes biometric information of a driver of a moving body (see at least Koji, Fig.3, Item 29, “biometric information sensor,” ¶¶ [0049]-[0051], which discloses a sensor capable of recognizing biological information of the driver) a driving behavior recognition portion that recognizes driving behavior of the driver, who is driving the moving body (see at least Koji Fig.3, Item 35, “driver behavior recognition unit,” ¶¶ [0063]-[0065] which discloses examples of the unit identifying driver behavior such as, their health condition, emotion, and physical behavior based on the output of the driver state sensor) a predicted risk score calculation portion that calculates, based on driving behavior of the driver recognized by the driving behavior recognition portion at a predetermined time point while the driver is driving the moving body and on-driving biometric information, which is biometric information of the driver, recognized by the biometric information recognition portion at the predetermined time point (see at least Koji [0084]-[0086], discloses the concept of a degree of risk, which may be associated with a predicted risk score calculated based on measured components of sensor data such as, the vehicle and driver recognition units; a specific example presented is calculating a level of risk based on detecting the gaze point (biometric data of the driver) of a driver of a vehicle and vehicle behavior indicative of speed, position, etc., to determine the degree of danger of a traveling scene as a result of the input information; [0102]-[0105], discloses a risk level indicative of driver abnormality against a predetermined threshold incorporated in the predicted score at a time of travel, this means a predicted risk score calculation portion that calculates, based on driving behavior of the driver recognized by the driving behavior recognition portion at a predetermined time point while the driver is driving the moving body and on-driving biometric information, which is biometric information of the driver, recognized by the biometric information recognition portion at the predetermined time point) a predicted risk score indicating a risk level regarding movement of the moving body due to driving of the driver after the predetermined time point (see at least Koji, ¶¶ [0060]-[0063], which discloses a predicted degree of risk indicative of vehicle behavior related to movement such as, speed, acceleration, yaw rate, etc., this means a predicted risk score indicating a risk level regarding movement of the moving body due to driving of the driver after a little time has passed from the first running scene) Claim Rejections - 35 USC § 103 07-06 AIA 15-10-15 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. 07-20-aia AIA 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. 07-21-aia AIA Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Koji in view of Suzuki Masaaki et al. (JP20110180394A), hereinafter referred to as Masaaki . Regarding claim 3, Koji is silent on, however, in the same field of endeavor, Masaaki teaches: the driver monitoring device according to claim 1, wherein the biometric information recognition portion recognizes, as the biometric information of the driver, a heart rate of the driver (see at least Masaaki, ¶¶ [0013]-[0014] which discloses the driver monitoring device capable of recognizing biometric information such as a driver’s heart rate) It would have been obvious to a person of ordinary skill in the art to modify Koji to include the driver monitoring device according to claim 1, wherein the biometric information recognition portion recognizes, as the biometric information of the driver, a heart rate of the driver as taught by Masaaki. The examiner would like to note that the disclosure of Koji accounts for driver abnormalities that have been identified as health risks include stroke, heart disease, etc.. however, there is no direct disclosure that a heart rate is measured according to the biometric information obtained. Incorporating this teaching would allow for an improvement to the base invention of Koji that further creates contingency for the health risk conditions already provided in the disclosure and integrates heart rate into biometric information that may aid in more accurate risk scoring by the system . Conclusion 07-96 AIA The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Kento (WO2021176633A1) discloses a driver state estimation device that collects driver-related information related to a driver of a vehicle and estimates whether the driver is in the normal state on the basis of the driver-related information collected by the information collection unit and estimation information that has been reset on the basis of a determination result from the state determination unit indicating that the driver-related information is driver-related information collected when the driver is in the normal state. Takeshi (WO2021251351A1) discloses a method for estimating the probability of danger occurring, as an accident risk, taking, as inputs, first vehicle-mounted sensor data collected in the past, danger occurrence data obtained by setting, in advance, information relating to occurrences of danger, and biometric sensor data of a driver driving a vehicle from the first vehicle-mounted sensor data to predict the accident risk level after a predetermined time. Any inquiry concerning this communication or earlier communications from the examiner should be directed to KIRSTEN JADE M SANTOS whose telephone number is (571)272-7442. The examiner can normally be reached Monday: 8:00 am - 4:00 pm, 6:00-8:00 pm (+ with flex). Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Rachid Bendidi can be reached at (571) 272-4896. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. 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If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /KIRSTEN JADE M SANTOS/Examiner, Art Unit 3664 /RACHID BENDIDI/Supervisory Patent Examiner, Art Unit 3664 Application/Control Number: 19/211,666 Page 2 Art Unit: 3664 Application/Control Number: 19/211,666 Page 3 Art Unit: 3664 Application/Control Number: 19/211,666 Page 4 Art Unit: 3664 Application/Control Number: 19/211,666 Page 5 Art Unit: 3664 Application/Control Number: 19/211,666 Page 6 Art Unit: 3664 Application/Control Number: 19/211,666 Page 7 Art Unit: 3664 Application/Control Number: 19/211,666 Page 8 Art Unit: 3664 Application/Control Number: 19/211,666 Page 9 Art Unit: 3664 Application/Control Number: 19/211,666 Page 10 Art Unit: 3664 Application/Control Number: 19/211,666 Page 11 Art Unit: 3664 Application/Control Number: 19/211,666 Page 12 Art Unit: 3664 Application/Control Number: 19/211,666 Page 13 Art Unit: 3664 Application/Control Number: 19/211,666 Page 14 Art Unit: 3664 Application/Control Number: 19/211,666 Page 15 Art Unit: 3664 Application/Control Number: 19/211,666 Page 16 Art Unit: 3664 Application/Control Number: 19/211,666 Page 17 Art Unit: 3664 Application/Control Number: 19/211,666 Page 18 Art Unit: 3664 Application/Control Number: 19/211,666 Page 19 Art Unit: 3664 Application/Control Number: 19/211,666 Page 20 Art Unit: 3664 Application/Control Number: 19/211,666 Page 21 Art Unit: 3664 Application/Control Number: 19/211,666 Page 22 Art Unit: 3664
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