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 .
Status of Claims
This action is in reply to the amendment filed on 03/31/26.
Claims 1, 2, 4-10 have been amended and are hereby entered.
Claim 3 has been canceled.
Claims 1, 2, 4-10 are currently pending and have been examined.
This action is made final.
Continuity/Foreign Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy of parent Application No. JP2024-030608, filed on 02/29/24. Accordingly, a priority date of 02/29/24 has been given to the instant application.
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, 9 and 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.
The terms “larger movement” and “smaller movement” in claims 1, 9, 10 are relative terms which renders the claim indefinite. The terms “larger movement” and “smaller movement” are not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree or defining these terms, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention.
Dependent claims 2, 4-8 are subsequently rejected as they inherit the deficiencies of parent Claim 1.
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, 2, 4-10 are rejected under 35 U.S.C.101 because the claimed invention is directed to a judicial exception (an abstract idea) without significantly more.
Step 1
Claims 1,2, 4-8 are drawn to a system, Claim 9 is drawn to a method, and Claim 10 is drawn to a non-transitory computer-readable medium storing a computer program, each of which are within the four statutory categories. Claims 1, 2, 4-10 are further directed to an abstract idea on the grounds set out in detail below.
Step 2A Prong 1
Claim 1 recites implementing the steps of:
generating related behavioral data of a related behavior that is a behavior excluding instruction of a subject intention from the measurement data,
acquiring one or more behavioral features that are respectively nonverbal features based on related behavioral data with respect to each of one or more related behaviors,
setting an enhancement amount of a first behavioral feature by applying a greater weight based on a behavior of the subject including larger movements and set an enhancement amount of a second behavioral feature by applying a smaller weight based on the behavior of the subject including smaller movements
estimating a psychological characteristic of the subject based on the one or more behavioral features, and
outputting estimated psychological characteristic data that is data expressing the psychological characteristic that is estimated.
These steps amount to managing personal behavior or relationships or interactions
between people and therefore recite certain methods of organizing human activity including managing personal behavior or relationships or interactions between people. Generating related behavioral data of a subject, acquiring a plurality of non-verbal behavioral features with respect to a plurality of related behaviors, setting an enhancement amount by applying different weights based on the size of subject movements, using the behavioral features to estimate a psychological characteristic of the subject, and providing an output of the estimated psychological characteristic data, are personal behaviors that may be performed by one individual observing another individual, such as a psychologist or behavioral therapist, a healthcare provider, or a person conducting an interview with a subject.
Claim 9 and Claim 10 recite implementing the steps of:
generating related behavioral data of related behaviors that is all or part of behaviors excluding designation of an intention of the subject from the measurement data,
acquiring one or more behavioral features that are respectively nonverbal features based on related behavioral data with respect to one or more respective related behaviors,
setting an enhancement amount of a first behavioral feature by applying a greater weight based on a behavior of the subject including larger movements and set an enhancement amount of a second behavioral feature by applying a smaller weight based on the behavior of the subject including smaller movements
estimating psychological characteristic of the subject based on the one or the plurality of behavioral features,
outputting estimated psychological characteristic data that expresses the estimated psychological characteristic.
These steps amount to managing personal behavior or relationships or interactions
between people and therefore recite certain methods of organizing human activity including managing personal behavior or relationships or interactions between people. Generating related behavioral data of a subject, acquiring a plurality of non-verbal behavioral features with respect to a plurality of related behaviors, setting an enhancement amount by applying different weights based on the size of subject movements, using the behavioral features to estimate a psychological characteristic of the subject, and providing an output of the estimated psychological characteristic data, are personal behaviors that may be performed by one individual observing another individual, such as a psychologist or behavioral therapist, a healthcare provider, or a person conducting an interview with the subject.
The above claims are therefore directed to an abstract idea.
Step 2A Prong 2
This judicial exception is not integrated into a practical application because the additional
elements within the claims only amount to:
A. Instructions to Implement the Judicial Exception. MPEP 2106.05(f)
The independent claims additionally recite:
an interface apparatus that is configured to be connected for communication with a subject apparatus, the subject apparatus including one or a plurality of sensors (Claim 1)
an arithmetic operation apparatus configured for communication with the interface apparatus as implementing the steps of the abstract idea (Claim 1)
a computer as implementing the steps of the abstract idea (Claim 9)
a non-transitory computer-readable medium storing a computer program that is executable by the computer as implementing the steps of the abstract idea (Claim 10)
a personality characteristic estimation model as implementing the step of estimating a psychological characteristic of the subject (Claim 1)
The broad recitation of general purpose computing elements at a high level of generality only amounts to mere instructions to implement the abstract idea using computing components as tools.
Regarding the interface apparatus, paras. [0020]-[0022] disclose:
In the following description, “interface apparatus” may be one or more interface devices. One or more interface devices may be at least one of the following interface devices. An I/O interface apparatus that is one or more input/output (I/O) interface devices.
An input/output (I/O) interface device is an interface device for at least one of the I/O device and a remote display computer. The I/O interface device for the display computer may be a communication interface device. At least one I/O device may be a user interface device, for example, an input device such as a keyboard and a pointing device, or an output device such as a display device.
A communication interface apparatus that is one or more communication interface devices. One or more communication interface devices may be one or more communication interface devices of the same type (for example, one or more network interface cards (NIC)) or two or more communication interface devices of different types (for example, an NIC and a host bus adapter (HBA)).
Therefore, this element is given its broadest reasonable interpretation as a general purpose computing element using normal input devices as sensors (e.g., microphone, camera, keyboard), all of which are functioning in their ordinary capacity to implement the steps of the abstract idea.
Regarding the subject apparatus including one or mor sensors, para. [0032] discloses “The subject apparatus 130 is an information processing terminal, for example, a computer such as a personal computer or a smartphone of a subject 101. The subject apparatus 130 includes: one or a plurality of sensors that measure a behavior of the subject 101; and a display device 112. One or more sensors are formed of, for example, a camera 102, an input device 111 (for example, a keyboard and a pointing device), or a microphone 11. In place of or in addition to the input device 111, the display device 112 may be a touch panel”. Therefore, this element is given its broadest reasonable interpretation as a general purpose computing device such as a smartphone or PC using normal input devices as sensors (e.g., microphone, camera, keyboard), all of which are functioning in their ordinary capacity to implement the steps of the abstract idea.
Regarding the arithmetic processing apparatus, specification para. [0035] discloses “he arithmetic operation apparatus 115 is a processor and executes a computer program” where para. [0036] discloses “a “processor” may be one or more processor devices. At least one processor device may typically be a microprocessor device such as a central processing unit (CPU). However, the processor device may be a processor device of other type such as a graphics processing unit (GPU). At least one processor device may be a single core or a multi-core. At least one processor device may be a processor core.” Therefore, this element is given its broadest reasonable interpretation as a general purpose processor functioning in its ordinary capacity to implement the steps of the abstract idea.
Regarding the computer (Claim 9), no particulars are disclosed. Therefore, this element is given its broadest reasonable interpretation as a general purpose computer functioning in its ordinary capacity (paras. [0032], [0033]).
Regarding a non-transitory computer-readable medium storing a computer program that is executable by the computer (Claim 10), no particulars are disclosed. Therefore, this element is given its broadest reasonable interpretation as general purpose computing instructions being executed by a general purpose computing device functioning in its ordinary capacity (paras. [0027]).
Regarding the personality characteristic estimation model, per paras. [0072], [0096], this is understood to amount to a machine learning model or multiple equation regression model applied on a general purpose computer. The broad recitation of a machine learning model, in this case to estimate a psychological characteristic of a subject, only amounts to using the machine learning model as a tool to apply data to a model and generate a result (see MPEP 2106.05(f)(2)).
B. Insignificant Extra-Solution Activity. MPEP 2106.05(g)
Claim 1 additionally recites:
receive measurement data related to a behavior performed by a subject and based on measurement performed by the one or more sensors from the subject apparatus via the interface apparatus
Claims 9 and 10 additionally recite:
receiving measurement data related to a behavior performed by a subject and based on measurement performed by one or more sensors from a subject apparatus;
The above elements amount to insignificant extra-solution activity in the form of mere data gathering; they serve as pre-solution activity to gather data for use in the claimed process.
These elements in Sections A and B above are therefore not sufficient to integrate the abstract idea into a practical application. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually.
The above claims, as a whole, are therefore directed to an abstract idea.
Step 2B
The present claims do not include additional elements that are sufficient to amount to
more than the abstract idea because the additional elements or combination of elements amount to no more than a recitation of:
A. Instructions to Implement the Judicial Exception. MPEP 2106.05(f)
As explained above, claims 1, 9 and 10 only recite the aforementioned computing elements as tools for performing the steps of the abstract idea, and mere instructions to perform the abstract idea using a computer is not sufficient to amount to significantly more than the abstract idea. MPEP 2106.05(f).
B. Insignificant Extra-Solution Activity. MPEP 2106.05(g)
Likewise, as explained above, the elements of the arithmetic operation apparatus is configured to receive measurement data related to a behavior performed by a subject and based on measurement performed by one or more sensors from the subject apparatus via the interface apparatus, and, receiving measurement data related to a behavior performed by a subject and based on measurement performed by one or more sensors from a subject apparatus, only amounts to insignificant extra-solution activity in the form of mere data gathering.
C. Well-Understood, Routine and Conventional Activities. MPEP 2106.05(d)
In addition to amounting to insignificant extra-solution activity the elements in Section B above constitute well-understood, routine and conventional activity. The elements of the arithmetic operation apparatus is configured to receive measurement data related to a behavior performed by a subject and based on measurement performed by one or more sensors from the subject apparatus via the interface apparatus, and, receiving measurement data related to a behavior performed by a subject and based on measurement performed by one or more sensors only amount to receiving or transmitting data over a network and/or storing/retrieving data in memory, which have been previously held to be well-understood, routine and conventional when claimed at a high level of generality or as insignificant extra-solution activity. See MPEP 2106.05(d)(II).
Thus, taken alone, the additional elements do not amount to significantly more than the
above-identified judicial exception. Looking at the limitations as an ordered combination adds
nothing that is not already present when looking at the elements taken individually. Their
collective functions merely provide conventional computer implementation.
Depending Claims
Dependent claims recite additional subject matter which further narrows or defines the abstract idea embodied in the claims:
Claim 2 recites wherein the one or more of sensors includes a camera and the measurement data includes moving image data that is data expressing a moving image in which the subject imaged by the camera appears, which further narrows the scope of independent claim 1. Claim 2 additionally recites recognizing a region of a head itself of the subject or a region that includes the head of the subject from the moving image data, and setting an enhancement amount of a behavioral feature calculated with respect to the head region larger than an enhancement amount of a behavioral feature calculated related to a region other than the head region by applying a greater weight to the behavioral feature calculated with respect to the head region when estimating the psychological characteristic, which are also certain methods of organizing human activity including managing personal behaviors, as they are behaviors that could be performed by one person observing another. As discussed above with respect to Claim 1, recitation of “the arithmetic operation apparatus” only amounts to mere instructions to apply the abstract idea. MPEP 2106.05(f). This is not sufficient to integrate the judicial exception into a practical application or amount to significantly more.
Claim 4 recites limitations pertaining to a related behavior value that is a value of a related behavior is acquired from related behavioral data of the related behavior, which is also certain methods of organizing human activity including managing personal behaviors, a person could acquire/manipulate data. Claim 4 also recites limitations pertaining to determining the enhancement amount of the first behavioral feature based on determining larger movements of the subject is based on at least one of an average value, a standard deviation, a median value, a third quartile and a maximum value of a time series of the related behavior value, and determining the enhancement amount of the second behavioral feature behavior of the subject is based on at least one of a minimum value, a first quartile, and a second quartile of a time series of related behavior value, which further narrows the scope. These limitations are not sufficient to integrate the judicial exception into a practical application or amount to significantly more.
Claim 5 recites limitations pertaining to wherein the related behavioral data is data indicating a length of an answer time from a point of time that a question is provided to the subject to a point of time that an answer to the question is given, and the one or more behavioral feature include a behavioral feature based on the answer time or an amount of change in the answer time, which further narrows the scope. These limitations are not sufficient to integrate the judicial exception into a practical application or amount to significantly more.
Claim 6 recites limitations pertaining to wherein the one or more sensors include a camera, the measurement data includes moving image data that is data expressing a moving image in which the subject imaged by the camera appears, which further narrow the scope. Claim 6 also recites limitations pertaining to a related behavior value that is a value of a related behavior is acquired from related behavioral data, the behavioral feature is acquired from a time series of related behavior value, and determining, for each measurement window range of the moving image data, whether a change in a related behavior value of consecutive frames constituting the measurement window range satisfies a condition, detecting a related behavior value satisfying the condition as an outlier when a result of the determination is true, and correcting the detected outlier, which are also certain methods of organizing human activity including managing personal behaviors, as they are behaviors that could be performed by one person observing another. As discussed above with respect to Claim 1, recitation of “the arithmetic operation apparatus” only amounts to mere instructions to apply the abstract idea. MPEP 2106.05(f). This is not sufficient to integrate the judicial exception into a practical application or amount to significantly more.
Claim 7 recites limitations pertaining to estimating, for each of the measurement window ranges, a standard deviation of each related behavior value with respect to a median value within the measurement window range, determining whether or not the related behavior value that is over N times larger than the standard deviation from the median value is within the measurement window range (N being a predetermined value larger than 1), and in a case where the determination result is an outlier that is a true related behavior value, replacing the outlier with the median value, which are also certain methods of organizing human activity including managing personal behaviors, as they are behaviors that could be performed by individual performing statistical calculations/analysis. As discussed above with respect to Claim 1, recitation of “the arithmetic operation apparatus” only amounts to mere instructions to apply the abstract idea. MPEP 2106.05(f). This is not sufficient to integrate the judicial exception into a practical application or amount to significantly more.
Claim 8 recites limitations pertaining to wherein the measurement data is data relating to a behavior performed by the subject in a self-interview that is an interview where a virtual robot is an interviewer and the subject is a person who receives an interview and measured by the one or more sensors, which further narrows the scope. These limitations are not sufficient to integrate the judicial exception into a practical application or amount to significantly more.
Dependent claims 2, 4-8 recite additional subject matter which, as discussed above with respect to integration of the abstract idea into a practical application, amount to invoking computers as a tool to perform the abstract idea. Dependent claims recite additional subject matter which amount to limitations consistent with the additional elements in the independent claims. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation.
The dependent claims have been given the full two-part analysis including analyzing the additional limitations both individually and in combination. The dependent claims, when analyzed individually, and in combination, are also held to be patent ineligible under 35 U.S.C. 101 as they include all of the limitations of claim 1. The additional recited limitations of the dependent claims fail to establish that the claims do not recite an abstract idea because the additional recited limitations of the dependent claims merely further narrow the abstract idea. Beyond the limitations which recite the abstract idea, the claims recite additional elements consistent with those identified above with respect to the independent claims which encompass adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f). Accordingly, these additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
Dependent claims 2, 4-8 recite additional subject matter which amounts to additional elements consistent with those identified in the analysis of Claim 1 above. As discussed above with respect to Claim 1 and integration of the abstract idea into a practical application, recitation of these additional elements only amounts to invoking computers as a tool to perform the abstract idea. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation.
Dependent claims 2, 4-8, when analyzed as a whole, are held to be patent ineligible under 35 U.S.C. 101 because the additional recited limitation(s) fail(s) to establish that the claim(s) is/are not directed to an abstract idea without significantly more. These claims fail to remedy the deficiencies of their parent claims above, and are therefore rejected for at least the same rationale as applied to their parent claims above, and incorporated herein.
For the reasons stated, Claims 1, 2, 4-10 fail the Subject Matter Eligibility Test and are consequently rejected under 35 U.S.C. 101.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
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.
Claim(s) 1, 9, 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hill (US Publication 20120002848A1) in view of Qian et. al. (US Publication 20230111865A1).
Regarding Claim 1, Hill discloses:
an interface apparatus that is configured to be connected for communication with a subject apparatus, the subject apparatus including one or more sensors ([0049] teaches on collecting video via a webcam or video camera (“sensor”) which is “mounted on” or “built into” a “personal computer”, which is interpreted as a “subject apparatus including one or more sensors; [0107] teaches on a “user input module” which can be a keyboard, touch screen, vocal commands/responses, or any other method of interfacing with the computer system; Examiner interprets the user input module as being synonymous with “interface apparatus”; if the input module can “interface” with the computer system (subject apparatus), it is interpreted as being connected); and
an arithmetic operation apparatus connected for communication with the interface apparatus ([0107] teaches on processor 420, which is interpreted as the “arithmetic operation apparatus” (Applicant’s specification para. [0035] states this element is “a processor”; per para. [0107]/Fig. 21, the interview module is a computer system including user input module (interface apparatus) and a processor); wherein the arithmetic operation apparatus is configured to:
receive measurement data related to a behavior performed by a subject and based on measurement performed by the one or more sensors of the subject apparatus via the interface apparatus ([0107] teaches on a processor, which is interpreted as the arithmetic operation apparatus; [0049] teaches on using a web cam or video camera mounted onto/built into a personal computer, which can capture video images of a person as they are speaking, hearing, seeing presentations of statements, or otherwise engaged in behavior; the web cam/video camera is interpreted as a “sensor” built into a personal computer, which reads on “subject apparatus”; per Applicant’s specification paras. [0062], measurement data “includes data expressing the answer inputted via the input device” and [0068], “measurement data” is defined as “the measurement data from the subject apparatus 130 includes moving image data that expresses a moving image in which the subject 101 captured by the camera 102 is imaged”; therefore, Examiner interprets “video images” to read on broadest reasonable interpretation of this limitation as video images include “moving image data”; Examiner interprets “speaking, hearing, seeing presentations” to read on “behavior performed by a subject”; [0072] teaches on using standardized questions to determine a person’s personality type through a structured interview (participating in interview/answering questions is interpreted as the behavior performed by the subject); [0074] further teaches on reviewing video files of facial muscle activity and expressions of people being questioned (e.g., receiving “measurement data” (video) related to a behavior performed by a subject (responding to questions); per [0062] of instant specification, “measurement data” is understood to include “data expressing the answer via the inputted device 111” and as such, Examiner interprets the video of subject’s answers to questions, e.g., those shown in Figs. 12-13, to read on the claim language);
generate related behavioral data of a related behavior that is a behavior excluding instruction of a subject intention from the measurement data ([0072] teaches on using standardized questions to determine a person’s personality type through a structured interview to determine personality type; this is achieved by profiling a mixture/predominant display of emotions that best fit a given Big Five Factor personality trait; a person’s personality type may be revealed based on facial muscle activity or expression results from a sample piece of video and specific line of questions; [0074] further teaches on observing in real time or reviewing video files of facial muscle activity and expressions of people being questioned and singular instances of facial muscle movements and expressions are detected (interpreted “generating related behavioral data of a related behavior” as facial muscle activity and expressions are captured while the subject is responding to questions, e.g., the facial muscle activity and expressions are a related behavior of the subject responding to questions); [0097] teaches on observing and noting muscle activity contractions or other forms of movements such as duration, intensity and exact timing of such muscle activity; these observations may be during a close-up shot of an interview; per instant specification [0038], Examiner interprets the broadest reasonable interpretation “a behavior excluding designation of an intention” to be generating data of any behaviors of the subject other than the subject answering a question (“excluding designation of an intention of the subject”), e.g., body language; facial expressions are understood to be behaviors other than the subject answering the question or the subject’s answer to the question; [0107] teaches on a processor, which is interpreted as the arithmetic operation apparatus),
acquire one or more behavioral features that are respectively nonverbal features based on related behavioral data with respect each of one or more related behaviors ([0075] teaches on analyzing facial muscle activity and expressions using “facial coding”, a method of using standards to analyze emotions which stands out for its rigor and documentation, which a person’s emotions are gauged through “comprehensive or selective facial measurements” – Examiner interprets these “facial measurements” to read on “behavioral features” as the measurements are features of the related behavior (facial measurements, while responding to a question); facial measurements are non-verbal features based on the related behavioral data of the respective related behavior; [0107] teaches on a processor, which is interpreted as the arithmetic operation apparatus),
[setting an enhancement amount of a first behavioral feature by applying a weight] ([0058] teaches on coding to emotions or weighted emotional values; emotions coded from a detected single expression can be weighted as an indication of the likely strength of the emotion),
use at least one personality characteristic estimation model to estimate a psychological characteristic of the subject based on the one more behavioral features ([0075] as cited above teaches on using facial coding using “behavioral features” (e.g., facial measurements as taught by Hill) to gauge the emotion of a person; [0076] teaches on using facial coding (“FACS”) to identify muscle activities corresponding to one or more of seven core emotions, happiness, surprise, fear, anger, sadness, disgust, and contempt – interpreted as estimating psychological characteristic; [0074] teaches on using emotional recognition software for “automated facial coding” where [0112] teaches on a facial coding processing module that can be utilized to read facial muscle activity, AUs or general expressions based on the “repetitious refinement of algorithms trained to detect the action units that correspond to emotions in FACS or through any other method of analyzing and scoring facial expressions” – interpreted as synonymous with “at least one personality characteristic estimation model”; [0111] teaches on analysis steps being performed by a processor), and
output estimated psychological characteristic data that is data expressing the psychological characteristic that is estimated ([0039], [0040] and Figs. 12, 13 respectively, teach on a facial coding transcript which is coded to reveal positive or negative valence of a person’s speech when answering a question or revealing “particular emotions” (interpreted as “psychological characteristics”; per [0056] valence is interpreted as degree of positive vs. negative emoting a person shows, revealing their degree of positive emotional response; Fig. 12 shows subject’s response to a question and indications of where the subject had positive/negative emotions; Fig. 13 shows the question and subject’s response, as well as information displayed (e.g., outputted estimated psychological characteristic data) indicating the subject had a “surprise expression” and “fear shown”, suggesting “person is afraid or consequences or misassigning responsibility and guilt” – Examiner notes that “surprise” and “fear” are cited regarding Hill para. [0076] in the above limitation as a core emotion that can be identified from facial activities/expression; [0111] teaches on the processor aspects).
Hill may not explicitly disclose, but Qian, which is directed to spatial motion attention for intelligent video analytics, teaches:
set an enhancement amount of a first behavioral feature by applying a greater weight based on a behavior of the subject including larger movements ([0004] teaches on having more weighted values (interpreted as “greater” weights) for areas corresponding to areas in a motion image that reflect more motion; a weighted value is interpreted as an “enhancement amount”) and set an enhancement amount of a second behavioral feature by applying a smaller weight based on the behavior of the subject including smaller movements ([0004] teaches on having less weighted values for areas that correspond to areas in the motion image that reflect less motion; Examiner notes that per [0007] Qian’s “more” and “less” weighted values are understood to pertain to the weight value of an area and not the total number of weights).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to modify Hill with these teachings of Qian, to set enhancement amounts for different behavioral features of Hill by applying greater weights for larger movements and lower weights for smaller movements, with the motivation of enhancing data so that areas where motion is observed to be larger can be weighted higher in order to pay attention to that area where the larger motion is observed (Qian [0008]).
Regarding Claim 9, Hill discloses:
receiving measurement data related to a behavior performed by a subject and based on measurement performed by one or more sensors from a subject apparatus ([0049] teaches on using a web cam or video camera mounted onto/built into a personal computer, can capture video images of a person as they are speaking, hearing, seeing presentations of statements, or otherwise engaged in behavior; the web cam/video camera is interpreted as a “sensor” built into a personal computer, which reads on “subject apparatus”; per Applicant’s specification paras. [0062], measurement data “includes data expressing the answer inputted via the input device” and [0068], “measurement data” is defined as “the measurement data from the subject apparatus 130 includes moving image data that expresses a moving image in which the subject 101 captured by the camera 102 is imaged”; therefore, Examiner interprets “video images” to read on broadest reasonable interpretation of this limitation as video images include “moving image data”; Examiner interprets “speaking, hearing, seeing presentations” to read on “behavior performed by a subject”; [0072] teaches on using standardized questions to determine a person’s personality type through a structured interview (participating in interview/answering questions is interpreted as the behavior performed by the subject); [0074] further teaches on reviewing video files of facial muscle activity and expressions of people being questioned (e.g., receiving “measurement data” (video) related to a behavior performed by a subject (responding to questions); per [0062] of instant specification, “measurement data” is understood to include “data expressing the answer via the inputted device 111” and as such, Examiner interprets the video of subject’s answers to questions, e.g., those shown in Figs. 12-13, to read on the claim language);
generating related behavioral data of related behaviors that is all or part of behaviors excluding designation of an intention of the subject from the measurement data ([0072] teaches on using standardized questions to determine a person’s personality type through a structured interview to determine personality type; this is achieved by profiling a mixture/predominant display of emotions that best fit a given Big Five Factor personality trait; a person’s personality type may be revealed based on facial muscle activity or expression results from a sample piece of video and specific line of questions; [0074] further teaches on observing in real time or reviewing video files of facial muscle activity and expressions of people being questioned and singular instances of facial muscle movements and expressions are detected (interpreted “generating related behavioral data of related behaviors” as facial muscle activity and expressions are captured while the subject is responding to questions, e.g., the facial muscle activity and expressions are a related behavior of the subject responding to questions); [0097] teaches on observing and noting muscle activity contractions or other forms of movements such as duration, intensity and exact timing of such muscle activity; these observations may be during a close-up shot of an interview; per instant specification [0038] and as explained above in Claim Interpretations section, Examiner interprets the broadest reasonable interpretation of this “excluding designation of an intention” to be generating data of any behaviors of the subject other than the subject answering a question (“excluding designation of an intention of the subject”), e.g., body language, facial expressions are understood to be behaviors other than the subject answering the question or the subject’s answer to the question),
acquiring one or more behavioral features that are respectively nonverbal features based on related behavioral data with respect to one or more respective related behaviors ([0075] teaches on analyzing facial muscle activity and expressions using “facial coding”, a method of using standards to analyze emotions which stands out for its rigor and documentation, which a person’s emotions are gauged through “comprehensive or selective facial measurements” – Examiner interprets these “facial measurements” to read on “behavioral features” as the measurements are features of the related behavior (facial measurements, while responding to a question); facial measurements are non-verbal features based on the related behavioral data of the respective related behavior);
[setting an enhancement amount of a first behavioral feature by applying a weight] ([0058] teaches on coding to emotions or weighted emotional values; emotions coded from a detected single expression can be weighted as an indication of the likely strength of the emotion),
estimating psychological characteristic of the subject based on the one or more behavioral features ([0075] as cited above teaches on using facial coding using “behavioral features” (e.g., facial measurements as taught by Hill) to gauge the emotion of a person; [0076] teaches on using facial coding (“FACS”) to identify muscle activities corresponding to one or more of seven core emotions, happiness, surprise, fear, anger, sadness, disgust, and contempt – interpreted as estimating psychological characteristic);
outputting estimated psychological characteristic data that expresses the estimated psychological characteristic ([0039], [0040] and Figs. 12, 13 respectively, teach on a facial coding transcript which is coded to reveal positive or negative valence of a person’s speech when answering a question or revealing “particular emotions” (interpreted as “psychological characteristics”; per [0056] valence is interpreted as degree of positive vs. negative emoting a person shows, revealing their degree of positive emotional response; Fig. 12 shows subject’s response to a question and indications of where the subject had positive/negative emotions; Fig. 13 shows the question and subject’s response, as well as information displayed (e.g., outputted estimated psychological characteristic data) indicating the subject had a “surprise expression” and “fear shown”, suggesting “person is afraid or consequences or misassigning responsibility and guilt” – Examiner notes that “surprise” and “fear” are cited regarding Hill para. [0076] in the above limitation as a core emotion that can be identified from facial activities/expression).
Hill may not explicitly disclose, but Qian, which is directed to spatial motion attention for intelligent video analytics, teaches:
set an enhancement amount of a first behavioral feature by applying a greater weight based on a behavior of the subject including larger movements ([0004] teaches on having more weighted values (interpreted as “greater” weights) for areas corresponding to areas in a motion image that reflect more motion; a weighted value is interpreted as an “enhancement amount”) and set an enhancement amount of a second behavioral feature by applying a smaller weight based on the behavior of the subject including smaller movements ([0004] teaches on having less weighted values for areas that correspond to areas in the motion image that reflect less motion; Examiner notes that per [0007] Qian’s “more” and “less” weighted values are understood to pertain to the weight value of an area and not the total number of weights).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to modify Hill with these teachings of Qian, to set enhancement amounts for different behavioral features of Hill by applying greater weights for larger movements and lower weights for smaller movements, with the motivation of enhancing data so that areas where motion is observed to be larger can be weighted higher in order to pay attention to that area where the larger motion is observed (Qian [0008]).
Regarding Claim 10, Hill/Qian teach the limitations of Claim 9. Claim 10 recites limitations that are the same or substantially similar to Claim 9, and the discussion above with respect to Claim 9 is equally applicable to Claim 10. The only different is that Claim 10 is directed to a “non-transitory computer-readable medium storing a computer program that is executable by a computer”. Hill additionally teaches on this architecture as implementing steps of the claimed invention (see Hill, at least paras. [0107], [0109], [0111]). Claim 10 is rejected for the same reasons as Claim 9.
Claim(s) 2 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hill (US Publication 20120002848A1) in view of Qian et. al. (US Publication 20230111865A1) as applied to Claim 1 above, and further in view of Kim (KR20250092518A).
Regarding Claim 2, Hill/Qian teach the limitations of Claim 1. Hill further discloses wherein the one or more plurality of sensors includes a camera ([0049], teaching on using a web cam or video camera mounted onto/built into a personal computer; [0108] further teaches on the camera module which includes a video camera/web cam):
the measurement data includes moving image data that is data expressing a moving image in which the subject imaged by the camera appears ([0049] teaches on a webcam/video camera capturing video images of a person as they are speaking, hearing, seeing written presentations, etc.; [0108] teaches on the video camera/web cam capturing video footage allowing for viewing of at least 2/3 of the person’s face – video is interpreted as a “moving image”; footage of the person’s face is interpreted as the subject appearing in the moving image), and:
the arithmetic operation apparatus is further configured to recognize a region of a head itself of the subject or a region that includes the head of the subject from the moving image data ([0074] teaches on using software to perform automated facial coding, taking into account 43 facial muscles for the purposes of detecting singular instances of muscle movements and expressions; Fig. 5 illustrates a human face indicating the location of facial features which can be utilized – if the software can detect and measure specific facial muscle movements/expressions, Examiner interprets this as teaching on the system recognizing the subject’s head in order to recognize which muscles are being utilized).
Hill does not disclose the following, but Kim, which is directed to a method and device for managing patient emotion, teaches: set an enhancement amount of a behavioral feature calculated with respect to the head region larger than an enhancement amount of a behavioral feature calculated related to a region other than the head region by applying a greater weight to the behavioral feature calculated with respect to the head region when estimating the psychological characteristic (Page 6, last para. continuing to page 7, first paragraph, teaches on sensing data from different body portions, e.g., head, wrist, ankle, chest; the processor may set a “high weight” for the head (“greater weight” with respect to head region) and a “low weight” for the ankle and wrist).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to modify Hill/Qian with these teachings of Kim, to apply a greater weight (interpreted as enhancement amount) to behavioral features calculated with respect to the head region and a lower weight (enhancement amount) to behavioral features associated with a region other than the head, with the motivation of weight different regions of the body to consider the importance of the regions (Kim, page 6, last paragraph).
Claim(s) 4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hill (US Publication 20120002848A1) in view of Qian et. al. (US Publication 20230111865A1) as applied to Claim 1 above, further in view of Sheth (WIPO Publication WO 2022254462A1), and further in view of Kano (US Publication 20230240623A1).
Regarding Claim 4, Hill/Kim teach the limitations of Claim 1. Hill further discloses wherein a related behavior value that is a value of a related behavior is acquired from related behavioral data of the related behavior ([0075] teaches on facial coding through “comprehensive or selective facial measurements”; Examiner interprets measurements to teach on a “value” of the related behavior, e.g., a related behavior value);
behavioral feature ([0075] teaches on analyzing facial muscle activity and expressions using “facial coding”, a method of using standards to analyze emotions which stands out for its rigor and documentation, which a person’s emotions are gauged through “comprehensive or selective facial measurements” – Examiner interprets these “facial measurements” to read on “behavioral features” as the measurements are features of the related behavior (facial measurements, while responding to a question).
Hill may not explicitly disclose, but Qian, which is directed to spatial motion attention for intelligent video analytics, teaches:
determining the enhancement amount of the first feature based on determining larger movements of the subject based on determining larger movements of the subject is determined based on [an amount of motion] ([0004] teaches on having more weighted values (interpreted as “greater” weights) for areas corresponding to areas in a motion image that reflect more motion; a weighted value is interpreted as an “enhancement amount”)
determining the enhancement amount of the second feature based on determining smaller movements of the subject is determined based on [an amount of motion] ([0004] teaches on having less weighted values for areas that correspond to areas in the motion image that reflect less motion; Examiner notes that per [0007] Qian’s “more” and “less” weighted values are understood to pertain to the weight value of an area and not the total number of weights).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to modify Hill with these teachings of Qian, to set enhancement amounts based on determining larger and smaller movements based on the amount of motion of the subject, with the motivation of enhancing data so that areas where motion is observed to be larger can be weighted higher in order to pay attention to that area where the larger motion is observed (Qian [0008]).
Hill/Qian do not teach, but Sheth, which is directed to a medical monitoring device, teaches: an amount is at least one of an average value, a standard deviation, a median value, a third quartile and a maximum value of a time series of the related value ([0052] teaches on using a sliding window across a time-series of data; for each window, the median and standard deviation are determined; a median value can be a feature that indicates size of data points, e.g., how large).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to modify Hill/Qian with these teachings of Sheth, use Sheth’s median or standard deviation value as the weight amount of Qian, with the motivation of using the mean and standard deviation to identify and subsequently remove outlying data and anomalies to obtain a “clean” dataset (Sheth [0051]).
Hill/Qian/Sheth do not teach, but Kano, which is directed to a medical information display apparatus, teaches:
an amount is at least one of a minimum value, a first quartile, and a second quartile of a time series value ([0069] teaches on displaying a first quantile value, second quantile value (Examiner interprets ‘quantiles’ to be synonymous with ‘quartiles’) and minimum value on the basis of time series data over a reference period).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to further modify Hill/Qian/Sheth with these teachings of Yano, to use Yano’s first/second quantile of Yano as the weight amount of Qian, with the motivation of using the data to determine a state of the individual corresponding to the time period (Yano, Abstract).
Claim(s) 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hill (US Publication 20120002848A1) in view of Qian et. al. (US Publication 20230111865A1) as applied to Claim 1 above, and further in view of Mani et. al. (US Publication 20150339684A1).
Regarding Claim 5, Hill/Qian teach the limitations of Claim 1 but does not teach the following. Mani, which is directed to survey data processing, teaches
wherein the [obtained] data is data indicating a length of an answer time from a point of time that a question is provided to the subject to a point of time that an answer to the question is given ([0015] teaches on receiving a first response (“answer”) to a first survey question (“question”); a “response time” indicates how much time has elapsed from the question being provided to the first response being provided), and the one or more behavioral feature include a behavioral feature based on the answer time or an amount of change in the answer time ([0015] teaches on a response time being less than a predetermined time interval; time taken to respond being less than predetermined interval is interpreted as a “behavioral feature” which is based on the actual answer time).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to modify Hill/Qian with these teachings of Mani, to determine and use the length of time that it takes to receive an answer to a question as the “related behavioral data” of Hill, and to use this time as a behavioral feature, with the motivation of determining credibility of the user’s response based on response time, because responses being provided in less than a particular amount of time elapsed may indicate poor credibility (Mani [0015]).
Claim(s) 6-7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hill (US Publication 20120002848A1) in view of Qian et. al. (US Publication 20230111865A1) as applied to Claim 1 above, further in view of Sheth (WIPO Publication WO2022254462A1).
Regarding Claim 6, Hill/Qian teach the limitations of Claim 1. Hill further discloses wherein the one or more sensors include a camera ([0049], teaching on using a web cam or video camera mounted onto/built into a personal computer; [0108] further teaches on the camera module which includes a video camera/web cam), the measurement data includes moving image data that is data expressing a moving image in which the subject imaged by the camera appears ([0049] teaches on a webcam/video camera capturing video images of a person as they are speaking, hearing, seeing written presentations, etc.; [0108] teaches on the video camera/web cam capturing video footage allowing for viewing of at least 2/3 of the person’s face – video is interpreted as a “moving image”; footage of the person’s face is interpreted as the subject appearing in the moving image), a related behavior value that is a value of a related behavior is acquired from related behavioral data ([0075] teaches on facial coding through “comprehensive or selective facial measurements”; Examiner interprets measurements to teach on a “value” of the related behavior), the behavioral feature is acquired from a time series of related behavior value ([0095] teaches on utilizing frame-by-frame, split second measurements (“time series” of related behavior values; [0116] further teaches on identifying duration and intensity (behavioral feature) of facial muscle expression (related behavior) from captured video analyzed on a second by second basis, e.g., 30 frames per second), and the arithmetic operation apparatus is further configured to determine, for each measurement window range of the moving image data, whether a change in a related behavior value of consecutive frames constituting the measurement window range satisfies a condition ([0095] teaches on utilizing frame-by-frame, second by second measurements to detect possible instances of lying; the system can determine for whether muscle activity has a “natural onset (smooth and fast, versus slow and jerky onsets for posed expressions)” – determining “onset” being smooth, slow, fast, jerky is interpreted as determining changes in behavioral values of consecutive frames within a measurement window range; the system can note that expressions are “asymmetrical” as indicating the expression is forced or contrived; identifying odd timing, such as expression arriving too late or too early in conjunction with expressed statements and is “out of synch”, when a surprised look or smile lasts longer than expected, or detecting multiple action units (muscles) peak simultaneously or fail to peak, which are all indications of an “unnatural, posed expression”; [0095] further teaches on Fig. 18 and what a natural expression looks like vs. a faked/posed expression and sustain itself as a “butte” with a distinct peak and end quickly – any of the aforementioned means of detecting natural vs. faked/posed expression are interpreted as satisfying a condition, e.g., odd timing or out of synch statements are a condition; detecting a butte shape with distinct peak and quick drop off are interpreted as satisfying the condition of a non-natural expression).
Hill/Quan do not teach the following, but Sheth, which is directed to a medical monitoring device, teaches detect a value satisfying the condition as an outlier when a result of a determination is true, and correct the detected outlier ([0052] teaches on extracting time series data using a configurable-width sliding window across a time series; for each window, the filter calculates the median and estimates the window’s standard deviation; if more than 3 out from the window’s median, the point is identified as an outlier and the outlier is replaced with the window’s median – interpreted as “correcting the detecting outlier”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to modify Hill/Qian with these teachings of Sheth, to detect a value satisfying a condition as an outlier when the determination of Hill is true (e.g., condition is satisfied as taught by preceding limitation), and to correct the detected outlier, with the motivation of removing outlying data and anomalies to obtain a “clean” dataset and replacing the outlier with the median value to provide a complete data set without missing data (Sheth [0051]).
Regarding Claim 7, Hill/Qian/Sheth teach the limitations of Claim 6. Hill/Qian do not teach, but Sheth further teaches wherein the arithmetic operation apparatus ([0017], [0018] teach on a processing unit/processor which are interpreted as reading on arithmetic operation apparatus) is further configured to estimate, for each of the measurement window ranges, a standard deviation of each value with respect to a median value within the measurement window range ([0052] teaches on extracting time series data using a configurable-width sliding window across a time series, e.g., “measurement window range”; for each window, the filter calculates the median and estimates the window’s standard deviation),
determine whether or not the value that is over N times larger than the standard deviation from the median value is within the measurement window range (N being a predetermined value larger than 1) ([0052] teaches on extracting time series data using a configurable-width sliding window across a time series; for each window, the filter calculates the median and estimate the window’s standard deviation; if more than 3 out from the window’s median, the point is identified as an outlier; Examiner interprets 3 as “N” within the sliding window (“measurement window” range) and in a case where the determination result is an outlier that is a true value, replace the outlier with the median value ([0052] teaches on replacing a point more than standard deviations out from the windows median, replacing it with the window’s median).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to modify Hill/Qian with these teachings of Sheth, to estimate a standard deviation for each measurement window for the related behavior value of Hill, determine whether the value is more than N deviations from the median value within the window, and replace the outlier with the median value when an outlier is detected, with the motivation of removing outlying data and anomalies to obtain a “clean” dataset and replacing the outlier with the median value to provide a complete data set without missing data (Sheth [0051]).
Claim(s) 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hill (US Publication 20120002848A1) in view of Qian et. al. (US Publication 20230111865A1) as applied to Claim 1 above, and further in view of Shellnutt (US Publication 20070185723A1).
Regarding Claim 8, Hill discloses the limitations of Claim 8 but does not disclose the following. Shellnutt, which is directed to a method and apparatus for facilitating employment interviews, teaches: wherein the measurement data is data relating to a behavior performed by the subject in a self-interview that is an interview where a virtual robot is an interviewer and the subject is a person who receives an interview and measured by the one or more sensors ([0004] teaches on capturing real time audio and video of a job interview between a job seeker and a virtual assistant, the audio/video are recorded and able to be replayed for viewing at a later time; [0013] teaches on using a “web cam” to capture a job seeker answering interview questions; the web cam is interpreted as a sensor which captures the video of [0004]; [0016] teaches on “job seekers” (subjects) interviewing for jobs over the internet; job seekers will converse with a Virtual Assistant (interpreted as virtual robot) and answer prearranged questions prescribed by the employers; employers can watch the job seeker conversing with the virtual assistant by accessing a recording; [0022] teaches on a “computer-generated” virtual assistant which is animated and moves, speaks and sounds like a living human being).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to modify Hill with these teachings of Shellnutt, so to use the measurement data pertaining to a behavior of the subject in a self-interview with a virtual robot, with the motivation of enabling job seekers to interview for jobs at a time and location that are preferable for the job seeker while providing time and cost savings for the employer as they do not have to actually conduct the interview themselves (Shellnutt [0011], [0013], [0016]).
Response to Applicant’s Remarks/Arguments
Please note: When referencing page numbers of Applicant’s response, references are to page numbers as printed.
Claim Objections
The objections to Claims 9 and 10 for typographical/spelling error of “intension” are withdrawn in view of Applicant’s amendments to these claims.
Rejections under 35 USC 112(a)
The rejections of Claims 1, 9, 10 and corresponding dependent claims for lack of written description pertaining to the “estimation” limitation are withdrawn in view of Applicant’s remarks to relevant portions of specification and amendments.
Rejections under 35 USC 112(b)
The rejections of Claims 1 and 4, and corresponding dependent claims are withdrawn in view of Applicant’s amendments to Claim 1 and 4. As claim 3 has been canceled by Applicant, the rejection under 112(b) is moot.
Rejections under 35 USC 101 – non-statutory subject matter
Regarding the rejection of Claim 10 under 35 USC 101 for being directed to non-statutory subject matter, this rejection is withdrawn as Applicant has amended Claim 10 such that it falls within a statutory category.
Rejections under 35 USC 101 – judicial exception
Regarding the rejection of Claims 1, 2, 4-10 under 35 USC 101, Applicant’s remarks have been fully considered but are not persuasive.
Applicant argues:
The claims are not directed to an a abstract idea (page 13)
Regarding (A), the Examiner respectfully disagrees. The Examiner respectfully disagrees. MPEP 2106. 04(a)(2)(II) states that a claimed invention is directed to certain methods of organizing human activity (an abstract idea) if the identified claim elements contain limitations that encompass fundamental economic principles or practices, commercial or legal interactions, or managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions). The Examiner submits that the identified claim elements represent a series of personal behaviors that a person or person, with or without the aid of a computer, would follow to estimate a psychological characteristic of the subject and provide an output of the estimated psychological characteristic data. Applicant has not pointed to anything in the claims that fall outside of this characterization. Because the claim elements fall under a set of personal behaviors that a person or persons would follow to estimate and provide an indication of a psychological characteristic of a subject, the claimed invention is directed to an abstract idea. This argument is not persuasive.
Applicant's independent claims 1, 9, and 10 are directed to an improvement in the functioning of another technology, namely an improvement in the technology for communication through a computer interface that includes detection of psychological characteristics of a subject during the electronic communications (page 18)
Regarding (B), the Examiner respectfully disagrees. MPEP 2106.04(d)(1) states that a practical application may be present where the claimed invention improves another technology. See also MPEP 2106.05(a)(II). Applicant’s claim is confined to a general-purpose computer (see Spec. Paras. [0032]-[0036]) and does not recite “another technology.” Because no other technology is recited in the claim, the claim cannot improve another technology (see, e.g., MPEP 2106.05(I)(A)(i) describing an example of an improvement to another technology where the abstract idea implemented on a computer improved the claimed additional element of a rubber molding machine). Applicant’s claimed invention recites the additional element(s) of an interface apparatus that is configured to be connected for communication with a subject apparatus, the subject apparatus including one or a plurality of sensors, an arithmetic operation apparatus configured for communication with the interface apparatus, and personality characteristic estimation model in Claim 1 (representative). While these additional elements implement the steps of the abstract idea, there is no indication that these additional elements operate in a manner different than they normally operate. [note: for example, using the arithmetic apparatus (interpreted as a processor per [0035]-[0036] to generate related behavioral data, acquire one or more behavioral features, set an enhancement amount of behavioral features, estimate a personality characteristic and output the estimated characteristic does not improve the computer system or processor; they are operating as they normally would operate.] Operating another device in the manner it normally operates is insufficient to improve that other technology. As such, these additional elements are not improved through implementation of the abstract idea and a practical application is not present.
Regarding citations to paras. [0005] and [0008] of Applicant’s specification at page 18, Examiner is unable to identify evidence of any additional elements that improve the functioning of a computer or another technology. Regarding para. [0008], Examiner submits that the ability to estimate the psychological characteristic of a subject without making the subject perform a dedicated behavior is not an improvement provided by one or more additional elements.
Regarding remarks at last paragraph on page 18 continuing to page 19, Examiner respectfully disagrees that the judicial exception is integrated into a practical application. As discussed above, the additional elements only amount to general purpose computing components used to apply the abstract idea. This is not sufficient to integrate the judicial exception into a practical application. MPEP 2106.05(f).
Regarding remarks at top of page 19 pertaining to “a technical solution to a technical problem”, Examiner submits that the problem of “determining the psychological characteristics of a remote subject, such as during an interview of other conversation conducted through computer communication technology”, as described in the specification, is not a probably caused by the technological environment of the claim (a computer system), as evidenced by Applicant’s next statement, that “when conducting a conversation through a computer interface (as opposed to in-person), it may be more difficult for a participant to determine psychological characteristics of another participant”. Examiner submits that by “providing an indication of psychological characteristics of a subject without requiring the use of any particular questions of the type conventionally required for psychological evaluations”, the claimed invention may provide an improvement to the abstract idea itself – e.g., an improved way of determining psychological characteristics of a subject which uses behaviors rather than particular questions conventionally used for psychological evaluations. Examiner submits that this may be an improvement to the abstract idea, e.g., instead of asking a subject particular questions used for psychological intervention, an observer could watch and analyze their behaviors to determine psychological characteristics based on the user’s behaviors/movements. Regarding integration of a judicial exception into a practical application, please see 2106.04(d)(II) which states, “The analysis under Step 2A Prong Two is the same for all claims reciting a judicial exception, whether the exception is an abstract idea, a law of nature, or a natural phenomenon (including products of nature). Examiners evaluate integration into a practical application by: (1) identifying whether there are any additional elements recited in the claim beyond the judicial exception(s); and (2) evaluating those additional elements individually and in combination to determine whether they integrate the exception into a practical application, using one or more of the considerations introduced in subsection I supra, and discussed in more detail in MPEP §§ 2106.04(d)(1), 2106.04(d)(2), 2106.05(a) through (c) and 2106.05(e) through (h)”, and MPEP 2106.05(a) which states, “It is important to note, the judicial exception alone cannot provide the improvement. The improvement can be provided by one or more additional elements.” Applicant has not provided, nor can Examiner find evidence of, how any of the additional elements identified above in main 101 analysis section are providing an improvement over prior art systems. The additional elements identified above are understood to be computing components functioning in their normal operating capacity, which is not sufficient to integrate the judicial exception into a practical application.
These arguments are not persuasive.
The claims include significantly more than the alleged abstract idea (page 19)
Regarding (C), the Examiner respectfully disagrees. Applicant argues at the top of page 20 “Applicant's claims recite meaningful unconventional elements that amount to
significantly more than the alleged abstract idea. In particular, Applicant's claims 1, 9,
and 10, as presented herein, include specific recitations directed to other than what
is well-understood, routine, and conventional in the field”. However, Applicant has not cited to, nor can Examiner find, evidence in Applicant’s specification regarding how the combination of additional elements provides an inventive concept that is not well understood, routine and conventional in the field.
Regarding remarks directed to BASCOM, Examiner respectfully disagrees that the instant application and claims are analogous to BASCOM. See MPEP 2106.06(b). The claims in BASCOM were found to be eligible because they presented a technology-based improvement to methods in which web filtering was performed which overcame disadvantages with prior art systems disclosed in the specification by using a non-conventional arrangement of web filters (e.g., additional elements). Unlike BASCOM, Applicant has not provided evidence in the specification as originally filed to demonstrate how the claimed invention provides a non-conventional arrangement of additional elements.
Regarding remarks at bottom of page 20 continuing to page 21, and particular Applicant’s remark at page 21 “The above-emphasized additional elements of Applicant’s claim 1…”, Examiner respectfully submits that Applicant has presented Claim 1 its entirety, including limitations falling within the scope of the abstract idea. This is not persuasive for identifying how additional elements amount to significantly more than the judicial exception. At page 21-22, Applicant appears to be arguing the limitations falling within the scope of the abstract idea (e.g., generating related behavioral data). Examiner submits that a “specific technique” falls within the scope of the abstract idea and is not sufficient to amount to significantly more. Furthermore, Applicant respectfully submits that the “ordered combination” pertains to additional elements. An “ordered combination” of specific steps isn’t enough if they’re all within the abstract idea and merely implemented by generic computing elements or software. MPEP 2106.05(I)(B).
These arguments are not persuasive.
Regarding remarks directed to deponent claims at page 22: The dependent claims, when analyzed individually, and in combination, are also held to be patent ineligible under 35 U.S.C. 101 as they include all of the limitations of claim 1. Applicant has not offered specific arguments other than to assert that the dependent claims ultimately depend from Claim 1 and are patient eligible at least due to their dependency from an allowable base claim, which is not persuasive. As discussed above with respect to claim 1, Claim 1 remains rejected under 35 USC 101.
For all of the above reasons, the rejections of Claims 1-2, 4-10 under 35 USC 101 are maintained.
Rejections under 35 USC 102/103
Applicant’s arguments with respect to claim(s) 1, 9, 10 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. The Qian reference has been cited in combination with Hill to teach on the amended limitations in the independent claims.
Regarding the rejection of dependent Claims 2, 4-8, the Applicant has not offered any arguments with respect to these claims other than to reiterate the argument(s) present for the claims from which they depend. As such, the rejection of these claims is also maintained.
The prior art rejections of Claims 1, 2, 4-10 are maintained under 35 USC 103.
Conclusion
Examiner respectfully requests that Applicant provides citations to relevant paragraphs of specification for support for amendments in future correspondence.
The following relevant prior art not cited is made of record:
US Publication 20220192556 A1, teaching on predictive, diagnostic and therapeutic applications of wearables for mental health
US Publication 20150242707A1, teaching on a system and method for predicting personality traits, capabilities and suggested interactions from images of a person
US Publication 20190080799 A1, teaching on identifying and targeting personality type and behaviors
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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 extension fee 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 date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ANNE-MARIE K ALDERSON whose telephone number is (571)272-3370. The examiner can normally be reached on Mon-Fri 9:00am-5:00pm EST, and generally schedules interviews in the timeframe of 2:00-5:00pm EST.
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, Fonya Long, can be reached on 571-270-5096. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/ANNE-MARIE K ALDERSON/Primary Examiner, Art Unit 3682
Prosecution Insights