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 .
Response to Amendment
The amendment filed 28 April 2026 has been entered. Claim(s) 1-2, 5-6, and 8-19 are pending in the application. Applicant’s amendments to the claims have overcome each and every objection to the claims previously set forth in the Office Action mailed 28 January 2026. Interpretation under 35 U.S.C. 112(f) is additionally withdrawn in light of the amendments to the claims.
Claim Objections
Claims objected to because of the following informalities:
Claim 1, line 4 “the user’s eye movement” should be “a user’s eye movement”
Claim 1, line 10 “merging the preprocess attention data” should be “merging the preprocessed attention data to produce merged attention test data”.
Claim 1, line 11 “reducing the merged attention test data dimensionally” should be “reducing the merged attention test data dimensionally to produce reduced attention test data”.
Claim 10, line 19 “merge the preprocess attention data” should be “merge the preprocessed attention data to produce merged attention test data”.
Claim 10, line 20 “reduce the merged attention test data dimensionally” should be “reduce the merged attention test data dimensionally to produce reduced attention test data”.
Appropriate correction is required.
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- 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.
Claim 1 recites the limitation “attention test data generated by performing the standardized attention test”. There is insufficient antecedent basis for “standardized attention test”. The limitation is interpreted as referring to attention test data generated by the user performing a standardized attention test.
Claims 2, 5-6, 8-9 and 11 are rejected under 35 U.S.C. 112(b) as indefinite due to their dependence on claim 1, which has been rejected as indefinite.
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.
Utilizing the two step process adopted by the Supreme Court (Alice Corp vs CLS Bank Int'l, US
Supreme Court, 110 USPQ2d 1976 (2014) and the recent 101 guideline Federal Register Vol. 84, No., Jan
2019)), determination of the subject matter eligibility under the 35 U.S.C. 101 is as follows: Specifically, the Step 1 requires claim belongs to one of the four statutory categories (process, machine, manufacture, or composition of matter). If Step 1 is satisfied, then in the first part of Step 2A (Prong One), identification of any judicial recognized exceptions in the claim is made. If any limitation in the claim is identified as judicial recognized exception, then in the second part of Step 2A (Prong Two), determination is made whether the identified judicial exception is being integrated into practical application. If the identified judicial exception is not integrated into a practical application, then in Step 2B, the claim is further evaluated to see if the additional elements, individually and in combination provide "inventive concept" that would amount to significantly more than the judicial exception. If the element and combination of elements do not amount to significantly more than the judicial recognized exception itself, then the claim is ineligible under the 35 U.S.C. 101.
Claims 1-2, 5-6, and 8-19 are rejected under 35 U.S.C. 101.
Claim 1 is rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception, in this case an abstract idea, without significantly more. The claim recite(s) "providing, using a learning model, mental disorder diagnosis and treatment response information by inputting the generated user attention information and the reduced attention test data to the learning model". This judicial exception is not integrated into a practical application and the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Claim 1 satisfies Step 1, namely the claim is directed to one of the four statutory classes, method. Following Step 2A Prong one, any judicial exceptions are identified in the claims. In claim 1, the limitations "providing, using a learning model, mental disorder diagnosis and treatment response information by inputting the generated user attention information and the reduced attention test data to the learning model" are abstract ideas as they are directed to a mental process and/or mathematical calculation, as with no further limitations being provided regarding the learning model the action of using a generic model to provide diagnosis and treatment response information may be performed in the human mind using various calculations and judgments based on received data in comparison to known information relating to diagnoses and treatments. With the identification of an abstract idea, the next phase is to proceed Step 2A, Prong Two, wherewith additional elements and taken as a whole, evaluation occurs of whether the identified abstract idea is integrated into a practical application.
In Step 2A, Prong Two, the claim does not recite any additional elements or evidence that amounts to significantly more than the judicial exception. Besides the abstract idea, the claim recites the additional elements “generating user attention information based on the user's eye movement; receiving the generated user attention information and attention test data generated by performing the standardized attention test; preprocessing the attention test data by estimating missing values and standardizing the attention test data; merging the preprocess attention test data; reducing the merged attention test data dimensionally” and “wherein the generating the user attention information comprises: determining, from gaze coordinate values using eve tracking, a degree of attention on whether the user is looking at the monitor screen during the standardized test or a target area set within the monitor screen based on a pre-set number of frames per second; setting an area of interest in the target area within the monitor screen during the standardized test, and determining whether the user is focusing on the set area of interest based on pre-set criteria information; setting remaining areas other than the area of interest set in the target area within the monitor screen as non-interest areas, and determining response inhibition information related to a user's gaze at the set non-interest areas using visual indicators including a commission error, a response time, and a total time and generating the user attention information based on the degree of attention, whether the user is focusing, and the response inhibition information”. However, these components may be seen as the use of well-understood, routine, or conventional elements to perform a non-mental process in order to gather data for the mental process step, much like the example given in MPEP 2106.04(d)(2)(c), such that these limitations are extra-solution activity and thus do not integrate the judicial exception into a practical application. The generating and receiving steps leads to the final step of “providing, using a learning model, mental disorder diagnosis and treatment response information” such that the end result of use of the system is only the generic mental disorder diagnosis and treatment response information which may be any generic output, or no output at all. As providing this information is not defined as requiring any further action, such as a particular form of prophylaxis or treatment or an improvement to a computer or other technology, the claim limitations constitute mere generation of data, in this case the measurement of data relating to user attention information, such that the claim does not integrate the judicial exception into any practical application. Under the broadest reasonable interpretation, the claim elements are recited with a high level of generality (as written, the process may be performed by a person in an undefined manner using any generic learning model) that there are no meaningful limitations to the abstract idea. Consequently, with the identified abstract idea not being integrated into a practical application, the next step is Step 2B, evaluating whether the additional elements provide "inventive concept" that would amount to significantly more than the abstract idea.
In Step 2B, claim 1 does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The limitation of “generating user attention information based on the user's eye movement; receiving the generated user attention information and attention test data generated by performing the standardized attention test; preprocessing the attention test data by estimating missing values and standardizing the attention test data; merging the preprocess attention test data; reducing the merged attention test data dimensionally” and “wherein the generating the user attention information comprises: determining, from gaze coordinate values using eve tracking, a degree of attention on whether the user is looking at the monitor screen during the standardized test or a target area set within the monitor screen based on a pre-set number of frames per second; setting an area of interest in the target area within the monitor screen during the standardized test, and determining whether the user is focusing on the set area of interest based on pre-set criteria information; setting remaining areas other than the area of interest set in the target area within the monitor screen as non-interest areas, and determining response inhibition information related to a user's gaze at the set non-interest areas using visual indicators including a commission error, a response time, and a total time and generating the user attention information based on the degree of attention, whether the user is focusing, and the response inhibition information” constitutes extra-solution activity to the judicial exception, which does not amount to an inventive concept when the activity is well-understood, routine, or conventional, and are thus not indicative of integration into a practical application. The claim limitation constitutes adding a generic monitoring screen and eye-tracking system, which Eizenman (US 20140148728 A1) describes as well-understood, routine or conventional in its description of various prior art references which include eye tracking systems and related computer-based monitoring systems (Paragraphs 0003-0012) as well as “computing devices that include, but are not limited to, desk-top computers, portable computers, mobile computing devices such as tablets or cell phones with either internal eye-tracking devices (i.e., eye-tracking devices that are supported by the operating system of the computing devices) or eye-tracking devices that are external to the computing device (eg., data from the eye-tracker is transferred through one of the communication ports of the computing device)” (Paragraph 0043). Bower (US 20190216392 A1) similarly discloses that such elements are well-understood, routine, or conventional in the art in paragraphs 0045, 0142, and 0371 which describe common user response measurement means such as eye-tracking software/devices and computing systems including a main computer and desktop display. Abel Fernandez (US 20210174959 A1) additionally discloses that eye tracking as a diagnostic tool has been implemented in the art. As discussed above with respect to integration of the abstract idea into a practical application, the present elements amount to no more than mere indications to apply the exception.
In Summary, claim 1 recites abstract idea without being integrated into a practical application, and does not provide additional elements that would amount to significantly more. As such, taken as a whole, the claim and is ineligible under the 35 U.S.C. 101.
Claim 10 is rejected for similar reasons.
Claims 2, 5, 8-9, and 11-12 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception, in this case an abstract idea, without significantly more. As each of these claims depends from claim 1, which was rejected under 35 U.S.C. 101 in paragraph 10 of this action, these claims must be evaluated on whether they sufficiently add to the practical application of claim 1, or comprise significantly more than the limitations of claim 1.
Besides the abstract idea of claim 1: claim 2 recites further limitations of the abstract idea which are themselves abstract, in this case where a person alone or with a generic computer may be capable of using a data set for diagnosing mental disorders and predicting treatment responses to construct a model; claims 5, 8-9, and 11-12 recite further limitations of the additional elements which amount to the use of well-understood, routine, or conventional elements to perform a non-mental process in order to gather data for the mental process step, much like the example given in MPEP 2106.04(d)(2)(c), where the well-understood, routine, or conventional elements are the same as those of claim 1, and the claims merely recite further common measurements which may be performed with these elements and which are generated pre-solution to be used in the abstract idea.
The claim element of claim 1 of a method of diagnosing mental disorders and predicting treatment responses performed by a psychiatric examination system is recited with a high level of generality (as written, the steps may be carried out by a person alone or with a generic computer in any undefined manner). This limitation provides no practical application, nor does it provide meaningful limitations to the abstract idea.
Claims 13-19 are rejected for similar reasons.
Claim Rejections - 35 USC § 103
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.
Claim(s) 1-2, 5, 8-11, 13-14, and 16-18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Eizenman (US 20140148728 A1) in view of Katnani (US 20200029880 A1 ), further in view of Vaughan (US 11972336 B2).
Regarding claims 1 and 10, Eizenman teaches a method of diagnosing mental disorders and predicting treatment responses performed by a psychiatric examination system (Paragraph 0013-0018, 0036-- a method of identifying individuals with neuropsychiatric disorders or to predict and determine the efficacy of treatment of the disorder or detecting individuals who suffer a trauma to the brain by acquiring information about visual scanning behaviour and fluctuations of visual scanning behaviour of individuals) including a memory storing instructions and a processor coupled to the memory and configured to execute the instructions (Paragraph 0036—computing module…), the method comprising:
generating user attention information based on the user’s eye movement(Paragraph 0014-0018-- presenting to the individual a sequence of visual stimuli, wherein each visual stimulus is comprised of multiple images with specific characteristics, measuring the point-of-gaze of said subject on the visual stimuli; Paragraph 0037-0044-- Visual stimuli are presented on a computer monitor… Participants view a sequence of slides and the eye movement data is collected by a computer…steps of a) Presenting images; b) monitoring and recording eye movements during the presentation);
receiving the generated user attention information and attention test data generated by performing the standardized attention test (Paragraph 0034-- The present invention uses parameters derived from the subject's VSB when viewing images to identify individual with neuropsychiatric disorders or to predict the efficacy of a treatment of a disorder; paragraph 0128-0129--differences between the relative fixation times on social images and neutral images are used for the identification of apathy (using a naive Baysian Classifier)…; claim 9-- determination of biases comprises the comparison of statistical measures of individual visual scanning parameters with those of controls using confidence intervals, likelihood ratio detectors, linear classifiers, non-linear and neural network classifiers or a combination thereof.); and
providing, using a learning model, mental disorder diagnosis and treatment response information by inputting the generated user attention information and attention test data to the learning model (Paragraph 0013-0014-- predict and determine the efficacy of treatment of the disorder; claim 9-- determination of biases comprises the comparison of statistical measures of individual visual scanning parameters with those of controls using confidence intervals, likelihood ratio detectors, linear classifiers, non-linear and neural network classifiers or a combination thereof.)
wherein the generating of the user attention information comprises:
determining, from gaze coordinate values using eye tracking, a degree of attention on whether a user is looking at the monitor screen on which the test is being performed or a target area set within the monitor screen on the basis of a pre-set number of frames per second (Paragraph 0044-0047-- Fixations can be identified, for example, by clusters of gaze points that are within a specific distance (e.g. 1 degree) from each other for a time period that is greater than a minimum (eg., 200 milliseconds). Each fixation can be characterized by a set of parameters (FIG. 3(a)) such as: mean position on the display, duration and the order in the sequence of fixations from the time that a visual stimulus was presented. Each fixation is linked to a specific image on the display so that the fixation behaviour can be analysed with respect to the defining characteristics of images presented to the subject (see FIG. 3(b)) and with respect to the defining characteristics of specific regions (areas of interest) within an image.; paragraph 0049-0065-- Total number of fixations on each image or AOI within an image during each slide presentation… Relative number of fixations: Total number of fixations on each image or AOI within an image divided by the total number of fixations on all images or AOIs on the slide… Relative duration of fixations: Total duration of fixations on each image or AOI within an image divided by the total number of fixations on all images or AOIs on the slide…)
setting an area of interest in a target area within the monitor screen on which the test is being performed (Paragraph 0037-0047-- Visual stimuli are presented on a computer monitor (for example, a 19 inch monitor) and each visual stimulus (slide) includes several distinct images…AOI within the image (e.g., color, corners)), and determining whether the user is focusing on the set area of interest on the basis of pre-set criteria information (Paragraph 0046-- If the average fixation position falls within the boundaries of an image or an area of interest (AOI) within an image, the characteristics of the image (e.g., valence, complexity) and the AOI within the image (e.g., color, corners) are recorded as part of the description of the fixation; paragraph 0049-0065-- Total number of fixations on each image or AOI within an image during each slide presentation… Relative number of fixations: Total number of fixations on each image or AOI within an image divided by the total number of fixations on all images or AOIs on the slide… Relative duration of fixations: Total duration of fixations on each image or AOI within an image divided by the total number of fixations on all images or AOIs on the slide…).
generating the user attention information based on the degree of attention (Paragraph 0044-0047), whether the user is focusing (Paragraph 0046, 0049-0065).
However, Eizenman fails to explicitly teach setting remaining areas other than the area of interest set in the target area within the monitor screen as non-interest areas, and determining response inhibition information related to a user's gaze at the set non-interest areas using visual indicators including a commission error, a response time, and a total time and generating the user attention information based on the response inhibition information.
Katnani, in the same field of endeavor of a system and method for determining a mental condition of a user based on eye measurements (Abstract, paragraph 0006, 0010), discloses wherein the generating of the user attention information includes setting the remaining areas other than an area of interest set in a target area within the monitor screen on which the test is being performed as non- interest areas, and determining response inhibition information related to a user's gaze at the set non-interest areas using visual indicators (Paragraph 0010, 0033, 0039, 0059-- In one embodiment, the inhibitory reflex test comprises an anti-saccade task. In this case, displaying the inhibitory reflex test may comprise displaying a motionless target in a center of a field of vision of the user, and subsequently displaying a first visual stimulus in a periphery of the field of vision of the user. The user may be instructed to fixate on the motionless target, and to make a saccade in a direction away from the first visual stimulus when the first visual stimulus is displayed in the periphery of the field of vision of the user… The level of impairment of the user may be determined by determining either a reaction time or an error of the user in response to the anti-saccade task) including a commission error, a response time, and a total time (Katnani paragraph 0010, 0034-0037, 0042, 0059-0060—reaction time… period of time…the number of false responses…number of lapses in attention); and generating the user attention information based on the response inhibition information (0010, 0033, 0039, 0059).
It would have been obvious to one having ordinary skill in the art at the time of filing to modify the method of Eizenman to additionally include the response inhibition of Katnani in order to predictably improve the method by monitoring additional metrics of eye movement which may correspond to changes in mental functioning of the user, where Katnani discloses that response inhibition changes may demonstrate an individual’s capacity for sustained attention and response control (Paragraph 0039-0041 of Katnani).
However, Eizenman fails to explicitly disclose preprocessing the attention test data by estimating missing values and standardizing the attention test data; merging the preprocess attention test data; reducing the merged attention test data dimensionally.
Vaughan, in the same field of endeavor of a system for identifying cognitive or mental disorders in subjects, discloses receiving the generated user attention information and attention test data generated by performing the standardized attention test (Col. 21, line 19-52--The visual gaze, duration of gaze and facial expression information can be acquired with methods and apparatus known to one of ordinary skill in the art, and acquired an input into the diagnostic and therapeutic modules; Col. 29, line 43-Col. 30, line 12--as a subject participates in the diagnostic tests, the subject's feature value for each evaluated feature (e.g., subject's answer to a question) can be queried against the assessment model to identify the statistical correlation, if any, of the subject's feature value to one or more screened behavioral, neurological or mental health disorders….);
preprocessing the attention test data by estimating missing values and standardizing the attention test data and merging the preprocess attention test data (Fig. 6; Col. 31, line 35-Col. 32, line 49--The preprocessing module can be further configured to standardize the encoding of feature values…The preprocessing module can be further configured to impute any missing data values, such that downstream modules can correctly process the data…);
reducing the merged attention test data dimensionally (Col. 32, line 50-Col. 33, line 11-- for each feature value, a probability distribution may be extracted that describes the probability of the specific feature value for predicting each of the plurality of behavioral, neurological or mental health disorders to be screened by the diagnostic tests. The machine learning algorithm can be used to extract these statistical relationships from the training data and build an assessment model that can yield an accurate prediction of a developmental disorder when a dataset comprising one or more feature values is fitted to the model; col. 34, line 52-53--The feature selection procedure may include a determination of an optimal number of features.);
providing, using a learning model, mental disorder diagnosis and treatment response information by inputting the generated user attention information and the reduced attention test data to the learning model (Fig. 6, 8).
It would have been obvious to one having ordinary skill in the art at the time of filing to modify the method of Eizenman to utilize the data processing steps of Vaughan in order to predictably improve the accuracy of the system while minimizing the computational load by providing a larger amount of standardized data such that the data is compatible for comparison and additionally reducing the dimensions of the data to ignore irrelevant or unnecessary data and thus reduce computational load.
Regarding claim 2 and 13, the combination of Eizenman, Katnani, and Vaughan teaches the method of claim 1. Eizenman additionally teaches wherein the learning model is constructed by training using a data set for diagnosing mental disorders and predicting treatment responses (paragraph 0014-0018, 0036, 0042, 0072--making a determination of biases in visual scanning behaviour of the individual, by comparing the statistical measures of the individual to the statistical measures of controls; claim 9-- determination of biases comprises the comparison of statistical measures of individual visual scanning parameters with those of controls using confidence intervals, likelihood ratio detectors, linear classifiers, non-linear and neural network classifiers or a combination thereof…In accordance with the present invention for each visual scanning parameter or a set of visual scanning parameters statistical tests that compare the statistical description(s) of the VSB of the individual being tested with the statistical description of the VSB of control groups to determine if the individual suffers from the specific disorder that the assessment task is designed to identify. The control group can be a group of individuals that do not suffer from the disorder that the assessment task is designed to identify or/and a control group of individuals that suffer from the disorder that the assessment task is designed to identify).
Regarding claim 5 and 14, the combination of Eizenman, Katnani, and Vaughan teaches the method of claim 1. Eizenman additionally teaches wherein the generating of the user attention information includes determining eye movement state information related to the user's eye movement on a target area within the monitor screen during the standardized test on which the test is being performed using the number of saccades or eye movement fixation (paragraph 0049-0065-- Total number of fixations on each image or AOI within an image during each slide presentation… Relative number of fixations: Total number of fixations on each image or AOI within an image divided by the total number of fixations on all images or AOIs on the slide… Relative duration of fixations: Total duration of fixations on each image or AOI within an image divided by the total number of fixations on all images or AOIs on the slide…).
Regarding claim 8 and 16, the combination of Eizenman, Katnani, and Vaughan teaches the method of claim 1. However, Eizenman does not explicitly disclose wherein the generating of the user attention information includes measuring latency time data for a time until user's eye movement occurs in order to gaze at a new stimulus when the new stimulus appears on the monitor screen during the standardized test, in a case in which latency time data on a time until the user's eye movement occurs is greater than or equal to pre-set criteria.
Katnani, in the same field of endeavor of a system and method for determining a mental condition of a user based on eye measurements (Abstract, paragraph 0006, 0010), discloses wherein the generating of the user attention information includes measuring latency time data for a time until user's eye movement occurs in order to gaze at a new stimulus when the new stimulus appears on the monitor screen on which the test is being performed, in a case in which latency time data on a time until the user's eye movement occurs is greater than or equal to pre-set criteria (Paragraph 0058-0079, 0230, 0258-0279-- ii. an average saccadic latency, saccadic latency defined as an amount of time for the subject to initiate a saccade to the zone… a degree of compromise in executive processes, with increased saccadic latency).
It would have been obvious to one having ordinary skill in the art at the time of filing to modify the method of Eizenman to additionally include the latency measurements of Katnani in order to predictably improve the method by monitoring additional metrics of eye movement which may correspond to changes in mental functioning of the user, where Katnani discloses that response inhibition changes may demonstrate an individual’s executive processing ability (Paragraph 0058-0079, 0230, 0258-0279 of Katnani).
Regarding claim 9 and 17, the combination of Eizenman, Katnani, and Vaughan teaches the method of claim 1. However, Eizenman does not explicitly disclose wherein the generating of the user attention information includes extracting data on a change in pupil size of a user according to: an area of interest which is set in a target area within the monitor screen during the standardized test and time.
Katnani, in the same field of endeavor of a system and method for determining a mental condition of a user based on eye measurements (Abstract, paragraph 0006, 0010), discloses wherein the generating of the user attention information includes extracting data on a change in pupil size of a user according to: an area of interest which is set in a target area within the monitor screen during the standardized test; and time (Paragraph 0025-0027, 0034-0040, 0107-0110, 0131-0134, 0148-0151, 0200-0206-- a. track the pupil diameter of the subject reading the text; and b. if the pupil diameter of the subject does not show a reduction as advancing in reading the text, then report in the test report that that a compromise in executive processes is detected… a means [17] for measuring a pupil diameter of the subject, wherein the processor is further configured for calculating fixation durations on targets of person while performing the visual test, if the fixation duration of the subject [645] while fixating on targets is lower than for the control group, then report in the test report that that a compromise in attentional and executive processes is detected).
It would have been obvious to one having ordinary skill in the art at the time of filing to modify the method of Eizenman to additionally include the pupil diameter monitoring of Katnani in order to predictably improve the method by monitoring additional metrics of eye movement which may correspond to changes in mental functioning of the user, where Katnani discloses that response inhibition changes may demonstrate an individual’s attention executive processing ability (Paragraph 0025-0027, 0034-0040, 0107-0110, 0131-0134, 0148-0151, 0200-0206 of Katnani).
Regarding claim 11 and 18, the combination of Eizenman, Katnani, and Vaughan teaches the method of claim 1. Eizenman additionally teaches wherein the mental disorders include an Attention-Deficit/Hyperactivity Disorder (ADHD) (Claim 2—attention deficit hyperactivity disorder).
Claim(s) 6 and 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Eizenman in view of Suzuki (US 20190311484 A1).
Regarding claim 6 and 15, the combination of Eizenman, Katnani, and Vaughan teaches the method of claim 1. However, Eizenman does not explicitly disclose wherein the generating of the user attention information includes calculating speed information on user's eye movement by using gaze coordinates of a user's gaze on the monitor screen during the standardized test or a target area set within the monitor screen and time data, and measuring a variation of the calculated speed information on the user's eye movement.
Suzuki, in the same field of endeavor of monitoring a mental state of a user based on eye movement tracking (Paragraph 0001-0003), discloses wherein the generating of the user attention information includes calculating speed information on user's eye movement by using gaze coordinates of a user's gaze on the monitor screen on which the test is being performed or a target area set within the monitor screen and time data (Paragraph 0041-0044-- The moving state input unit 21 receives and inputs information indicating eye movement speeds in a time series which is transmitted from the camera 10. The moving state input unit 21 outputs the input information indicating the eye movement speeds to the saccade period extracting unit 22), and measuring a variation of the calculated speed information on the user's eye movement (Paragraph 0041-0044, 0047-- extracts a saccade period in which an eye performs a micro-saccade based on timer-series variation of the eye movement speeds indicated by the information input from the moving state input unit 21).
It would have been obvious to one having ordinary skill in the art at the time of filing to modify the method of Eizenman to additionally include the speed determination of Suzuki in order to predictably improve the method by monitoring additional metrics of eye movement which may correspond to changes in mental functioning of the user.
Claim(s) 12 and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Eizenman in view of Katnani, further in view of Vaughan, further in view of Herzallah (US 20210204853 A1), further in view of Krueger (US 20230210442 A1).
Regarding claim 12 and 19, the combination of Eizenman, Katnani, and Vaughan teaches the method of claim 1. Eizenman additionally teaches a visual simple selective attention test (paragraph 0014, 0036-0044).
However, Eizenman fails to explicitly disclose the standardized attention test includes an auditory simple selective attention test, an inhibition- sustained attention test, an interference-selective attention test, a divided attention test, and a working memory test.
Katnani, in the same field of endeavor of a system and method for determining a mental condition of a user based on eye measurements (Abstract, paragraph 0006, 0010), teaches an inhibition-sustained attention test (Paragraph 0010-0011, 0039-0043).
Herzallah, in the same field of endeavor of a system for diagnosing a mental health condition including eye tracking (Paragraph 0034), teaches working memory tests (Paragraph 0050).
Krueger, in the same field of endeavor of a system for diagnosing a mental health condition including eye tracking, teaches that numerous cognitive function tests may be performed with visual targets on a display (Paragraph 0487) including an auditory simple selective attention test (Paragraph 0487-0489), an interference-selective attention test (Paragraph 0491), and a divided attention test (Paragraph 0244, 0424, 0490-0492).
Krueger additionally motivates receiving the generated user attention information and attention test data generated by performing the standardized attention test where the standardized attention test includes a variety of different tasks (Paragraph 0194-- When assessing cognitive deficits for human health disorders or impairments, numerous visual tasks can be performed with visual targets on a display. For example, ocular parameter measurements, including smooth pursuit, vestibulo-ocular reflex cancellation, pupillometry, eyeblink information, and dynamic visual acuity, use visual targets for testing and all provide information about cognition and inattentiveness. There are other visual cognitive function tests which can be viewed on a display and detect cognitive deficits).
It would have been obvious to one having ordinary skill in the art at the time of filing to modify the method of Eizenman to include additional standardized attention tests as described by Katnani, Herzallah, and Krueger in order to predictably improve the accuracy of the method by providing more comprehensive data regarding the user’s abilities which may indicate possible mental disorders and deficits.
Response to Arguments
Applicant's arguments filed 28 April 2026 regarding the rejection of the claims under 35 U.S.C. 101 have been fully considered but they are not persuasive.
Regarding step 2A, prong 1, the applicant argues that the claims are not directed toward any mental process or mathematical concept.
While the applicant argues that “provides, by using a learning model, mental disorder diagnosis and treatment response information” cannot by done by a human mind, this is not found convincing at this time the current claim language provides no further details of the learning model such that the broadest reasonable interpretation of the learning model includes even very simple models which would not preclude it from being performed in the human mind alone or with the aid of pen and paper. The applicant additionally argues that “setting an area of interest and non-interest areas on the monitor screen” cannot be performed in the human mind, but this may be seen as the use of well-understood, routine, or conventional elements to perform an act of mere data gathering as this step may be performed using a generic computer and functions merely to provide data to be used in the abstract step as described above in this action.
Regarding step 2A, prong 2, the applicant argues that the newly added features of the claim reflect technical improvement in the field of eye-tracking based diagnosing mental disorders and predicting treatment responses systems and methods.
While the applicant argues that the configuration as claimed constitutes a technical solution to a technical problem by reducing computational load and memory requirements, this step similarly may be seen as the use of well-understood, routine, or conventional elements to perform an act of mere data gathering as this step may be performed using a generic computer and functions merely to provide data to be used in the abstract step as described above in this action, where each step of pre-processing, merging, standardizing, and reducing dimensionality of data may be performed by a generic computer and serves merely to prepare data for use in the abstract step.
Regarding step 2B, applicant argues that the claimed invention provides a non-conventional and inventive combination of known elements, citing “determining response inhibition information related to a user's gaze at the set non-interest areas using visual indicators including a commission error, a response time, and a total time and preprocessing the attention test data by estimating missing values and standardizing the attention test data, merging preprocess attention test data, and reducing the merged attention test data dimensionally which is not taught in the prior art. Taking all the additional elements individually, and in combination, claims as a whole amount to significantly more than the abstract idea. Accordingly, the pending claims should be patentable in view of the additional elements of the pending claims”.
However, as noted above, the claim limitations amount to determine known parameters of user attention from well-understood, routine, or conventional elements in the field of eye-tracking based diagnosing mental disorders and predicting treatment responses systems and methods, in this case eye tracking cameras and generic computers, wherein the processing and determination of such parameters may be seen as insignificant extra-solution activity akin to the examples of computer functions and laboratory techniques provided in MPEP2106.05(d)(II). Furthermore, while the applicant argues that these elements are not taught in the prior art, Vaughan and Katnani, cited above, sufficiently suggest all of the discussed limitations. The claims as a whole amount to the use of well-understood, routine, or conventional elements to gather data to be provided for a mental process step, wherein the claim lacks details of the learned model or utilized data which would preclude the additional elements from being seen as well-understood, routine, or conventional or which would preclude the step currently identified as abstract from being performed in the human mind.
Applicant’s arguments with respect to claim(s) 1-5 and 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.
In particular, Vaughan has been newly cited to disclose the newly added limitations of data processing which are not taught by Eizenman. The additional limitations incorporated from now-canceled claim 7 are taught by Katnani as previously described and not otherwise argued against by the applicant.
Rejection under 35 U.S.C. 102/103 in view of Bower is withdrawn at this time.
Conclusion
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 nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/ANNA ROBERTS/Examiner, Art Unit 3791
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