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 Arguments
Regarding the previous 35USC 112(b), the amendments overcome the rejections.
Applicant’s arguments with respect to claim(s) 1-7 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.
Applicant's arguments filed 9/26/25 have been fully considered but they are not persuasive.
Applicant alleges that the claims do not recite an abstract idea which the Examiner traverses, as the determining steps and classifying steps listed below can be considered mental process steps once the data is received from the generic computer and data gathering elements. Applicant further alleges the claims are integrated into practical application in lieu of the recitations of “a sensor configured… on the output” on page 15. These limitations are addressed below as either mental processes, well understood, routine, and conventional computer components used to gather data on data gathering components for insignificant extra solution activity (e.g. output to a display, not practically utilizing the data).
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 1-9 and 21-31 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Each of claims 1-9 and 21-31 have been analyzed to determine whether it is directed to any judicial exceptions.
Step 1. – claims 1-9 and 21-31 recite a machine or system.
Step 2A, Prong 1
Each of claims 1-9 and 21-31 recites at least one step/function:
Claim 1
…for determining a difference between the user based on the determined difference in the measured eye movements of the user
Classify… the difference…efficacy of the treatment as classifications;
Claim 21
Determine, …, a difference between the eye movements.. effect of the treatment
Determine, a measure of an efficacy… of the user
Classify,…, the difference between… treatment as classifications,
Claim 31
Determining,…, one or more saccade, … first eye movement measurements
Determining,…, one or more saccade,…second eye movement measurements,
Determining, …a difference between… period of time.
Determining,…, an efficacy…the difference
Regarding claims 1, 21, and 31, a practitioner of the device could identify a task by mentally choosing one. A practitioner of the device could also measure eye movements of a subject by mentally observing the subject’s eyes move prior to and after treatment, and while the subject performs a task. A practitioner of the device could determine a difference between the eye movements of a subject by mentally distinguishing a difference of observed eye movement data or eye movement data displayed on a screen. A practitioner of the device could also determine a measure of efficacy of the treatment of the subject by mentally comparing the eye movement measurement differences. Furthermore, a practitioner of the device could display a recommended course of treatment based on the determined measure of efficacy by telling it to the subject.
Further, dependent Claims 2-9 and 22-30 merely include limitations that either further define
the abstract idea (and thus don’t make the abstract idea any less abstract) or amount to
no more than generally linking the use of the abstract idea to a particular technological
environment or field of use because they’re merely incidental or token additions to the
claims that do not alter or affect how the process steps are performed.
Specifically, dependent Claim 2 recites “The system of claim 1, further comprising a second sensor configured to measure a biomarker, and wherein the instructions, when executed by the processor, further cause the system to: measure, by the second sensor, the biomarker of the user while the user performs the task and prior to the treatment of the user; and measure, by the second sensor, the biomarker of the user while performing the task after the treatment.” The underlined portions merely include limitations that further define the abstract idea (and thus don’t make the abstract idea any less abstract).
Dependent 3 recites “The system of claim 2, wherein the instructions, when executed by the processor, further cause the system to determine a difference between the measured biomarker of the user prior to and after the treatment of the user.” The underlined portions merely include limitations that further define the abstract idea (and thus don’t make the abstract idea any less abstract).
Dependent Claim 4 recites “The system of claim 3, wherein determining the measure of the efficacy of the treatment of the user is further based on the difference in the measured biomarker of the user.” The underlined portions merely include limitations that further define the abstract idea (and thus don’t make the abstract idea any less abstract).
Dependent 5 recites “The system of claim 3, wherein the biomarker includes at least one of a heart rate, a head movement, or fidgeting of the user.” The underlined portions merely include limitations that further define the abstract idea (and thus don’t make the abstract idea any less abstract).
Dependent Claim 6 recites “The system of claim 1, wherein the task includes a section of text displayed on a screen for the user to read.” The underlined portions merely include limitations that further define the abstract idea (and thus don’t make the abstract idea any less abstract).
Dependent Claim 7 recites “The system of claim 1, wherein the sensor includes an eye-tracking device.” The underlined portions merely include limitations that further define the abstract idea (and thus don’t make the abstract idea any less abstract). It is noted that an eye tracking device is an additional element that performs insignificant extra-solution activity.
Similarly, claims 8, 9, and 22-30 further limit the abstract idea as denoted above.
Therefore, none of the Claims 1-9 and 21-31 amount to significantly more than the abstract idea itself. Accordingly, Claims 1-9 and 21-31 are not patent eligible and rejected under 35 U.S.C. 101.
Step 2A, Prong 2
The above identified abstract idea in each of claims 1-9, 21-21 are not integrated into a practical application because the additional elements, either alone or in combination, generally link the use of the above-identified abstract idea to a particular technological environment or field of use. More specifically, the additional elements of: a sensor, a processor, a memory, a trained learning model, a second sensor, a screen, a user device, and an eye-tracking device, in Claims 1-9, and 21-31 are generally recited computer or machine elements which do not improve the functioning of a computer, or any other technology or technical field. Nor do these above-identified additional elements serve to apply the above-identified abstract idea with, or by use of, a particular machine, effect a transformation or apply or use the above-identified abstract idea in some other meaningful way beyond generally linking the use thereof to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception. Furthermore, the above-identified additional elements do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer. For at least these reasons, the abstract idea identified above in independent Claims 1, 21, and 31 (and their respective dependent claims) are not integrated into a practical application under 2019 PEG.
The various steps as set forth in dependent claims 2-9 and 22-30 are insignificant extra-solution activity and are regarded as pre-solution activity such as data gathering, and selecting data to manipulate for the solution which amounts to necessary data gathering and outputting (Identified as underlined text above in Step 2A Prong 1 for dependent claims 2-9 and 22-30). All uses of the recited abstract idea require such data gathering or data output. For at least these reasons, the abstract idea identified above in independent Claims 1, 21, and 31 (and their respective dependent claims) are not integrated into a practical application under 2019 PEG.
Moreover, the above-identified abstract idea is not integrated into a practical application under 2019 PEG because the claimed method and system merely implements the above-identified abstract idea (e.g., mental process and certain method of organizing human activity) using rules (e.g., computer instructions) executed by a computer (e.g., CPU or processor as claimed) or uses well understood, conventional or routine elements.
In other words, these claims are merely directed to an abstract idea with additional generic computer elements which do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer or machine elements. Additionally, Applicant’s specification does not include any discussion of how the claimed invention provides a technical improvement realized by these claims over the prior art or any explanation of a technical problem having an unconventional technical solution that is expressed in these claims. That is, like Affinity Labs of Tex. v. DirecTV, LLC, the specification fails to provide sufficient details regarding the manner in which the claimed invention accomplishes any technical improvement or solution. Thus, for these additional reasons, the abstract idea identified above in independent Claims 1, 21, and 31 (and their respective dependent claims) is not integrated into a practical application under the 2019 PEG.
Accordingly, independent Claims 1, 21, and 31 (and their respective dependent claims) are each directed to an abstract idea under 2019 PEG.
Step 2B
None of Claims 1-9 and 21-31 include additional elements that are sufficient to amount to significantly more than the abstract idea for at least the following reasons.
These claims require the additional elements of a processor, a memory, a trained learning model, and a screen, as recited in independent Claims 1, 21, and 31 and their dependent claims.
The above-identified additional elements are generically claimed computer or machine components which enable the above-identified abstract idea(s) to be conducted by performing the basic functions of automating mental tasks. The courts have recognized such computer functions as well understood, routine, and conventional functions when claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity. See, Versata Dev. Group, Inc. v. SAP Am., Inc. , 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); and OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93.
Per Applicant’s specification, the processor can be a microprocessor, CPU, GPU, TPU, controller (Paragraph [0042], lines 4-7); the memory can be any medium storage suitable for the storage of data or instruction set aside from a transitory waveform, including RAM, ROM, a hard drive, floppy disk, and a CD-ROM (Paragraph [0057], lines 4-8); the trained learning model is described as executed by the processor (Paragraph [0085], lines 7-9); and the screen is described without detailed structure to be a computer, tablet, or cell phone screen (Paragraph [0067], lines 8-9).
The elements a sensor, a second sensor, an eye-tracking device as recited in independent Claims 1, 21, and 31 and their dependent claims amount to mere data gathering at a higher level of generality in conjunction with the abstract idea that uses conventional, routine, and well known elements - see MPEP 2106.04(d); MPEP 2106.05(g); Electric Power Group, 830 F.3d 1350 (Fed. Cir. 2016); Alice Corp. v. CLS Bank Int'l, 110 USPQ2d 1976 (2014)).
Per Applicant’s specification, the sensor is described functionally to track eye movements of a user and in an exemplary fashion to include an eye-tracking device, imaging device or smartwatches, devices with accelerometers, devices with magnetometers, heart rate monitors, or webcams (Paragraph [0065], lines 4-9); the second sensor is described functionally to measure a biomarker including a heart rate, a head movement, and/or fidgeting among other biomarkers (Paragraph [0068], lines 1-5); and the eye-tracking device is described functionally to detect, sense, track, and process eye movement and in an exemplary fashion to include a camera, phone, image capturing device (Paragraph [0046], lines 3-6).
The above elements do not qualify as significantly more because the use of a system for evaluating a condition of a user with ADHD comprising a first sensor/an eye-tracking device and a second sensor is merely adding insignificant extra-solution activity to the judicial exception, e.g., mere data gathering at a higher level of generality in conjunction with the abstract idea that uses conventional, routine, and well known elements - see MPEP 2106.04(d); MPEP 2106.05(g).
The elements a first sensor/an eye-tracking device and a second sensor are well-understood, routine, and conventional, as evidenced by Costa (Paragraph [0047], lines 5-12, The body motion can be captured using well known motion caption devices and methods including, but not limited to, remote sensing devices such as cameras and reflective sensor (e.g., mm and high frequency sensing) and subject worn sensing devices, such as, accelerometers, gyroscopes, magnetometers, force sensitive resistors, inertial navigation devices, and combinations of remote sensing devices and body worn sensing devices) Costa therefore indicates cameras and accelerometers are well-understood, routine, and conventional.
Accordingly, in light of Applicant’s specification, the claimed terms a sensor, a processor, a memory, a trained machine learning model, a second sensor, a screen, and an eye-tracking device, are reasonably construed as generic computing devices or machine elements. Like SAP America vs Investpic, LLC (Federal Circuit 2018), it is clear, from the claims themselves and the specification, that these limitations require no improved computer resources, just already available computers, with their already available basic functions, to use as tools in executing the claimed process.
Furthermore, Applicant’s specification does not describe any special programming or algorithms required for the sensor, processor, memory, trained machine learning model, second sensor, screen, and eye-tracking device. This lack of disclosure is acceptable under 35 U.S.C. §112(a) since this hardware performs non-specialized functions known by those of ordinary skill in the computer arts. By omitting any specialized programming or algorithms, Applicant's specification essentially admits that this hardware is conventional and performs well understood, routine and conventional activities in the computer industry or arts. In other words, Applicant’s specification demonstrates the well-understood, routine, conventional nature of the above-identified additional elements because it describes these additional elements in a manner that indicates that the additional elements are sufficiently well-known that the specification does not need to describe the particulars of such additional elements to satisfy 35 U.S.C. § 112(a) (see Berkheimer memo from April 19, 2018, (III)(A)(1) on page 3). Adding hardware that performs “‘well understood, routine, conventional activit[ies]’ previously known to the industry” will not make claims patent-eligible (TLI Communications).
The recitation of the above-identified additional limitations in Claims 1-9 and 21-31 amounts to mere instructions to implement the abstract idea on a computer or machine. Simply using a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); and TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Moreover, implementing an abstract idea on a generic computer, does not add significantly more, similar to how the recitation of the computer in the claim in Alice amounted to mere instructions to apply the abstract idea of intermediated settlement on a generic computer.
A claim that purports to improve computer capabilities or to improve an existing technology may provide significantly more. McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314-15, 120 USPQ2d 1091, 1101-02 (Fed. Cir. 2016); and Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335-36, 118 USPQ2d 1684, 1688-89 (Fed. Cir. 2016). However, a technical explanation as to how to implement the invention should be present in the specification for any assertion that the invention improves upon conventional functioning of a computer, or upon conventional technology or technological processes. That is, the disclosure must provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. Here, Applicant’s specification does not include any discussion of how the claimed invention provides a technical improvement realized by these claims over the prior art or any explanation of a technical problem having an unconventional technical solution that is expressed in these claims. Instead, as in Affinity Labs of Tex. v. DirecTV, LLC 838 F.3d 1253, 1263-64, 120 USPQ2d 1201, 1207-08 (Fed. Cir. 2016), the specification fails to provide sufficient details regarding the manner in which the claimed invention accomplishes any technical improvement or solution.
For at least the above reasons, the system and method of Claims 1-9 and 21-31 are directed to applying an abstract idea as identified above on a general purpose computer without (i) improving the performance of the computer itself, or (ii) providing a technical solution to a problem in a technical field. None of Claims 1-9 and 21-31 provides meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that these claims amount to significantly more than the abstract idea itself.
Taking the additional elements individually and in combination, the additional elements do not provide significantly more. Specifically, when viewed individually, the above-identified additional elements in independent Claims 1, 21, and 31 (and their dependent claims) do not add significantly more because they are simply an attempt to limit the abstract idea to a particular technological environment. That is, neither the general computer elements nor any other additional element adds meaningful limitations to the abstract idea because these additional elements represent insignificant extra-solution activity. When viewed as a combination, these above-identified additional elements simply instruct the practitioner to implement the claimed functions with well-understood, routine and conventional activity specified at a high level of generality in a particular technological environment. As such, there is no inventive concept sufficient to transform the claimed subject matter into a patent-eligible application. When viewed as whole, the above-identified additional elements do not provide meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that the claims amount to significantly more than the abstract idea itself. Thus, Claims 1-9 and 21-31 merely apply an abstract idea to a computer and do not (i) improve the performance of the computer itself (as in Bascom and Enfish), or (ii) provide a technical solution to a problem in a technical field (as in DDR).
Therefore, none of the Claims 1-9 and 21-31 amounts to significantly more than the abstract idea itself. Accordingly, Claims 1-9 and 21-31 are not patent eligible and rejected under 35 U.S.C. 101.
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 and 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over U.S. PG Pub No. US20160192838A1 to Hirsh in view of Jimenez et al. (Eye Vergence Responses During an Attention Task in Adults With ADHD and Clinical Controls. (2021) Journal of Attention Disorders, 25(9), 1302-1310) in further view of Bjerrum (WO2020/069712).
Hirsh discloses a system for evaluating a treatment of a user for attention deficit hyperactivity disorder (ADHD) (Examiner notes invention is an apparatus for recording ocular parameters as described in Paragraph [0007], lines 1-2; wherein the invention is directed to quantifying the effects of pharmaceuticals to assess efficacy of treatment as described in Paragraph [0006], lines 1-4; and wherein the specific conditions that are assessed include attention deficit hyperactivity disorder (ADHD) as described in Paragraph [0062], lines 1-3) the system comprising:
a sensor configured to measure eye movements of the user (Figure 1, digital camera 10, Paragraph [0007], lines 2-3, The apparatus includes a digital camera for capture of eye measurements), while the user performs a task (Paragraph [0047], lines 1-6, The exposing and image-capturing steps are performed while the individual is focusing visually on a distant object (either actually or via visual illusion within a video display) and also while the individual is focusing visually on a near object (either actually or via visual illusion within a video display)., Examiner notes focusing visually on a distant and near object as a task) on a user device, the sensor in electronic communication with the user device (system is performed on a computer diagnostic system);
a processor (Figure 1, processor 26); and a memory (Figure 1, data memory 24 and controller 18), including instructions, which, when executed by the processor, cause the system to (Paragraph [0038], lines 3-6, The control 18 can be a software-implemented control using a microprocessor, a firmware-implemented control using a microcontroller, or any of various other forms of controls, Examiner notes software-implemented control using a microprocessor as including instructions executed by a processor):
identify, by the processor the task (Examiner notes identification of task per applicant specification as a selection of a test or evaluation protocol generated on a user interface Paragraph [0045], lines 9-10. Under broadest reasonable interpretation, the video display of Hirsh performs this operations similarly in displaying distant and near objects as described in Paragraph [0047], lines 1-6);
prior to the treatment of the user (Paragraph [0051], lines 1-4, measuring, and record-generating steps may be carried out on the individual both before and after administration to the individual of a central nervous system-acting drug, Examiner notes administration of a central nervous system-acting drug as treatment) and while the user performs the task on the user device(Paragraph [0047], lines 1-3, The exposing and image-capturing steps are performed while the individual is focusing visually on a distant object (either actually or via visual illusion within a video display, Examiner notes focusing visually on a distant object as a task), measure the eye movements of the user with the sensor (Paragraph [0007], lines 2-3, The apparatus includes a digital camera for capture of eye measurements);
while the user is under an effect of the treatment of the user (Paragraph [0051], lines 1-4, measuring, and record-generating steps may be carried out on the individual both before and after administration to the individual of a central nervous system-acting drug, Examiner notes after administration of a central nervous system-acting drug as during treatment) and while the user performs the task on the user device (Paragraph [0047], lines 1-3, The exposing and image-capturing steps are performed while the individual is focusing visually on a distant object (either actually or via visual illusion within a video display, Examiner notes focusing visually on a distant object as a task), measure the eye movements of the user with the sensor (Paragraph [0007], lines 2-3, The apparatus includes a digital camera for capture of eye measurements);
determine, by a trained machine learning model (processing performed by algorithms) a difference between the eye movements of the user prior to and after the treatment of the user (Paragraph [0058], lines 1-6, The methods of the invention further includes self-assessment of a subject using a portable device, such as a “smartphone,” e.g. an iPhone™ device, having a camera and an installed application that can process image data as described herein and compare it to stored control data of the patient or a wider control population, Examiner notes stored control data of the patient as pre-treatment results; Paragraph [0008], lines 7-11, Comparison of a patient's parameters at one time point to a previous time point, and parallel comparisons to controls, is also useful for adjusting treatment based on patient-specific reaction or tolerance, Examiner notes patient’s parameters at a previous time point as capable of being pre-treatment results and comparison of a patient’s parameters as determining a difference);
determine, by the processor, a measure of an efficacy of the treatment of the user based on the determined difference in the measured eye movements of the user (Paragraph [0058], lines 6-9, For example, a contemplated method provides patients with ADD/ADHD an indication that their stimulant mediation is wearing off, and that they need to take a small dose of short acting agent, Examiner notes the indication of the medication wearing off as a measure of treatment efficacy being low or reduced); and display a recommended a course of treatment for the user based on the determined measure of efficacy (Paragraph [0058], lines 6-11, For example, a contemplated method provides patients with ADD/ADHD an indication that their stimulant mediation is wearing off, and that they need to take a small dose of short acting agent. Such a method may be accompanied by an alarm integrated within the device and programming for same, Examiner notes instruction of taking a small dose of short acting agent and alarm integrated within the device as displaying a recommended course of treatment for the user); and
wherein the sensor includes an eye-tracking device (Paragraph [0036], lines 1-6, The digital camera may be a ‘still’ image camera or a ‘video’ camera, as those terms are commonly used. However, the digital camera should be capable of capturing a number of images per second providing a basis for a statistically significant measurement of the change in any of the measurable variables identified herein, Examiner notes digital camera as eye-tracking device).
However, Hirsh does not disclose determining a difference of eye movements of a user based on a trained machine learning model.
Jimenez et al. teaches determining a difference of eye movements of a user based on a trained (Page 1304, Column 2, Paragraph 4, lines 1-4, A feature selection strategy on vergence signal was followed to obtain relevant parts of the signal that were later used to train a random forest classifier for ADHD prediction, Examiner notes random forest classifier as machine learning model) machine learning model (Page 1305, Column 2, Paragraph 1, lines 1-3, we had to apply machine learning techniques that searched for differences in the vergence responses).
Hirsh and Jimenez et al. are considered analogous to the claimed invention because they are in the same field of task-based ADHD assessment devices. It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the processor of Hirsh to incorporate the teachings of Jimenez et al. by adding a trained learning model for determining the difference of measure eye movements prior to and after treatment. Doing so would allow for classification of ADHD based on differential features of eye vergence as described in Page 1303, Column 1, Paragraph 2, lines 20-22; and furthermore, allow large sets of time series to be used as input data as described in Paragraph 1304, Column 2, Paragraph 3, lines 6-10, as referenced by Jimenez et al.
Hirsch and Jimenez fail to teach classify, by the trained machine learning model, the difference between the eye movements before and after treatment of the user and the measure of the efficacy of the treatments as classifications and output, by the trained machine learning model, a recommended modification to the treatment based on the classifications.
Bjerrum teaches a system for evaluating a treatment of a user for ADHD where the treatment to teach classify, by the trained machine learning model (page 8, lines 24-28), the difference between the eye movements before and after treatment of the user and the measure of the efficacy of the treatments as classifications (page 40, lines 10 to 23) and output based on the trained machine learning model, a recommended modification to the treatment based on the classifications (page 3, lines 7-10).
Therefore it would have been obvious at the effective filing date of the invention to modify the systems of Hirsch and Jimenez with the teachings of Bjerrum to evaluate and adjust treatment, the motivation being this would effectively evaluate the treatment such that it could be adjusted to put the eye response into the closest normal human range.
Claim(s) 2-5 are rejected under 35 U.S.C. 103 as being unpatentable over Hirsh in view of Jimenez as applied to claim 1 above, in further view of Bjerrum (WO2020/069712) and further in view of U.S. PG Publication No. US20140330159A1 to Costa et al. (hereinafter Costa).
Regarding Claim 2, Hirsh as modified Jimenez teaches the system of claim 1.
However, Hirsh as modified by Jimenez does not teach further comprising a second sensor configured to measure a biomarker, and wherein the instructions, when executed by the processor, further cause the system to: measure, by the second sensor, the biomarker of the user while the user performs the task and prior to the treatment of the user; and measure, by the second sensor, the biomarker of the user while performing the task after the treatment.
Costa teaches further comprising a second sensor configured to measure a biomarker (Examiner notes the tracking system can employ a motion capture system to obtain the motion of subject’s body elements over time such as the head, hands and arms as described in Paragraph [0047], lines 2-5; and body motion as being captured using well known motion caption devices inclusive of accelerometers as described in Paragraph [0047], lines 5-12; Examiner notes biomarker per applicant specification as a heart rate, head movement, and/or fidgeting in Paragraph [0011], lines 1-2; Examiner notes head motion as head movement and arm and hand motion as fidgeting and accelerometer as sensor configured to measure head, hand or arm), and wherein the instructions, when executed by the processor, further cause the system to: measure, by the second sensor, the biomarker of the user while the user performs the task (Paragraph [0019], lines 6-9, The task monitor can include one or more sensors that monitor a subject interacting with the device while performing one or more visuo-motor tasks and provide data to the computer system, Examiner notes monitoring of subject as measuring via one or more sensors and biomarker as head movement captured by accelerometer as cited above) and prior to the treatment of the user (Examiner notes a subject performs a neurologic function task and the data is analyzed using a neuromotor index as described in Paragraph [0038], lines 4-14; and an initial NI value can be used as a baseline from which to evaluate the subject to indicate the existence of disease or disability as described in Paragraph [0044], lines 4-6; Examiner notes baseline where subject is evaluated for disability as pre-treatment measurement during task).
and measure, by the second sensor, the biomarker of the user while performing the task (Paragraph [0019], lines 6-9, The task monitor can include one or more sensors that monitor a subject interacting with the device while performing one or more visuo-motor tasks and provide data to the computer system, Examiner notes monitoring of subject as measuring via one or more sensors, and biomarker as head movement captured by accelerometer as cited above) after the treatment (Examiner notes a subject performs a neurologic function task and the data is analyzed using a neuromotor index as described in Paragraph [0038], lines 4-14; and subsequent evaluations during and after treatment can be compared with one or more prior evaluations (NI values) to assess the effectiveness of the treatment and/or therapy as described in Paragraph [0044], lines 6-9; Examiner notes subsequent evaluations as administration of sensor-monitored tasks, and during/after treatment and therapy as after the treatment has been administered).
Hirsh, Jimenez et al., and Costa are considered analogous to the claimed invention because they are in the same field of task-based neurological assessment devices.
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system of Hirsh to incorporate the teachings of Costa by adding a second sensor for measuring a biomarker prior to and after treatment. It would be further obvious to modify the processor to include communication with the second sensor. Doing so would allow for further monitoring of an administered drug dosage, as referenced by Costa (Paragraph [0067], lines 8-14, The data obtained from repeated assessments taken over time can be compared to determine how the patient progresses through healing, rehabilitation, training, therapy, etc. These measures can also be used to determine the efficacy of a drug dosage).
Regarding Claim 3, Costa teaches wherein the instructions, when executed by the processor, further cause the system to determine a difference between the measured biomarker of the user prior to and after the treatment of the user (Examiner notes the task data can be analyzed using a neuromotor index including a complexity index which can be compared to a baseline index as described in Paragraph [0038], lines 7-14; and further subsequent evaluations during treatment and therapy can be compared with one or more prior evaluations as described in Paragraph [0044], lines 6-9; Examiner notes task data as biomarker sensor measurements, baseline index and prior evaluations as pre-treatment measurements, and comparison of baseline index or prior evaluations to further subsequent evaluations during treatment as determining a difference of the biomarker measurements).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system of Hirsh to incorporate the teachings of Costa by determining a difference of measurements from a biomarker sensor prior to and after treatment. Doing so would allow for an assessment of effectiveness of treatment or therapy, as referenced by Costa (Paragraph [0038], lines 10-15, a Complexity Index (CI) which can be compared to a standard or baseline index for the subject to detect disease or disability, or the CI can be compared to prior performance data and CI values for the subject to assess effectiveness of treatment or therapy).
Regarding Claim 4, Costa teaches determining the measure of the efficacy of the treatment of the user (Paragraph [0044], lines 15-19, The efficacy of treatment or therapy can be assessed according to embodiments of the invention by comparing current NI values with prior NI values to determine whether current NI values are greater, indicating increased complexity and a return to healthy state. An initial NI value can be used as a baseline from which to evaluate the subject to indicate the existence of disease or disability. During treatment and therapy, further subsequent evaluations in accordance with the invention can be compared with one or more prior evaluations (NI values) to assess the effectiveness of the treatment and/or therapy, Examiner notes NI value comparison as determination of efficacy of treatment with an increase in NI value indicating positive or increased treatment efficacy) being further based on the difference in the measured biomarker of the user (Paragraph [0038], lines 7-14, The task data can be analyzed using a neuromotor index. This index can include a multiscale complexity analysis in order to determine a quantitative assessment, such as a Complexity Index (CI) which can be compared to a standard or baseline index for the subject to detect disease or disability, … to assess effectiveness of treatment or therapy, Examiner notes task data as biomarker sensor measurements)
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system of Hirsh to incorporate the teachings of Costa by determining an efficacy of treatment based on the biomarker differences. Doing so would allow for progression of healing to be tracked over time, as referenced by Costa (Paragraph [0067], lines 8-11, The data obtained from repeated assessments taken over time can be compared to determine how the patient progresses through healing, rehabilitation, training, therapy, etc.).
Regarding Claim 5, Costa teaches the biomarker includes at least one of a heart rate, a head movement, or fidgeting of the user (Paragraph [0047], lines 2-5, the tracking system can employ a motion capture system to obtain the body motion over time of the subject’s entire body or elements of the subject's body (e.g., head, arms, hands, legs and feet), Examiner notes head motion as head movement and arm and hand motion as fidgeting).
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system of Hirsh to incorporate the teachings of Costa by measuring head movements or fidgeting as the additional biomarker. Doing so would allow for further monitoring of an administered drug dosage, as referenced by Costa (Paragraph [0067], lines 8-14, The data obtained from repeated assessments taken over time can be compared to determine how the patient progresses through healing, rehabilitation, training, therapy, etc. These measures can also be used to determine the efficacy of a drug dosage).
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Hirsh in view
of Jimenez and Bjerrum (WO2020/069712) as applied to claim 1 above, and further in view of KR Publication No. KR20210019266A (hereinafter ‘266, cited on 6/6/2022 IDS).
Regarding Claim 6, ‘266 teaches wherein the task includes a section of text displayed on a screen for the user to read (Figure 9 depicts electronic form of text passage, Paragraph [0049] lines 1-4, the diagnostic document is a diagnostic medium in the form of an electronic document, and may be a document that electronically describes the relationship and importance between the existing texts and/or images by classifying regions according to their structural and semantic functions. have. Specifically, the diagnostic document may be provided in a form of text).
Hirsh, Jimenez et al.,and ‘266 are considered analogous to the claimed invention because they are in the same field of eye tracking devices for ADHD management.
It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the processor of Hirsh to incorporate the teachings of ‘266 by presenting a section of text on the video display for the user to read. Doing so would further allow for risk of ocular movement-related disorders such as ADHD to be diagnosed through gaze measurement as described in Paragraph [0019], lines 5-7.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Munoz 6,231,187) which is drawn to measuring eye movements and ADD/ADHD.
THIS ACTION IS MADE FINAL. 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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ALEX M VALVIS whose telephone number is (571)272-4233. The examiner can normally be reached 9:00-5:00 M-F.
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ALEX M. VALVIS
Supervisory Patent Examiner
Art Unit 3791
/ALEX M VALVIS/ Supervisory Patent Examiner, Art Unit 3791
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