DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . This action is responsive to pending claims 1-21 filed 6/16/2022 .
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP §§ 706.02(l)(1) - 706.02(l)(3) for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
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Claim(s) 1-10, 12-15, 17-21 are rejected on the ground of nonstatutory double patenting as being unpatentable over claim(s) 1 of U.S. Patent No. 9378658 B2 in view of Dagum (US 20170258383 A1). Although the claims at issue are not identical, they are not patentably distinct from each other for the reasons listed below.
Current Application
Reference patent (US 9378658 B2)
Claim 1. A training method for enhancing the mental capabilities of a user, the method comprising:
collecting contextual information regarding a user;
presenting the user with a cognitive task, wherein the cognitive task includes a stimuli and the task specifies a desired response to the stimuli;
collecting feedback from the user regarding the cognitive task;
assessing the performance of the user in relation to the cognitive task;
generating guidance for the user based upon the contextual information, the feedback, and the assessed performance.
1. In a computerized meta-attention trainer, a computerized training method for enhancing meta-attention of a user, the method comprising:
presenting a user with a cognitive task via a user interface of a computerized meta-attention trainer, wherein the cognitive task includes a stimuli and the task specifies a
desired response to the stimuli;
assessing attentional control of the user in relation to the cognitive task via the user interface of the computerized meta-attention trainer;
providing at least one of an instruction and a feedback via the user interface of the computerized meta-attention trainer, based on the attentional control assessment, to
the user, thereby enabling the user to reflect on the meta attention of the user, and
Hence, claim 1 differs from the reference claim 1 in that the reference claim is absent recitation of collecting contextual information regarding the user, wherein the guidance is based upon the contextual information.
Dagum discloses: collecting contextual information regarding the user. (0059-61: location, qualitative characteristics, type, URL context, date and time, etc. are collected, these being recorded to better aid in generating inferences for generating cognitive assessment and guidance, see fig.8, 0092-93); wherein the guidance is based upon the contextual information (fig.8, 0092-93).
It would have been obvious before the effective filing date to a person of ordinary skill in the art to modify the reference claim by incorporating the context data including environment, date, time, etc. of Dagum. Both concern the art of cognitive testing and recommendation, and the incorporation would have, according to Dagum, incorporate additional cognitive metrics to help the user achieve positive cognitive outcomes (0061, 0092-93).
Claim 2: … wherein the stimuli is presented at a plurality of random inter-stimulus intervals (ISI), and wherein the random inter-stimulus intervals are substantially between a reaction-reset interval and an attention-sustaining interval
1. … wherein the stimuli is presented at a plurality of random inter-stimulus intervals (ISI), and wherein the random
inter-stimulus intervals are substantially between a reaction-reset interval and an attention-sustaining interval, thereby improving the user's meta-attention including
knowledge of factors that influence the user's attention and an awareness of the user's attentional processes as they occur and improving the users attentional control.
Hence, claim 2 is contained within Claim 1 of the reference patent.
For claim 3, the reference claim 1 modified by Dagum discloses claim 1, as described above. Dagum further discloses: wherein the guidance is generated by a rule-based engine (0092: inference of behavioral activity , such as based on cognitive score prediction fig.7B:713, see also pipeline of fig.3:600-800 for using feature extraction to generate guidance and reports, such as via rule-based neural networks (0047, 0087), hence, generating via rule based engines.
For claim 4, the reference claim 1 modified by Dagum discloses claim 1, as described above. Dagum further discloses: wherein the guidance is generated by an Al model (0092: inference of behavioral activity, such as based on cognitive score prediction fig.7B:713, see also pipeline of fig.3:600-800 for using feature extraction to generate guidance and reports, such as via neural networks (0047, 0087), hence, generating via AI models).
For claim 5, the reference claim 1 modified by Dagum discloses claim 1, as described above. Dagum discloses: wherein the feedback includes EEG data (fig.6A:609, 0080; fig.8, 0090 contemplates using EEG data for generating cognitive inference reports (fig.8:805-807) and recommendations (809-811)).
For claim 6, the reference claim 1 modified by Dagum discloses claim 1, as described above. Dagum discloses: wherein the context includes biometric data collected from the user (0059, 0094-95: evaluation via gyroscope, etc. of physical exercise while running, hence, device constitutes physical exercise equipment; see also 0075: wearable electronic devises for biometric data, this data being integrated into a pattern or feature learning (see fig.6:609, 615, etc.) for generating cognitive and behavioral inference and guidance (fig.8), environmental conditions (0059-61: location, qualitative characteristics, type, URL context, etc. are recorded), date, and time (0059: date and time), these being recorded to better aid in generating inferences for generating cognitive assessment and guidance, see fig.8, 0092-93.
For claim 7, the reference claim 1 modified by Dagum discloses claim 1, as described above. Dagum further discloses: wherein the guidance includes resource documents (fig.8:809-811, 0092-93: providing resource documents including educational material, information regarding groups, forums) and progression to an advanced cognitive task (ibid: setting advanced or new targets for cognitive activity, see also 0067).
Claim 8: … wherein a device is used to present the cognitive task to the user
1. … presenting a user with a cognitive task via a user interface of a computerized meta-attention trainer, wherein the cognitive task includes a stimuli and the task specifies a
desired response to the stimuli;
For claim 8, the reference claim 1 modified by Dagum discloses claim 1, as described above. As shown above, reference claim 1 further discloses: wherein a device is used to present the cognitive task to the user (¶2: “computerized trainer” with user interface constitutes a presenting device).
For claim 9, the reference claim 1 modified by Dagum discloses claim 8, as described above. Dagum discloses: wherein where the device is one of a smartphone, a tablet, a personal computer, a VR headset, and an augmented reality headset (0047).
For claim 10, the reference claim 1 modified by Dagum discloses claim 8, as described above. Dagum discloses: wherein the device is integrated into physical exercise equipment (0059, 0094-95: evaluation via gyroscope, etc. of physical exercise while running, hence, device constitutes physical exercise equipment; see also 0075: wearable electronic devises for biometric data, this data being integrated into a pattern or feature learning (see fig.6:609, 615, etc.) for generating cognitive and behavioral inference and guidance (fig.8)).
Claims 12-15, 17-21 recite analogous products and are hence likewise rejected.
Claim(s) 11, 16 are rejected on the ground of nonstatutory double patenting as being unpatentable over claim(s) 1 of U.S. Patent No. 9378658 B2 in view of Dagum (US 20170258383 A1) in view of the Specifications of U.S. Patent No. 9378658 B2.
For claim 11, the reference claim 1 modified by Dagum discloses claim 8, as described above. The reference claim modified by Dagum does not disclose: wherein the stimuli is a near-threshold stimuli.
Simpson (US 9378658 B2) discloses: wherein the stimuli is a near-threshold stimuli (fig.7, c.7¶5-c.8¶1: Gabor patches constitute near threshold stimuli).
It would have been obvious before the effective filing date to a person of ordinary skill in the art to modify the reference claim modified by Dagum by incorporating the Gabor patches of Simpson. Both concern the art of cognitive testing and recommendation, and the incorporation would have, according to Simpson, allow testing of meta-attention control (c.7¶5).
For claim 16, the reference claim 1 modified by Dagum modified by the Specifications discloses claim 11, as described above. Dagum further discloses: wherein the feedback includes EEG data (fig.6A:609, 0080; fig.8, 0090 contemplates using EEG data for generating cognitive inference reports (fig.8:805-807) and recommendations (809-811)).
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.
Claim(s) 1-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The 35 U.S.C. 101 subject matter eligibility analysis first asks whether the claim is directed to one of the four statutory categories (Step 1). It next asks whether the claim is directed to an abstract idea (Step 2A), via Prong 1, whether an abstract idea (e.g., mathematical concept, mental process, certain methods of organizing human activity) is recited, and Prong 2, whether it is integrated into a practical application. It finally asks whether the claim as a whole includes additional elements that amount to significantly more than the judicial exception (Step 2B). See MPEP 2106.
STEP 1: The claims falls within one of the four statutory categories:
Claims 1-11, 16 recite methods and claims 12-15, 17-21 recite a computer product embodied within non-transitory memory, and hence, the claims recite statutory categories.
STEP 2A PRONG 1: The claims recite a judicial exception:
Claim 1 is directed to diagnostic processes for evaluating and providing guidance on cognitive performance. Hence, it is directed to an abstract idea, a certain method of organizing human activity, see MPEP 2106.04(a)(2) §II.C, “Managing Personal Behavior or Relationships or Interactions Between People”, particularly “iii. Mental process that a neurologist should follow when testing a patient for nervous system malfunctions”, as well as mental processes for the performance of that method.
It comprises the steps of collecting contextual information about the user (a mental process performed via observation and memory), presenting the user with a task comprising a stimuli and a response (a method of organizing human behavior, of managing personal behavior via testing such as by a neurologist), collecting feedback from the user regarding the task (a mental process of observing and judging responses to form a diagnosis), assessing the performance of the user (a mental process of observation and judgment to form a diagnosis), and generating guidance based upon the observed contextual information, the observed feedback, and the assessed performance (a mental process of compiling and generating the diagnosis). As these steps recite a method of managing personal human behavior and mental processes, as might be performed mentally by a human neurologist, they are directed toa an abstract idea.
Claim 2 is directed to the stimuli being presented at random inter-stimulus intervals between a reaction-reset interval and an attention sustaining interval. However, the presenting of stimuli according to intervals during a neurological diagnosis is a process that may be performed by a clinician during diagnosis and hence is directed to a certain method of organizing human activity.
For claim 3, the use of a system of rules in order to generate guidance is directed to a mental process, as the consideration and applying of rules via a rule engine may be performed in the mind.
Claims 5, 16 recites the collection EEG data for consideration. However, the collection of graphical data related to a neural diagnosis may be performed in the mind.
Claim 6 recites the collection of biometric data environmental conditions, date, and time. However, the collection of such data may be performed by the mind via observation and hence constitutes a mental process.
In claim 7, the generation of guidance documents and the consideration of additional diagnostics may both be performed in the mind.
STEP 2A PRONG 2: The claims do not integrate the exception into a practical application:
For claim 1-3, 5-7 no additional elements are recited.
Claim 4 recites the additional element of using an AI model to generate the guidance. However, the use of AI models constitutes mere instructions to implement an abstract idea on a computer via machine learning algorithms and hence does constitute an integration into a practical application.
Claim 8-10 recites using a device, e.g., a tablet, a personal computer, a personal exercise equipment, etc., to present the cognitive task to the user. However, the use of computing devices constitutes mere instructions to implement an abstract idea on a computer via and hence does constitute an integration into a practical application.
Claim 11 recites the use of a near-threshold stimuli in the diagnosing of a cognitive condition. However, the use of near-threshold stimuli such as Gabor patches in a general way (such as, for example, to test eyesight) is simply the general linking of the diagnostic method to a particular field, that of visual stimuli. Hence, it does not constitute an integration into a practical application.
STEP 2B: The claim as a whole do not include additional elements that amount to significantly more than the abstract idea:
For claim 1-3, 5-7 no additional elements are recited.
Claim 4 recites the additional element of using an AI model to generate the guidance. However, the use of AI models is well-understood, routine and conventional (WURC) in the field of diagnostic inference and hence does not constitute significantly more.
Claims 8-10 recites using a device, e.g., a tablet, a personal computer, , a personal exercise equipment, etc., to present the cognitive task to the user. However, the use of these computing devices is well-understood, routine and conventional (WURC) in the field of diagnostic inference and hence does not constitute significantly more.
Claim 11 recites the use of a near-threshold stimuli in the diagnosing of a cognitive condition. However, the use of near-threshold stimuli such as Gabor patches is well-understood, routine and conventional (WURC) in the field of cognitive examination and hence does not constitute significantly more (2b)
The remaining claims 12-21 recite products embodied on computer-readable media corresponding to the above methods and are hence rejected in the similar way. Furthermore, the non-transitory computer-readable media embodiment constitutes mere instructions to apply the exception to a computing environment and hence does not constitute an integration into a practical application (2a-2). Furthermore, the use of computer products on a general purpose computer is well-understood, routine and conventional (WURC) and hence does not constitute significantly more (2b).
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-3, 8-9, 11-14, 19-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Simpson (US 9378658 B2).
For claim 1, Simpson discloses: a training method for enhancing the mental capabilities of a user (figs. 2, c.5¶4 gives overview of assessing and providing feedback for enhancement of user attention control), the method comprising:
collecting contextual information regarding a user (c.5¶2: collecting history of user, such as for delivering feedback, see also c.5¶4: feedback including historical statistics; c.8¶2: delivering historical feedback);
presenting the user with a cognitive task, wherein the cognitive task includes a stimuli and the task specifies a desired response to the stimuli (figs.5-7, c.6 last¶-c.8¶1 gives various instances of possible cognitive tasks, including (1) inhibition of response task requiring selective response or non-response to stimuli, the presentation specifying desired response instances (fig.5), (2) low variance task comprising stimuli requiring desired timing response (fig.6); and (3) timing specificity task requiring timely and correct response to liminal stimuli (fig.7));
collecting feedback from the user regarding the cognitive task (ibid: user response is collected for the various tasks above);
assessing the performance of the user in relation to the cognitive task (ibid: the performance of the user for each task is assessed, such as for feedback display (fig.6: timeliness feedback) and for determining correctness (figs.5, 7));
generating guidance for the user based upon the contextual information, the feedback, and the assessed performance (fig.8, c.8¶2: based on the user historical information, the feedback to stimulus given, and the scored performance, a feedback guidance is given based on scores, see also fig.2:220, c.5¶4: provision of post-training scoring, historical statistics, and guidance for reflecting on scores).
For claim 2, Simpson discloses the method of claim 1, as described above. Simpson further discloses: wherein the stimuli is presented at a plurality of random inter-stimulus intervals (ISI), and wherein the random inter-stimulus intervals are substantially between a reaction-reset interval and an attention-sustaining interval (c.12: claim 1).
For claim 3, Simpson discloses the method of claim 1, as described above. Simpson further discloses: wherein the guidance is generated by a rule-based engine (fig.2, c.5¶4: scoring engine for cognitive task upon which guidance is based constitutes a rule-based scoring engine).
For claim 8, Simpson discloses the method of claim 1, as described above. Simpson further discloses: wherein a device is used to present the cognitive task to the user (fig.1 gives device overview, such as for screenshots figs.12-14).
For claim 9, Simpson discloses the method of claim 8, as described above. Simpson further discloses: wherein where the device is one of a smartphone, a tablet, a personal computer, a VR headset, and an augmented reality headset (c.5¶3: smartphone, tablet, laptop personal computer).
For claim 11, Simpson discloses the method of claim 1, as described above. Simpson further discloses: wherein the stimuli is a near-threshold stimuli (fig.7, c.7¶5-c.8¶1: Gabor patches constitute near threshold stimuli).
Claims 12-14, 19-20 recite analogous computer products to the above methods and are hence rejected for the same 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) 4-7, 10, 15-18, 21 are rejected under 35 U.S.C. 103 as being unpatentable over Simpson (US 9378658 B2) in view of Dagum (US 20170258383 A1).
For claim 4, Simpson discloses the method of claim 1, as described above. Simpson does not disclose: wherein the guidance is generated by an Al model.
Dagum discloses: wherein the guidance is generated by an Al model (0092: inference of behavioral activity, such as based on cognitive score prediction fig.7B:713, see also pipeline of fig.3:600-800 for using feature extraction to generate guidance and reports, such as via neural networks (0047, 0087), hence, generating via AI models).
It would have been obvious before the effective filing date to a person of ordinary skill in the art to modify the method of Simpson by incorporating the AI model technique of Dagum. Both concern the art of cognitive testing and recommendation, and the incorporation would have, according to Dagum, allow assessment and actioning on cognitive function via nonlinear models (0047).
For claim 5, Simpson discloses the method of claim 1, as described above. Simpson does not disclose: wherein the feedback includes EEG data.
Dagum discloses: wherein the feedback includes EEG data (fig.6A:609, 0080; fig.8, 0090 contemplates using EEG data for generating cognitive inference reports (fig.8:805-807) and recommendations (809-811)).
It would have been obvious before the effective filing date to a person of ordinary skill in the art to modify the method of Simpson by incorporating the EEG data of Dagum. Both concern the art of cognitive testing and recommendation, and the incorporation would have, according to Dagum, incorporate additional cognitive metrics to help the user achieve positive cognitive outcomes (0092-93).
For claim 6, Simpson discloses the method of claim 1, as described above. Simpson further discloses: wherein the context includes biometric data collected from the user (c.5¶2: collecting history of user, such as for delivering feedback, see also c.5¶4: feedback including historical statistics; c.8¶2: delivering historical feedback constitutes biometric data).
Simpson does not disclose: the context including environmental conditions, date, and time.
Dagum discloses: the context including environmental conditions (0059-61: location, qualitative characteristics, type, URL context, etc. are recorded), date, and time (0059: date and time), these being recorded to better aid in generating inferences for generating cognitive assessment and guidance, see fig.8, 0092-93.
It would have been obvious before the effective filing date to a person of ordinary skill in the art to modify the method of Simpson by incorporating the context data including environment, date, time, etc. of Dagum. Both concern the art of cognitive testing and recommendation, and the incorporation would have, according to Dagum, incorporate additional cognitive metrics to help the user achieve positive cognitive outcomes (0061, 0092-93).
For claim 7, Simpson discloses the method of claim 1, as described above. Simpson does not disclose: wherein the guidance includes resource documents and progression to an advanced cognitive task.
Dagum discloses: wherein the guidance includes resource documents (fig.8:809-811, 0092-93: providing resource documents including educational material, information regarding groups, forums) and progression to an advanced cognitive task (ibid: setting advanced or new targets for cognitive activity, see also 0067).
It would have been obvious before the effective filing date to a person of ordinary skill in the art to modify the method of Simpson by incorporating the guidance documents and progression of Dagum. Both concern the art of cognitive testing and recommendation, and the incorporation would have, according to Dagum, allow adjusting of targets and guidance based on observed changes (0093), hence improving user guidance.
For claim 10, Simpson discloses the method of claim 8, as described above. Simpson does not disclose: wherein the device is integrated into physical exercise equipment.
Dagum discloses: wherein the device is integrated into physical exercise equipment (0059, 0094-95: evaluation via gyroscope, etc. of physical exercise while running, hence, device constitutes physical exercise equipment; see also 0075: wearable electronic devises for biometric data, this data being integrated into a pattern or feature learning (see fig.6:609, 615, etc.) for generating cognitive and behavioral inference and guidance (fig.8)).
It would have been obvious before the effective filing date to a person of ordinary skill in the art to modify the method of Simpson by incorporating the physical exercise equipment and data of Dagum. Both concern the art of cognitive testing and recommendation, and the incorporation would have, according to Dagum, allow integration of additional data for generating cognitive assessment and guidance (0075, 0090-93).
Claims 15-18, 21 recite analogous computer products to the above methods and are hence rejected for the same reasons.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Alailima (US 20200114115 A1) discloses a cognitive assessment technique via deep learning.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to LIANG LI whose telephone number is (303)297-4263. The examiner can normally be reached Mon-Fri 9-12p, 3-11p MT (11-2p, 5-1a ET).
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/LIANG LI/
Primary examiner AU 2143