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 .
Preliminary Amendment
2. Applicant’s preliminary amendment filed on July 23, 2025 has been entered. Claims 1-23 have been cancelled. Claims 24-43 have been added. Claims 24-43 are pending in this application.
Double Patenting
3. 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 § 2146 et seq. 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).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
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4. Claims 24-43 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1 and 22-23 of U.S. Patent No. 12,287,918 in view of Keane (US 2020/0073475).
Below is a comparison between patented claim 1 and present claim 24:
Present claim 24
Patented claim 1
A system comprising: a brain activity monitoring device or system configured to obtain data relating to at least one parameter relating to brain activity of a user; and
at least one computer or computerized system, communicatively coupled with the brain activity monitoring device or system, comprising at least one processor and at least one memory, the at least one processor being configured to:
provide at least one graphical user interface, on at least one display of at least one display device, for use in optimization of at least one aspect of generation of at least one of two or more signals;
based at least in part on at least a portion of the obtained data, obtain from the user the two or more signals, wherein each of the two or more signals is generated by the user at least in part by the user engaging in specific thinking to cause one or more values of one or more parameters relating to the brain activity of the user to meet one or more specified conditions, wherein the one or more parameters are associated with the at least one parameter; determine two or more data values, wherein each data value of the two or more data values corresponds with a signal of the two or more signals;
based at least in part on at least two of the two or more data values, determine a set of at least two data values, wherein determining the set of at least two data values comprises forming the set of at least two data values;
based at least in part on the set of at least two data values, determine a message for presentation or a command for implementation, on at least one system or device; and determine output at least in part for causing presentation of the message or implementation of the command on the at least one system or device;
wherein that which is thought in the specific thinking is not required to be related to the message or the command.
A system comprising: a brain activity monitoring device or system configured to obtain data relating to at least one parameter relating to brain activity of a user; and
at least one computer or computerized system, communicatively coupled with the brain activity monitoring device or system, comprising at least one processor and at least one memory, the at least one processor being configured to:
based at least in part on at least a portion of the obtained data, obtain from the user two or more signals, wherein each of the two or more signals is generated by the user at least in part by the user engaging in specific thinking to cause one or more values of one or more parameters relating to the brain activity of the user to meet one or more specified conditions, wherein the one or more parameters are associated with the at least one parameter; determine two or more data values, wherein each data value of the two or more data values corresponds with a signal of the two or more signals;
based at least in part on at least two of the two or more data values, determine a set of at least two data values, wherein determining the set of at least two data values comprises forming the set of at least two data values;
based at least in part on the set of at least two data values, determine a message for presentation or a command for implementation, on at least one system or device; and determine output at least in part for causing presentation of the message or implementation of the command on the at least one system or device;
wherein that which is thought in the specific thinking is not required to be related to the message or the command.
As can be seen above, the only difference between claims is that patented claim 1 fails to disclose “provide at least one graphical user interface, on at least one display of at least one display device, for use in optimization of at least one aspect of generation of at least one of two or more signals”.
However, Keane discloses a system (Fig. 1; [0028], e.g., Brain Training Feedback System 100) comprising:
a brain activity monitoring device or system ([0028]-[0029], e.g., an electrode cap 102) configured to obtain data relating to at least one parameter relating to brain activity of a user (Fig. 2; [0032], e.g., obtain brain waves relating to frequency or amplitude relating to brain activity of a user); and
at least one computer or computerized system (Figs 1 and 4; [0029], e.g., Brain Wave Processing and Monitoring System (BWPMS) 120), communicatively coupled with the brain activity monitoring device or system (Fig. 1; [0029], e.g., coupled with the electrode cap via paths 105 and 112), comprising at least one processor (Fig. 4; e.g., signal processing units 413, 417) and at least one memory (e.g., data storage unit 418), the at least one processor being configured to:
provide at least one graphical user interface, on at least one display of at least one display device (Fig. 9D; [0086], e.g., provide a GUI on a display screen of a display device), for use in optimization of at least one aspect of generation of at least one of two or more signals ([0042], [0059], [0062], [0086], e.g., set up training and system parameters including frequencies, sample rates, feedback modalities for optimizing the generation of the two or more signals).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to use the teachings of Keane in the invention as taught by patented claim 1 for providing at least one graphical user interface for setting up training and system parameter in order to optimize generation of two or more signals.
Regarding claim 25, patented claim 1 in view of Keane further discloses the system of claim 24, wherein the optimization of at least one aspect of generation of at least one of two or more signals comprises user optimization (Keane, [0042], [0059], e.g., user sets up training and system parameters).
Regarding claim 26, patented claim 1 in view of Keane further discloses the system of claim 25, wherein the optimization of at least one aspect of generation of at least one of two or more signals comprises providing the graphical user interface for obtaining at least one of: user entry of input, and user selection of at least one item displayed on the graphical user interface (Keane, Fig. 9D; [0042], [0059], [0086], e.g., user selects at least one item displayed on the GUI).
Regarding claim 27, patented claim 1 in view of Keane further discloses the system of claim 24, wherein the optimization of at least one aspect of generation of at least one of two or more signals comprises use of at least one algorithm (Keane, Figs 1 and 5; [0030], [0065]-[0068], e.g., using artificial intelligence algorithms for optimizing the generation of at least two or more signals).
Regarding claim 28, patented claim 1 in view of Keane further discloses the system of claim 27, wherein the optimization of at least one aspect of generation of at least one of two or more signals comprises use of at least one artificial intelligence algorithm (Keane, Figs 1 and 5; [0030], [0065]-[0068]).
Regarding claim 29, patented claim 1 in view of Keane further discloses the system of claim 28, wherein the optimization of at least one aspect of generation of at least one of two or more signals comprises use of at least one artificial intelligence assistant (Keane, Figs 1 and 5; [0030], [0042], e.g., a set of AI-Assisted Brain Wave Processing and Monitoring Engines (ABWPME) 160 are used to optimize the generation of at least two or more signals).
Regarding claim 30, patented claim 1 in view of Keane further discloses the system of claim 24, wherein the at least one processor is configured to use at least one artificial intelligence algorithm in optimizing at least one aspect of: generation of at least one of the two or more signals, obtaining from the user at least one of the two or more signals, determining at least one of the two or more data values, determining the set of at least two data values, determining the message or the command, and determining the output (Keane, Figs 11-12; [0041]-[0042], [0098], [0102]-[0105], e.g., generate the brain wave signals by one or more of the ABWPME 160 engines).
Regarding claim 31, patented claim 1 in view of Keane further discloses the system of claim 24, wherein the at least one processor is configured to use at least one artificial intelligence algorithm in enabling a user to provide input for use in the optimizing of at least one aspect of: generation of at least one of the two or more signals, obtaining from the user at least one of the two or more signals, determining at least one of the two or more data values, determining the set of at least two data values, determining the message or the command, and determining the output (Keane, [0030], [0042], [0059], e.g., enabling the user to set up training parameters for use in optimizing generation of at least one of the two or more signals).
Regarding claim 32, patented claim 1 in view of Keane further discloses the system of claim 24, wherein the at least one processor is configured to use at least one artificial intelligence algorithm in automatically optimizing of at least one aspect of: generation of at least one of the two or more signals, obtaining from the user at least one of the two or more signals, determining at least one of the two or more data values, determining the set of at least two data values, determining the message or the command, and determining the output (Keane, [0030], [0042], [0068], [0112], e.g., the feedback modalities are determined automatically by one or more of the ABWPME 160 engines).
Regarding claim 33, patented claim 1 in view of Keane further discloses the system of claim 24, wherein the optimization of at least one aspect of generation of at least one of two or more signals comprises user adjustments (Keane, [0083], e.g., the administrator to tune the currently displayed neurofeedback session on-the-fly (dynamically) while the session is underway).
Regarding claim 34, the main difference between present claim 34 and patented claim 1 is that patented 1 fails to disclose “use at least one artificial intelligence algorithm in optimizing at least one aspect of: generation of at least one of the two or more signals, obtaining from the user at least one of the two or more signals, determining at least one of the two or more data values, determining the set of at least two data values, determining the message or the command, and determining the output; wherein that which is thought in the specific thinking is not required to be related to the message or the command”.
However, Keane discloses a system (Fig. 1; [0028], e.g., Brain Training Feedback System 100) comprising:
a brain activity monitoring device or system ([0028]-[0029], e.g., an electrode cap 102) configured to obtain data relating to at least one parameter relating to brain activity of a user (Fig. 2; [0032], e.g., obtain brain waves relating to frequency or amplitude relating to brain activity of a user); and
at least one computer or computerized system (Figs 1 and 4; [0029], e.g., Brain Wave Processing and Monitoring System (BWPMS) 120), communicatively coupled with the brain activity monitoring device or system (Fig. 1; [0029], e.g., coupled with the electrode cap via paths 105 and 112), comprising at least one processor (Fig. 4; e.g., signal processing units 413, 417) and at least one memory (e.g., data storage unit 418), the at least one processor being configured to:
based at least in part on at least a portion of the obtained data, obtain from the user two or more signals (Fig. 2; [0032], e.g., obtain two or more brain wave signals); and
use at least one artificial intelligence algorithm in optimizing generation of at least one aspect of: generation of at least one of the two or more signals, obtaining from the user at least one of the two or more signals, determining at least one of the two or more data values, determining the set of at least two data values, determining the message or the command, and determining the output (Figs 1 and 5; [0030], [0042], e.g., artificial intelligence algorithms are used in optimizing generation of the two or more brain wave signals by providing feedback to the user).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to use the teachings of Keane in the invention as taught by patented claim 1 for using at least one artificial intelligence algorithm in optimizing generation of two or more signals by providing feedback so that the user can adjust brain activity to obtain desired outcomes (see [0019] of Kean).
Regarding claim 35, patented claim 1 in view of Keane further discloses the system of claim 34, wherein the at least one processor is configured to use the at least one artificial intelligence algorithm in enabling a user to provide input for use in optimizing at least one aspect of: generation of at least one of the two or more signals, obtaining from the user at least one of the two or more signals, determining at least one of the two or more data values, determining the set of at least two data values, determining the message or the command, and determining the output (Keane, [0042], [0059], e.g., enabling the user to set up training parameters for use in optimizing generation of at least one of the two or more signals).
Regarding claim 36, patented claim 1 in view of Keane further discloses the system of claim 34, wherein the at least one processor is configured to use the at least one artificial intelligence algorithm in automatically optimizing at least one aspect of: generation of at least one of the two or more signals, obtaining from the user at least one of the two or more signals, determining at least one of the two or more data values, determining the set of at least two data values, determining the message or the command, and determining the output (Keane, [0042], [0068], [0112], e.g., the feedback modalities are determined automatically by one or more of the ABWPME 160 engines).
Regarding claim 37, patented claim 1 in view of Keane further discloses the system of claim 34, wherein the optimization of at least one aspect of generation of at least one of the two or more signals comprises user optimization (Keane, [0042], [0059], e.g., user sets up training parameters).
Regarding claim 38, patented claim 1 in view of Keane further discloses the system of claim 34, wherein the at least one processor is configured to provide at least one graphical user interface, on at least one display of at least one display device, for use in optimization of at least one aspect of generation of at least one of the two or more signals (Keane, Fig. 9D; [0042], [0059], [0086], e.g., display a GUI on the display enabling the user to set up training and system parameters).
Claim 39 is similarly rejected over patented claim 22 in view of Keane.
Claim 40 is similarly rejected over patented claim 23 in view of Keane.
Regarding claim 41, patented claim 22 in view of Keane further discloses the method of claim 39, wherein the optimization of at least one aspect of generation of at least one of two or more signals comprises user optimization (Keane, Fig 9D; [0042], [0059], e.g., user sets up training and system parameters).
Regarding claim 42, patented claim 22 in view of Keane further discloses the method of claim 41, wherein the optimization of at least one aspect of generation of at least one of two or more signals comprises providing the graphical user interface for obtaining at least one of: user entry of input, and user selection of at least one item displayed on the at least one graphical user interface (Keane, Fig. 9D; [0042], [0059], [0086], e.g., user selects at least one item displayed on the GUI).
Regarding claim 43, patented claim 22 in view of Keane further discloses the method of claim 42, comprising using at least one artificial intelligence algorithm in optimizing at least one aspect of: generation of at least one of the two or more signals, the obtaining from the user at least one of the two or more signals, determining at least one of the two or more data values, determining the set of at least two data values, determining the message or the command, and determining the output (Keane, Figs 1 and 5; [0030], [0042], e.g., artificial intelligence algorithms are used in optimizing generation of the two or more brain wave signals by providing feedback to the user).
Allowable Subject Matter
5. Claims 24-43 would be allowable if a Terminal Disclaimer is filed to overcome the Double Patenting rejection(s) set forth in this Office action.
Conclusion
6. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Altschuler et al. (US 5,840,040) discloses a system comprising: a portable EEG recording system configured to obtain data relating to power spectrum relating to brain activity of a user; and a microcomputer configured to: based at least in part on at least a portion of the obtained data, obtain two or more signals for the data, wherein each of the two or more signals is generated by the user by the user engaging in specific thinking.
YOO et al. (US 2021/0365117) discloses a method comprising: measuring neural-related signals of an individual to obtain a sensed neural signal when the individual generates a task-irrelevant thought; transmitting the sensed neural signal to a processor; and associating, via the processor, the sensed neural signal with a first device input command and a second device input command.
Aleem et al. (US 2015/0084860) discloses a method including: detecting muscle activity of a user of a wearable EMG device by a set of EMG sensors, wherein the muscle activity corresponds to a gesture performed by a user; in response to detecting muscle activity of the user by the set of EMG sensors, providing a set of signals from the set of EMG sensors to the processor; determining a set of values from the set of signals by the processor; ranking each value in the set of values by the processor, wherein ranking each value in the set of values by the processor includes assigning a rank number to each value in the set of values by the processor; generating a permutation of a digit string based at least in part on the rank number of each value in the set of values by the processor; and identifying the gesture by the processor based at least in part on the permutation of the digit string.
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/HONG ZHOU/ Primary Examiner, Art Unit 2629