DETAILED ACTION
Claims 1-20 filed August 7th 2025 are pending in the current action.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on January 26th 2026 has been entered.
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-20 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.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1, 2, 4, 6, 11-14, 16, 17, 19, and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Frank et al. (US2015/0227193) in view of Klappert et al. (US2015/0272496) in view of Lazlo et al. (US10,952,680)
Consider claim 1, where Frank teaches a method of increasing an autonomy of an individual to operate an external electronic device, the method comprising: providing a brain-computer interface configured to record a neural activity of the individual, where the brain-computer interface comprises a neural recording device implanted within the individual, wherein the neural recording device is configured to detect the neural activity (See Frank Fig. 8 and ¶174-176 where the device 358 is a battery powered sensor that measures a physiological signal and is attached to or implanted in the user (e.g., GSR or EEG).) and is operatively connected to a control unit, where the control unit is configured to produce an output signal for interacting with the external electronic device; (See Frank ¶1-4 where measurements of brainwaves not only enable computer systems to receive input and commands from users, but also allows the computer systems to evaluate the users' emotional state) and receiving an activation signal from the individual to switch the brain-computer interface to an active mode from an idle mode, where the activation signal is generated by the individual using neural activity. (See Frank ¶260 where measuring the user with the EEG may help determine to what extent the user was really frightened while watching the video clip; however, if the predicted value is too low, it is not likely that the clip is going to scare the user at all, so the system chooses not to waste power on confirming that. Thus, if the expected emotional response is below the threshold, the controller 108 may select a "low power" mode of operation for the device 112, in which the device 112 consumes very little power. However, if the expected emotional response reaches the threshold, the controller 108 may select a "regular" mode of operation for the device 112, in which the device 112 consumes significantly more power than in the low power mode. Thus, when the measurement exceeds a threshold the system is sent a signal to transition from a “low power” mode to a “regular” mode.)
Frank provides suggestion for the limitation the brain-computer interface is operatively connected to a control unit, where the control unit is configured to produce an output signal for interacting with the external electronic device. However Frank does not explicitly teach the interaction with the external electronic device. However in an analogous field of endeavor Klappert teaches the interaction with the external electronic device. (See Klappert Fig. 3 and ¶97-99, 110 where the brainstate of the user is monitored using monitoring component 316 and then interpreted by the control circuitry 304 and send and receive commands using I/O path 302 that connects to other user equipment such as a TV via path 302 a message from a remote server) Therefore, it would have been obvious for one of ordinary skill in the art that the control unit of Frank used with various forms of digital media (See Frank ¶2) may include external devices as taught by Klappert. One of ordinary skill in the art would have been motivated to perform the modification for the advantage of/ benefit of using known devices with the indicated function for their intended use.
Frank teaches a mode of operation selection implicitly or explicitly made by measuring brainwaves with EEG (See Frank ¶69-72 where the power consumption of the device operating in the first mode of operation is significantly higher than the power consumption of the device operating in the second mode of operation. If the threshold is reached, a first mode of operation in which the user's brainwaves are measured extensively (e.g., by measuring multiple bands of frequencies) may be selected. For example, measuring the user with the EEG may help determine to more precisely how the user felt towards elements in the content. A mode of operation for a device, such as the modes 287a and/or 287b, may be implicitly or explicitly selected. ) However, Frank does not explicitly teach the activation signal comprises a neural pattern intentionally generated by the individual to command a mode transition. However, in an analogous field of endeavor Lazlo teaches the activation signal comprises a neural pattern intentionally generated by the individual to command a mode transition.(See Lazlo Fig. 4 and col 8 line 60- col 9 line 26 where the system (e.g., system 100) receives EEG signals from the system's sensors placed on (e.g., removably attached or otherwise coupled to) the user's scalp (step 420). The system can decompose the signal into a time series of signal amplitude and/or change in signal amplitude and perform mathematical operations on the time series to determine the user's intent. For example, the mathematical operations can associate a change in signal amplitude above a certain threshold and within a certain time (e.g., with 50 ms or less) of presenting the user with the information with a particular intention (e.g., an affirmative response) and a change in signal amplitude below the threshold with the opposite intention (e.g., a negative response). ) Therefore, it would have been obvious to one of ordinary skill in the art that measured EEG signal above a threshold to explicitly indicate a mode selection as taught by Frank can be associated with a particular intention as taught by Lazlo. One of ordinary skill in the art would have been motivated to perform the modification for the advantage of/ benefit of using known methods of associating user intent to explicitly convey a selection.
Consider claim 2, where Frank teaches the method of claim 1, where receiving the activation signal from the individual to switch the brain-computer interface to the active mode from the idle mode occurs without assistance from a caregiver. (See Frank ¶260 where when the measurement exceeds a threshold the system is sent a signal to transition from a “low power” mode to a “regular” mode. Such an occurrence happens automatically from the measurement)
Consider claim 4, where Frank in view of Klappert in view of Lazlo teaches the method of claim 3, where coupling the control unit and the external electronic device occurs wirelessly. (See Klappert Fig. 3 and ¶97-99, 110 where the brainstate of the user is monitored using monitoring component 316 and then interpreted by the control circuitry 304 and send and receive commands using I/O path 302 that connects to other user equipment such as a TV via path 302 a message from a remote server) Therefore, it would have been obvious for one of ordinary skill in the art that the control unit of Frank used with various forms of digital media (See Frank ¶2) may include external devices as taught by Klappert. One of ordinary skill in the art would have been motivated to perform the modification for the advantage of/ benefit of using known devices with the indicated function for their intended use.
Consider claim 6, where Frank in view of Klappert in view of Lazlo teaches the method of claim 1, wherein the brain-computer interface is configured to transmit operational data from the brain-computer interface to a remote electronic dashboard, where the remote electronic dashboard permits an individual to record activity of the brain-computer interface. (See Frank Fig. 6 and ¶60, 114-118 where the processor is remote, thus transmitting the commands remotely)
Consider claim 7, where Frank in view of Klappert in view of Lazlo teaches the method of claim 6, wherein the brain-computer interface is configured to transmit operational data from the brain-computer interface to the remote electronic dashboard wirelessly. (See Frank ¶60 where the processor is remote, thus transmitting the commands remotely)
Consider claim 11, where Frank in view of Klappert in view of Lazlo teaches the method of claim 1, where the brain-computer interface is configured to enter the idle mode wherein the brain-computer interface draws less power and records less neural activity of the individual than in the active mode. (See Frank ¶350-352 where while operating at the first measuring rate 176a, the device 177 takes significantly fewer measurements of affective response, per unit of measurement time, compared to the number of measurements taken by the device 177 while operating at the second measuring rate 176b)
Consider claim 12, where Frank in view of Klappert in view of Lazlo teaches the method of claim 1, wherein a power that the brain-computer interface draws when in the idle mode is less than a power that the brain-computer interface draws when in the active mode. (See Frank ¶260 where Measuring the user with the EEG may help determine to what extent the user was really frightened while watching the video clip; however, if the predicted value is too low, it is not likely that the clip is going to scare the user at all, so the system chooses not to waste power on confirming that. Thus, if the expected emotional response is below the threshold, the controller 108 may select a "low power" mode of operation for the device 112, in which the device 112 consumes very little power. However, if the expected emotional response reaches the threshold, the controller 108 may select a "regular" mode of operation for the device 112, in which the device 112 consumes significantly more power than in the low power mode. Thus, when the measurement exceeds a threshold the system is sent a signal to transition from a “low power” mode to a “regular” mode.)
Consider claim 13, where Frank teaches a method of increasing an autonomy of an individual to operate an external electronic device, the method comprising: providing a brain-computer interface configured to record a neural activity of the individual, where the brain-computer interface comprises a neural recording device and an external electronic device; (See Frank Fig. 8 and ¶174-176 where the device 358 is a battery powered sensor that measures a physiological signal and is attached to or implanted in the user (e.g., GSR or EEG).) receiving an activation signal from the individual to switch the brain-computer interface to an active mode from an idle mode, where the activation signal is generated by the individual using neural activity; (See Frank ¶260 where measuring the user with the EEG may help determine to what extent the user was really frightened while watching the video clip; however, if the predicted value is too low, it is not likely that the clip is going to scare the user at all, so the system chooses not to waste power on confirming that. Thus, if the expected emotional response is below the threshold, the controller 108 may select a "low power" mode of operation for the device 112, in which the device 112 consumes very little power. However, if the expected emotional response reaches the threshold, the controller 108 may select a "regular" mode of operation for the device 112, in which the device 112 consumes significantly more power than in the low power mode. Thus, when the measurement exceeds a threshold the system is sent a signal to transition from a “low power” mode to a “regular” mode.) where the neural recording device is implanted within the individual and is configured to detect the neural activity and is operatively connected to an external electronic device; (See Frank ¶1-4 where measurements of brainwaves not only enable computer systems to receive input and commands from users, but also allows the computer systems to evaluate the users' emotional state) where the external electronic device is configured to produce an output signal in response to receiving a signal from the neural recording device; and where the brain-computer interface is configured to enter the idle mode wherein the brain-computer interface draws less power than in the active mode. (See Frank ¶260 where measuring the user with the EEG may help determine to what extent the user was really frightened while watching the video clip; however, if the predicted value is too low, it is not likely that the clip is going to scare the user at all, so the system chooses not to waste power on confirming that. Thus, if the expected emotional response is below the threshold, the controller 108 may select a "low power" mode of operation for the device 112, in which the device 112 consumes very little power. However, if the expected emotional response reaches the threshold, the controller 108 may select a "regular" mode of operation for the device 112, in which the device 112 consumes significantly more power than in the low power mode. Thus, when the measurement is below a threshold the system is sent a signal to transition to a “low power” mode from a “regular” mode.)
Frank provides suggestion for the limitation the brain-computer interface is operatively connected to a control unit, where the control unit is configured to produce an output signal for interacting with the external electronic device. However Frank does not explicitly teach the interaction with the external electronic device. However in an analogous field of endeavor Klappert teaches the interaction with the external electronic device. (See Klappert Fig. 3 and ¶97-99, 110 where the brainstate of the user is monitored using monitoring component 316 and then interpreted by the control circuitry 304 and send and receive commands using I/O path 302 that connects to other user equipment such as a TV via path 302 a message from a remote server) Therefore, it would have been obvious for one of ordinary skill in the art that the control unit of Frank used with various forms of digital media (See Frank ¶2) may include external devices as taught by Klappert. One of ordinary skill in the art would have been motivated to perform the modification for the advantage of/ benefit of using known devices with the indicated function for their intended use.
Frank teaches a mode of operation selection implicitly or explicitly made by measuring brainwaves with EEG (See Frank ¶69-72 where the power consumption of the device operating in the first mode of operation is significantly higher than the power consumption of the device operating in the second mode of operation. If the threshold is reached, a first mode of operation in which the user's brainwaves are measured extensively (e.g., by measuring multiple bands of frequencies) may be selected. For example, measuring the user with the EEG may help determine to more precisely how the user felt towards elements in the content. A mode of operation for a device, such as the modes 287a and/or 287b, may be implicitly or explicitly selected. ) However, Frank does not explicitly teach the activation signal comprises a neural pattern intentionally generated by the individual to command a mode transition. However, in an analogous field of endeavor Lazlo teaches the activation signal comprises a neural pattern intentionally generated by the individual to command a mode transition.(See Lazlo Fig. 4 and col 8 line 60- col 9 line 26 where the system (e.g., system 100) receives EEG signals from the system's sensors placed on (e.g., removably attached or otherwise coupled to) the user's scalp (step 420). The system can decompose the signal into a time series of signal amplitude and/or change in signal amplitude and perform mathematical operations on the time series to determine the user's intent. For example, the mathematical operations can associate a change in signal amplitude above a certain threshold and within a certain time (e.g., with 50 ms or less) of presenting the user with the information with a particular intention (e.g., an affirmative response) and a change in signal amplitude below the threshold with the opposite intention (e.g., a negative response). ) Therefore, it would have been obvious to one of ordinary skill in the art that measured EEG signal above a threshold to explicitly indicate a mode selection as taught by Frank can be associated with a particular intention as taught by Lazlo. One of ordinary skill in the art would have been motivated to perform the modification for the advantage of/ benefit of using known methods of associating user intent to explicitly convey a selection.
Consider claim 14, where Frank in view of Klappert in view of Lazlo teaches the method of claim 13, where receiving the activation signal from the individual to switch the brain-computer interface from the idle mode to the active mode occurs without assistance from a caregiver. (See Frank ¶260 where when the measurement exceeds a threshold the system is sent a signal to transition from a “low power” mode to a “regular” mode. Such an occurrence happens automatically from the measurement)
Consider claim 16, where Frank in view of Klappert in view of Lazlo teaches the method of claim 13, wherein the brain-computer interface is configured to transmit operational data from the brain-computer interface to a remote electronic dashboard, where the remote electronic dashboard permits an individual to record activity of the brain-computer interface. (See Frank Fig. 6 and ¶60, 114-118 where the processor is remote, thus transmitting the commands remotely)
Consider claim 17, where Frank in view of Klappert in view of Lazlo teaches the method of claim 16, wherein the brain-computer interface is configured to transmit operational data from the brain-computer interface to the remote electronic dashboard wirelessly. (See Frank ¶60 where the processor is remote, thus transmitting the commands remotely)
Consider claim 19, where Frank in view of Klappert in view of Lazlo teaches the method of claim 13, where the brain-computer interface is configured to enter the idle mode wherein the brain-computer interface draws less power and records less neural activity of the individual than in the active mode. (See Frank ¶350-352 where while operating at the first measuring rate 176a, the device 177 takes significantly fewer measurements of affective response, per unit of measurement time, compared to the number of measurements taken by the device 177 while operating at the second measuring rate 176b)
Consider claim 20, where Frank in view of Klappert in view of Lazlo teaches a method of increasing an autonomy of an individual to operate an external electronic device, the method comprising: providing a brain-computer interface configured to record a neural activity of the individual, where the brain-computer interface comprises a neural recording device and an external electronic device; (See Frank Fig. 8 and ¶174-176 where the device 358 is a battery powered sensor that measures a physiological signal and is attached to or implanted in the user (e.g., GSR or EEG).) receiving an activation signal from the individual to switch the brain-computer interface from an active mode to an idle mode, where the activation signal is generated by the individual using neural activity; (See Frank ¶260 where measuring the user with the EEG may help determine to what extent the user was really frightened while watching the video clip; however, if the predicted value is too low, it is not likely that the clip is going to scare the user at all, so the system chooses not to waste power on confirming that. Thus, if the expected emotional response is below the threshold, the controller 108 may select a "low power" mode of operation for the device 112, in which the device 112 consumes very little power. However, if the expected emotional response reaches the threshold, the controller 108 may select a "regular" mode of operation for the device 112, in which the device 112 consumes significantly more power than in the low power mode. Thus, when the measurement is below a threshold the system is sent a signal to transition to a “low power” mode from a “regular” mode.) where the neural recording device is implanted within the individual and is configured to detect the neural activity and is operatively connected to an external electronic device; where the external electronic device is configured to produce an output signal in response to receiving a signal from the neural recording device; and where the brain-computer interface is configured to enter the active mode wherein the brain-computer interface draws more power in the active mode than the brain-computer interface draws in the idle mode. (See Frank ¶260 where measuring the user with the EEG may help determine to what extent the user was really frightened while watching the video clip; however, if the predicted value is too low, it is not likely that the clip is going to scare the user at all, so the system chooses not to waste power on confirming that. Thus, if the expected emotional response is below the threshold, the controller 108 may select a "low power" mode of operation for the device 112, in which the device 112 consumes very little power. However, if the expected emotional response reaches the threshold, the controller 108 may select a "regular" mode of operation for the device 112, in which the device 112 consumes significantly more power than in the low power mode. Thus, when the measurement exceeds a threshold the system is sent a signal to transition from a “low power” mode to a “regular” mode.)
Frank provides suggestion for the limitation the brain-computer interface is operatively connected to a control unit, where the control unit is configured to produce an output signal for interacting with the external electronic device. However Frank does not explicitly teach the interaction with the external electronic device. However in an analogous field of endeavor Klappert teaches the interaction with the external electronic device. (See Klappert Fig. 3 and ¶97-99, 110 where the brainstate of the user is monitored using monitoring component 316 and then interpreted by the control circuitry 304 and send and receive commands using I/O path 302 that connects to other user equipment such as a TV via path 302 a message from a remote server) Therefore, it would have been obvious for one of ordinary skill in the art that the control unit of Frank used with various forms of digital media (See Frank ¶2) may include external devices as taught by Klappert. One of ordinary skill in the art would have been motivated to perform the modification for the advantage of/ benefit of using known devices with the indicated function for their intended use.
Frank teaches a mode of operation selection implicitly or explicitly made by measuring brainwaves with EEG (See Frank ¶69-72 where the power consumption of the device operating in the first mode of operation is significantly higher than the power consumption of the device operating in the second mode of operation. If the threshold is reached, a first mode of operation in which the user's brainwaves are measured extensively (e.g., by measuring multiple bands of frequencies) may be selected. For example, measuring the user with the EEG may help determine to more precisely how the user felt towards elements in the content. A mode of operation for a device, such as the modes 287a and/or 287b, may be implicitly or explicitly selected. ) However, Frank does not explicitly teach the activation signal comprises a neural pattern intentionally generated by the individual to command a mode transition. However, in an analogous field of endeavor Lazlo teaches the activation signal comprises a neural pattern intentionally generated by the individual to command a mode transition.(See Lazlo Fig. 4 and col 8 line 60- col 9 line 26 where the system (e.g., system 100) receives EEG signals from the system's sensors placed on (e.g., removably attached or otherwise coupled to) the user's scalp (step 420). The system can decompose the signal into a time series of signal amplitude and/or change in signal amplitude and perform mathematical operations on the time series to determine the user's intent. For example, the mathematical operations can associate a change in signal amplitude above a certain threshold and within a certain time (e.g., with 50 ms or less) of presenting the user with the information with a particular intention (e.g., an affirmative response) and a change in signal amplitude below the threshold with the opposite intention (e.g., a negative response). ) Therefore, it would have been obvious to one of ordinary skill in the art that measured EEG signal above a threshold to explicitly indicate a mode selection as taught by Frank can be associated with a particular intention as taught by Lazlo. One of ordinary skill in the art would have been motivated to perform the modification for the advantage of/ benefit of using known methods of associating user intent to explicitly convey a selection.
Claim(s) 3, 9, 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Frank in view of Klappert in view of Lazlo as applied to claim 1 above, in further view of Chizeck et al. (US2014/0228701)
Consider claim 3, where Frank in view of Klappert in view of Lazlo teaches the method of claim 1, further comprising coupling the control unit and the external electronic device to acquire more data, (See Frank ¶260 where Measuring the user with the EEG may help determine to what extent the user was really frightened while watching the video clip; however, if the predicted value is too low, it is not likely that the clip is going to scare the user at all, so the system chooses not to waste power on confirming that. Thus, if the expected emotional response is below the threshold, the controller 108 may select a "low power" mode of operation for the device 112, in which the device 112 consumes very little power. However, if the expected emotional response reaches the threshold, the controller 108 may select a "regular" mode of operation for the device 112, in which the device 112 consumes significantly more power than in the low power mode. Thus, when the measurement exceeds a threshold the system is sent a signal to transition from a “low power” mode to a “regular” mode.) however Frank does not explicitly teach to reduce a calibration time for the brain-computer interface when entering the active mode. However, in an analogous field of endeavor Chizeck teaches calibration requirements involving a set of time series data. (See Chizeck ¶85-87 where multiple time series of data are taken from the brain to be processed and calibrated) Therefore, it would have been obvious for one of ordinary skill in the art that opening up more time series of data to be recorded over a period of time would speed up the calibration. One of ordinary skill in the art would have been motivated to perform the modification for the advantage of/ benefit of using regular collection of data to perform the regular calibration.
Consider claim 9, where Frank in view of Klappert in view of Lazlo teaches the method of claim 1, however, they do not explicitly teach wherein the brain-computer interface is configured to permit the individual to initiate calibration of the brain-computer interface when entering the active mode. However, in an analogous field of endeavor Chizeck teaches the limitation. (See Chizeck ¶111-112 where the start calibration input can be a manual input; e.g., a button is pressed or other operation performed by a user or other entity to initiate calibration process 400, the user input enters the device into an active mode and triggers calibration) Therefore, it would have been obvious for one of ordinary skill in the art to modify the calibration of Frank by allowing a user to enter the calibration process as taught by Chizeck. One of ordinary skill in the art would have been motivated to perform the modification for the advantage of/ benefit of periodically re-calibrating to improve performance.
Consider claim 18, where Frank in view of Klappert in view of Lazlo teaches the method of claim 13, however, they do not explicitly teach wherein the brain-computer interface is configured to permit the individual to initiate calibration of the brain-computer interface when entering the active mode. However, in an analogous field of endeavor Chizeck teaches the limitation. (See Chizeck ¶111-112 where the start calibration input can be a manual input; e.g., a button is pressed or other operation performed by a user or other entity to initiate calibration process 400, the user input enters the device into an active mode and triggers calibration) Therefore, it would have been obvious for one of ordinary skill in the art to modify the calibration of Frank by allowing a user to enter the calibration process as taught by Chizeck. One of ordinary skill in the art would have been motivated to perform the modification for the advantage of/ benefit of periodically re-calibrating to improve performance.
Claim(s) 5, 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Frank in view of Klappert in view of Lazlo as applied to claim 1 above, in further view of Wen et al. (US2022/0248958)
Consider claim 5, where Frank in view of Klappert in view of Lazlo teaches the method of claim 1, however they do not explicitly teach wherein the brain-computer interface is configured for coupling to a recharging supply by the individual. However, in an analogous field of endeavor Wen teaches the limitation. (See Wen figs. 3-5 and 977 where the devices are in communication with a charging pad) Therefore, it would have been obvious for one of ordinary skill in the art that the devices of Frank would be able to be charged as taught by Wen. One of ordinary skill in the art would have been motivated to perform the modification for the advantage of/ benefit of being able to continuously use electronic devices using the known method of charging the electronic device.
Consider claim 15, where Frank in view of Klappert in view of Lazlo teaches the method of claim 13, however they do not explicitly teach wherein the brain-computer interface is configured for coupling to a recharging supply by the individual. However, in an analogous field of endeavor Wen teaches the limitation. (See Wen figs. 3-5 and 977 where the devices are in communication with a charging pad) Therefore, it would have been obvious for one of ordinary skill in the art that the devices of Frank would be able to be charged as taught by Wen. One of ordinary skill in the art would have been motivated to perform the modification for the advantage of/ benefit of being able to continuously use electronic devices using the known method of charging the electronic device.
Claim(s) 8, 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Frank in view of Klappert in view of Lazlo as applied to claim 1 above, in further view of Marquez Chin et al. (US2017/0172497)
Consider claim 8, where Frank in view of Klappert in view of Lazlo teaches the method of claim 1, however, they do not explicitly teach wherein the brain-computer interface is configured to have a latency of five seconds or less. However, in an analogous field of endeavor Marquez Chin teaches wherein the brain-computer interface is configured to have a latency of five seconds or less. (See Marquez Chin 9185-186 where the event-related desynchronization (ERD) signal from a in some cases was observed and the intended activity classified as early 1.5 seconds prior to movement, and in one example was detected in real-time an average of 0.62 seconds before movement.) Therefore, it would have been obvious that the neural signal controlled prosthetic limb of Frank would have a similar latency as expressed by Marquez Chin. One of ordinary skill in the art would have recognized that Marquez Chin teaches the common range in the art for the neural signal controlled prosthetic limb.
Consider claim 10, where Frank in view of Klappert in view of Lazlo teaches the method of claim 1, however Frank does not explicitly teach wherein the individual is a paralyzed individual. However, in an analogous field of endeavor Marquez Chin teaches wherein the individual is a paralyzed individual. (See Marquez Chin 9188-189 where the limb is a paralyzed limb) Therefore, it would have been obvious for one of ordinary skill in the art that the prosthetic limb of Frank would be for a Marquez Chin. One of ordinary skill in the art would have recognized a common use case for a prosthetic would be for a paralyzed individual.
Conclusion
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WILLIAM LU
Primary Examiner
Art Unit 2624
/WILLIAM LU/Primary Examiner, Art Unit 2624