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 .
Claim Rejections - 35 USC § 102
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 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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-12 is/are rejected under 35 U.S.C. 102(a)(1) and 102(a)(2) as being anticipated by Lim (US 20200360715 A1).
Regarding claim 1, Lim teaches a method for adaptive transcranial photobiomodulation (see Abstract; transcranial photobiomodulation) comprising:
measuring biometric signals of an individual using biometric sensors (see [0130]; an EEG device having one or mode electrodes for reading and recording subject's electrical brain activity);
processing the biometric signals (see [0131]; the collected data is sent to a device for analysis);
adapting photobiomodulation based upon the processed biometric signals (see [0132]; PBM parameters are set with adjustments made in view of the EEG data analysis);
providing photobiomodulation to the individual ([0167]; irradiation is delivered via a controller assembly in accordance with the selected parameters); and
creating a biofeedback loop wherein the photobiomodulation is adapted (see [0138]; the parameters can be automatically modified in view of the data analysis and the system can preferably generate a negative feedback loop to trigger the delivery of modulating parameters) to bring the biometric signals of the individual toward a target state (see [0085]; the therapy may be targeted in order to achieve particular therapeutic outcomes).
Regarding claim 2, Lim teaches the method of claim 1, wherein the biometric sensors are EEG sensors (see [0163]; EEG device 1000, such as an EEG cap 1010 with one or more electrodes 1012).
Regarding claim 3, Lim teaches the method of claim 2, wherein the biometric signals are the measurement of one or more electrical and optical signals that change based on activity from the brain (see [0151]; EEG electrodes read and record a subject's electrical brain activity).
Regarding claim 4, Lim teaches the method of claim 3, wherein the step of measuring the biometric signals comprises determining the baseline biometric signals of the individual (see [0164-0165]; the subject's brain wave properties are compared to normal brain wave properties and if present, abnormal brain wave properties are detected and identified. This comparison then informs the parameter setting of the stimulation protocol, so it can be regarded as baseline biometric signals; Figs. 10-16B illustrate data of subjects’ changes after treatment based on comparison to baseline data).
Regarding claim 5, Lim teaches the method of claim 4, wherein the baseline biometric signals may be one or more of band power or peak band frequency (see [0039-0040]; EEG signals are characterized by its amplitude, phase, and spatio-temporal patterns).
Regarding claim 6, Lim teaches the method of claim 5, further comprising provision of a head mounted wearable device to the individual comprising the biometric sensors, at least one source for the photobiomodulation light pulses and a control unit (see Fig. 2, [0139]; head mounted wearable apparatus 100 having irradiation units 110, 112, 114, 116, 118, and 120, and controller assembly 108).
Regarding claim 7, Lim teaches the method of claim 6, wherein the target state is set by user or technician input to the control unit, or is selected independently by the control unit (see [0138]; the parameters can be modified manually or automatically with regard to the analyzed data; and
[0207-0208]; key parameters can be adjusted for customized PBM intervention to achieve desired outcomes, the system may also be coupled with a database for a closed loop system, that could automate the selection and execution of parameters to correct aberrant brain oscillations).
Regarding claim 8, Lim teaches the method of claim 7, wherein the adaptation of the photobiomodulation to bring the biometric signals toward the target state is accomplished by modulating one or more attributes of the PBM and assessing the effect on the measured biometric signals (see [0207]; the parameters would involve changes in pulse frequency, power-output, pulse, and duty cycle and can be adjusted based on data analysis).
Regarding claim 9, Lim teaches the method of claim 8, wherein the modulated attributes of the PBM may include one or more of LED location, LED duty cycle, LED power, pulse frequency, pulse duration, pulse gap duration, repeat duration and pause interval (see [0085]; the appropriate parameters for light stimulation are selected including wavelength, energy, power, radiant exposure or dose or fluence, exposure times, wave type, frequency, duty cycle).
Regarding claims 10 and 11, Lim teaches the method of claim 9, wherein the adaptation of the photobiomodulation is accomplished to bring EEG band power, brain band power, or peak band frequency toward a target state through reference to changes in baseline metrics (see [0169-0170]; EEG data is used to detect whether oscillations are coherent or non-coherent and coherency/synchrony data may be used to select operational parameters for treatment using the system) and creation of a feedback loop (see [0207-0208]; key parameters can be adjusted for customized PBM intervention to achieve desired outcomes, the system may also be coupled with a database for a closed loop system, that could automate the selection and execution of parameters to correct aberrant brain oscillations).
Regarding claim 12, Lim teaches the method of claim 11, wherein the wearable device further comprises a wireless communication modality allowing for control of the wearable device by a smartphone or other wireless-enabled device (see [0130-0137]; connection between components including EEG cap, computing device, and system interface may be established wirelessly).
Claim(s) 1-12 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Sverdlov et al (US 20210205634 A1).
Regarding claim 1, Sverdlov teaches a method for adaptive transcranial photobiomodulation (see [0013]; transcranial delivery of illuminating light) comprising:
measuring biometric signals of an individual (see [0130]; continuously collected EEG data) using biometric sensors (see [0068]; photobiomodulation device 110 may have EEG sensor system 120);
processing the biometric signals (see [0134-0135]; analyze initial EEG data and correlate EEG data with observed symptoms);
adapting photobiomodulation based upon the processed biometric signals (see [0136]; therapeutic photobiomodulation is applied based on the EEG data);
providing photobiomodulation to the individual (see [0136]; tPBM is applied); and
creating a biofeedback loop wherein the photobiomodulation is adapted to bring the biometric signals of the individual toward a target state (see [0137]; the device gradually adjusts power until the minimal change in brain oscillations is detected, the device operates at the lowest power that achieves the desired oscillation).
Regarding claim 2, Sverdlov teaches the method of claim 1 wherein the biometric sensor is an EEG sensor (see Fig. 4, [0068]; EEG sensor system 120).
Regarding claim 3, Sverdlov teaches the method of claim 2, wherein the biometric signals are the measurement of one or more electrical signals that change based on activity from the brain (see [0016]; EEG electrodes to monitor brain activity before, during, or after therapeutic session).
Regarding claim 4, Sverdlov teaches the method of claim 3, wherein the step of measuring the biometric signals comprises determining the baseline biometric signals of the individual (see [0134]; analyze initial EEG data for epileptiforms, long-range coherence and hemispheric dominance, which creates a baseline of symptoms for the subsequent tPBM to be based upon).
Regarding claim 5, Sverdlov teaches the method of claim 4, wherein the baseline biometric signals may be one or more of band power or peak band frequency (see [0143]; EEG sensor array to measure brain electric field conditions, [0136]; based on power readings from EEG data, the device stimulates prefrontal cortex to increase power within alpha and beta frequency bands and decrease power of delta and theta bands).
Regarding claim 6, Sverdlov teaches the method of claim 5, further comprising provision of a head mounted wearable device (see Fig. 1, head wearable device) to the individual comprising the biometric sensors (see Fig. 4, [0068]; EEG sensor system 120), at least one source for the photobiomodulation light pulses (see Fig. 4, [0068]; light emitter panels 115a-115e) and a control unit (see Fig. 5, [0069]; processor board 111 including components to control functions of device).
Regarding claim 7, Sverdlov teaches the method of claim 6, wherein the target state is set by user or technician input to the control unit, or is selected independently by the control unit (see [0143]; operating parameters can be automatically adjusted by the system or manually adjusted by the clinician including a minimum and maximum thresholds that define the target state).
Regarding claim 8, Sverdlov teaches the method of claim 7, wherein the adaptation of the photobiomodulation to bring the biometric signals toward the target state is accomplished by modulating one or more attributes of the PBM and assessing the effect on the measured biometric signals (see [0136-0139]; the power is adjusted gradually until the minimal change in brain oscillation is detected, the device operates at the lowest power that achieves the desired oscillation).
Regarding claim 9, Sverdlov teaches the method of claim 8, wherein the modulated attributes of the PBM may include LED power (see [0137]; the device can adjust power gradually).
Regarding claim 10, Sverdlov teaches the method of claim 9, wherein the adaptation of the photobiomodulation is accomplished to bring EEG band power or peak band frequency toward a target state through reference to changes in baseline metrics and creation of a feedback loop (see [0136-0139]; tPBM is applied based on EEG data wherein the power is automatically adjusted until the minimal brain oscillation is detected, brain oscillations corresponding to alpha, beta, delta and/or theta power bands).
Regarding claim 11, Sverdlov teaches the method of claim 9, wherein the adaptation of the photobiomodulation is accomplished to bring brain band power or peak band frequency toward a target state through reference to changes in baseline metrics and creation of a feedback loop (see (see [0136-0139]; tPBM is applied based on EEG data wherein the power is automatically adjusted until the minimal brain oscillation is detected, brain oscillations corresponding to alpha, beta, delta and/or theta power bands).
Regarding claim 12, Sverdlov teaches the method of claim 11, wherein the wearable device further comprises a wireless communication modality allowing for control of the wearable device by a smartphone or other wireless-enabled device (see [0058-0060]; computing device 150 and photobiomodulation device 110 can communicate with one another through a wireless connection 118).
Conclusion
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/A.J.S./Examiner, Art Unit 3792 /ALLEN PORTER/Primary Examiner, Art Unit 3796