DETAILED ACTION
Notice of Pre-AIA or AIA Status
In the present application, filed on or after March 16, 2013, claims 1-2 and 7-20 have been considered and examined under the first inventor to file provisions of the AIA .
Respond to Applicant’s Arguments/Remarks
Applicant’s arguments, see Remarks, filed 08/07/2026, with respect to the rejection(s) of claims 1-6 and 12-20 has been fully considered and the results as followings:
On pages 14-15 of Applicant remarks, Applicant argues that the amended claimed invention recites limitations of allowable claim 7. Thus, the amended claimed invention is allowable. Examiner respectfully disagrees with Applicant because the amended claimed invention recites rejectable limitations of claim 7. Therefore, Applicant arguments, with respect to the rejection(s) of claims 1-6 and 12-20, based solely on the limitations as amended, has been fully considered but are moot because the arguments do not apply to the new combination of references including prior art being used in the current rejection (see below for detail) under new grounds of rejection, necessitated by amendment.
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 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.
Claims 1-2, 12 and 16-20 are rejected under 35 U.S.C. 103 as being unpatentable over Read et al. (Read – US 2022/0225920 A1) in view of Aimone et al. (Aimone – US 2016/0077547 A1) and further in view of Hwang et al. (Hwang – US 2016/0210407 A1).
As to claim 1, Read discloses a communication device, comprising at least one processor, in which a presented reaction changes according to a psychological state of an evaluation target person, wherein:
the at least one processor (Read: FIG. 1 the headband dual core processor) acquires first brainwave information from at least one sensor (Read: [0115]-[0118] and FIG. 1 the inputs ) of the evaluation target person (Read: Abstract, [0114]-[0115], [0117], [0127], [0150]-[0152], [0155] , and FIG. 1 the inputs: The sensing module can be configured to detect, measure, record, quantify, and/or read one or more biological signals of a subject. The one or more biological signals can comprise, for example, brain waves or brain signals. The one or more biological signals can comprise an electrical signal and/or an oscillatory signal. The one or more biological signals can be represented as one or more EEG waves or waveforms (also referred to herein as brain waves or brain signals). The one or more biological signals can include an electroencephalogram (EEG) signal, an electromyogram (EMG) signal, an electrocorticogram (ECoG) signal, field potentials within a motor cortex or other regions of the brain, or combinations thereof);
the at least one processor (Read: FIG. 1 the headband dual core processor) determines a first reaction, based on the first brainwave information (Read: [0117], [0129]-[0130], [0133]-[0136], [0150]-[0152], [0155], [0164], [0167]-[0168], and FIG. 1: The one or more biological signals can correspond to a particular mental state of the subject. For example, in a first mental state, the subject may exhibit a first set of biological signals with a first set of characteristics, whereas in a second mental state, the subject may exhibit a second set of biological signals with a second set of characteristics. The characteristics associated with the biological signals may comprise, for example, a wavelength, a frequency, an amplitude, a phase, a center frequency, a phase difference, a variance, a co-variance, or any other physical property associated with the one or more biological signal);
the at least one processor determines the psychological state of the evaluation target person based on a change from a ratio of an amplitude of the first brainwave information in a predetermined frequency band relative to a total amplitude in the first brainwave information to a ratio of an amplitude of the second brainwave information in the predetermined frequency band relative to a total amplitude in the second brainwave information (Read: [0018], [0045], [0057], [0075], [0124], [0135]-[0136], [0139], [0145]-[0148], [0152], [0157], and FIG. 1: the biomarkers can comprise one or more ratios between two brainwave oscillation frequency bands that define brain-states (e.g., a theta/alpha ratio, a beta/alpha ratio, an alpha/[slow wave+delta wave+theta wave ratio], etc.). In some cases, the biomarkers can comprise a measurement of a coherence between brainwave oscillations recorded from the same electrode and/or across a plurality of different electrodes. In other cases, the biomarkers can comprise brain-state and frequency defined EEG biomarkers (e.g., individualized sigma occurring in stage 2 sleep). In some cases, the biomarkers can comprise non-neural biomarkers from other sensor signals (e.g., heartbeat sensors, pulse oximeters, etc.));
the at least one processor controls the communication device to output the first reaction and the second reaction from a reaction presentation unit (Read: [0141]-[0142], [0151]-[0152], [0156], [0161]-[0162], and FIG. 1 the audio speaker output: The audio speaker volume output can be varied in proportion to a user's individualized maximum and minimum alpha signal levels. The user's maximum and minimum mean alpha biomarker levels can be set to values of, for example, 8 dB and 3 dB, respectively, as determined in a prior data calibration session. The maximum and minimum alpha biomarker levels can indicate maximal and minimal alertness levels, respectively. The user can practice alternately increasing and decreasing the audio speaker volume on 4 separate occasions (a, b, c and d) within a 1.5 hour session. To do so, the user simply focuses their attention on their forehead to increase alpha and as their attention relaxes audible feedback indicates relaxation).
Read does not explicitly disclose
the at least one processor acquires first brainwave information from at least one sensor and first biological information of the evaluation target person;
the at least one processor determines a first reaction, based on the first brainwave information and the first biological information of the evaluation target person acquired before the first reaction;
the at least one processor acquires second brainwave information and second biological information after the first reaction is determined;
the at least one processor acquires a change from the first brainwave information to the second brainwave information and from the first biological information to the second biological information from before the first reaction to after the first reaction;
the at least one processor generates state information indicating the psychological state of the evaluation target person, based on the change from the first brainwave information to the second brainwave information and from the first biological information to the second biological information;
the at least one processor determines a second reaction based on the generated state information;
the at least one processor determines the psychological state of the evaluation target person after the first reaction;
the at least one processor controls the communication device to output the first reaction and the second reaction from a reaction presentation unit;
the first reaction and the second reaction that is output from the reaction presentation unit are simulated expressions of the evaluation target person as a virtual person that represents the psychological state of the evaluation target person so that the psychological state of the evaluation target person can be communicated using the simulated expressions; and
the simulated expressions are at least one of an utterance, an action, and/or a facial expression.
However, it has been known in the art of monitoring condition of a user to implement the at least one processor controls the communication device to output the first reaction and the second reaction from a reaction presentation unit;
the first reaction and the second reaction that is output from the reaction presentation unit are simulated expressions of the evaluation target person as a virtual person that represents the psychological state of the evaluation target person so that the psychological state of the evaluation target person can be communicated using the simulated expressions; and
the simulated expressions are at least one of an utterance, an action, and/or a facial expression, as suggested by Aimone, which discloses
the at least one processor controls the communication device to output the first reaction and the second reaction from a reaction presentation unit; the first reaction and the second reaction that is output from the reaction presentation unit are simulated expressions of the evaluation target person as a virtual person that represents the psychological state of the evaluation target person so that the psychological state of the evaluation target person can be communicated using the simulated expressions (Aimone: [0167], [0170], and FIG. 10-11: The EEG readings from other members of the group affects the appearance of their avatars. e.g. if the person is relaxed, their avatars can glow blue; if they are tense, their avatars would glow red. The individual participants can look at their own avatars to determine how they are proceeding with the meditation session; their own avatars will change colour like those in the rest of the group. Emotions can also be displayed on the avatars; i.e. the words “ANGRY” or “ANXIOUS” can appear on their faces); and
the simulated expressions are at least one of an utterance, an action (Aimone: [0113], [0169], and FIG. 10-11: The device measures her brainwaves and changes the characteristics of the virtual pet accordingly to provide visual feedback. For example, the pet changes colour from green to red when Danielle is upset; it changes back from red to green when she enters a relaxed state. Alternatively, the pet can change its own behaviour: irritated, relaxed, angry, etc. The pet can be used as a mindfulness/meditation aide—Danielle tries to get her pet to change colour to a certain state to match whatever mindfulness goals she is aiming towards), and/or a facial expression (Aimone: [0112], [0167], [0170], and FIG. 10-11: The usage of the facial sensors (an example of bio-signal sensors of wearable device 1002, 1004) may allow for the mapping of a user's expression to the face of their avatar 1010, 1012 in a VR environment (e.g. to represent detected facial states with associated smiles, squints, winks, furrows, frowns, etc.). This can be augmented with brain signals from wearable device 1002, 1004 to do emotion estimation by device 1008, 1006. This estimate can further augment a characters appearance in the VR environment as an example of feedback.).
Therefore, in view of teachings by Read and Aimone, it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to implement in the biological signals processing system of Read to include the at least one processor controls the communication device to output the first reaction and the second reaction from a reaction presentation unit;
the first reaction and the second reaction that is output from the reaction presentation unit are simulated expressions of the evaluation target person as a virtual person that represents the psychological state of the evaluation target person so that the psychological state of the evaluation target person can be communicated using the simulated expressions; and
the simulated expressions are at least one of an utterance, an action, and/or a facial expression, as suggested by Aimone. The motivation for this is to provide a feedback to a user based on conditions of the user.
The combination of Read and Aimone does not explicitly disclose the at least one processor acquires first brainwave information from at least one sensor and first biological information of the evaluation target person;
the at least one processor determines a first reaction, based on the first brainwave information and the first biological information of the evaluation target person acquired before the first reaction;
the at least one processor acquires second brainwave information and second biological information after the first reaction is determined;
the at least one processor acquires a change from the first brainwave information to the second brainwave information and from the first biological information to the second biological information from before the first reaction to after the first reaction;
the at least one processor generates state information indicating the psychological state of the evaluation target person, based on the change from the first brainwave information to the second brainwave information and from the first biological information to the second biological information;
the at least one processor determines a second reaction based on the generated state information; and
the at least one processor determines the psychological state of the evaluation target person after the first reaction.
However, it has been known in the art of monitoring conditions of a user to implement the at least one processor acquires first brainwave information from at least one sensor and first biological information of the evaluation target person;
the at least one processor determines a first reaction, based on the first brainwave information and the first biological information of the evaluation target person acquired before the first reaction;
the at least one processor acquires second brainwave information and second biological information after the first reaction is determined;
the at least one processor acquires a change from the first brainwave information to the second brainwave information and from the first biological information to the second biological information from before the first reaction to after the first reaction;
the at least one processor generates state information indicating the psychological state of the evaluation target person, based on the change from the first brainwave information to the second brainwave information and from the first biological information to the second biological information;
the at least one processor determines a second reaction based on the generated state information; and
the at least one processor determines the psychological state of the evaluation target person after the first reaction, as suggested by Hwang, which discloses
the at least one processor acquires first brainwave information from at least one sensor and first biological information of the evaluation target person (Hwang: Abstract, [0026]-[0028], [0050]-[0055], [0060]-[0061], and FIG. 2-4: the device 100 may acquire bio-signals of a user via the sensor 110 (S201). The bio-signals may be signals that may be used to detect a user's status such as brainwaves, the amount of oxygen in cerebral blood flow, and pulses);
the at least one processor determines a first reaction (Hwang: [0049]-[0050], [0055]-[0057], [0067]-[0079], [0082]-[0083], [0133]-[0136], and FIG. 1-3: the device 100 may output at least one object as an audio and speech signal or vibration signal in order to apply an auditory or tactile stimulus to the user. Each object may be output as an audio and speech signal or vibration signal that can be recognized by the user. When an object corresponding to a user's desired task is output, a concentration level or excitation level derived from a brainwave signal may be increased. Thus, an ERP signal having a larger magnitude may be detected when an object corresponding to a user's desired task is output than when another object is output. The device 100 may select a user's desired task by selecting an object corresponding to a time point when the ERP signal has a relatively large magnitude compared to another magnitude), based on the first brainwave information and the first biological information of the evaluation target person (Hwang: Abstract, [0026]-[0028], [0050]-[0055], [0060]-[0061], and FIG. 2-4: The sensor 110 may acquire bio-signals from a user. The bio-signals may include brainwaves, pulses, an electrocardiogram, etc. If the bio-signals are brainwaves, the sensor 110 may acquire at least one selected from electroencephalogram (EEG), electrooculogram (EOG), electrocardiogram (ECG), electromyogram (EMG), and electrokardiogramm (EKG) signals. The sensor 110 may obtain the bio-signals by contacting the user' body and may come in different forms such as a headset, earphones, and a bracelet…the device 100 may acquire bio-signals of a user via the sensor 110 (S201). The bio-signals may be signals that may be used to detect a user's status such as brainwaves, the amount of oxygen in cerebral blood flow, and pulses) acquired before the first reaction (Hwang: FIG. 3);
the at least one processor acquires second brainwave information and second biological information after the first reaction is determined (Hwang: [0049]-[0050], [0055]-[0057], [0067]-[0079], [0082]-[0083], [0133]-[0136], and FIG. 1-3: the device 100 may output at least one object as an audio and speech signal or vibration signal in order to apply an auditory or tactile stimulus to the user. Each object may be output as an audio and speech signal or vibration signal that can be recognized by the user. When an object corresponding to a user's desired task is output, a concentration level or excitation level derived from a brainwave signal may be increased. Thus, an ERP signal having a larger magnitude may be detected when an object corresponding to a user's desired task is output than when another object is output. The device 100 may select a user's desired task by selecting an object corresponding to a time point when the ERP signal has a relatively large magnitude compared to another magnitude);
the at least one processor acquires a change from the first brainwave information to the second brainwave information and from the first biological information to the second biological information from before the first reaction to after the first reaction (Hwang: Abstract, [0026]-[0028], [0050]-[0055], [0060]-[0061], and FIG. 2-4: The sensor 110 may acquire bio-signals from a user. The bio-signals may include brainwaves, pulses, an electrocardiogram, etc. If the bio-signals are brainwaves, the sensor 110 may acquire at least one selected from electroencephalogram (EEG), electrooculogram (EOG), electrocardiogram (ECG), electromyogram (EMG), and electrokardiogramm (EKG) signals. The sensor 110 may obtain the bio-signals by contacting the user' body and may come in different forms such as a headset, earphones, and a bracelet…the device 100 may acquire bio-signals of a user via the sensor 110 (S201). The bio-signals may be signals that may be used to detect a user's status such as brainwaves, the amount of oxygen in cerebral blood flow, and pulses);
the at least one processor generates state information (Hwang: Abstract, [0026]-[0028], [0050]-[0055], [0060]-[0061], and FIG. 2-4: the device 100 may acquire bio-signals of a user via the sensor 110 (S201). The bio-signals may be signals that may be used to detect a user's status such as brainwaves, the amount of oxygen in cerebral blood flow, and pulses) indicating the psychological state of the evaluation target person, based on the change from the first brainwave information to the second brainwave information and from the first biological information to the second biological information (Hwang: Abstract, [0026]-[0028], [0050]-[0055], [0060]-[0061], and FIG. 2-4: The sensor 110 may acquire bio-signals from a user. The bio-signals may include brainwaves, pulses, an electrocardiogram, etc. If the bio-signals are brainwaves, the sensor 110 may acquire at least one selected from electroencephalogram (EEG), electrooculogram (EOG), electrocardiogram (ECG), electromyogram (EMG), and electrokardiogramm (EKG) signals. The sensor 110 may obtain the bio-signals by contacting the user' body and may come in different forms such as a headset, earphones, and a bracelet…the device 100 may acquire bio-signals of a user via the sensor 110 (S201). The bio-signals may be signals that may be used to detect a user's status such as brainwaves, the amount of oxygen in cerebral blood flow, and pulses);
the at least one processor determines a second reaction based on the generated state information; and the at least one processor determines the psychological state of the evaluation target person after the first reaction (Hwang: [0049]-[0050], [0057], [0067], [0075]-[0079], [0082]-[0083], [0133]-[0136], and FIG. 2-3: the device 100 may output at least one object as an audio and speech signal or vibration signal in order to apply an auditory or tactile stimulus to the user. Each object may be output as an audio and speech signal or vibration signal that can be recognized by the user. When an object corresponding to a user's desired task is output, a concentration level or excitation level derived from a brainwave signal may be increased. Thus, an ERP signal having a larger magnitude may be detected when an object corresponding to a user's desired task is output than when another object is output. The device 100 may select a user's desired task by selecting an object corresponding to a time point when the ERP signal has a relatively large magnitude compared to another magnitude).
Therefore, in view of teachings by Read, Aimone, and Hwang, it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to implement in the biological signals processing system of Read and Aimone to include the at least one processor acquires first brainwave information from at least one sensor and first biological information of the evaluation target person;
the at least one processor determines a first reaction, based on the first brainwave information and the first biological information of the evaluation target person acquired before the first reaction;
the at least one processor acquires second brainwave information and second biological information after the first reaction is determined;
the at least one processor acquires a change from the first brainwave information to the second brainwave information and from the first biological information to the second biological information from before the first reaction to after the first reaction;
the at least one processor generates state information indicating the psychological state of the evaluation target person, based on the change from the first brainwave information to the second brainwave information and from the first biological information to the second biological information;
the at least one processor determines a second reaction based on the generated state information; and
the at least one processor determines the psychological state of the evaluation target person after the first reaction, as suggested by Hwang. The motivation for this is to provide audio stimulation to a user based on conditions of the user.
As to claim 2, Read, Aimone, and Hwang disclose the limitations of claim 1 further comprising the communication device according to claim 1, wherein:
the at least one processor determines content of the simulated expressions (Aimone: [0112]-[0113], [0167], [0169]-[0170], and FIG. 10-11: The usage of the facial sensors (an example of bio-signal sensors of wearable device 1002, 1004) may allow for the mapping of a user's expression to the face of their avatar 1010, 1012 in a VR environment (e.g. to represent detected facial states with associated smiles, squints, winks, furrows, frowns, etc.). This can be augmented with brain signals from wearable device 1002, 1004 to do emotion estimation by device 1008, 1006. This estimate can further augment a characters appearance in the VR environment as an example of feedback) based on the first brainwave information and the second brainwave information (Hwang: Abstract, [0026]-[0028], [0050]-[0055], [0060]-[0061], and FIG. 2-4: The sensor 110 may acquire bio-signals from a user. The bio-signals may include brainwaves, pulses, an electrocardiogram, etc. If the bio-signals are brainwaves, the sensor 110 may acquire at least one selected from electroencephalogram (EEG), electrooculogram (EOG), electrocardiogram (ECG), electromyogram (EMG), and electrokardiogramm (EKG) signals. The sensor 110 may obtain the bio-signals by contacting the user' body and may come in different forms such as a headset, earphones, and a bracelet…the device 100 may acquire bio-signals of a user via the sensor 110 (S201). The bio-signals may be signals that may be used to detect a user's status such as brainwaves, the amount of oxygen in cerebral blood flow, and pulses); and
the at least one processor controls the communication device according to the determined content of the simulated expressions (Aimone: [0112]-[0113], [0167], [0169]-[0170], and FIG. 10-11: The usage of the facial sensors (an example of bio-signal sensors of wearable device 1002, 1004) may allow for the mapping of a user's expression to the face of their avatar 1010, 1012 in a VR environment (e.g. to represent detected facial states with associated smiles, squints, winks, furrows, frowns, etc.). This can be augmented with brain signals from wearable device 1002, 1004 to do emotion estimation by device 1008, 1006. This estimate can further augment a characters appearance in the VR environment as an example of feedback.).
As to claim 12, Read, Aimone, and Hwang disclose the limitations of claim 1 further comprising the communication device according to claim 1, wherein when the psychological state that is based on the acquired second brainwave information of the evaluation target person acquired after the first reaction is a predetermined state (Hwang: [0081]-[0084], and FIG. 2-4: The device 100 may measure brainwave signals at short time intervals of 1 to 5 seconds, and process content according to the brainwave signals, based on adjustment sensitivity set by the user or determined according to a predetermined algorithm. That is, like in 320, the device 100 may determine a user's status via measurement of brainwaves and process the music currently being reproduced to output sounds 380 and 390 (330, 340, and 350)), the at least one processor determines a predetermined reaction as the second reaction (Hwang: [0049]-[0050], [0057], [0067], [0075]-[0079], [0081]-[0084], [0133]-[0136], and FIG. 2-3: When the user learns to recognize the content processed by the device 100, he or she may unconsciously change his or her state gradually to a relaxed state 360. As the user's status changes to the relaxed state 360, the device 100 may process the music currently being reproduced to output the rich sounds 390).
As to claim 16, Read, Aimone, and Hwang disclose the limitations of claim 1 further comprising the communication device according to claim 1, wherein the at least one processor determines the first reaction (Read: [0141]-[0142], [0151]-[0152], [0156], [0161]-[0162], and FIG. 1 the audio speaker output: The audio speaker volume output can be varied in proportion to a user's individualized maximum and minimum alpha signal levels. The user's maximum and minimum mean alpha biomarker levels can be set to values of, for example, 8 dB and 3 dB, respectively, as determined in a prior data calibration session. The maximum and minimum alpha biomarker levels can indicate maximal and minimal alertness levels, respectively. The user can practice alternately increasing and decreasing the audio speaker volume on 4 separate occasions (a, b, c and d) within a 1.5 hour session. To do so, the user simply focuses their attention on their forehead to increase alpha and as their attention relaxes audible feedback indicates relaxation) based on at least one of a time at which the first reaction is determined (Aimone: [0024], [0028], [0057]-[0058], [0065]-[0066], [0169], and FIG. 10-11: The computing device 150 of the wearable device 105 is configured to create a VR environment on the stereoscopic display 110 and sound generator 140 for presentation to a user; receive bio-signal data of the user from the bio-signal sensors 120, at least one of the bio-signal sensors 120 comprising a brainwave sensor, and the received bio-signal data comprising at least brainwave data of the user; and determine brain state response elicited by the VR environment at least partly by determining a correspondence between the brainwave data and a predefined bio-signal measurement stored in a user profile, the predefined bio-signal measurement associated with predefined brain state response type) or an environment around the evaluation target person (Read: [0043], [0048], [0065], [0125]-[0126], [0140]-[0142], [0164]-[0167], and FIG. 1: the present disclosure provides a method for modulating brain states, comprising: (a) using (i) one or more sensors to detect at least one of a biological parameter of a subject and one or more biological signals of the subject and (ii) an additional sensor to detect one or more ambient conditions associated with a surrounding environment of the subject, wherein at least one of the one or more sensors is placed in contact with a portion of the subject's body; (b) processing the data obtained using the one or more sensors to compute one or more biomarkers for the subject; and (c) controlling an operation of one or more output devices, based on the one or more computed biomarkers and the data obtained using the additional sensor, to provide a stimulation to the subject to change a current state of the subject or to induce a desired state in the subject).
As to claim 17, Read, Aimone, and Hwang disclose the limitations of claim 2 further comprising the communication device according to claim 2, wherein the at least one processor determines the first reaction (Read: [0141]-[0142], [0151]-[0152], [0156], [0161]-[0162], and FIG. 1 the audio speaker output: The audio speaker volume output can be varied in proportion to a user's individualized maximum and minimum alpha signal levels. The user's maximum and minimum mean alpha biomarker levels can be set to values of, for example, 8 dB and 3 dB, respectively, as determined in a prior data calibration session. The maximum and minimum alpha biomarker levels can indicate maximal and minimal alertness levels, respectively. The user can practice alternately increasing and decreasing the audio speaker volume on 4 separate occasions (a, b, c and d) within a 1.5 hour session. To do so, the user simply focuses their attention on their forehead to increase alpha and as their attention relaxes audible feedback indicates relaxation) based on at least one of a time at which the first reaction is determined (Aimone: [0024], [0028], [0057]-[0058], [0065]-[0066], [0169], and FIG. 10-11: The computing device 150 of the wearable device 105 is configured to create a VR environment on the stereoscopic display 110 and sound generator 140 for presentation to a user; receive bio-signal data of the user from the bio-signal sensors 120, at least one of the bio-signal sensors 120 comprising a brainwave sensor, and the received bio-signal data comprising at least brainwave data of the user; and determine brain state response elicited by the VR environment at least partly by determining a correspondence between the brainwave data and a predefined bio-signal measurement stored in a user profile, the predefined bio-signal measurement associated with predefined brain state response type) or an environment around the evaluation target person (Read: [0043], [0048], [0065], [0125]-[0126], [0140]-[0142], [0164]-[0167], and FIG. 1: the present disclosure provides a method for modulating brain states, comprising: (a) using (i) one or more sensors to detect at least one of a biological parameter of a subject and one or more biological signals of the subject and (ii) an additional sensor to detect one or more ambient conditions associated with a surrounding environment of the subject, wherein at least one of the one or more sensors is placed in contact with a portion of the subject's body; (b) processing the data obtained using the one or more sensors to compute one or more biomarkers for the subject; and (c) controlling an operation of one or more output devices, based on the one or more computed biomarkers and the data obtained using the additional sensor, to provide a stimulation to the subject to change a current state of the subject or to induce a desired state in the subject).
As to claim 18, Read, Aimone, and Hwang disclose the limitations of claim 1 further comprising the communication device according to claim 1, wherein the at least one processor changes a living body which is presented to the reaction presentation unit according to the evaluation target person (Aimone: [0112]-[0113], [0167], [0169]-[0170], and FIG. 10-11: The usage of the facial sensors (an example of bio-signal sensors of wearable device 1002, 1004) may allow for the mapping of a user's expression to the face of their avatar 1010, 1012 in a VR environment (e.g. to represent detected facial states with associated smiles, squints, winks, furrows, frowns, etc.). This can be augmented with brain signals from wearable device 1002, 1004 to do emotion estimation by device 1008, 1006. This estimate can further augment a characters appearance in the VR environment as an example of feedback.).
As to claim 19, Read, Aimone, and Hwang discloses all the communication method as claimed that mirrors the communication device in claim 1; thus, claim 19 is interpreted and thus rejected for the reasons set forth above in the consideration and rejections of claim 1, and the details are as followings:
a communication method, performed by at least one processor, in which a presented reaction changes according to a psychological state of an evaluation target person, wherein the communication method comprising:
acquiring, by the at least one processor (Read: FIG. 1 the headband dual core processor), first brainwave information from at least one sensor (Read: [0115]-[0118] and FIG. 1 the inputs ) and first biological information (Hwang: Abstract, [0026]-[0028], [0050]-[0055], [0060]-[0061], and FIG. 2-4: the device 100 may acquire bio-signals of a user via the sensor 110 (S201). The bio-signals may be signals that may be used to detect a user's status such as brainwaves, the amount of oxygen in cerebral blood flow, and pulses) of the evaluation target person (Read: Abstract, [0114]-[0115], [0117], [0127], [0150]-[0152], [0155] , and FIG. 1 the inputs: The sensing module can be configured to detect, measure, record, quantify, and/or read one or more biological signals of a subject. The one or more biological signals can comprise, for example, brain waves or brain signals. The one or more biological signals can comprise an electrical signal and/or an oscillatory signal. The one or more biological signals can be represented as one or more EEG waves or waveforms (also referred to herein as brain waves or brain signals). The one or more biological signals can include an electroencephalogram (EEG) signal, an electromyogram (EMG) signal, an electrocorticogram (ECoG) signal, field potentials within a motor cortex or other regions of the brain, or combinations thereof);
determining, by the at least one processor, a first reaction (Hwang: [0049]-[0050], [0055]-[0057], [0067]-[0079], [0082]-[0083], [0133]-[0136], and FIG. 1-3: the device 100 may output at least one object as an audio and speech signal or vibration signal in order to apply an auditory or tactile stimulus to the user. Each object may be output as an audio and speech signal or vibration signal that can be recognized by the user. When an object corresponding to a user's desired task is output, a concentration level or excitation level derived from a brainwave signal may be increased. Thus, an ERP signal having a larger magnitude may be detected when an object corresponding to a user's desired task is output than when another object is output. The device 100 may select a user's desired task by selecting an object corresponding to a time point when the ERP signal has a relatively large magnitude compared to another magnitude) based on the first brainwave information and the first biological information of the evaluation target person acquired (Hwang: Abstract, [0026]-[0028], [0050]-[0055], [0060]-[0061], and FIG. 2-4: The sensor 110 may acquire bio-signals from a user. The bio-signals may include brainwaves, pulses, an electrocardiogram, etc. If the bio-signals are brainwaves, the sensor 110 may acquire at least one selected from electroencephalogram (EEG), electrooculogram (EOG), electrocardiogram (ECG), electromyogram (EMG), and electrokardiogramm (EKG) signals. The sensor 110 may obtain the bio-signals by contacting the user' body and may come in different forms such as a headset, earphones, and a bracelet…the device 100 may acquire bio-signals of a user via the sensor 110 (S201). The bio-signals may be signals that may be used to detect a user's status such as brainwaves, the amount of oxygen in cerebral blood flow, and pulses) before the first reaction (Hwang: FIG. 3);
acquiring, by the at least one processor, second brainwave information and second biological information after the first reaction is determined (Hwang: [0049]-[0050], [0055]-[0057], [0067]-[0079], [0082]-[0083], [0133]-[0136], and FIG. 1-3: the device 100 may output at least one object as an audio and speech signal or vibration signal in order to apply an auditory or tactile stimulus to the user. Each object may be output as an audio and speech signal or vibration signal that can be recognized by the user. When an object corresponding to a user's desired task is output, a concentration level or excitation level derived from a brainwave signal may be increased. Thus, an ERP signal having a larger magnitude may be detected when an object corresponding to a user's desired task is output than when another object is output. The device 100 may select a user's desired task by selecting an object corresponding to a time point when the ERP signal has a relatively large magnitude compared to another magnitude);
acquiring, by the at least one processor, a change from the first brainwave information to the second brainwave information and from the first biological information to the second biological information from before the first reaction to after the first reaction (Hwang: Abstract, [0026]-[0028], [0050]-[0055], [0060]-[0061], and FIG. 2-4: The sensor 110 may acquire bio-signals from a user. The bio-signals may include brainwaves, pulses, an electrocardiogram, etc. If the bio-signals are brainwaves, the sensor 110 may acquire at least one selected from electroencephalogram (EEG), electrooculogram (EOG), electrocardiogram (ECG), electromyogram (EMG), and electrokardiogramm (EKG) signals. The sensor 110 may obtain the bio-signals by contacting the user' body and may come in different forms such as a headset, earphones, and a bracelet…the device 100 may acquire bio-signals of a user via the sensor 110 (S201). The bio-signals may be signals that may be used to detect a user's status such as brainwaves, the amount of oxygen in cerebral blood flow, and pulses);
generating, by the at least one processor, state information indicating the psychological state of the evaluation target person (Hwang: Abstract, [0026]-[0028], [0050]-[0055], [0060]-[0061], and FIG. 2-4: the device 100 may acquire bio-signals of a user via the sensor 110 (S201). The bio-signals may be signals that may be used to detect a user's status such as brainwaves, the amount of oxygen in cerebral blood flow, and pulses), based on the change from the first brainwave information to the second brainwave information and from the first biological information to the second biological information (Hwang: Abstract, [0026]-[0028], [0050]-[0055], [0060]-[0061], and FIG. 2-4: The sensor 110 may acquire bio-signals from a user. The bio-signals may include brainwaves, pulses, an electrocardiogram, etc. If the bio-signals are brainwaves, the sensor 110 may acquire at least one selected from electroencephalogram (EEG), electrooculogram (EOG), electrocardiogram (ECG), electromyogram (EMG), and electrokardiogramm (EKG) signals. The sensor 110 may obtain the bio-signals by contacting the user' body and may come in different forms such as a headset, earphones, and a bracelet…the device 100 may acquire bio-signals of a user via the sensor 110 (S201). The bio-signals may be signals that may be used to detect a user's status such as brainwaves, the amount of oxygen in cerebral blood flow, and pulses);
determining, by the at least one processor, a second reaction based on the generated state information (Hwang: [0049]-[0050], [0057], [0067], [0075]-[0079], [0082]-[0083], [0133]-[0136], and FIG. 2-3: the device 100 may output at least one object as an audio and speech signal or vibration signal in order to apply an auditory or tactile stimulus to the user. Each object may be output as an audio and speech signal or vibration signal that can be recognized by the user. When an object corresponding to a user's desired task is output, a concentration level or excitation level derived from a brainwave signal may be increased. Thus, an ERP signal having a larger magnitude may be detected when an object corresponding to a user's desired task is output than when another object is output. The device 100 may select a user's desired task by selecting an object corresponding to a time point when the ERP signal has a relatively large magnitude compared to another magnitude);
determining, by the at least one processor, the psychological state of the evaluation target person after the first reaction (Hwang: Abstract, [0026]-[0028], [0050]-[0055], [0060]-[0061], and FIG. 2-4: The sensor 110 may acquire bio-signals from a user. The bio-signals may include brainwaves, pulses, an electrocardiogram, etc. If the bio-signals are brainwaves, the sensor 110 may acquire at least one selected from electroencephalogram (EEG), electrooculogram (EOG), electrocardiogram (ECG), electromyogram (EMG), and electrokardiogramm (EKG) signals. The sensor 110 may obtain the bio-signals by contacting the user' body and may come in different forms such as a headset, earphones, and a bracelet…the device 100 may acquire bio-signals of a user via the sensor 110 (S201). The bio-signals may be signals that may be used to detect a user's status such as brainwaves, the amount of oxygen in cerebral blood flow, and pulses) based on a change from a ratio of an amplitude of the first brainwave in a predetermined frequency band relative to a total amplitude in the first brainwave information to a ratio of an amplitude of the second brainwave information in the predetermined frequency band relative to a total amplitude in the second brainwave information (Read: [0018], [0045], [0057], [0075], [0124], [0135]-[0136], [0139], [0145]-[0148], [0152], [0157], and FIG. 1: the biomarkers can comprise one or more ratios between two brainwave oscillation frequency bands that define brain-states (e.g., a theta/alpha ratio, a beta/alpha ratio, an alpha/[slow wave+delta wave+theta wave ratio], etc.). In some cases, the biomarkers can comprise a measurement of a coherence between brainwave oscillations recorded from the same electrode and/or across a plurality of different electrodes. In other cases, the biomarkers can comprise brain-state and frequency defined EEG biomarkers (e.g., individualized sigma occurring in stage 2 sleep). In some cases, the biomarkers can comprise non-neural biomarkers from other sensor signals (e.g., heartbeat sensors, pulse oximeters, etc.)); and
controlling, by the at least one processor, the communication device to output the first reaction and the second reaction from a reaction presentation unit (Read: [0141]-[0142], [0151]-[0152], [0156], [0161]-[0162], and FIG. 1 the audio speaker output: The audio speaker volume output can be varied in proportion to a user's individualized maximum and minimum alpha signal levels. The user's maximum and minimum mean alpha biomarker levels can be set to values of, for example, 8 dB and 3 dB, respectively, as determined in a prior data calibration session. The maximum and minimum alpha biomarker levels can indicate maximal and minimal alertness levels, respectively. The user can practice alternately increasing and decreasing the audio speaker volume on 4 separate occasions (a, b, c and d) within a 1.5 hour session. To do so, the user simply focuses their attention on their forehead to increase alpha and as their attention relaxes audible feedback indicates relaxation),
wherein the first reaction and the second reaction that is output from the reaction presentation unit are simulated expressions of the evaluation target person as a virtual person that represents the psychological state of the evaluation target person so that the psychological state of the evaluation target person can be communicated using the simulated expressions (Aimone: [0167], [0170], and FIG. 10-11: The EEG readings from other members of the group affects the appearance of their avatars. e.g. if the person is relaxed, their avatars can glow blue; if they are tense, their avatars would glow red. The individual participants can look at their own avatars to determine how they are proceeding with the meditation session; their own avatars will change colour like those in the rest of the group. Emotions can also be displayed on the avatars; i.e. the words “ANGRY” or “ANXIOUS” can appear on their faces), and
wherein the simulated expressions are at least one of an utterance, an action (Aimone: [0113], [0169], and FIG. 10-11: The device measures her brainwaves and changes the characteristics of the virtual pet accordingly to provide visual feedback. For example, the pet changes colour from green to red when Danielle is upset; it changes back from red to green when she enters a relaxed state. Alternatively, the pet can change its own behaviour: irritated, relaxed, angry, etc. The pet can be used as a mindfulness/meditation aide—Danielle tries to get her pet to change colour to a certain state to match whatever mindfulness goals she is aiming towards), and/or a facial expression (Aimone: [0112], [0167], [0170], and FIG. 10-11: The usage of the facial sensors (an example of bio-signal sensors of wearable device 1002, 1004) may allow for the mapping of a user's expression to the face of their avatar 1010, 1012 in a VR environment (e.g. to represent detected facial states with associated smiles, squints, winks, furrows, frowns, etc.). This can be augmented with brain signals from wearable device 1002, 1004 to do emotion estimation by device 1008, 1006. This estimate can further augment a characters appearance in the VR environment as an example of feedback.).
As to claim 20, Read, Aimone, and Hwang discloses all the non-transitory computer-readable medium having recorded thereon a communication program that, when executed by a computer, causes the computer to perform operations as claimed that mirrors the communication device in claim 1; thus, claim 20 is interpreted and thus rejected for the reasons set forth above in the consideration and rejections of claim 1, and the details are as followings:
a non-transitory computer-readable medium having recorded thereon a communication program that, when executed by a computer, causes the computer to perform operations comprising:
acquiring first brainwave information from at least one sensor (Read: [0115]-[0118] and FIG. 1 the inputs ) and first biological information (Hwang: Abstract, [0026]-[0028], [0050]-[0055], [0060]-[0061], and FIG. 2-4: the device 100 may acquire bio-signals of a user via the sensor 110 (S201). The bio-signals may be signals that may be used to detect a user's status such as brainwaves, the amount of oxygen in cerebral blood flow, and pulses) of the evaluation target person (Read: Abstract, [0114]-[0115], [0117], [0127], [0150]-[0152], [0155] , and FIG. 1 the inputs: The sensing module can be configured to detect, measure, record, quantify, and/or read one or more biological signals of a subject. The one or more biological signals can comprise, for example, brain waves or brain signals. The one or more biological signals can comprise an electrical signal and/or an oscillatory signal. The one or more biological signals can be represented as one or more EEG waves or waveforms (also referred to herein as brain waves or brain signals). The one or more biological signals can include an electroencephalogram (EEG) signal, an electromyogram (EMG) signal, an electrocorticogram (ECoG) signal, field potentials within a motor cortex or other regions of the brain, or combinations thereof);
determining a first reaction (Hwang: [0049]-[0050], [0055]-[0057], [0067]-[0079], [0082]-[0083], [0133]-[0136], and FIG. 1-3: the device 100 may output at least one object as an audio and speech signal or vibration signal in order to apply an auditory or tactile stimulus to the user. Each object may be output as an audio and speech signal or vibration signal that can be recognized by the user. When an object corresponding to a user's desired task is output, a concentration level or excitation level derived from a brainwave signal may be increased. Thus, an ERP signal having a larger magnitude may be detected when an object corresponding to a user's desired task is output than when another object is output. The device 100 may select a user's desired task by selecting an object corresponding to a time point when the ERP signal has a relatively large magnitude compared to another magnitude) based on the first brainwave information and the first biological information of the evaluation target person acquired (Hwang: Abstract, [0026]-[0028], [0050]-[0055], [0060]-[0061], and FIG. 2-4: The sensor 110 may acquire bio-signals from a user. The bio-signals may include brainwaves, pulses, an electrocardiogram, etc. If the bio-signals are brainwaves, the sensor 110 may acquire at least one selected from electroencephalogram (EEG), electrooculogram (EOG), electrocardiogram (ECG), electromyogram (EMG), and electrokardiogramm (EKG) signals. The sensor 110 may obtain the bio-signals by contacting the user' body and may come in different forms such as a headset, earphones, and a bracelet…the device 100 may acquire bio-signals of a user via the sensor 110 (S201). The bio-signals may be signals that may be used to detect a user's status such as brainwaves, the amount of oxygen in cerebral blood flow, and pulses) before the first reaction (Hwang: FIG. 3);
acquiring second brainwave information and second biological information after the first reaction is determined (Hwang: [0049]-[0050], [0055]-[0057], [0067]-[0079], [0082]-[0083], [0133]-[0136], and FIG. 1-3: the device 100 may output at least one object as an audio and speech signal or vibration signal in order to apply an auditory or tactile stimulus to the user. Each object may be output as an audio and speech signal or vibration signal that can be recognized by the user. When an object corresponding to a user's desired task is output, a concentration level or excitation level derived from a brainwave signal may be increased. Thus, an ERP signal having a larger magnitude may be detected when an object corresponding to a user's desired task is output than when another object is output. The device 100 may select a user's desired task by selecting an object corresponding to a time point when the ERP signal has a relatively large magnitude compared to another magnitude);
acquiring a change from the first brainwave information to the second brainwave information and from the first biological information to the second biological information from before the first reaction to after the first reaction (Hwang: Abstract, [0026]-[0028], [0050]-[0055], [0060]-[0061], and FIG. 2-4: The sensor 110 may acquire bio-signals from a user. The bio-signals may include brainwaves, pulses, an electrocardiogram, etc. If the bio-signals are brainwaves, the sensor 110 may acquire at least one selected from electroencephalogram (EEG), electrooculogram (EOG), electrocardiogram (ECG), electromyogram (EMG), and electrokardiogramm (EKG) signals. The sensor 110 may obtain the bio-signals by contacting the user' body and may come in different forms such as a headset, earphones, and a bracelet…the device 100 may acquire bio-signals of a user via the sensor 110 (S201). The bio-signals may be signals that may be used to detect a user's status such as brainwaves, the amount of oxygen in cerebral blood flow, and pulses);
generating state information indicating a psychological state of the evaluation target person (Hwang: Abstract, [0026]-[0028], [0050]-[0055], [0060]-[0061], and FIG. 2-4: the device 100 may acquire bio-signals of a user via the sensor 110 (S201). The bio-signals may be signals that may be used to detect a user's status such as brainwaves, the amount of oxygen in cerebral blood flow, and pulses), based on the change from the first brainwave information to the second brainwave information and from the first biological information to the second biological information (Hwang: Abstract, [0026]-[0028], [0050]-[0055], [0060]-[0061], and FIG. 2-4: The sensor 110 may acquire bio-signals from a user. The bio-signals may include brainwaves, pulses, an electrocardiogram, etc. If the bio-signals are brainwaves, the sensor 110 may acquire at least one selected from electroencephalogram (EEG), electrooculogram (EOG), electrocardiogram (ECG), electromyogram (EMG), and electrokardiogramm (EKG) signals. The sensor 110 may obtain the bio-signals by contacting the user' body and may come in different forms such as a headset, earphones, and a bracelet…the device 100 may acquire bio-signals of a user via the sensor 110 (S201). The bio-signals may be signals that may be used to detect a user's status such as brainwaves, the amount of oxygen in cerebral blood flow, and pulses);
determining a second reaction based on the generated state information (Hwang: [0049]-[0050], [0057], [0067], [0075]-[0079], [0082]-[0083], [0133]-[0136], and FIG. 2-3: the device 100 may output at least one object as an audio and speech signal or vibration signal in order to apply an auditory or tactile stimulus to the user. Each object may be output as an audio and speech signal or vibration signal that can be recognized by the user. When an object corresponding to a user's desired task is output, a concentration level or excitation level derived from a brainwave signal may be increased. Thus, an ERP signal having a larger magnitude may be detected when an object corresponding to a user's desired task is output than when another object is output. The device 100 may select a user's desired task by selecting an object corresponding to a time point when the ERP signal has a relatively large magnitude compared to another magnitude);
determining the psychological state of the evaluation target person after the first reaction (Hwang: Abstract, [0026]-[0028], [0050]-[0055], [0060]-[0061], and FIG. 2-4: The sensor 110 may acquire bio-signals from a user. The bio-signals may include brainwaves, pulses, an electrocardiogram, etc. If the bio-signals are brainwaves, the sensor 110 may acquire at least one selected from electroencephalogram (EEG), electrooculogram (EOG), electrocardiogram (ECG), electromyogram (EMG), and electrokardiogramm (EKG) signals. The sensor 110 may obtain the bio-signals by contacting the user' body and may come in different forms such as a headset, earphones, and a bracelet…the device 100 may acquire bio-signals of a user via the sensor 110 (S201). The bio-signals may be signals that may be used to detect a user's status such as brainwaves, the amount of oxygen in cerebral blood flow, and pulses) based on a change from a ratio of an amplitude of the first brainwave in a predetermined frequency band relative to a total amplitude in the first brainwave information to a ratio of an amplitude of the second brainwave information in the predetermined frequency band relative to a total amplitude in the second brainwave information (Read: [0018], [0045], [0057], [0075], [0124], [0135]-[0136], [0139], [0145]-[0148], [0152], [0157], and FIG. 1: the biomarkers can comprise one or more ratios between two brainwave oscillation frequency bands that define brain-states (e.g., a theta/alpha ratio, a beta/alpha ratio, an alpha/[slow wave+delta wave+theta wave ratio], etc.). In some cases, the biomarkers can comprise a measurement of a coherence between brainwave oscillations recorded from the same electrode and/or across a plurality of different electrodes. In other cases, the biomarkers can comprise brain-state and frequency defined EEG biomarkers (e.g., individualized sigma occurring in stage 2 sleep). In some cases, the biomarkers can comprise non-neural biomarkers from other sensor signals (e.g., heartbeat sensors, pulse oximeters, etc.)); and
controlling the communication device to output the first reaction and the second reaction from a reaction presentation unit (Read: [0141]-[0142], [0151]-[0152], [0156], [0161]-[0162], and FIG. 1 the audio speaker output: The audio speaker volume output can be varied in proportion to a user's individualized maximum and minimum alpha signal levels. The user's maximum and minimum mean alpha biomarker levels can be set to values of, for example, 8 dB and 3 dB, respectively, as determined in a prior data calibration session. The maximum and minimum alpha biomarker levels can indicate maximal and minimal alertness levels, respectively. The user can practice alternately increasing and decreasing the audio speaker volume on 4 separate occasions (a, b, c and d) within a 1.5 hour session. To do so, the user simply focuses their attention on their forehead to increase alpha and as their attention relaxes audible feedback indicates relaxation),
wherein the first reaction and the second reaction that is output from the reaction presentation unit are simulated expressions of the evaluation target person as a virtual person that represents the psychological state of the evaluation target person so that the psychological state of the evaluation target person can be communicated using the simulated expressions (Aimone: [0167], [0170], and FIG. 10-11: The EEG readings from other members of the group affects the appearance of their avatars. e.g. if the person is relaxed, their avatars can glow blue; if they are tense, their avatars would glow red. The individual participants can look at their own avatars to determine how they are proceeding with the meditation session; their own avatars will change colour like those in the rest of the group. Emotions can also be displayed on the avatars; i.e. the words “ANGRY” or “ANXIOUS” can appear on their faces), and
wherein the simulated expressions are at least one of an utterance, an action (Aimone: [0113], [0169], and FIG. 10-11: The device measures her brainwaves and changes the characteristics of the virtual pet accordingly to provide visual feedback. For example, the pet changes colour from green to red when Danielle is upset; it changes back from red to green when she enters a relaxed state. Alternatively, the pet can change its own behaviour: irritated, relaxed, angry, etc. The pet can be used as a mindfulness/meditation aide—Danielle tries to get her pet to change colour to a certain state to match whatever mindfulness goals she is aiming towards), and/or a facial expression (Aimone: [0112], [0167], [0170], and FIG. 10-11: The usage of the facial sensors (an example of bio-signal sensors of wearable device 1002, 1004) may allow for the mapping of a user's expression to the face of their avatar 1010, 1012 in a VR environment (e.g. to represent detected facial states with associated smiles, squints, winks, furrows, frowns, etc.). This can be augmented with brain signals from wearable device 1002, 1004 to do emotion estimation by device 1008, 1006. This estimate can further augment a characters appearance in the VR environment as an example of feedback.).
Claims 13-15 are rejected under 35 U.S.C. 103 as being unpatentable over Read et al. (Read – US 2022/0225920 A1) in view of Aimone et al. (Aimone – US 2016/0077547 A1) and Hwang et al. (Hwang – US 2016/0210407 A1) and further in view of Kwalwasser et al. (Kwalwasser – US 2023/0218221 A1).
As to claim 13, Read, Aimone, and Hwang disclose the limitations of claim 1 further comprising the communication device according to claim 1, wherein the at least one processor generates a state, that infers the psychological state of the evaluation target person after the first reaction, by performing machine learning on a relationship between the first reaction and the change from the first brainwave information to the second brainwave information (Read: [0048], [0063], [0065]-[0066], [0081]-[0083], [0091], [0113], [0124]-[0126], [0161]-[0164], and FIG. 1: if a subject has difficulty falling asleep or experienced restless sleep, and the ambient sensors detect that there was ambient noise and ambient light above a certain threshold, or that the room temperature was too hot or cold, the ambient sensor data obtained using the ambient sensors can provide feedback to the subject or the processing module (described in greater detail below). In some cases, the feedback may comprise a notification to the subject to let the subject know that he or she was restless last night, and that such restlessness may be due to too much ambient light or too much noise in the room at a certain time. In some cases, the feedback may further comprise one or more suggestions to the subject (e.g., a suggestion for the subject to try using an eye mask), Aimone: [0112]-[0113], [0167], [0169]-[0170], and FIG. 10-11: The usage of the facial sensors (an example of bio-signal sensors of wearable device 1002, 1004) may allow for the mapping of a user's expression to the face of their avatar 1010, 1012 in a VR environment (e.g. to represent detected facial states with associated smiles, squints, winks, furrows, frowns, etc.). This can be augmented with brain signals from wearable device 1002, 1004 to do emotion estimation by device 1008, 1006. This estimate can further augment a characters appearance in the VR environment as an example of feedback, and Hwang: Abstract, [0026]-[0028], [0050]-[0055], [0060]-[0061], and FIG. 2-4: The sensor 110 may acquire bio-signals from a user. The bio-signals may include brainwaves, pulses, an electrocardiogram, etc. If the bio-signals are brainwaves, the sensor 110 may acquire at least one selected from electroencephalogram (EEG), electrooculogram (EOG), electrocardiogram (ECG), electromyogram (EMG), and electrokardiogramm (EKG) signals. The sensor 110 may obtain the bio-signals by contacting the user' body and may come in different forms such as a headset, earphones, and a bracelet…the device 100 may acquire bio-signals of a user via the sensor 110 (S201). The bio-signals may be signals that may be used to detect a user's status such as brainwaves, the amount of oxygen in cerebral blood flow, and pulses), based on the first brainwave information before the first reaction (Hwang: [0049]-[0050], [0057], [0067], [0075]-[0079], [0082]-[0083], [0133]-[0136], and FIG. 2-3: the device 100 may output at least one object as an audio and speech signal or vibration signal in order to apply an auditory or tactile stimulus to the user. Each object may be output as an audio and speech signal or vibration signal that can be recognized by the user. When an object corresponding to a user's desired task is output, a concentration level or excitation level derived from a brainwave signal may be increased. Thus, an ERP signal having a larger magnitude may be detected when an object corresponding to a user's desired task is output than when another object is output. The device 100 may select a user's desired task by selecting an object corresponding to a time point when the ERP signal has a relatively large magnitude compared to another magnitude).
The combination of Read, Aimone, and Hwang does not explicitly disclose a state learning unit which generates a state inference model that infers the state of the evaluation target person after the first reaction, by performing machine learning on a relationship between the first reaction and the change in the brainwave information.
However, it has been known in the art of monitoring conditions of a user to implement a state learning unit which generates a state inference model that infers the state of the evaluation target person after the first reaction, by performing machine learning on a relationship between the first reaction and the change in the brainwave information, as suggested by Kwalwasser, which discloses a state learning unit which generates a state inference model that infers the state of the evaluation target person after the first reaction, by performing machine learning on a relationship between the first reaction and the change in the brainwave information (Kwalwasser: Abstract, [0021]-[0022], [0025], [0028], [0030]-[0033], [0046]-[0049], and FIG. 1-3: The brain state model generator 160 trains one or more brain state models based on the extracted features from the brain activity signal and the user survey responses. In one embodiment, the brain state models are random forest regression models. In other embodiments, the brain state models utilize different machine learning techniques, e.g., neural networks, multinomial regressors, other decision trees, etc. The trained brain state models are configured to predict a value for the brain state (or the brain state value over time) based on an input brain activity signal. The brain state models may be stored in the data store 180. For a given user, the server 150 may select a brain state model that best fits the user's survey responses and brain activity data. The best fit model provides the closest prediction of the user's brain state value based on the brain activity data. The selected brain state model may be stored in a user profile for that user, such that the server 150 may provide tailored content to each user).
Therefore, in view of teachings by Read, Aimone, Hwang, and Kwalwasser it would have been obvious to one of the ordinary skill in the art before the effective filing date of the claimed invention to implement in the biological signals processing system of Read, Aimone, and Hwang to include a state learning unit which generates a state inference model that infers the state of the evaluation target person after the first reaction, by performing machine learning on a relationship between the first reaction and the change in the brainwave information, as suggested by Kwalwasser. The motivation for this is to provide stimulations to a user based on conditions of the user.
As to claim 14, Read, Aimone, Hwang, and Kwalwasser disclose the limitations of claim 13 further comprising the communication device according to claim 13, wherein
the at least one processor determines the second reaction based on the second brainwave information acquired after the first reaction (Hwang: [0081]-[0084], and FIG. 2-4: The device 100 may measure brainwave signals at short time intervals of 1 to 5 seconds, and process content according to the brainwave signals, based on adjustment sensitivity set by the user or determined according to a predetermined algorithm. That is, like in 320, the device 100 may determine a user's status via measurement of brainwaves and process the music currently being reproduced to output sounds 380 and 390 (330, 340, and 350)) and based on the psychological state of the evaluation target person inferred by the state inference model (Hwang: [0049]-[0050], [0057], [0067], [0075]-[0079], [0082]-[0083], [0133]-[0136], and FIG. 2-3: the device 100 may output at least one object as an audio and speech signal or vibration signal in order to apply an auditory or tactile stimulus to the user. Each object may be output as an audio and speech signal or vibration signal that can be recognized by the user. When an object corresponding to a user's desired task is output, a concentration level or excitation level derived from a brainwave signal may be increased. Thus, an ERP signal having a larger magnitude may be detected when an object corresponding to a user's desired task is output than when another object is output. The device 100 may select a user's desired task by selecting an object corresponding to a time point when the ERP signal has a relatively large magnitude compared to another magnitude).
As to claim 15, Read, Aimone, Hwang, and Kwalwasser disclose the limitations of claim 13 further comprising the communication device according to claim 13, wherein when a difference between the psychological state of the evaluation target person based on the second brainwave information after the first reaction (Hwang: Abstract, [0026]-[0028], [0050]-[0055], [0060]-[0061], and FIG. 2-4: the device 100 may acquire bio-signals of a user via the sensor 110 (S201). The bio-signals may be signals that may be used to detect a user's status such as brainwaves, the amount of oxygen in cerebral blood flow, and pulses) and the psychological state of the evaluation target person inferred by the state inference model (Kwalwasser: Abstract, [0021]-[0022], [0025], [0028], [0030]-[0033], [0046]-[0049], and FIG. 1-3: The brain state model generator 160 trains one or more brain state models based on the extracted features from the brain activity signal and the user survey responses. In one embodiment, the brain state models are random forest regression models. In other embodiments, the brain state models utilize different machine learning techniques, e.g., neural networks, multinomial regressors, other decision trees, etc. The trained brain state models are configured to predict a value for the brain state (or the brain state value over time) based on an input brain activity signal. The brain state models may be stored in the data store 180. For a given user, the server 150 may select a brain state model that best fits the user's survey responses and brain activity data. The best fit model provides the closest prediction of the user's brain state value based on the brain activity data. The selected brain state model may be stored in a user profile for that user, such that the server 150 may provide tailored content to each user) exceeds a predetermined threshold value (Read: [0124], [0139], [0145]-[0148], [0152], [0157], and FIG. 1: In some alternative embodiments, similar processes can be performed in parallel on separate spectral bands in order to generate an instantaneous biomarker such as a theta/alpha oscillatory frequency ratio. When the theta/alpha oscillatory frequency ratio crosses an arbitrary, predetermined threshold or a user defined decision variable (DV) level, the processing module can be configured to recognize this event as a trigger or a switch to modulate an audio speaker output or to turn the audio speaker output on or off), the at least one processor determines a predetermined reaction as the second reaction (Hwang: [0049]-[0050], [0057], [0067], [0075]-[0079], [0082]-[0083], [0133]-[0136], and FIG. 2-3: the device 100 may output at least one object as an audio and speech signal or vibration signal in order to apply an auditory or tactile stimulus to the user. Each object may be output as an audio and speech signal or vibration signal that can be recognized by the user. When an object corresponding to a user's desired task is output, a concentration level or excitation level derived from a brainwave signal may be increased. Thus, an ERP signal having a larger magnitude may be detected when an object corresponding to a user's desired task is output than when another object is output. The device 100 may select a user's desired task by selecting an object corresponding to a time point when the ERP signal has a relatively large magnitude compared to another magnitude).
Allowable Subject Matter
Claims 7-11 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all the limitations of the base claim and any intervening claims.
The following is a statement of reasons for the indication of allowable subject matter:
The prior art does not teach the combination of the limitations including wherein the at least one processor generates the state information based on a ratio of a magnitude of a first power spectrum to a magnitude of a second power spectrum in a heart rate of the evaluation target person; the total amplitude is a sum of amplitudes of an alpha wave, a beta wave, a theta wave, a gamma wave, and a delta wave; and a frequency band of the second power spectrum is a band in which a frequency is higher than that in a frequency band of the first power spectrum, as presented in claim 7. Although many of the limitations of the claims can be individually found in the prior art, there is no reasonable combination of references sufficient to teach the invention as claimed in claim 7.
Citation of Pertinent Art
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure:
Mizumoto et al., US 2023/0346275 A1, discloses sensibility measuring method and sensibility measuring system.
Park et al., US 10,667,714 B2, discloses method and system for detecting information of brain-heart connectivity by using pupillary variation.
Whang et al., US 2018/0279935 A1, discloses method and system for detecting frequency domain cardiac information by using pupillary response.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP §706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to QUANG PHAM whose telephone number is (571)-270-3668. The examiner can normally be reached 09:00 AM - 05:00 PM.
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/QUANG PHAM/Primary Examiner, Art Unit 2685
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