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 Objections
Claim 44 are objected to because of the following informalities:
Claim 44 line 3 should be “the first time interval” because it refers back to claim 41.
Claim 44 line 4 should be “the preliminary time interval” because it refers back to claim 41.
Many languages in claim 44 have same issue.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1 – 8, 10, 12, 14, 15, 17, 18, 20, 21, 23, 24, 25, 41, 44, 47 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 41 recites “a first time interval”.
Claim 41 recites “a preliminary time interval”.
Claim 41 recites “a subsequent time interval”.
Claim 41 is unclear “a first time interval” is same or different or overlapping “time interval” compare with “a preliminary time interval”, “a subsequent time interval”.
Does “a first time interval” included/overlapping in “a preliminary time interval” or “a subsequent time interval”?
Therefore, claim language is indefinite.
Claim 41 recites “analyzing the first set of brain signal data by calculating an amount of overlap of the at least two individual brain signals with respect to time during the first time interval; and
producing a first dynamic threshold to be a value corresponding to a percentile of the amount of overlap when a baseline threshold was satisfied by the first set of brain signal data of the first time interval, or
maintaining the baseline threshold for a subsequent time interval when the baseline threshold was not satisfied by the first set of brain signal data”.
One of claim interpretation of claim limitation can be “analyzing the first set of brain signal data by calculating an amount of overlap of the at least two individual brain signals with respect to time during the first time interval; and
producing a first dynamic threshold to be a value corresponding to a percentile of the amount of overlap when a baseline threshold was satisfied by the first set of brain signal data of the first time interval,”
Another claim interpretation of claim limitations can be “analyzing the first set of brain signal data by calculating an amount of overlap of the at least two individual brain signals with respect to time during the first time interval; and
maintaining the baseline threshold for a subsequent time interval when the baseline threshold was not satisfied by the first set of brain signal data”.
Claim 41 recites the limitation "the baseline threshold" in line 20. There is insufficient antecedent basis for this limitation in the claim.
Claim 44 recites the limitation "the first threshold" in line 10. There is insufficient antecedent basis for this limitation in the claim.
Claims 2 – 8, 10, 12, 14, 15, 17, 18, 20, 21, 23, 24, 25, 44, 47 have same issue because of claim dependency.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1 – 5, 7, 10, 12, 14 are rejected under 35 U.S.C. 103 as being unpatentable over Poltorak et al. (U.S. Patent Publication 20210041953 A1) in view of Brunner et al. (U.S. Patent Publication 20240074687 A1).
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Regarding claim 1, Poltorak discloses “A method for providing neurofeedback, comprising:
presenting, at a display device, stimuli to a subject to invoke generation of neurological signal stimulation in a brain of a subject; ([0278] Brain entrainment Brain entrainment, also referred to as brainwave synchronization and neural entrainment, refers to the capacity of the brain to naturally synchronize its brainwave frequencies with the rhythm of periodic external stimuli, most commonly auditory, visual, or tactile. Brainwave entrainment technologies are used to induce various brain states, such as relaxation or sleep, by creating stimuli that occur at regular, periodic intervals to mimic electrical cycles of the brain during the desired states, thereby “paining” the brain to consciously alter states. Recurrent acoustic frequencies, flickering lights, or tactile vibrations are the most common examples of stimuli applied to generate different sensory responses. It is hypothesized that listening to these beats of certain frequencies one can induce a desired state of consciousness that corresponds with specific neural activity. Patterns of neural firing, measured in Hz, correspond with alertness states such as focused attention, deep sleep, etc. [0281] Brainwaves, or neural oscillations, share the fundamental constituents with acoustic and optical waves, including frequency, amplitude and periodicity. The synchronous electrical activity of cortical neural ensembles can synchronize in response to external acoustic or optical stimuli and also entrain or synchronize their frequency and phase to that of a specific stimulus. Brainwave entrainment is a colloquialism for such ‘neural entrainment’, which is a term used to denote the way in which the aggregate frequency of oscillations produced by the synchronous electrical activity in ensembles of cortical neurons can adjust to synchronize with the periodic vibration of an external stimuli, such as a sustained acoustic frequency perceived as pitch, a regularly repeating pattern of intermittent sounds, perceived as rhythm, or of a regularly rhythmically intermittent flashing light. [0280] [0134])
measuring, at a brain signal detection device, ([0134] ach person was hooked up to electrodes that tease out and display specific brainwaves, along with a monitor that measured their heartbeat By controlling their breathing and learning to deliberately manipulate the waveforms on the screen in front of them, the novices managed to produce the alpha waves characteristic of the flow state. This, in turn, helped them improve their accuracy at hitting the targets.) a plurality of sets of brain signal data that include at least two individual brain signals from the subject's brain acquired during a neurofeedback session having a plurality of neurofeedback periods without acquiring ([0059] [0130] [0748]) the at least two individual brain signals during one or more break periods arranged between adjacent neurofeedback periods, ([0020] Brainwaves have been widely studied in neural activity generated by large groups of neurons, mostly by EEG. In general, EEG signals reveal oscillatory activity (groups of neurons periodically firing in synchrony), in specific frequency bands: alpha (7.5-12.5 Hz) that can be detected from the occipital lobe during relaxed wakefulness and which increases when the eyes are closed; delta (1-4 Hz), theta (4-8 Hz), beta (13-30 Hz), low gamma (30-70 Hz), and high gamma (70-150 Hz) frequency bands, where faster rhythms such as gamma activity have been linked to cognitive processing. Higher frequencies imply multiple groups of neurons firing in coordination, either in parallel or in series, or both, since individual neurons do not fire at rates of 100 Hz. Neural oscillations of specific characteristics have been linked to cognitive states, such as awareness and consciousness and different sleep stages. [0134] [0023] [0059] [0130] [0748] [0749]) wherein each of the at least two individual brain signals correspond to at least two locations on the subject's brain including a first location on the subject's left-side frontal lobe and a second location on the subject's right-side frontal lobe; ([0013] Emotions are thought to be associated with different parts of the brain: Frontal Lobe (movement of the body; personality; concentration, planning, problem solving; meaning of words; emotional reactions; speech; smell); Parietal Lobe (touch and pressure; taste; body awareness); Temporal Lobe (hearing; recognizing faces; emotion; long-term memory); Occipital Lobe (sight); Cerebellum (Latin for little brain, fine motor (muscle) control; balance and coordination (avoid objects and keep from falling)); Limbic Lobe (controls emotions like happiness, sadness, and love). [0020] [0021]) and
analyzing, at a data processing device in real time during the neurofeedback session, ([0024] EG signals may be captured and analyzed by a mobile device, often referred as “brain wearables”. [0130] To assess a users state of mind, a computer may be used to analyze the EEG signals produced by the brain of the user. [0411] Artificial neural networks have been employed to analyze EEG signals.) the brain signal data to determine a coherence value for a neurofeedback period of the plurality of neurofeedback periods based on a dynamic threshold, ([0031] Detecting different emotional states by EEG may be more appropriate using EEG-based functional connectivity. There are various ways to estimate EEG-based functional brain connectivity: correlation, coherence and phase synchronization indices between each pair of EEG electrodes had been used. The assumption is that a higher correlation map indicates a stronger relationship between two signals. (Brazier M A, Casby J U (1952) Cross-correlation and autocorrelation studies of electroencephalographic potentials. Electroen din neuro 4: 201-211). Coherence gives information similar to correlation, but also includes the covariation between two signals as a function of frequency. (Cantero J L, Atienza M, Salas R M, Gomez C M (1999) Alpha EEG coherence in different brain states: an electrophysiological index of the arousal level in human subjects. Neurosci lett 271: 167-70.) The assumption is that higher coherence indicates a stronger relationship between two signals. (Guevara M A, Corsi-Cabrera M (1996) EEG coherence or EEG correlation? Int J Psychophysiology 23: 145-153; Cantero J L, Atienza M, Salas R M, Gomez C M (1999) Alpha EEG coherence in different brain states: an electrophysiological index of the arousal level in human subjects. Neurosci lett 271: 167-70; Adler G, Brassen S, Jajcevic A (2003) EEG coherence in Alzheimer's dementia. J Neural Transm 110: 1051-1058; Deeny S P, Hillman C H, Janelle C M, Hatfield B D (2003) Cortico-cortical communication and superior performance in skilled marksmen: An EEG coherence analysis. J Sport Exercise Psy 25: 188-204.) Phase synchronization among the neuronal groups estimated based on the phase difference between two signals is another way to estimate the EEG-based functional connectivity among brain areas. It is. (Franaszczuk P J, Bergey G K (1999) An autoregressive method for the measurement of synchronization of interictal and ictal EEG signals. Biol Cybem 81: 3-9.))
Poltorak does not disclose “wherein the dynamic threshold is determined based at least in part on the coherence value from a prior neurofeedback period”.
Brunner discloses “wherein the dynamic threshold is determined based at least in part on the coherence value from a prior neurofeedback period”. (Figs 16, 17, 18, 19, [0060] As illustrated in FIG. 18 , the disclosed oscillation method includes transforming each raw time series of EM measurements into the time-frequency space to produce a time-frequency map 1 (see also FIG. 7A). In the time-frequency space, the 1/f pink noise is removed from the EM data to produce a flattened time-frequency map, shown also in FIG. 7B. This 1/f noise approach provides thresholds throughout the time-frequency space to identify potential detect periodic signals for each frequency point. [0061] [0069] [0071] . Claim does not define what is “dynamic threshold”. Threshold can be zero)
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to incorporate threshold by Brunner into device of Poltorak. The suggestion/motivation would have been to improve efficiency. (Brunner: [0060])
Regarding claim 2, Poltorak and Brunner disclose wherein the presenting, the measuring, and the analyzing provide a brain-computer interface (BCI) to promote brain signal coherence comprising a bilateral coordination of frequency power in the at least two individual brain signals with respect to a left hemisphere and a right hemisphere of the subject's brain. (Brunner [0010] brain-computer interface (BCI))
Regarding claim 3, Poltorak and Brunner disclose wherein the dynamic threshold is determined by adjusting a previous threshold value based on a ratio of coordination between frequency power in the at least two individual brain signals sampled in a corresponding previous neurofeedback period. (Brunner [0009], [0059] – [0062])
Regarding claim 4, Poltorak and Brunner disclose wherein the dynamic threshold is determined by calculating an amount of overlap of the at least two individual brain signals in the neurofeedback period with respect to time and producing a threshold value corresponding to a percentile of the amount of overlap. (Brunner [0009], [0059] – [0062])
Regarding claim 5, Poltorak and Brunner disclose wherein the calculating the amount of overlap includes determining a percentage of times the at least two individual brain signals peak together and the at least two individual brain signals trough together at each sampling time over the neurofeedback period and comparing the determined percentage to the percentile. (Brunner [0009], [0059] – [0062])
Regarding claim 7, Poltorak and Brunner disclose further comprising:
determining an optimal work-to-rest ratio based at least in part on the dynamic threshold. (Brunner Fig. 14, [0065])
Regarding claim 10, Poltorak and Brunner disclose wherein the at least two individual brain signals includes electroencephalogram (EEG) signals, and wherein a first EEG electrode is positioned at a right frontal lobe placement and a second EEG electrode is positioned at a left frontal lobe placement. (Poltorak [0013] [0020] [0021])
Regarding claim 12, Poltorak and Brunner disclose wherein the analyzing the brain signal data includes examining frequency power of the at least two individual brain signals acquired in a frequency range between 3 Hz and 90 Hz. (Brunner [0064])
Regarding claim 14, Poltorak and Brunner disclose wherein the stimuli presented to the subject includes at least one of visual stimuli, auditory stimuli, or tactile stimuli. (Poltorak [0024] [1071])
Allowable Subject Matter
Claim 41 would be allowable if rewritten or amended to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, set forth in this Office action.
Claims 44, 47 would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, set forth in this Office action and to include all of the limitations of the base claim and any intervening claims.
Claims 6, 8, 15, 17, 18, 20, 21, 23, 24, 25 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 20240261572 discloses BCI device on [0018]
US 20180021579 A1 discloses brain signal on [0011]
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/CHUN-NAN LIN/Primary Examiner, Art Unit 2629