DETAILED ACTION
This Office Action is responsive to the Amendment filed 09 December 2025. Claims 1 - 13 are now pending. The Examiner acknowledges the amendments to claims 1 – 3, 5 – 6, 8 – 11 and 13.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 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 7 - 8 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 7, the limitations “buffering stage”, “feed forward differential pre-amplification stage” and “adaptive amplification stage” are unclear as it raises the question if “stage” refers to a step/method/the way it operates or a physical component of the circuit.
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.
Claims 1 – 6 and 9 - 13 are rejected under 35 U.S.C. 103 as being unpatentable over Nguyen et al (2016, hereinafter Nguyen, NPL: U) in view of Bleichner et al (2017, hereinafter Bleichner, NPL: V).
Regarding claim 1, Nguyen teaches a system (abstract, “a biosignal recording system”, page 24, left column, paragraph 2) comprising:
a wearable device (abstract, “a biosignal recording system”, page 24, left column, paragraph 2) comprising:
an ear piece configured to be worn (abstract, “a biosignal recording system”, page 24, left column, paragraph 2) an ear of a patient;
one or more sensors coupled to the ear piece and configured to be in contact with the skin of the patient (page 21, left column, paragraphs 4 – 6; Figure 2) the ear of the patient;
a first processors (“microcontroller”, Figure 2) coupled to the one or more sensors (page 21, left column, paragraphs 4 – 6, Figure 2); and
a first computer readable medium (Figure 1, page 20; Examiner interprets there is a first medium in communication with the first processor/”microcontroller”.) in communication with the first processor (Figures 1 and 2), the first computer readable medium (Figure 1, page 20) having encoded thereon a first set of instructions executable by the first processor (“microcontroller”, Figure 2) to:
obtain, via the one or more sensors (page 21, left column, paragraphs 4 – 6; Figure 2), a first signal, wherein the first signal comprises one or more combined biosignals; and
transmit the first signal (Figure 2);
a host machine (“opensource brain-computer interface (OpenBCI) board”, page 22, right column, paragraph 2, and an associated computer; Examiner interprets an associated computer is coupled to the “opensource brain-computer interface (OpenBCI) board”.) coupled to the wearable device, the host machine further comprising:
a second processor (“Gold Standard Device”, page 20, left column, paragraph 1, Figure 1; page 20, right column, paragraph 5); and
a second computer readable medium (Figure 1, page 20; Examiner interprets there is a second medium in communication with the second processor/”Gold Standard Device”.) in communication with the second processor (Figure 2), the second computer readable medium (Figure 1, page 20) having encoded thereon a second set of instructions executable by the second processor (Figure 1, page 20) to:
obtain, via the wearable device, the first signal (“acquires the biosignal that is then preprocessed”, page 20, right column, paragraph 5, Figure 1);
separate the first signal into one or more individual biosignals (“(2) Signal separation - The preprocessed signal is next separated into EEG, EOG, and EMG through an adaptive separation method supervised by a spectral template matrix generated using a gold-standard device”, page 20, right column, paragraph 5, Figure 1);
identify, via a machine learning model (“a trained sleep staging model”, page 20, right column, paragraph 5 – page 21, left column, paragraph 1, Examiner interprets “trained sleep staging model” to read on “machine learning model”.), one or more features associated with a wakefulness state (“(3) Sleep stage classification – Finally, features are extracted from all three separated signals and input into a trained sleep staging model to obtain sleep stages at 30-second granularity.”, page 20, right column, paragraph 5 – page 21, left column, paragraph 1; Figure 1; part “3.2 Adaptive supervised signal separation”);
extract the one or more features from each of the one or more individual biosignals (“(3) Sleep stage classification – Finally, features are extracted from all three separated signals and input into a trained sleep staging model to obtain sleep stages at 30-second granularity.”, page 20, right column, paragraph 5 – page 21, left column, paragraph 1; Figure 1; part “3.2 Adaptive supervised signal separation”); and
determine, based on the one or more features extracted from the one or more individual biosignals, a wakefulness classification of the patient (“(3) Sleep stage classification – Finally, features are extracted from all three separated signals and input into a trained sleep staging model to obtain sleep stages at 30-second granularity.”, page 20, right column, paragraph 5 – page 21, left column, paragraph 1; Figure 1; part “3.3 Automatic sleep stage classification”).
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Nguyen does not teach the wearable device that is behind-the-ear.
However, Bleichner discloses “miniature electrodes placed in and around the human ear are a feasible solution, as they are sensitive enough to pick up electrical signals stemming from various brain and non-brain source” (Bleichner: abstract) and teaches a wearable device that is behind-the-ear (Figures 1B – 1C, page 3). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Nguyen such that the wearable device is behind-the-ear, as taught by Bleichner, for the benefit of “enable[ing] signal amplification close to sensor sites in a system sufficiently compact” (Bleichner: page 11, left column, paragraph 1).
Regarding claim 2, Nguyen and Bleichner teach all limitations of claim 1. The modified invention of Nguyen and Bleichner teaches the one or more individual biosignals includes at least one of an electroencephalogram (EEG) signal (page 19, right column paragraph 4, Figure 1; see part "3.2 Adaptive supervized signal separation" which refers to the "signal captured" as being "a mixture of EEG, EOG, and EMG signals", page 20, left column, paragraph 8), electrooculography (EOG) signal (page 19, right column paragraph 4, Figure 1; see part "3.2 Adaptive supervized signal separation" which refers to the "signal captured" as being "a mixture of EEG, EOG, and EMG signals", page 20, left column, paragraph 8), electromyography (EMG) signal (page 19, right column paragraph 4, Figure 1; see part "3.2 Adaptive supervized signal separation" which refers to the "signal captured" as being "a mixture of EEG, EOG, and EMG signals", page 20, left column, paragraph 8), and electrodermal activity (EDA) signal.
Regarding claim 3, Nguyen and Bleichner teach all limitations of claim 1. The modified invention of Nguyen and Bleichner teaches the system comprising a simulation output array (Figure 2), the stimulation output array comprising at least one of a light source, speaker, electrode (Nguyen: “electrode”, Figure 2, page 21, left column paragraphs 2 – 6, Figure 1; see part "3.1 In-ear signal acquisition”), antenna, or magnetic coil.
Regarding claim 4, Nguyen and Bleichner teach all limitations of claim 3. The modified invention of Nguyen and Bleichner teaches the ear piece worn (Nguyen: abstract, “a biosignal recording system”, page 24, left column, paragraph 2) further includes the stimulation output array (Nguyen: Figure 2, page 21, left column paragraphs 2 – 6, Figure 1; see part "3.1 In-ear signal acquisition”).
Regarding claim 5, Nguyen and Bleichner teach all limitations of claim 3. The modified invention of Nguyen and Bleichner teaches the second set of instructions (Nguyen: Figure 1, page 20) is further executable by the second processor (Nguyen: “Gold Standard Device”, page 20, left column, paragraph 1, Figure 1; page 20, right column, paragraph 5) to:
control operation of the stimulation output array (Nguyen: Figure 2) based on the wakefulness classification (Nguyen: see “3.3 Automatic sleep stage classification”),
wherein if the wakefulness classification is indicative of a microsleep state (Nguyen: Figures 3 – 4, see “3.3 Automatic sleep stage classification”), controlling the operation of the stimulation output array includes activating one or more of the at least one of the light source, speaker, electrode (Nguyen: “electrode”, Figure 2, page 21, left column paragraphs 2 – 6, Figure 1; see part "3.1 In-ear signal acquisition”), antenna, or magnetic coil of the stimulation output array (Nguyen: Figure 2).
Regarding claim 6, Nguyen and Bleichner teach all limitations of claim 3. The modified invention of Nguyen and Bleichner teaches the first set of instructions is further executable by the first processor (“microcontroller”, Figure 2) to:
obtain, from the host machine (“opensource brain-computer interface (OpenBCI) board”, page 22, right column, paragraph 2, and an associated computer; Examiner interprets an associated computer is coupled to the “opensource brain-computer interface (OpenBCI) board”.), the wakefulness classification (“sleep stages”, page 21, left column, paragraph 1; Figure 1) (“acquires the biosignal that is then preprocessed”, page 20, right column, paragraph 5, Figure 1); and
control the operation of the stimulation output array (Nguyen: Figure 2) based on the wakefulness classification (“sleep stages”, page 21, left column, paragraph 1; Figure 1), wherein if the wakefulness classification (“sleep stages”, page 21, left column, paragraph 1; Figure 1) is indicative of a microsleep state (Figure 1), controlling the operation of the stimulation output array (Nguyen: Figure 2) includes activating at least one of the light source, speaker, electrode (Nguyen: “electrode”, Figure 2, page 21, left column paragraphs 2 – 6, Figure 1; see part "3.1 In-ear signal acquisition”), antenna, or magnetic coil of the stimulation output array (Nguyen: Figure 2) (Nguyen: see “3.3 Automatic sleep stage classification”).
1Regarding claim 9, Nguyen and Bleichner teach all limitations of claim 1. The modified invention of Nguyen and Bleichner teaches the first set of instructions is further executable by the first processor (“microcontroller”, Figure 2) to:
sample the first signal obtained from the one or more sensors at a first sampling rate to produce a first signal at the first sampling rate (“To sample and digitize the in-ear signal, our sensor was connected to an opensource brain-computer interface (OpenBCI) board [19] configured at 2kHz with a gain of 24”, page 22, right column, paragraph 2); and
average two or more samples of the first signal to produce a first signal at a second sampling rate than the first sampling rate (“To sample and digitize the in-ear signal, our sensor was connected to an opensource brain-computer interface (OpenBCI) board [19] configured at 2kHz with a gain of 24. On the other hand, the ground truth was collected using Trackit Mark III supported by LifeLines Neurodiagnostic Systems Inc. [26] configured at 256Hz with a 0.1–70Hz pre-filter. After that, the Polysmith software [20] was run to score the ground-truth signals including 6-channel EEG, 2-channel EOG, and 2-channel EMG into different sleep stages at every 30-second segment.”, page 22, right column, paragraph 2).
Regarding claim 10, Nguyen and Bleichner teach all limitations of claim 1. The modified invention of Nguyen and Bleichner teaches the system (Nguyen: abstract, “a biosignal recording system”, page 24, left column, paragraph 2) separating the first signal into one or more individual biosignals (Nguyen: Figure 1) further comprises:
applying a respective bandpass filter for each of the one or more individual biosignals to the first signal, each respective bandpass filter further comprising a respective bandpass frequency associated with each of the one or more individual biosignals (Nguyen: “(1) Data acquisition – By plugged into the ear canal, our wearable recorder acquires the biosignal that is then preprocessed to eliminate noise through different band-pass filters;”, page 20, right column, paragraph 5; Figure 1).
Regarding claim 11, Nguyen and Bleichner teach all limitations of claim 10. The modified invention of Nguyen and Bleichner teaches the system (Nguyen: abstract, “a biosignal recording system”, page 24, left column, paragraph 2) separating the first signal into one or more individual biosignals (Nguyen: Figure 1) further comprises:
recovering, via a transfer learning model built from a ground-truth signal, components of each of the one or more individual biosignals from frequency ranges that overlap with other individual biosignals of the one or more individual biosignals (Nguyen: see part "3.2 Adaptive supervised signal separation" which refers to "a learning process" which "is developed [ ... ] from the ground truth EEG, EOG, and EMG"; see also Fig. 1 - Signal Separation – Gold Standard Device and Template Matrix Generation).
Regarding claim 12, Nguyen and Bleichner teach all limitations of claim 10. The modified invention of Nguyen and Bleichner teaches the system (Nguyen: abstract, “a biosignal recording system”, page 24, left column, paragraph 2) determining the wakefulness classification of the patient further comprises determining whether the patient is in a microsleep state or an awake state (Figure 3, see “3.3 Automatic sleep stage classification”).
Regarding claim 13, Nguyen and Bleichner teach all limitations of claim 10. The modified invention of Nguyen and Bleichner teaches the system (Nguyen: abstract, “a biosignal recording system”, page 24, left column, paragraph 2) determining the wakefulness classification of the patient farther comprises quantifying, via the machine learning model (Nguyen: “a trained sleep staging model”, page 20, right column, paragraph 5 – page 21, left column, paragraph 1, Examiner interprets “trained sleep staging model” to read on “machine learning model”.), a wakefulness level based on the captured biosignals from behind the ears (Bleichner: page 7, see “SLEEP STAGING”),
wherein the wakefulness level indicates an estimated probability that the patient is in a microsleep state (Nguyen: Figures 3 - 4, see “3.3 Automatic sleep stage classification”).
Response to Arguments
Applicant’s arguments, see page 11, filed 9 December 2025, with respect to claim objections have been fully considered and are persuasive in light of the amendments. The claim objections for claims 2 – 3, 5 and 6 of 9 June 2025 have been withdrawn.
Applicant’s arguments, see pages 12 - 13, filed 9 December 2025, with respect to 35 U.S.C. 112(b) rejections have been fully considered and are persuasive in light of the amendments. The 35 U.S.C. 112(b) rejections of 9 June 2025 have been withdrawn except the following one:
Claim 7, the limitations “buffering stage”, “feed forward differential pre-amplification stage” and “adaptive amplification stage” are unclear as it raises the question if “stage” refers to a step/method/the way it operates or a physical component of the circuit.
Applicant's arguments filed 9 December 2025 with respect to 35 U.S.C. 103 rejections have been fully considered but they are not persuasive. Applicant contends “Bleichner does not teach "an ear piece configured to be worn behind an ear of a patent. […] It does not teach or suggest an ear piece.”
However, Bleichner discloses a wearable device that is behind-the-ear (Figures 1B – 1C, page 3). Examiner interprets Figures 1B – 1C to be an ear piece as it is behind an ear of a patient which appears to be similarly configured as the instant application’s drawings. The Examiner suggests applicant to amend claims by adding structural limitation to the claim language to overcome 35 U.S.C. 103 rejections to distinguish what is being understood by the applicant to be a behind the ear wearable device. Additionally, See rejection above.
Conclusion
The examiner notes that, though no art has been applied against claims 7 and 8 at this time, they are not presently allowable. The question of prior art will be revisited upon resolution of the clarity issue noted above.
THIS ACTION IS MADE FINAL. 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 nonprovisional extension fee (37 CFR 1.17(a)) 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.
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/JULIE THI TRAN/Examiner, Art Unit 3791 /ALEX M VALVIS/Supervisory Patent Examiner, Art Unit 3791