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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 3/26/26 has been entered.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1, 3, 5-9, 11, 13, 15, 17 and 19 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites the steps determining whether the impedance between two of the ear-side measurement units is less than a preset threshold and if it is collect the signal and obtaining attention type of the user based on the signal.
The limitation of determining whether the impedance is less than a threshold and obtaining an attention type, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting “a processor” nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the processor, “determining” and “obtaining” in the context of this claim encompasses the user manually determining if a signal level is below a threshold and making a mental determination from the signal about the attention level. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea. Similarly, the mathematics recited in claim 7 fall under the “Mathematical Concepts” grouping of abstract ideas.
This judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements of obtaining bioelectric signal via measurement units. These units involve mere data gathering and amount to insignificant extra-solutional activity, specifically pre-solutional activity. Additionally, the processor and the measurement units are recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using generic computer components. Accordingly, these additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. Similarly the dependent claims do not include additional elements that amount to significantly more. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept and well-understood, routine and conventional activity is not sufficient to amount to significantly more than the abstract idea itself. The claim is not patent eligible.
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, 3, 5-9, 11, 13, 15, 17 and 19 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. It is unclear what is considered an “attention type.” It is unclear if the attention type is all of the alternatives of awake or asleep or distracted or focused state or is it only those pairs as separate determinations. The amount of alternatives in the claim make it unclear what the determination is. Defining the attention type as being based on the EEG signal does not clarify what the attention type is or what if any determination is made.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1, 3, 5, 9, 11, 13, 15, 17 and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Mackellar et al. US 2017/0041699 in view of Turner US 2018/0116514.
Regarding claims 1, 9, 13 and 17, Mackellar discloses a user attention detection method, wherein the method comprises:
obtaining a user electroencephalogram signal from the user bioelectrical signal; and
alerting the user based on the attention type of the user indicating that the user is in the distracted state or that the user is asleep ([¶83,84] an alert can be generated when distraction is determined. [¶70-76] the device can provide audio feedback based on the computed cognitive state) wherein the attention type of the user is based on the user electroencephalogram signal ([¶63,64,72,84,87] the device can use machine learning including to determine attention and various psychological states),
wherein the ear-side wearing apparatus comprises a plurality of ear-side signal measurement units, each ear-side signal measurement unit is an electrode ([FIG. 4a] sensors 210, 222 and 224), and
a transmitter configured to send the EEG signal to a signal apparatus ([¶41] the EEG signal can be transmitted to a mobile device for analysis).
Mackellar discloses determine contact quality based on impedance ([¶56, 54-60] contact quality can be determined and measured and can be based on impedance) but does not specifically disclose collecting bioelectrical signals from the two ear-side signal measurement units when the impedance between the two ear-side signal measurement units is less than the preset threshold, and obtaining the user bioelectrical signal based on a potential difference signal corresponding to the bioelectrical signals collected by the two ear-side signal measurement units.
Turner teaches a similar in-ear device that measures EEG and uses impedance to determine whether to collect and process signals. Specifically determining if the impedance between two electrodes is below a threshold and if it is then collecting the signals ([¶24,43,59] impedance below a certain threshold indicates a reliable signal and collection is started). Therefore, it would have been obvious to one of ordinary skill in the art prior to the time of filing to combine the device of Mackellar with the thresholds of Turner in order to have a better signal to noise ratio for better monitoring ([¶59]).
Regarding claims 3, 11, 15 and 19, Mackellar discloses the ear-side wearing apparatus is a single-ear-side wearing apparatus ([FIG. 4a]), and the plurality of ear-side signal measurement units comprise a plurality of single-ear-side signal measurement units ([¶13,92] electrodes 210 and sensors 222 and 214); and
Mackellar does not disclose the impedance thresholds. Turner teaches collecting bioelectrical signals from the two ear- side signal measurement units when the impedance between the two ear-side signal measurement units is less than the preset threshold, and obtaining the user bioelectrical signal based on a potential difference signal corresponding to the bioelectrical signals collected by the two ear-side signal measurement units comprises when the impedance between the two single-ear-side signal measurement units is less than the preset threshold, obtaining the user bioelectrical signal based on a potential difference signal corresponding to bioelectrical signals collected by the two single-ear-side signal measurement units ([¶24,43,59] impedance below a certain threshold indicates a reliable signals and collection is started).
Regarding claim 5, Mackellar discloses using amplifiers in the determination of the EEG which would most likely be differential amplifiers, as the EEG is determined based on the differences in the electrode pairs readings, it is not made clear in reference to figures 8-12. Turner specifically discloses the obtaining the user bioelectrical signal based on a potential difference signal corresponding to the bioelectrical signals collected by the two ear-side signal measurement units comprises: obtaining, by using a differential circuit, the potential difference signal corresponding to the bioelectrical signals collected by the two ear-side signal measurement units, and using the potential difference signal as the user bioelectrical signal ([¶26,43]).
Claim(s) 6-8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Mackellar et al. in view of Turner further in view of Wang et al. “Attention Drawing of Movie Trailers Revealed by Electroencephography Using Sample Entropy”
Regarding claim 6, Mackellar discloses determining attention ([¶66]) and using machine learning ([¶87]) but does not specifically disclose calculating a sample entropy value of the user electroencephalogram signal, and analyzing the attention type of the user based on the sample entropy value and the machine learning model. Wang teaches a similar EEG processing method that uses SampEn in order to determine attention and interest ([pg. 11] sample entropy is used to determine attention or inattention). Therefore, it would have been obvious to one of ordinary skill in the art prior to the time of filing to combine the device of Mackellar with the teachings of SampEn calculation of Wang in order to provide a measure of attention less affected by fatigue ([pg. 11]).
Regarding claim 7, Mackellar does not specifically disclose the calculation. Wang teaches a similar EEG attention monitoring method that teaches intercepting the user electroencephalogram signal of a preset time length, and obtaining N signal sampling points from the user electroencephalogram signal of the preset time length, wherein the N signal sampling points are u(1), u(2), ..., and u(N); sequentially intercepting m sampling points based on the N signal sampling points by using each of u(1), u(2), ..., and u(N-m+1) as a start point to construct N-m+1 m-dimensional vectors; calculating, for each of the N-m+1 m-dimensional vectors, a ratio of a quantity of vectors that are in all the other vectors and whose distances to the m-dimensional vector are less than r to a quantity of all the other vectors, and calculating an average value of the obtained N-m+1 ratios to obtain a first average value; sequentially intercepting m+1 sampling points based on the N signal sampling points by using each of u(1), u(2), ..., and u(N-m) as a start point to construct N-m (m+1)-dimensional vectors; calculating, for each of the N-m (m+1)-dimensional vectors, a ratio of a quantity of vectors that are in all the other vectors and whose distances to the (m+1)-dimensional vector are less than r to a quantity of all the other vectors, and calculating an average value of the obtained N-m ratios to obtain a second average value; and calculating a sample entropy (SampEn) value based on a ratio of the first average value to the second average value ([pgs. 8-9] the same determination is used with a computed ratio based on the averages of A and B). Therefore, it would have been obvious to one of ordinary skill in the art prior to the time of filing to combine the device of Mackellar with the teachings of SampEn calculation of Wang in order to provide a measure of attention less affected by fatigue ([pg. 11]).
Regarding claim 8, Mackellar discloses the machine learning model is an SVM classifier, wherein machine learning is performed by using the SVM classifier to obtain a segmentation value ([¶87] the device can use a SVM in order to make its determination including on focus level). Wang teaches the attention type of the user is determined and the sample entropy value ([pg. 11]).
Response to Arguments
Applicant's arguments filed 3/3/26 have been fully considered but they are not persuasive.
Regarding Applicant’s argument that claims include features that cannot be performed in the human mind, Examiner respectfully disagrees. Applicant argues that the human mind cannot collect a bioelectric signal. This is true, however, the collection of the signal is not part of the abstract idea. The collection also fails to provide significantly more as it is pre-solutional to the abstract idea. Similarly, alerting the using could still be performed in the human mind, but the alerting is also not considered part of the abstract idea that could be a mental concept. Even if the alert is specifically a display or something a human could not physically do it still would not add significantly more to the abstract idea as it is post-solutional output.
Regarding Applicant’s arguments against the 103 rejection, Examiner respectfully disagrees. Applicant argues that Turner does not teach determining the impedance between two electrodes. Turner teaches determining the impedance for each electrode and determining the impedance of each electrode is determining the impedance between electrodes. Specifically, when a pair of electrodes is selected the impedance between them is determined because the impedance for every electrode was determined.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL ANTHONY CATINA whose telephone number is (571)270-5951. The examiner can normally be reached 10-6pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Robert Chen can be reached at 5712723672. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/MICHAEL A CATINA/Examiner, Art Unit 3791
/TSE W CHEN/Supervisory Patent Examiner, Art Unit 3791
Prosecution Insights