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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 20 November 2025 has been entered.
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 2, 5, 6, 8, and 12-14 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. Claims 2 and 5 both recite the phrase “the examiner or other operator”. As there is no previous mention of an examiner or other operator, the phrase lacks proper antecedent basis. For this examination, the phrase in both claims is being interpreted as “an examiner or other operator”. Claim 5 recites the phrase “a flexible material”. It is unclear if this flexible material is the same as or different than the frame of claim 1. As best understood by the specification, the frame is the flexible material. For this examination, the frame of claim 1 is being interpreted as the flexible material of claim 5. Further regarding claim 5, the phrase “rapidly apply” renders the claim indefinite as the term “rapidly” is a relative term. It is unclear what is to be considered “rapidly”. Regarding claim 12, the phrase “the examiner” lacks proper antecedent basis. For this examination, the phrase is being interpreted as “an examiner”. Further regarding claim 12, it is unclear to whom “one or more users” is referring. Is the examinee one of the users? Is the examiner one of the users? Clarification is requested. For this examination, anyone capable of seeing, hearing, feeling the provided feedback will be considered a user. Regarding claim 13, the phrase “configured to perform train a machine learning or statistical model” renders the claim indefinite. For this examination, the phrase is being interpreted as “configured to train a machine learning or statistical model”. Regarding claim 14, the phrase “the one or more examination devices” lacks proper antecedent basis. For this examination, claim 14 is being interpreted such that it reads “… responsive to the collection of additional data from the plurality of sensors…”.
Claims not explicitly rejected above are rejected due to their dependence on a rejected base claim.
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.
Section 33(a) of the America Invents Act reads as follows:
Notwithstanding any other provision of law, no patent may issue on a claim directed to or encompassing a human organism.
Claims 1-3 and 5-14 are rejected under 35 U.S.C. 101 and section 33(a) of the America Invents Act as being directed to or encompassing a human organism. See also Animals - Patentability, 1077 Off. Gaz. Pat. Office 24 (April 21, 1987) (indicating that human organisms are excluded from the scope of patentable subject matter under 35 U.S.C. 101). The phrase “with each sensor placed in contact with the body of the examinee” in claim 1 improperly incorporates human tissue into the claimed invention. It is suggested that the phrase be amended to read “with each sensor configured to be placed in contact with the body of the examinee” in order to remove the recitation of human tissue. Claims 2, 3, and 5-14 are rejected due to their dependence on claim 1.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1, 2, and 5-10 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Al-Ali et al.’673 (US Pub No. 2012/0083673 – previously cited).
Regarding claim 1, Figures 1A and 1B of Al-Ali et al.’673 disclose an EEG detection system (section [0009]), the system comprising: a wearable head-mounted device 120 (also see Figure 3A and sections [0084-0085]), comprising: a frame (see any of Figures 3A-3O, and in particular, Figure 13A) configured to be arranged on a body of an examinee, the frame comprising an adhesive layer (Figure 13A, adhesive layer 890; section [0153]) configured to secure the frame to the body of the examinee, the frame configured to be flexible to position respective portions of the frame at a same portion of the body when arranged on bodies of different examinees (sections [0085], [0152-0153]); a plurality of sensors arranged at different locations of the frame (sections [0084-0085], [0094-0099], [0106-0109], Figure 2A, sensors 310,330,320,300, Figure 3A, sensors 260,440, and Figure 13A), with each sensor placed in contact with the body of the examinee by the frame (sections [0013], [0085], [0109], [0114]) and configured to capture electrical signals from a portion of the body of the examinee; and a data acquisition apparatus (Figure 1A, element 140) configured to process electrical signals from the sensors and wirelessly transmit said electrical signals to a receiver device (sections [0087], [0092-0102]), the receiver device (Figure 1A, element 150) being configured with one or more processors to receive and process data transmitted by the data acquisition apparatus (section [0079], and section [0102] – in order to give quantitative or qualitative assessments of the patient’s well being based on data obtained from the data acquisition device, the receiver device must include one or more processors to receive and process the data), the data acquisition apparatus comprising: one or more non-transitory computer-readable storage media to store data generated by the head-mounted device (section [0084] – in order to evaluate physiological parameters using trend analysis, data generated by the head-mounted device must be stored in one or more computer storage media).
Regarding claim 2, the EEG detection system comprises a display device configured to present virtual content to the examinee, examiner or other operator (Figure 1A, element 150, sections [0014], [0079], [0105], [0154]).
Regarding claim 5, a flexible material (frame 120) is used to connect the sensors in a pre-specified arrangement such that the examinee, examiner or other operator may rapidly apply the sensors at the desired locations without having to place each sensor individually (Figures 3A and 13A show the sensors within the frame/flexible material in a pre-specified arrangement; sections [0085], [0150], [0153]).
Regarding claim 6, the flexible material and said sensors may be manufactured in a plurality of arrangements, including variation in number and/or position of sensors, that may be interchangeably attached to the data acquisition device according to examinee characteristics, desired exam or clinical use case (this is inherent – the flexible material and sensors may be manufactured in any desired arrangement).
Regarding claim 7, the plurality of sensors and said data acquisition apparatus are arranged into the same device (section [0086] - as sensor 120 and data acquisition device 140 of Figure 1A are capable of being connected via a wired connection, they are part of the same device).
Regarding claim 8, said display device and said receiver device configured with one or more processors are the same device (Figure 1A shows a display on receiver device 150, and see Figure 14).
Regarding claim 9, the head-mounted device is further configured with one or more sensors from the group comprising: an oximeter; a temperature sensor; a gyroscope; an accelerometer; and a heart rate monitor (see TITLE, section [0009], and Figure 2A and its description thereof).
Regarding claim 10, said one or more non-transitory computer-readable storage media are further configured to store: a database for quality comparison; a database for feature identification; a database for pattern identification; and a database for patient stratification and population analysis (any database storing received EEG/signal data can be used for quality comparison, feature identification, pattern identification, patient stratification, and population analysis).
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 3 is rejected under 35 U.S.C. 103 as being unpatentable over Al-Ali et al.’673, as applied to claim 1, in view of Jordan et al.’674 (US Pub No. 2015/0257674 – previously cited).
Regarding claim 3, Al-Ali et al.’673 discloses all of the elements of the claimed invention, as discussed in paragraph 8 above, except for the data acquisition apparatus continuously transmitting one or more EEG signals to said receiver device. Jordan et al.’674 teaches continuously transmitting data from a data acquisition apparatus to a receiver device, wherein the continuously transmitted data is displayed in real-time. Jordan e tal.’674 teaches that continuously transmitting and displaying data assists a technician or other expert viewing EEG data to identify trends quickly (sections [0155], [0158]). It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to have modified the data acquisition apparatus of Al-Ali et al.’673 to be configured to continuously transmit one or more EEG signals to the receiver device, as this would allow for the real-time display of EEG data and quick trend analysis by an examiner or other operator of the system. Furthermore, it would have been obvious to try configuring the data acquisition apparatus of Al-Ali et al.’673 to continuously transmit one or more EEG signals to the receiver device as it would be choosing from a finite number of identified, predictable solutions (continuous data transmission or non-continuous data transmission), with a reasonable expectation of success.
Claims 11 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over Al-Ali et al.’673, as applied to claim 10, in view of Jordan et al.’674 further in view of Brown et al.’973 (US Pub No. 2014/0187973) further in view of Gevins’571 (US Pub No. 2008/0167571 – previously cited).
Regarding claim 11, Al-Ali et al.’673 discloses all of the elements of the current invention, as discussed in paragraph 8 above, except for the one or more processors being configured to perform operations comprising: accessing the database for quality comparison to assess the quality of exam data, accessing the database for feature identification to extract or identify features from the exam data, accessing the database for pattern identification to extract or identify patterns from the exam data, and accessing the database for patient stratification and population analysis to extract or identify patient stratification or other population analysis.
Jordan et al.’674 teaches assessing the quality of stored exam data in order to determine whether EEG electrodes are properly coupled to an examinee and/or are functioning properly, and further provides an output to an examiner or other operator indicating poorly functioning electrodes (sections [0139-0141]). It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to have modified the one or more processors of Al-Ali et al.’673 to be configured to access a database for quality comparison, assess the quality of exam data, and provide an output of the assessment, as taught by Jordan et al.’674, as this would notify an examiner or other operator of poorly functioning EEG electrodes. The modification to Al-Ali et al.’673 would allow the examiner or other operator to take steps to reposition or replace poorly functioning EEG electrodes.
Al-Ali et al.’673 in view of Jordan et al.’674 discloses all of the elements of the current invention, as discussed above, except for extracting or identifying features from the exam data and extracting or identifying patterns from the exam data. Brown et al.’973 teaches predicting when an examinee under anesthesia will regain consciousness by accessing EEG data from a database, extracting or identifying features from the EEG data, and extracting or identifying patterns from the EEG data (sections [0007], [0054-0056]). It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to have modified the one or more processors of Al-Ali et al.’673 in view of Jordan et al.’674 to be configured to access EEG data from a database, extract or identify features from the EEG data, and extract or identify patterns from the EEG data, as taught by Brown et al.’973, as this would help in predicting when the examinee under anesthesia will regain consciousness.
Al-Ali et al.’673 in view of Jordan et al.’674 further in view of Brown et al.’973 discloses all of the elements of the current invention, as discussed above, except for said one or more processors being configured to extract or identify patient stratification or other population analysis. Gevins et al.’571 teaches accessing a database for patient stratification and population analysis, and identifying patient stratification or other population analysis in order to classify a patient as a strong, average, or mild/non-responder to a particular drug (sections [0050] and [0080]). It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to have modified the one or more processors of Al-Ali et al.’673 in view of Jordan et al.’674 further in view of Brown et al.’973 to be configured to access a database for patient stratification and population analysis, and identify patient stratification or other population analysis, as taught by Gevins et al.’571, as it would allow the EEG detection system of Al-Ali et al.’673 in view of Jordan et al.’674 further in view of Brown et al.’973 to classify the examinee as a strong, average, or mild/non-responder to a particular drug based on their analyzed EEG signals.
Regarding claim 12, Al-Ali et al.’673 teaches that responsive to the collection of additional data from the plurality of sensors, the one or more processors are configured to create data visual guide elements that are displayed to the examinee or the examiner (sections [0102], [0105], and see Figure 14), and cause the head-mounted device to provide feedback to one or more users in the form of light, sound, or vibration (section [0105]).
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Al-Ali et al.’673 in view of Jordan et al.’674 further in view of Brown et al.’973 further in view of Gevins’571, as applied to claim 12, further in view of Sarrafzadeh et al.’712 (US Pub No. 2015/0257712 – previously cited).
Al-Ali et al.’673 in view of Jordan et al.’674 further in view of Brown et al.’973 further in view of Gevins’571 discloses all of the elements of the current invention, as discussed in paragraph 11 above, except for the one or more processors being configured to train a machine learning or statistical model on data stored in the one or more non-transitory computer-readable storage media; and the one or more non-transitory computer-readable storage media being further configured to store model architecture, parameter values, and any other variables required to implement said machine learning or statistical model.
Al-Ali et al.’673 in view of Jordan et al.’674 further in view of Brown et al.’973 further in view of Gevins’571 requires analyzing signals from a plurality of sensors to determine a quantitative representation of a depth of consciousness (sections [0084], [0102], [0103], [0105]), but fails to provide details of the analysis. Sarrafzadeh et al.’712 teaches training a machine learning model or statistical model on data stored in a non-transitory computer-readable storage medium, wherein the machine learning model or statistical model identifies patterns in acquired data in order to detect occurrences of a medical event of interest in real time (see ABSTRACT, and sections [0007-0009], [0032-0050], and [0067]). It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to have configured the one or more processors of Al-Ali et al.’673 in view of Jordan et al.’674 further in view of Brown et al.’973 further in view of Gevins’571 to train a machine learning model or statistical model to identify patterns in the acquired data (captured electrical signals), as taught by Sarrafzadeh et al.’712, as it would provide a means by which to provide a quantitative representation of the examinee’s depth of consciousness (different depths of consciousness are each a medical event of interest).
One of ordinary skill in the art would readily realize that in order to use the machine learning or statistical model, the one or more non-transitory computer-readable storage media would need to store the model architecture, parameter values and any other variables required to implement said machine learning or statistical model.
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Al-Ali et al.’673 in view of Jordan et al.’674 further in view of Brown et al.’973 further in view of Gevins’571 further in view of Sarrafzadeh et al.’712, as applied to claim 13, further in view of Chen et al.’580 (US Pub No. 2013/0231580 – previously cited).
Al-Ali et al.’673 in view of Jordan et al.’674 further in view of Brown et al.’973 further in view of Gevins’571 further in view of Sarrafzadeh et al.’712 discloses all of the elements of the current invention, as discussed in paragraph 12 above, except for the one or more processors being configured to re-train the machine learning or statistical model with an updated data set.
Chen et al.’580 teaches retraining a classifier with an updated data set in order to improve the accuracy of the classifier (section [0059]). It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to have modified the one or more processors of Al-Ali et al.’673 in view of Jordan et al.’674 further in view of Brown et al.’973 further in view of Gevins’571 further in view of Sarrafzadeh et al.’712 such that they are configured to re-train the machine learning or statistical model with an updated data set, as it would improve the accuracy of the machine learning or statistical model.
Response to Arguments
Applicant’s amendments to the claims have overcome the previous rejections under 35 U.S.C. 112(a) and 35 U.S.C. 112(b) (with the exception of the indefiniteness issue in claim 5 regarding “rapidly apply”). However, as noted in paragraph 4 above, new rejections under 35 U.S.C. 112(b) are warranted. Applicant’s arguments with respect to the prior art rejections of the claims have been considered and are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Warwick et al.’449 (US Pub No. 2013/0338449 – previously cited) discloses multiple elements of claims 1-3, 5-8 and 10, and further teaches one or more processors configured to train a machine learning or statistical model on data stored in a non-transitory computer-readable medium, wherein the processors are also configured to retrain the machine learning or statistical model with an updated data set. Chakravarthy et al.’142 (US Pub No. 2011/0295142 – previously cited) teaches a database for quality comparison. Harris et al.’430 (US Pub No. 2011/0166430 – previously cited) teaches a database for patient stratification and population analysis. Ray et al.’497 (US Pub No. 2017/0196497 – previously cited) teaches retraining a machine learning model with an updated data set. Picard et al.’090 (US Pub No. 2014/0081090 – previously cited) teaches retraining a machine learning model with an updated data set.
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/ETSUB D BERHANU/Primary Examiner, Art Unit 3791