DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after 16 March 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation ("BRI") using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The BRI of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) (or pre-AIA 35 U.S.C. 112, sixth paragraph) is invoked.
As explained in MPEP § 2181(I), claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f):
(A) the claim limitation uses the term "means" or "step" or a term used as a substitute for "means" that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term "means" or "step" or the generic placeholder is modified by functional language, typically, but not always linked by the transition word "for" (e.g., "means for") or another linking word or phrase, such as "configured to" or "so that"; and
(C) the term "means" or "step" or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word "means" (or "step") in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f). The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word "means" (or "step") in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f). The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word "means" (or "step") are being interpreted under 35 U.S.C. 112(f), except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word "means" (or "step") are not being interpreted under 35 U.S.C. 112(f), except as otherwise indicated in an Office action.
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 pre-AIA 35 U.S.C. 112, 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.
Claim(s) 4, 15 and claims dependent thereon is/are rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, 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 pre-AIA the applicant regards as the invention.
Regarding claim 4 and claims dependent thereon, the limitation "wherein the respiration rate is determined from a respiration signal that measures breathing of the user, and further comprising: invoking a machine learning model to determine the respiration signal from at least one of the internal audio stream or the external audio stream based on the user condition" is indefinite. Claim 1, on which claim 4 depends, requires determining the respiration rate based on each of the internal audio stream, the external audio stream, and the input indicating the user condition. However, claim 4 encompasses the respiration signal, from which the respiration rate is determined, being determined from either the internal or external audio stream based on the user condition. It is unclear how invoking a machine learning model to determine the respiration signal from either the internal audio stream or the external audio stream based on the user condition as recited in claim 4 utilizes each of the internal audio stream, the external audio stream, and the input indicating the user condition in determining a respiration rate as required by claim 1.
Regarding claim 15 and claims dependent thereon, the limitation "validating an aggressor signal, caused by an ambient sound outside of the head worn system, based on an additional audio stream from an additional microphone" is indefinite. It is unclear what is being validated. There is no indication in the claim that "an aggressor signal caused by an ambient sound outside of the head worn system" is present, determined, etc. from any of the previously recited data (audio streams, respiration signal, etc.). Accordingly, it is unclear what is being validated and how, if at all, it relates to the received audio streams, determined respiration signal, etc. of claim 12.
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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1, 7, 11, 17 and 19-20 is/are rejected under 35 U.S.C. 102(a)(1) and/or 35 U.S.C. 102(a)(2) as being anticipated by US 2022/0409134 A1 (Oztaskent).
Regarding claims 1, 11 and 17, Oztaskent discloses a non-transitory computer readable medium, said medium storing instructions operable to cause one or more processors to perform a method (e.g., ¶ [0003]), the method comprising:
receiving an input indicating a user condition (e.g., ¶ [0087] during exercise, a first model may determine that the user is only breathing and/or analyzing gyroscope information to infer a user is engaging in a run);
receiving an internal audio stream from an in-ear microphone (¶ [0017] second microphone in an earbud configured to detect sounds from within the ear canal; ¶ [0087] inner microphone; etc.) and an external audio stream from an external microphone of a head worn system (¶ [0017] first microphone in the earbud configured to obtain signals or sounds external to the user through aerial conduction);
enhancing the internal audio stream, based on the external audio stream, to generate an enhanced audio stream (¶¶ [0040]-[0041] external microphones record external audio that can be later identified and removed from the signals recorded by the one or more microphones directed toward the user);
determining a respiration rate of a user based on the enhanced audio stream (that is a function of the internal audio stream and the external audio stream, as noted above), and the input indicating the user condition (¶ [0087] a second model determines information related to breathing in response to the output from the first model, wherein the second model analyzes information from one or more sensors (e.g. inner microphone and thermometer) to analyze breathing rate, breathing depth, breathing patterns, and exertion by the user; ¶¶ [0040]-[0041]; etc.).
Regarding claim 7, Oztaskent discloses the respiration rate is determined from a respiration signal by distinguishing the respiration signal from aggressor signals caused by ambient sounds outside of the head worn system (¶ [0041] external microphone(s) can be used to filter out audio signals from a source external to the user from the audio signals recorded by the one or more microphones directed toward the user).
Regarding claims 19-20, Oztaskent discloses the method comprises invoking a machine learning model to determine the respiration rate (¶ [0087]), wherein the machine learning model is run by a system including at least one of the in-ear microphone or the external microphone or run by a companion device in communication with at least one of the in-ear microphone or the external microphone (¶¶ [0005]-[0006]).
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
Determining the scope and contents of the prior art.
Ascertaining the differences between the prior art and the claims at issue.
Resolving the level of ordinary skill in the pertinent art.
Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1, 4-6, 10 and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over US 2008/0139955 A1 (Hansmann) in view of US 2022/0409134 A1 (Oztaskent).
Regarding claims 1 and 17, Hansmann discloses and/or suggests a non-transitory computer readable medium, said medium storing instructions operable to cause one or more processors to perform a method (throughout document, control unit of monitor 1 executing the disclosed method(s)), the method comprising:
receiving an input indicating a user condition (e.g., ¶¶ [0042]-[0044] evaluating sensor for assessing user state/condition, such as physical/sports activities);
receiving a first data stream from a first sensor (e.g., ¶ [0019] sensor that measures bone conduction, e.g., at the ear) and an external audio stream from an external microphone (e.g., ¶ [0007] at least two different sensors; ¶ [0018] microphone sensor acquiring breath sounds in the vicinity of an inlet to the airways) of a head worn system (e.g., Fig. 1; ¶ [0028]); and
determining a respiration rate of a user based on the first data stream, the second data stream, and the input indicating the user condition (¶ [0031] respiration rate of the user of the device is determined such that the different respiration rates measured by different sensors are taken into account; ¶ [0043] quality of each sensor/rate is taken into account in the determination, wherein quality may be determined based on the evaluating sensor and/or user condition indicated thereby).
Hansmann does not expressly disclose the first data stream from the first sensor is an internal audio stream from an in-ear microphone. However, as noted above, Hansmann does disclose said sensor may comprise a sensor that measures bone conduction at the ear.
Oztaskent discloses/suggests a method comprising, inter alia, receiving an internal audio stream from an in-ear microphone (¶ [0039] microphone 110 positioned within the ear 20; microphone 110 can record audio signals occurring within the ear canal that are caused by the user performing actions, such as breathing, generated by vibration of an eardrum, bone conductions, and/or other vibrating structures/tissues).
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 method of Hansmann with receiving an internal audio stream from an in-ear microphone as disclosed/suggested by Oztaskent as a simple substitution of one suitable sensor for measuring bone conduction at the ear for another to yield no more than predictable results. See MPEP 2143(I)(B).
Regarding claim 4, Hansmann as modified discloses/suggests a greater weight is applied to either the internal audio stream or the external audio stream based on the user condition (e.g., ¶ [0040] quality values from measurements with different sensors can also be taken into account further with different weights; ¶ [0043] a lower quality value may be assigned to a sensor based on condition detected by evaluating sensor; ¶ [0008]; etc.).
Regarding claim 5, Hansmann as modified discloses/suggests a greater weight is applied to the internal audio stream when aggressor signals in the internal audio stream are below a threshold (e.g., ¶ [0035], ¶ [0054], etc. a quality value associated with a sensor/signal may be determined based on signal-to-noise ratio of the signal; ¶ [0040] quality values from measurements with different sensors can also be taken into account further with different weights; etc.).
Regarding claim 6, Hansmann as modified discloses/suggests a greater weight is applied to the external audio stream when there are more aggressor signals in the internal audio stream than the external audio stream (e.g., ¶ [0035], ¶ [0054], etc. a quality value associated with a sensor/signal may be determined based on signal-to-noise ratio of the signal; ¶ [0040] quality values from measurements with different sensors can also be taken into account further with different weights; etc.).
Regarding claim 10, Hansmann as modified discloses/suggests the method comprises determining a trust score associated with the respiration rate based on the user condition (e.g., ¶ [0042] evaluating sensor for inferring user condition shall display information on the quality or reliability of a respiration rate).
Claim(s) 2 is/are rejected under 35 U.S.C. 103 as being unpatentable over Oztaskent.
Regarding claim 2, Oztaskent discloses the limitations of claim 1, as discussed above, and further discloses triggering determination of the respiration rate when the user condition indicates the user is exercising (¶ [0087] first model determines the user is only breathing during exercise, which causes the second model for determining information related to breathing, e.g., respiration rate, to be determined). Alternatively/Additionally, Oztaskent discloses/suggests receiving input indicating a user condition (e.g., ¶ [0087] gyroscope data) indicating a user condition (e.g., likely engaging in a run), wherein, when the user condition is exercising (e.g., running), the model for determining respiration rate gyroscope information can be further utilized in analyzing respiration information, and further discloses/suggests analyzing breathing pattern in response to an event (¶ [0090]). 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 method of Oztaskent with triggering determination of the respiration rate when the user condition indicates the user is exercising (e.g., the first model being configured to classify a state as exercising, and initiating the second model in response thereto) in order to facilitate analyzing a user's breathing patterns in response to exercise.
Claim(s) 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over Oztaskent in view of in view of "Estimation of Respiratory Rate from Breathing Audio" (Harvill).
Regarding claim 3, Oztaskent discloses the limitations of claim 1, as discussed above, and further discloses invoking a machine learning model to determine respiration rate from at least one of the internal audio stream or the external audio stream based on the user condition (e.g., ¶ [0087] determining respiration rate based on a second ML model in response to output from a first ML model indicative of user condition). Oztaskent does not expressly disclose respiration rate is determined from a respiration signal that measures breathing of the user, wherein a machine learning model is invoked to determine the respiration signal from at least one of the internal audio stream or the external audio stream.
Harvill discloses a method comprising invoking a machine learning model to determine a respiration signal from an audio stream; and determining respiration rate from the respiration signal (pgs. 4601-4602, Methods).
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 method of Oztaskent with invoking a machine learning model to determine a respiration signal from at least one of the internal audio stream or the external audio stream; and determining the respiration rate from the respiration signal as disclosed and/or suggested by Harvill in order to provide an accurate respiration rate determination (Harvill, pg. 4602) and/or as a simple substitution of one suitable ML-based method for determining respiration rate for another to yield no more than predictable results. See MPEP 2143(I)(B).
Claim(s) 8, 12-14, 16 and 19-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hansmann in view of Oztaskent as applied to claim(s) 1 and 17 above, and further in view of Harvill; or alternatively over Hansmann in view of Oztaskent and Harvill.
Regarding claim 8, Hansmann as modified discloses/suggests the limitations of claim 1, as discussed above, but does not disclose the respiration rate is determined based on a first machine learning model that determines a first respiration signal from features extracted from the internal audio stream and a second machine learning model that determines a second respiration signal from features extracted from the external audio stream.
Harvill discloses estimating respiration rate from audio by invoking a machine learning model to determine the respiration rate (throughout document).
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 method of Hansmann with the respiration rate being determined based on a first machine learning model that determines a first respiration signal from features extracted from the internal audio stream and a second machine learning model that determines a second respiration signal from features extracted from the external audio stream as disclosed/suggested by Harvill in order to provide a more accurate (than non-learning respiration rate methods) respiration rate determination based on the data from each microphone (Harvill, pg. 4602).
Regarding claim 12, Hansmann discloses/suggests a non-transitory computer readable medium storing instructions operable to cause one or more processors to perform a method (throughout document, control unit of monitor 1 executing the disclosed method(s)), the method comprising:
receiving a first data stream from a first sensor (e.g., ¶ [0019] sensor that measures bone conduction, e.g., at the ear) and an external audio stream from an external microphone of a head worn system (e.g., ¶ [0007] at least two different sensors; ¶ [0018] microphone sensor acquiring breath sounds in the vicinity of an inlet to the airways) of a head worn system (e.g., Fig. 1; ¶ [0028]);
determining a respiration signal that measures breathing of a user based on a user condition indicating utilizations of the first data stream and the external audio stream (¶ [0031] individual respiration rates measured by different sensors; ¶ [0043] quality for a sensor/individual rate may be determined based on the evaluating sensor and/or user condition indicated thereby; ¶ [0061] individual quality values; etc.); and
determining a respiration rate of the user based on the respiration signal (e.g., ¶ [0060] individual rates and quality values combined to determine respiration rate).
Hansmann does not expressly disclose the first data stream from the first sensor is an internal audio stream from an in-ear microphone. However, as noted above, Hansmann does disclose said sensor may comprise a sensor that measures bone conduction at the ear.
Oztaskent discloses/suggests a method comprising, inter alia, receiving an internal audio stream from an in-ear microphone (¶ [0039] microphone 110 positioned within the ear 20; microphone 110 can record audio signals occurring within the ear canal that are caused by the user performing actions, such as breathing, generated by vibration of an eardrum, bone conductions, and/or other vibrating structures/tissues).
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 method of Hansmann with receiving an internal audio stream from an in-ear microphone as disclosed/suggested by Oztaskent as a simple substitution of one suitable sensor for measuring bone conduction at the ear for another to yield no more than predictable results. See MPEP 2143(I)(B).
Hansmann as modified does not disclose invoking a machine learning model to determine a respiration signal that measures breathing of a user.
Harvill discloses a method comprising invoking a machine learning model to determine a respiration signal from an audio stream; and determining respiration rate from the respiration signal (pgs. 4601-4602, Methods).
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 method of Hansmann invoking a machine learning model to determine a respiration signal (e.g., from each microphone stream) as taught/suggested by Harvill, wherein the machine learning model determines the respiration signal (e.g., a weighted individual rate for each microphone) based on a user condition indicating utilizations of the internal audio stream and the external audio stream (e.g., in determining the final respiration rate value) in order to provide a more accurate (than non-learning respiration rate methods) individual respiration rate determination based on the data from each microphone (Harvill, pg. 4602) that is weighted corresponding to the detected user condition (Hansmann, ¶ [0043]).
Regarding claim 13, Hansmann as modified discloses/suggests giving greater weight to one of the internal audio stream or the external audio stream, and lesser weight to the other of the internal audio stream or the external audio stream, based on the user condition (e.g., ¶ [0043]).
Regarding claim 14, Hansmann as modified discloses/suggests the limitations of claim 12, as discussed above, but does not expressly disclose selecting between either the internal audio stream or the external audio stream based on the user condition. However, Hansmann does disclose there may be circumstances/user conditions in which a sensor, e.g., an external microphone, cannot provide sufficiently accurate or reliable data on respiration rate because of ambient noise, e.g., when a user is jogging/running (¶ [0008]). 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 method of Hansmann with selecting between either the internal audio stream or the external audio stream based on the user condition (e.g., assigning a "0" weight to external audio stream when ambient noise is too high while the user is jogging/running) in order to ensure an accurate/reliable respiration rate can be provided during said condition (Hansmann, ¶ [0008]).
Regarding claim 16, Hansmann as modified discloses/suggests determining a trust score associated with the respiration rate based on the user condition (e.g., ¶ [0042] evaluating sensor for inferring user condition shall display information on the quality or reliability of a respiration rate).
Regarding claim 19, Hansmann as modified discloses/suggests the limitations of claim 17, as discussed above, and discloses/suggests the determination of respiration rate is performed by a system including at least one of the in-ear microphone or the external microphone (e.g., Fig. 1, monitor 1 includes the control unit as well as sensors for determining respiration rate). Hansmann as modified does not disclose the method comprises invoking a machine learning model to determine the respiration rate, wherein the machine learning model is run by said system.
Harvill discloses estimating respiration rate from audio by invoking a machine learning model to determine the respiration rate (throughout document).
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 method of Hansmann with invoking a machine learning model to determine the respiration rate as disclosed/suggested by Harvill in order to provide a more accurate (than non-learning respiration rate methods) respiration rate determination based on the microphone data (Harvill, pg. 4602).
Regarding claim 20, Hansmann as modified discloses/suggests the limitations of claim 17, as discussed above, but does not disclose the method comprises invoking a machine learning model to determine the respiration rate.
Harvill discloses estimating respiration rate from audio by invoking a machine learning model to determine the respiration rate (throughout document).
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 method of Hansmann with invoking a machine learning model to determine the respiration rate as disclosed/suggested by Harvill in order to provide a more accurate (than non-learning respiration rate methods) respiration rate determination based on the microphone data (Harvill, pg. 4602).
Hansmann as modified does not disclose the machine learning model is run by a companion device in communication with at least one of the in-ear microphone or the external microphone. However, Hansmann does disclose the system having the in-ear and external microphones (e.g., Fig. 1) may be in communication with a companion device (e.g., Fig. 3).
Oztaskent discloses a system comprising, inter alia, an in-ear microphone and an external microphone (¶ [0017]), wherein the system is configured analyzed information from one or more sensors to determine at least respiration rate by invoking a machine learning model (¶ [0087]), wherein the machine learning model is run by the system, or a companion device (e.g., ancillary device) in communication with said system (e.g., ¶¶ [0005]-[0006]).
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 method of Hansmann with the machine learning model being run by a/them companion device in communication with the in-ear microphone and/or the external microphone as disclosed/suggested by Oztaskent in order to conserve resources (battery, processing power, etc.) of the in-ear and/or head worn system, as the machine learning model may be computationally intensive (Oztaskent, ¶ [0005]) and/or as a simple substitution of one suitable processing configuration for another (¶¶ [0005]-[0006]) to yield no more than predictable results. See MPEP 2143(I)(B).
Claim(s) 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Oztaskent in view of US 2020/0312321 A1 (Voix).
Regarding claim 9, Oztaskent discloses the limitations of claim 1, as discussed above, but does not disclose validating the respiration rate of the user based on an additional audio stream from an additional microphone.
Voix discloses/suggests validating a result/parameter determined by a machine learning model based on an additional audio stream from an additional microphone (e.g., ¶ [0077]).
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 method of Oztaskent with validating the respiration rate of the user based on an additional audio stream from an additional microphone as disclosed/suggested by Voix in order to facilitate verifying the accuracy of and/or the model used for respiration rate determination (¶ [0066]; ¶ [0077]; etc.).
Claim(s) 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Oztaskent (or Hansmann in view of Oztaskent as applied to claim(s) 17, and further) in view of US 2020/0352456 A1 (Joseph).
Regarding claim 18, Oztaskent discloses (or Hansmann as modified discloses/suggests) the limitations of claim 17, as discussed above, but does not expressly disclose the respiration rate is updated periodically.
Joseph discloses a comparable system, wherein the system is configured to update a respiration rate periodically (e.g., ¶ [0145] correlating measured sound, measured every, e.g., few seconds or minutes, into a measurement of respiration rate).
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 method of Oztaskent (or Hansmann) with the respiration rate being updated periodically in order to conserve power/battery of the head-worn/in ear device.
Conclusion
The prior art made of record and not relied upon is considered pertinent to Applicant's disclosure: PTO-892.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Meredith Weare whose telephone number is 571-270-3957. The examiner can normally be reached Monday - Friday, 9 AM - 5 PM.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. Applicant is encouraged to use the USPTO Automated Interview Request at http://www.uspto.gov/interviewpractice to schedule an interview.
If attempts to reach the examiner by telephone are unsuccessful, the examiner's supervisor, Tse Chen, can be reached on 571-272-3672. 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.
/Meredith Weare/Primary Examiner, Art Unit 3791
Prosecution Insights