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 .
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 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.
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 12 April 2026 has been entered.
Status of Claims
Claims 1, 4, 6, 8, 10, 13-15, 17-20, 24, 25, 27, 28, 30, 32, 34, and 36 are pending; claims 1, 6, 8, 13, 27, 28, and 30 have been amended; claims 2, 3, 5, 7, 9, 11, 12, 16, 21-23, 26, 29, 31, 33, 35, and 37 have been cancelled; claims 13-15, 17-20, 24, and 25 have been withdrawn; and claims 1, 4, 6, 8, 10, 27, 28, 30, 32, 34, and 36 currently are under consideration for patentability.
Response to Arguments
Applicant’s arguments with respect to claims 1, 4, 6, 8, 10, 27, 28, 30, 32, 34, and 36 have been considered but 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.
Applicant has amended the independent claims to explicitly recite a high-impedance microelectrode inserted into a predetermined peripheral nerve fascicle to record postganglionic skin sympathetic nervous activity or muscle sympathetic nervous activity. Applicant argues that the previously presented references of Libbus and Barbieri do not disclose or suggest the amended limitations. The Examiner has addressed the amended limitations in the updated text of the rejection below and has removed the previous base reference of Libbus, rendering moot the arguments directed towards Libbus.
Claim Rejections - 35 USC § 103
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claims 1, 10, 27, 28, 34, and 36 are rejected under 35 U.S.C. 103 as being unpatentable over Bright (US 2016/0317621 A1) in view of Barbieri et al. (US 2018/0233234 A1).
Regarding claim 1, Bright describes a method for estimating sympathetic arousal of a subject ([0009]), the method comprising the steps of
obtaining one or more sympathetic nervous activity (SNA) signals, the one or more SNA signals being obtained by percutaneously inserting a high-impedance microelectrode into a predetermined peripheral nerve fascicle to record postganglionic skin sympathetic nervous activity or muscle sympathetic nervous activity for one or more data participants ([0235], [0337])
obtaining physiological data from the one or more data participants and from the subject ([0235], [0575]), the physiological data including heart rate data ([0575]), wherein the one or more SNA signals and the physiological data of the one or more data participants are obtained simultaneously ([0575], monitoring sympathetic tone to determine the efficacy of neuromodulatory therapy)
processing the one or more SNA signals to determine one or more features of the one or more SNA signals and processing the physiological data to determine one or more features of the physiological data ([0575] - [0576])
Regarding claim 1, Bright does not explicitly disclose
providing the one or more features of the physiological data and of the one or more SNA signals to generate a correlation engine, the correlation engine being configured to correlate the one or more features of the physiological data with a database representing the one or more SNA signals including the postganglionic skin sympathetic nervous activity or muscle sympathetic nervous activity of the one or more data participants
wherein the correlation engine is configured to estimate a sympathetic nervous activity level of the subject
However, Barbieri also describes a method for estimating sympathetic arousal of a subject ([0007], [0062]), including the steps of
providing the one or more features of the physiological data and of the one or more SNA signals to generate a correlation engine, the correlation engine being configured to correlate the one or more features of the physiological data with a database representing the one or more SNA signals ([0034])
wherein the correlation engine is configured to estimate a sympathetic nervous activity level of the subject ([0053])
As Barbieri is also directed towards estimating a subject’s sympathetic arousal and is in a similar field of endeavor, it would have been obvious to a person having ordinary skill in the art at the time the invention was filed to use the physiological data and the sympathetic nervous activity signals, including the postganglionic skin sympathetic nervous activity or muscle sympathetic nervous activity of the one or more data participants, generated by Bright, within a correlation engine similar to that described by Barbieri, as doing so advantageously allows the resulting method to accurately predict a user’s sympathetic state.
Regarding claim 10, Barbieri describes the steps of
storing the physiological data and the estimated skin sympathetic nervous activity level of the subject on a server ([0021], [0073])
sending the physiological data or the estimated sympathetic nervous activity level of the subject to the subject or to a health clinician ([0073], for example via a mobile device or wearable smart device)
sending the physiological data or the one or more features of the physiological data to a server hosting the correlation engine ([0073]; “the acquisition and detection module 104 and the index calculation module 106 may be installed on or operable by a server”)
Regarding claim 27, Bright describes a system of estimating sympathetic arousal of a subject ([0009]) the system comprising
a device configured to receive physiological data of one or more data participants and of the subject ([0235], [0575]), the physiological data including heart rate data ([0575])
a high-impedance microelectrode configured to obtain one or more sympathetic nervous activity (SNA) signals from the one or more data participants, wherein the high-impedance microelectrode is configured to obtain the one or more SNA signals, to be inserted into a predetermined peripheral nerve fascicle of the one or more data participants and record postganglionic skin sympathetic nervous activity or muscle sympathetic nervous activity for one or more data participants ([0235], [0337])
Regarding claim 27, Bright does not explicitly disclose
a database for storing the recorded postganglionic skin sympathetic nervous activity or muscle sympathetic nervous activity of the one or more data participants
a processor configured to process the one or more SNA signals to determine one or more features of the one or more SNA signals and process the physiological data to determine one or more features of the physiological data
a correlation engine based on the one or more features of the one or more SNA signals and of the physiological data, the correlation engine is configured to estimate a sympathetic nervous activity level of the subject
wherein the correlation engine is configured to correlate the database and the one or more features of physiological data including the heart rate data obtained from the one or more data participants
However, Barbieri also describes a system for estimating sympathetic arousal of a subject ([0007], [0062]), including
a database for storing the recorded postganglionic skin sympathetic nervous activity or muscle sympathetic nervous activity of the one or more data participants ([0021], [0065])
a processor configured to process the one or more SNA signals to determine one or more features of the one or more SNA signals and process the physiological data to determine one or more features of the physiological data ([0034])
a correlation engine based on the one or more features of the one or more SNA signals and of the physiological data, the correlation engine is configured to estimate a sympathetic nervous activity level of the subject ([0034], [0053])
wherein the correlation engine is configured to correlate the database and the one or more features of physiological data including the heart rate data obtained from the one or more data participants ([0034])
Regarding claim 28, Barbieri describes wherein the one or more data participants are exposed to various stressors to record the one or more SNA signals of the one or more data participants ([0062]), and wherein each feature of the one or more SNA signals is assigned a value indicative of a sympathetic nervous activity level ([0053]).
Regarding claim 34, Barbieri describes a server, wherein the database and the correlation engine are hosted on the server, and wherein the device is configured to communicate with the server to send the physiological data processed by the processor to the server ([0021], [0073]).
Regarding claim 36, Barbieri describes wherein the correlation engine is a machine learning algorithm ([0061]) comprising a logistic regression classifier to estimate the sympathetic nervous activity level of the subject ([0006], [0042]), and wherein the device is a wearable device ([0073]).
Claims 4, 6, 30, and 32 are rejected under 35 U.S.C. 103 as being unpatentable over Bright in view of Barbieri, further in view of Maarek (US 2017/0224232 A1).
Regarding claim 4, Bright in view of Barbieri suggests the method of claim 1, including wherein the correlation engine is configured to correlate the one or more features of the one or more SNA signals with the heart rate data (Barbieri: [0034]) and wherein each feature of the one or more SNA signals is assigned a value indicative of a sympathetic nervous activity level (Barbieri: [0053]). Bright and Barbieri do not explicitly disclose wherein the correlation engine is configured to correlate one or more features of the one or more SNA signals with a combination of features selected from one or more features of the galvanic skin response data, skin blood perfusion data, and heart rate data. However, Maarek also describes a method for estimating sympathetic activity of a subject ([0007], [0035]), including correlating one or more features of SNA signals with a combination of galvanic skin response data, skin blood perfusion data, and heart rate data ([0024], [0034]). As Maarek is also directed towards assessing a patient’s sympathetic activity and is in a similar field of endeavor, it would have been obvious to a person having ordinary skill in the art at the time the invention was filed to incorporate measurement of galvanic skin response data, skin blood perfusion data, and heart rate data, similar to that described by Maarek, when using the method described by Bright and Barbieri, as doing so advantageously allows the resulting method to account for these physiological parameters which are known to affect sympathetic activity.
Regarding claim 6, Bright in view of Barbieri suggests the method of claim 1, but Bright and Barbieri do not explicitly disclose wherein obtaining the physiological data comprises obtaining skin resistance data and photoplethysmography data from the subject, wherein the skin resistance data is processed to obtain the galvanic skin response data, and wherein the photoplethysmography data is processed to obtain the skin blood perfusion data and the heart rate data. However, Maarek also describes assessing a patient’s sympathetic activity ([0007], [0035]), including obtaining skin resistance data and photoplethysmography data from a subject ([0034] - [0035]), wherein the skin resistance data is processed to obtain galvanic skin response data ([0039]) and wherein the photoplethysmography data is processed to obtain skin blood perfusion data and heart rate data ([0034] - [0035]). As Maarek is also directed towards assessing a patient’s sympathetic activity and is in a similar field of endeavor, it would have been obvious to a person having ordinary skill in the art at the time the invention was filed to incorporate a skin resistance sensor and a photoplethysmograph similar to that described by Maarek when using the method described by Bright and Barbieri, as doing so advantageously allows the resulting method to account for these physiological parameters which are known to affect sympathetic activity.
Regarding claim 30, Bright in view of Barbieri suggests the system of claim 27, including wherein the correlation engine is configured to correlate the one or more features of the SNA signals with the heart rate data (Barbieri: [0034]), but Bright and Barbieri do not explicitly disclose wherein the correlation engine is configured to correlate one or more features of the SNA signals with a combination of features of physiological data. However, Maarek also describes a method for estimating sympathetic activity of a subject ([0007], [0035]), including correlating one or more features of SNA signals with a combination of physiological data ([0024], [0034]). As Maarek is also directed towards assessing a patient’s sympathetic activity and is in a similar field of endeavor, it would have been obvious to a person having ordinary skill in the art at the time the invention was filed to incorporate measurement of physiological data, similar to that described by Maarek, when using the system described by Bright and Barberi, as doing so advantageously allows the resulting method to account for these physiological parameters which are known to affect sympathetic activity.
Regarding claim 32, Bright in view of Barbieri suggests the system of claim 27, but Bright and Barbieri do not explicitly disclose wherein the device is configured to receive skin resistance data and photoplethysmography data from the subject and wherein the processor is configured to process the skin resistance data to obtain the galvanic skin response data and process the photoplethysmography data to obtain the skin blood perfusion data and the heart rate data. However, Maarek also describes assessing a patient’s sympathetic activity ([0007], [0035]), including obtaining skin resistance data and photoplethysmography data from a subject ([0034] - [0035]), wherein the skin resistance data is processed to obtain galvanic skin response data ([0039]) and wherein the photoplethysmography data is processed to obtain skin blood perfusion data and heart rate data ([0034] - [0035]). As Maarek is also directed towards assessing a patient’s sympathetic activity and is in a similar field of endeavor, it would have been obvious to a person having ordinary skill in the art at the time the invention was filed to incorporate a skin resistance sensor and a photoplethysmograph similar to that described by Maarek when using the system described by Bright and Barbieri, as doing so advantageously allows the resulting method to account for these physiological parameters which are known to affect sympathetic activity.
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Bright in view of Barbieri, further in view of Rocon de Lima et al. (US 2014/0336722 A1).
Regarding claim 8, Bright in Barbieri suggests the method of claim 1. Barbieri further describes
wherein the correlation engine is a machine learning algorithm configured to correlate the one or more features of the physiological data with the sympathetic nervous activity signals stored in the database ([0061], supervised or unsupervised learning algorithms), and wherein the machine learning algorithm comprises a regression classifier configured to estimate the sympathetic nervous activity level of the subject ([0006], [0042]).
Neither Bright nor Barbieri explicitly disclose
processing the one or more SNA signals to produce a root-mean-square sympathetic nerve activity (RMS SNA) signal
identifying one or more spikes in the RMS SNA signal
detecting a SNA burst based on the one or more spikes
However, Rocon de Lima also describes a method of processing physiological data ([0009]), including the steps of
processing one or more signals to produce a root-mean-square activity signal ([0130])
identifying one or more spikes in the RMS signal ([0130])
detecting a burst based on the one or more spikes ([0130])
As Rocon de Lima is also directed towards processing physiological data and is in a similar field of endeavor, it would have been obvious to a person having ordinary skill in the art at the time the invention was filed to perform analysis steps similar to those described by Rocon de Lima on the sympathetic nerve activity signals described by Bright and Barbieri, as doing so advantageously enhances the accuracy of the resulting method in estimating the sympathetic nervous activity level of the subject.
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Conclusion
Any inquiry concerning this communication or earlier communications from the Examiner should be directed to Ankit D. Tejani, whose telephone number is 571-272-5140. The Examiner may normally be reached on Monday through Friday, 8:30AM through 5:00PM EST. 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, Carl Layno, can be reached by telephone at 571-272-4949. 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 at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (in USA or Canada) or 571-272-1000.
/Ankit D Tejani/
Primary Examiner, Art Unit 3796
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