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 .
Response to Arguments
Applicant’s arguments, see Remarks, filed 10/10/2025, with respect to the objection to the specification in light of the amendments have been fully considered and are persuasive. The objection of the specification has been withdrawn.
Applicant’s arguments, see Remarks, filed 10/10/2025, with respect to the objection to claims 1 and 6 in light of the amendments have been fully considered and are persuasive. The objection of claims 1 and 6 has been withdrawn.
The terminal disclaimer has been acknowledged.
Applicant's arguments filed 10/10/2025 have been fully considered but they are not persuasive. The applicant argues that Howard 2013 does not disclose that the stimulation and sensing devices each comprise at least one device that uses both electrical and optical methodologies. However, paragraph [0070] teaches deep brain stimulation which typically involves electrical stimulation and paragraph [0105] teaches optical stimulation (deliver signal to the targeted neural tissue via invasive or non-invasive…implanted optical probes). Additionally, the same paragraph states “one or more effectors used to stimulate target neural tissue”. Therefore, there is motivation to use different end effectors at the same time.
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 6-10 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Howard et al., (US 20130338526); hereinafter Howard 2013 (cited previously).
Regarding claim 6, Howard 2013 discloses a computer program product (figure 4, part 400, described in [0019] computer system) comprising a non-transitory computer readable storage (figure 4, part 408 called memory) having program instructions embodied therewith (figure 4 part 420 operating system), the program instructions executable by a server computer system comprising a processor (figure 4, part 402A CPU), memory (figure 4 part 408 memory) accessible by the processor, and computer program instructions stored in the memory and executable by the processor (figure 4) , the program instructions comprising: program instructions and data stored in the memory to configure the processor to control a plurality of stimulation devices (figure 3 effectors described in [0106]) connected to signal output circuitry interfacing the processor with the plurality of stimulation devices to generate and transmit stimulation signals (figures 3 and 5 interface 2, described in [0105]); program instructions and data stored in the memory to configure the processor to receive sensed signals a plurality of sensing devices (figure 3 sensors described in [0013]) connected to signal input circuitry interfacing the processor with the plurality of sensing devices (figures 3 and 5 interface 1 described in [0104]);
Wherein the signal output circuitry and the signal input circuitry are configured to enable simultaneous stimulation and sensing ([0079] The LXIO modality consists of a computational method that can analyze with numerous processes simultaneously); and
program instructions and data stored in the memory to configure the processor to perform dynamic closed loop feedback of the stimulation signals based on the received sensed signals (figure 6 described in [0045] ) to provide self-guided, self-directed diagnostics and treatment of neural conditions ([0028], [0106]) using at least one recipe for a treatment strategy guided by artificial intelligence ([0132]-[0133]).
Howard 2013 further teaches the plurality of stimulation devices comprises at least one stimulation device providing both electrical ([0070] deep brain stimulation which typically involves electrical stimulation) and optical stimulation ([0105] deliver signal to the targeted neural tissue via invasive or non-invasive…implanted optical probes) and wherein the plurality of sensing devices comprises at least one sensing device providing both electrical ([0028] electroencephalography (EEG) and optical ([0013] a variety of sensors (which implement read modalities) and effectors (which implement write modalities), analyzes the response signals and provides series of signals to the brain or spinal cord).
Regarding claim 7, Howard 2013 further discloses (Figures 1-3) that the plurality of stimulation devices comprises at least one of stimulation devices in the implantable device providing electrical stimulation (implanted device found in [0105]).
Regarding claim 8, Howard 2013 further discloses (Figures 1-3) that the plurality of sensing devices (sensors) comprises at least an Electro Encephalogram (EEG) device (EEG sensing modality described in [0014]).
Regarding claim 9, Howard 2013 further discloses that program instructions to perform: applying stimulation based on a first version of stimulation parameters (data from presumptive Alzheimer’s patient [0020]); sensing results of the applied stimulation to form patient treatment results data ([0020]) ; modifying the first version of stimulation parameters using the patient treatment results data to form a second version of stimulation parameters; and applying stimulation based on the second version of stimulation parameters (description of cyclic nature of process found in [0021]).
Regarding claim 10, Howard 2013 further discloses (Figures 1-3) that program instructions to perform: applying stimulation based on a version of stimulation parameters (data from presumptive Alzheimer’s patient [0020]); sensing results of the applied stimulation to form patient treatment results data ([0020]); modifying the version of stimulation parameters using the patient treatment results data to form a modified version of stimulation parameters; and repeating the applying, sensing, and modifying using each modified version of stimulation parameters (description of cyclic nature of process found in [0021]).
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:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ruffini et al (US20110190846) (cited previously); hereinafter Ruffini in view of Howard et al (US20170258390A1); hereinafter Howard 2017 and Howard et al (US 20130338526); hereinafter Howard 2013.
Regarding claim 1, Ruffini (Figure 1) discloses a system to provide self-guided, self- directed diagnostics and treatment of neural conditions ([0024] lines 5-7) comprising: a processor (SR + PDPU in figure 1, described in [0081] and [0086] respectively), memory (memory of SCM [0084]) accessible by the processor, and program instructions and data ([0062] lines 6-9) stored in the memory; a plurality of stimulation devices (E1-E3 in figure 1, [0056]) comprising electrical stimulation devices connected to signal output circuitry ([0080] communications module) interfacing the processor with the plurality of stimulation devices ([0080] communications module), wherein the program instructions and data stored in the memory are configured so that the processor generates and transmits stimulation signals to the plurality of stimulation devices; and a plurality of sensing devices (S1-S3 in figure 1 and described in [0022]) comprising electrical sensing devices connected to signal input circuitry interfacing the processor with the plurality of sensing devices ([0075],[0083] wherein the SCM controls both stimulation and sensing elements and communicates in both directions), wherein the program instructions and data stored in the memory are further configured so that the processor receives sensed signals from the plurality of sensing devices;
Wherein the signal output circuitry and the signal input circuitry are configured to enable simultaneous stimulation and sensing ([0079] The LXIO modality consists of a computational method that can analyze with numerous processes simultaneously); and
wherein the program instructions and data stored in the memory are further configured so that the processor performs real-time dynamic closed loop feedback of the stimulation signals ([0024]) based on the received sensed signals to provide self-guided, self-directed diagnostics and treatment of neural conditions ([0034]-[0037]). Ruffini teaches using generic algorithms that can include machine learning or artificial intelligence algorithms, however Ruffini fails to teach specifically artificial intelligence that comprises general machine learning models or a model targeted for a specific neural condition. Howard 2017 teaches using at least one recipe for a treatment strategy guided by artificial intelligence ([0073] section 9 presents a 2 part analysis using machine learning, [0355] machine learning to diagnose pain in the context of Parkinson’s Disease). It would have been obvious to a person having ordinary skill in the art before the effective filing date of this invention to modify Ruffini with Howard 2017 because there is some teaching, suggestion, or motivation to do so. Ruffini outlines how machine learning as an approach to recognize symptoms is especially relevant when the labels of the dataset are not known and the goal is to find the hidden structure of the data ([0329]).
The combination of Ruffini and Howard 2017 fails to teach that the plurality of stimulation devices providing both electrical and optical stimulation. Howard 2013 teaches the plurality of stimulation devices comprises at least one stimulation device providing both electrical ([0070] deep brain stimulation which typically involves electrical stimulation) and optical stimulation ([0105] deliver signal to the targeted neural tissue via invasive or non-invasive…implanted optical probes) and wherein the plurality of sensing devices comprises at least one sensing device providing both electrical ([0028] electroencephalography (EEG) and optical ([0013] a variety of sensors (which implement read modalities) and effectors (which implement write modalities), analyzes the response signals and provides series of signals to the brain or spinal cord). It would have been obvious to a person having ordinary skill in the art before the effective filing date of this invention to modify Ruffini and Howard 2017 with Howard 2013 because analyzing responses and a series of signals using analytical methods allows for treating the patient-,tissue-, and disorder-specific signal patterns.
Regarding claim 2, the combination of Ruffini, Howard 2017, and Howard 2013 teaches the system of claim 1. Ruffini (Figure 1) further discloses that the plurality of stimulation devices (E1-En) comprises a Transcranial Direct Current Stimulation (tDCS) device ([0026]).
Regarding claim 3, the combination of Ruffini, Howard 2017, and Howard 2013 teaches the system of claim 2. Ruffini (Figure 1) further discloses that the plurality of sensing devices (S1-Sn) comprises an Electro Encephalogram (EEG) device ([0047]).
Regarding claim 4, the combination of Ruffini, Howard 2017, and Howard 2013 teaches the system of claim 3. Ruffini (Figure 1) further discloses that the program instructions and data stored in the memory are configured so that the processor performs: applying stimulation based on a first version of stimulation parameters ([0036]); sensing results of the applied stimulation to form patient treatment results data ([0022]); modifying the first version of stimulation parameters using the patient treatment results data to form a second version of stimulation parameters ([0024]) ; and applying stimulation based on the second version of stimulation parameters ([0025]).
Regarding claim 5, the combination of Ruffini, Howard 2017, and Howard 2013 teaches the system of claim 3. Ruffini (Figure 1) further discloses that the program instructions and data stored in the memory are configured so that the processor performs: applying stimulation
based on a version of stimulation parameters ([0036]); sensing results of the applied stimulation to form patient treatment results data ([0022]); modifying the version of stimulation parameters using the patient treatment results data to form a modified version of stimulation parameters ([0024]); and repeating the applying, sensing, and modifying using each modified version of stimulation parameters ([0037]).
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Dhrasti SNEHAL Dalal whose telephone number is (571)272-0780. The examiner can normally be reached Monday - Thursday 8:30 am - 6:00 pm, Alternate Friday off, 8:30 am - 5:00 pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Carl Layno can be reached at (571) 272-4949. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/D.S.D./Examiner, Art Unit 3796
/CARL H LAYNO/Supervisory Patent Examiner, Art Unit 3796