DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application is being examined under the pre-AIA first to invent provisions.
Claim Rejections - 35 USC § 103
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 (i.e., changing from AIA to pre-AIA ) 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.
The following is a quotation of pre-AIA 35 U.S.C. 103(a) which forms the basis for all obviousness rejections set forth in this Office action:
(a) A patent may not be obtained through the invention is not identically disclosed or described as set forth in section 102, if the differences between the subject matter sought to be patented and the prior art are such that the subject matter as a whole would have been obvious at the time the invention was made to a person having ordinary skill in the art to which said subject matter pertains. Patentability shall not be negated by the manner in which the invention was made.
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
The factual inquiries for establishing a background for determining obviousness under pre-AIA 35 U.S.C. 103(a) 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.
This application currently names joint inventors. In considering patentability of the claims under pre-AIA 35 U.S.C. 103(a), the examiner presumes that the subject matter of the various claims was commonly owned at the time any inventions covered therein were made absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and invention dates of each claim that was not commonly owned at the time a later invention was made in order for the examiner to consider the applicability of pre-AIA 35 U.S.C. 103(c) and potential pre-AIA 35 U.S.C. 102(e), (f) or (g) prior art under pre-AIA 35 U.S.C. 103(a).
Claim 1-3, and 5-18 are rejected under pre-AIA 35 U.S.C. 103(a) as being unpatentable over Liao(US-20120271182-A1) in view of Litt(US 6658287 B1), and further in view of Liao(US 9498162 B2), herein after referred to as Liao B (all previously cited).
Regarding claims 1-2, 8, 11-12 and 16, Liao disclose a system (100 in fig.1), comprising: a body data collection module (110) configured to collect body data comprising a time series of a first body signal of a patient, wherein the first body signal is a cardiac signal [0032-0034], and a non-transitory computer readable program storage unit (410 in fig.4) encoded with instructions that, when executed by a processor [0053], performs a method, comprising: receiving the time series of the first body signal of the patient from the body data collection module [0012,0041], determining a first sliding time window and a second sliding time window for the time series of the first body signal [Abstract,0041]; applying to the first sliding window and the second sliding window [0048]; determining an indication of onset of a seizure based on the application to the first sliding window and the second sliding window [0010-0015]; delivering a therapy via a therapy unit for the seizure at a particular time, wherein the therapy, the particular time, are based upon the determination of the onset of the seizure [0007]; and determining a termination of the seizure based on the application to the first sliding window and the second sliding window [0010-0015]. Liao discloses substantially the invention as claimed but failed to disclose an autoregression algorithm and specify a “sliding” time window.
However, Litt teaches “According to the present invention, a large set of independent, instantaneous and historical features are extracted from the intracranial EEG, real-time brain activity data and/or other physiologic data. Once extracted, the features are processed by a prediction algorithm or intelligent prediction subsystem, such as a wavelet neural network(Detailed Description of the Invention, paragraph 8). The time at which an automated algorithm (such as the one according to the present invention) first predicts seizure onset. This will ordinarily be well in advance of any visible changes in the EEG or changes in the patient's behavior, and importantly, prior to EO. PTOT=Prediction-To-Onset Time=EO minus AP(Detailed Description of the Invention, paragraph 4). It can be shown that this amounts to a logistic nonlinear regression that gives an estimate of probability in the output independently of feature distribution(The System, paragraph 65)”.
However, Liao B discloses “wherein at least the first window of the first time period of the second window of the first time period are sliding windows, and further comprising identifying, via the analyzer device, the onset of the seizure event based on a first window of a second time period and a second window of the second time period(claim 7)”. Thus, it would have been obvious to one of ordinary skills in the art by the effective filing date to specify that the time windows in Liao are the sliding windows of Liao B.
Regarding claims 3 and 13, Liao disclose wherein the time series body signal is a measurement of a patient's heart activity [0012].
Regarding claim 5, Liao disclose wherein at least one of the delivered therapy [0007] or a time elapsed from a last seizure [0042].
Regarding claim 6, Liao disclose wherein the therapy unit is further configured to determine at least one of: based upon the seizure onset, the seizure termination, or both [0053].
Regarding claim 7, Liao disclose a monitoring device with one or more processors configured to: determining at least one value selected from the duration of the seizure [0043,0059].
Regarding claims 9 and 17, Liao disclose wherein the second body signal is selected from an accelerometer signal [0007,0077].
Regarding claims 10 and 18, Liao in view of Tran and Liao B teach the system of claim 1 and the method of claim 11, but Liao fails to disclose estimating the degree of nonstationarity of the first body signal. However, Litt teaches “The single number is, for example, the mean value of fractal dimension, or the standard deviation of energy, or the number of spikes within the subgroup window. When this number goes outside 3 standard deviations (3.sigma.) above or below a center line, an "out-of-control" condition is recorded. The system estimates the center line and control limits from data under "in-control" (nonpreseizure) conditions(Examples of Useful Features and how they are Extracted, paragraph 16). The degree of nonstationary is the mean or change over time of the obtained data which is taught by Litt. Thus, it would have been obvious to one of ordinary skills in the art by the effective filing date to modify Liao to estimate the degree of nonstationary to analyze the consistency and accuracy of the heart rate data.
Regarding claim 14, Liao disclose at least one responsive action selected from: delivering, by a therapy unit, a therapy for the seizure at a particular time, wherein at least one of the therapy, the particular time, or both is based upon the determination of the onset of the seizure; determining an efficacy of the therapy [0007].
Regarding claim 15, Liao disclose wherein at least one of the delivered therapy [0007] or a time elapsed from a last seizure [0053].
Response to Arguments
Applicant's arguments filed 1/21/2026 have been fully considered but they are not persuasive. Applicant argues that the prior art referenced fails to disclose “wherein the therapy and the particular time are based upon the determination of the onset of the seizure”, however, Litt teaches “ In addition, the system may be programmed to automatically trigger preventative actions, such as the application of an electrical shock, the delivery of one or more drugs or the activation of a pacing algorithm which can be employed to abort the seizure or mitigate the severity of a seizure. Outputs from the device may be used to train the patient in a biofeedback scheme to learn to abort seizures themselves(Summary of the Invention, paragraph 4). Also unique to this invention, therapeutic intervention triggered by this prediction method is adjusted according to the probability measure output and/or time horizon to seizure so that as seizures become closer and more likely, modalities or parameters of the intervention measure (duration, strength, etc.), such as a more aggressive therapy, is triggered to abort the event(Examples of Useful Features for Seizure Prediction, paragraph 33)”. Litt teaches automatically administering treatments as soon as a seizure is detected, as well as the ability to administer therapy at a specific time based on seizure predicted time. Litt, in combination with the Liao references, discloses all the claimed material and therefore, the 103 rejections for all claims stand.
Conclusion
THIS ACTION IS MADE FINAL. 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 MARIA CATHERINE ANTHONY whose telephone number is (703)756-4514. The examiner can normally be reached 7:30 am - 4:30 pm, EST, M-F.
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/MARIA CATHERINE ANTHONY/Examiner, Art Unit 3796 /CARL H LAYNO/Supervisory Patent Examiner, Art Unit 3796