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 .
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.
Claims 1-24 are rejected under 35 U.S.C. 101 because have been rejected under 35 U.S.C. 101 because the claims are directed toward an abstract idea without significantly more.
Step 1: Independent Claims 1 and 13 recite a method and system. Thus, they are directed to statutory categories of invention.
Step 2A, Prong 1:
Claims 1 and 13 recite the following claim limitations:
Obtaining biometric sensor data from a user
Generating a set of processed biometric sensor data from the set of biometric sensor data
Generating a set of features from the processed biometric sensor data which are associated with one or more characteristic physiological event phase
determining from the set of generated features, the set of processed biometric sensor data, or both the set of generated features and the processed biometric sensor data, a confidence score for each characteristic physiological event phase of the one or more characteristic physiological event phase indicating a presence of that phase in a data segment
determining, from a relation between the confidence score of each of the characteristic physiological event phase, a final confidence score indicating an occurrence of a physiological event based on a relation between the one or more physiological event phase confidence scores
determining, from an accumulation of final confidence scores, a cumulative confidence score indicating an occurrence of a particular physiological event, wherein the physiological event comprises one or more characteristic physiological event phases
providing a potential physiological event alert based on the cumulative confidence score
These limitations, under their broadest reasonable interpretation, cover concepts that can be practically performed in the human mind, i.e. by using pen and paper. With a plurality of measurements, a human could reasonably identify features in the signal, determine a confidence the features indicates the occurrence of a physiological event by looking to the accumulations of confidence scores, and then alert others to the results.
Step 2A, Prong 2:
Claims 1 and 13 recite the further limitations:
biometric sensors, and obtaining physiological data from the biometric sensors
hardware processors
non-transitory storage media
electronically providing a physiological event alert based on the cumulative confidence score.
Electronically receiving a plurality of measurements over an unspecified time span is merely insignificant pre-solution activity (See MPEP 2106.05(g)).
The recitation of one or more processors and computer storage media with computer-usable instructions that, when executed by the one or more processors, implement a method are merely reciting both the processors and computer storage media at a high-level of generality, and the computer readable storage media merely instructs the processors to carry out the steps of the method. In other words, the computer components are being used as a tool to carry out the method (See MPEP 2106.05(f)).
The usage of electronically providing a physiological event alert based on the cumulative confidence score is merely insignificant post solution activity (see MPEP 2106.05(a)(II), “Examples that the courts have indicated may not be sufficient to show an improvement to technology include… iii. Gathering and analyzing information using conventional techniques and displaying the result, TLI Communications, 823 F.3d at 612-13, 118 USPQ2d at 1747-48;”).
Thus, the abstract idea is not integrated into a practical application. The combination of these additional elements is no more than insignificant extra solution activity, and mere instructions to apply the exception using generic computer components (the processors and computer readable storage media). Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application. The claim is directed to an abstract idea.
Step 2B:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed with respect to Step 2A Prong Two, the additional elements in the claim amount to no more than insignificant extra solution activity and mere instructions to apply the exception using a generic computer component. The same analysis applies here in 2B and does not provide an inventive concept.
For the "electrically receiving..." step that was considered insignificant extra-solution activity in Step 2A Prong Two, it has been re-evaluated in Step 2B and determined to be well-understood, routine, conventional activity in the field. The following evidence supports such a determination:
• electronically receiving a plurality of measurements of physiological variables for a patient, the plurality of measurements being acquired over a time span
o (See MPEP 2106.05(d) II. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network).
For these reasons, there is no inventive concept. The claim is not patent eligible. Even when viewed as a whole, nothing in the claim adds significantly more to the abstract idea.
Dependent Claims:
Claims 2 and 14 recite limitations that further define the type of data collected, and are merely limiting the physiological variables to a particular fields of use.
Claims 3, 8, 15, and 20 recite limitations that are routine and conventional in the field of patient monitoring (wearable devices such as wristwatches or glasses, usage of a user interface), see Gluckman as an example.
Claims 4-7, 10-12, 16-19, and 22-24 further limit the abstract idea by introducing limitations which are indicative of concepts practically performable in the human mind (finding features specific to a condition, specific methods of calculating and comparing confidence values).
Claims 9 and 21 further specify where the alert is provided, but as set forth above this is insignificant post-solution activity, and providing medical alerts to others (caregivers/providers/guardians) is routine and conventional (see Gluckman below as an example).
Claim Rejections - 35 USC § 102
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.
(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.
Claims 1-6, 8-18, and 20-24 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by U.S. Patent Publication 20190328306 awarded to Gluckman et al, hereinafter Gluckman.
Regarding Claims 1 and 13, Gluckman teaches the method and system for physiological event detection and alerting (abstract), comprising: one or more biometric sensors that capture, record, or both capture and record biosensor data from a user (Para. 0021); one or more hardware processors and one or more non-transitory computer readable media that stores instructions, that when executed by the one or more hardware processors, perform a method of physiological detection and alerting (Para. 0011) comprising: obtaining, from one or more biometric sensors, a set of biometric sensor data from a user (Para. 0021); generating, by one or more hardware processors, a set of processed biometric sensor data from a set of biometric sensor data (Para. 0032); generating, by the one or more hardware processors, a set of features from the processed biometric sensor data which are associated with one or more characteristic physiological event phase, wherein data based on an association between the set of features and the one or more characteristic physiological event phase is stored in one or more non-transitory storage media (Para. 0055, “In some implementations, the one or more computer-readable media cause the one or more processors to perform operations further comprising determining, by the system, a quantification of the brain-periphery temporal association, wherein providing the estimate of risk of a future physiological event is based on the quantification of the brain-periphery temporal association”); determining, from a relation between the confidence score of each of the characteristic physiological event phase using the one or more hardware processors, a final confidence score indicating an occurrence of a physiological event based on a relation between the one or more physiological event phase confidence scores (Para. 0144, “identifying, by the system, a probability of the one or more target periphery feature representations within a defined time window of one or more of the target brain feature representations”); determining, from an accumulation of final confidence scores using the one or more hardware processors, a cumulative confidence score indicating an occurrence of a particular physiological event, wherein the physiological event comprises one or more characteristic physiological event phases (Para. 0144, “Identifying, by the system, a probability of the one or more target periphery feature representations within a defined time window of one or more of the target brain feature representations to generate an estimated cumulative probability distribution; determining, by the system a brain-periphery temporal association between the one or more target brain feature representations and the one or more target periphery feature representations based on the estimated cumulative probability distribution; and providing, by the system, an indication of the temporal association”); and providing, by the one or more hardware processors, a potential physiological event alert based on the cumulative confidence score (Paras. 0056-0057).
Regarding Claims 2 and 14, Gluckman teaches the inventions above, wherein the one or more biometric sensors comprise an accelerometer (Para. 0043) and a photoplethysmography (PPG) sensor (Para. 0021).
Regarding Claims 3 and 15, Gluckman teaches the inventions above, wherein the one or more biometric sensors are incorporated into a wearable device comprising of a wristwatch (Para. 0030, “watch body, watch band”).
Regarding Claims 4 and 16, Gluckman teaches the inventions above, further comprising: processing the set of biometric sensor data to produce the set of processed biometric sensor data by reducing a data set imbalance between physiological events and non-physiological events in the processed biometric sensor data by iteratively training and using one or more models to identify anomalous segments in non-physiological event biometric data to produce a balanced dataset, wherein the one or more models comprises one or more anomaly detection methods (Para. 0156, “In some implementations, the process 500 can optionally be used to build or train (e.g., via machine learning) a model for determination of brain-periphery temporal association, brain-periphery coincidence, and/or brain-periphery coincidence rate. In such implementations of the process, stages 511-571 and 512-572 are used to identify or generate a modified threshold range or modified predetermined range. The modified threshold or predetermined range can then be provided as an output to a user or stored in a memory, e.g., on computer-readable media, for later use in process 500. The user can then return to stages 511 and 512 to repeat process 500 for the same, different, or new data using the modified threshold or predetermined range. In this manner, the predetermined range can be set to useful or statistically significant values specific to a chosen disease, periphery measurement, group of mammals, or individual mammal or patient”); and using the balanced dataset to rain one or more classifiers for each characteristic physiological event phase that produces the confidence score for each characteristic physiological event phase (Para. 0094).
Regarding Claims 5 and 17, Gluckman teaches the inventions above, wherein the set of features from the processed biometric sensor data that are generated use techniques comprising one or more of a time domain feature extraction (Para. 0648).
Regarding Claims 6 and 18, Gluckman teaches the inventions above, wherein the relation between the confidence scores determining the final score comprises techniques of aggregating the confidence scores comprising an arithmetic expression of the confidence scores (Para. 0078), a probabilistic graphical model (Para. 0120), or combinations thereof.
Regarding Claims 8 and 20, Gluckman teaches the inventions above, wherein the physiological event alert (Para 0137, “Optionally, the process can further include providing an indication, such as, e.g., a graphical or tabular output of the target brain and/or periphery activity representations. In some implementations, the output can be a physical output, an image on a graphical user interface, an audible output, or the like. In some implementations, the target brain and/or periphery activity representations are representative of likely abnormal brain and/or periphery events or aberrations in the mammal's average brain and/or periphery activity”) is provided on a user interface of a wearable device worn by the user (Para. 0150, “For example, a wearable sensing device can, in some implementations, include brain and/or periphery data sensors, one or more data recording and control units, the data processing system, and, optionally, one or more input/output interfaces”).
Regarding Claims 9 and 21, Gluckman teaches the inventions above, wherein the potential physiological event alert is provided to one or more of the user, a caregiver, a healthcare provider, or a legal guardian (Para. 0128, “The system 210 may be coupled to peripheral devices such as a display screen (e.g., on smartphone 220) for presenting information to a user, patient, or healthcare provider, and an input interface (e.g., on smartphone 220) for receiving user inputs. Moreover, the system 210 may include a variety of components known to one of ordinary skill in the art that facilitate processing of physiological data in the processes described herein”).
Regarding Claims 10 and 22, Gluckman teaches the inventions above, wherein a physiological event is any event that causes one or more characteristic patterns that can be identified through or more of the biometric sensors, these events comprising: epileptic seizures (Para. 0111).
Regarding Claims 11 and 23, Gluckman teaches the inventions above, wherein the physiological event comprises a neurological event, a cardiac event, or combinations thereof (abstract).
Regarding Claims 12 and 24, Gluckman teaches the inventions above, wherein the neurological event is a seizure (Para. 0111).
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 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.
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.
Claims 7 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Publication 20190328306 awarded to Gluckman et al, hereinafter Gluckman as applied to Claim 1 above, and further in view of U.S. Patent Publication 20200138320 awarded to Parvizi et al, hereinafter Parvizi.
Regarding Claims 7 and 19, Gluckman teaches the invention above. Gluckman does not teach wherein the accumulation of final confidence scores to generate the cumulative confidence score comprises a first order infinite impulse response (IIR) filter.
However, in the art of brain wave detection (abstract), Parvizi teaches using an IIR filter to improve signal clarity and reject non-seizure related brain waves (Para. 0063), and further teaches the usage of a specific filter such as an IIR filter is a known design choice to one of ordinary skill in the art (Para. 0063). Experimentally, this configuration was found to be the optimal choice for rejecting analog front-end DC-bias (Para. 0063).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Gluckman by Parvizi, i.e. by using the IIR filter in Parvizi in the system of Gluckman, for the predictable purpose of improving signal clarity and detection as taught above, and further as Parvizi teaches above that the usage is a known design choice for rejecting analog front-end DC-bias.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Jess Mullins whose telephone number is (571)-272-8977. The examiner can normally be reached between the hours of 9:00 a.m. to 5:00 p.m. PST M-F.
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/JLM/
Examiner, Art Unit 3792
/UNSU JUNG/Supervisory Patent Examiner, Art Unit 3792
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