DETAILED ACTION
Acknowledgements
This office action is in response to the claims filed August 05, 2025.
Claims 1-24 are pending.
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 .
Information Disclosure Statement(s)
The information disclosure statement (IDS) submitted on 08/05/2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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 to under 35 U.S.C 101 as not being directed to eligible subject matter based on the grounds set out in detail below:
Independent Claims 1, 9, and 17:
Eligibility Step 1 (does the subject matter fall within a statutory category?):Independent Claim 1 falls within the statutory category of method.
Claim 9 falls within the statutory category of machine.
Claim 17 falls within the statutory category of article of manufacture.
Eligibility Step 2A-1 (does the claim recite an abstract idea, law of nature, or natural phenomenon?): Independent claims 1, 9, and 17 claimed invention is directed to an abstract idea without significantly more.
The claim elements which set forth the abstract idea in the independent claims (Claim 1 as representative):
A …[…]…method comprising:
receiving data indicative of brainwave activity over a particular time period;
determining, based on the data, at least one metric associated with at least one sleep state for a subject;
determining, based on the at least one metric, a risk level associated with seizure activity for the subject;
and generating an output indicating the risk level.
The abstract idea is “certain methods of organizing human activity” by managing personal behavior and following rules and instructions to generate a risk level of seizure for a patient based on data received (see MPEP § 2106.04(a)(2))
Eligibility Step 2A-2 (does the claim recite additional elements that integrate the judicial exception into a practical application?): For Independent claims 1, 9, and 17 judicial exception is not integrated into a practical application.
Independent claim 1 recites the additional claim elements below:
A computer
Examiner takes the applicable considerations stated in MPEP 2106.04 (d) and analyzes them below in light of the instant applications disclosure and claim elements as a whole.
The additional element, A computer, is performing the abstract idea and is merely recited as “apply-it” or an equivalent as a computer tool to implement the abstract idea
Independent claim 9 recites the additional claim elements not already recited in independent claim 1 below:
A system comprising one or more data processors; and a non-transitory computer readable storage medium containing instructions
Examiner takes the applicable considerations stated in MPEP 2106.04 (d) and analyzes them below in light of the instant applications disclosure and claim elements as a whole.
The additional element, A system comprising one or more data processors; and a non-transitory computer readable storage medium containing instructions, is performing the abstract idea merely recited as “apply-it” or an equivalent as a computer tool to receive, analyze, and output data
Independent claim 17 recites the additional claim elements not already recited in independent claim 1 below:
A computer-program product tangibly embodied in a non-transitory machine- readable storage medium
Examiner takes the applicable considerations stated in MPEP 2106.04 (d) and analyzes them below in light of the instant applications disclosure and claim elements as a whole.
The additional element, A computer-program product tangibly embodied in a non-transitory machine- readable storage medium, is performing the abstract idea merely recited as “apply-it” or an equivalent as a computer tool to receive, analyze, and output data
Accordingly, independent claims 1, 9, and 17 as a whole do not integrate the recited abstract idea into a practical application (MPEP 2106.05(f) and 2106.04(d)(1).
Eligibility Step 2B (Does the claim amount to significantly more?): The independent claims do does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the computer element as analyzed above in step 2A prong 2, is merely applying the abstract idea and therefore, does not amount to significantly more. The claim is patent ineligible.
Dependent Claims 2-8, 10-16, and 18-24
Eligibility Step 1 (does the subject matter fall within a statutory category?):
The dependent claims 2-8 fall within the statutory category of method.
The dependent claims 10-16 fall within the statutory category of machine.
The dependent claims 18-24 fall within the statutory category of article of manufacture.
Eligibility Step 2A-1 (does the claim recite an abstract idea, law of nature, or natural phenomenon?): Dependent claims 2-8, 10-16, and 18-24 claimed invention is directed to an abstract idea without significantly more. The claims continue to limit the independent claim 1, 9, and 17 abstract idea by (1) further limiting the atleast one metric, (2) further limiting the particular sleep state, (3) further limiting receiving of data, (4) further limiting the particular time period, and (5) further limiting the output of the risk level. Therefore, the dependent claims inherit the same abstract idea which is “certain methods of organizing human activity” by managing personal behavior and following rules and instructions to generate a risk level of seizure for a patient based on data received (see MPEP § 2106.04(a)(2))
Eligibility Step 2A-2 (does the claim recite additional elements that integrate the judicial exception into a practical application?): For claims 2-8, 10-16, and 18-24 this judicial exception is not integrated into a practical application.
The dependent claims recite the below additional elements not already recited in the independent claims
a RF transmitter-receiver associated with a multi-electrode device
Examiner takes the applicable considerations stated in MPEP 2106.04 (d) and analyzes them below in light of the instant applications disclosure and claim elements as a whole.
The additional elements, a RF transmitter-receiver associated with a multi-electrode device, is recited as “apply-it” or an equivalent to gather data
Accordingly, the dependent claims as a whole do not integrate the recited abstract idea into a practical application (MPEP 2106.05(f) and 2106.04(d)(1).
Eligibility Step 2B (Does the claim amount to significantly more?): The dependent claims do not include additional elements that amount to significantly more for the same reasons given in Prong 2. The claims are patent ineligible.
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.
Claims 1-6, 9-14, and 17-22 are rejected under 35 U.S.C. 103 as being unpatentable over Giftakis et. al (hereinafter Giftakis) (US8812098B2) in view of Karoly et. al (hereinafter Karoly) (CA3070980C)
As per claim 1, Giftakis teaches:
A computer-implemented method comprising: receiving data indicative of brainwave activity over a particular time period; (Col. 6 lines 31-42 discloses, “In the example illustrated in FIG. 1, therapy system 10 includes a sensing module that senses bioelectrical signals within brain 24 of patient 12. The bioelectrical brain signals may reflect changes in electrical current produced by the sum of electrical potential differences across brain tissue. Examples of bioelectrical brain signals include, but are not limited to, an EEG signal, an ECoG signal, a local field potential (LFP) sensed from within one or more regions of a patient's brain, and action potentials from single cells within the patient's brain. In addition, in some examples, a bioelectrical brain signal includes a signal indicative of the measured impedance of tissue of brain 24 over time.”)
determining, based on the data, at least one metric associated with at least one sleep state for a subject; (Col. 6 lines 49-59 and Col. 7 lines 18-20 discloses, “IMD 16 or another component of system 10 may determine a sleep stage of patient 12, using any suitable technique. For example, as described in further detail below, a processor of IMD 16 may determine the sleep stage patient 12 is in based on a frequency characteristic of one or more bioelectrical brain signals of patient 12 sensed via electrodes 22A, 22B of leads 20A and 20B, respectively, or via a separate electrode array that is electrically coupled to IMD 16 or a separate sensing device. In some examples, the bioelectrical brain signal may be detected from external electrodes that are placed on the patient's scalp to sense brain signals….[…]…IMD 16 may determine that patient 12 is in a particular sleep stage, e.g., REM sleep, during a particular period of time.”/ examiner notes instant application defines in [0007] sleep metric as time for a particular sleep state)
determining, based on the at least one metric, a risk level associated with seizure activity for the subject; (Col. 7 lines 21-39 discloses, “For example, IMD 16 may determine whether or not patient 12 experienced or is experiencing a seizure event at some point during the particular period of time. Based on the seizure state of patient 12 during the particular sleep stage, IMD 16 may subsequently 25 generate a seizure probability metric for the particular sleep stage. As noted above, the seizure probability metric may be indicative of the probability or likelihood that patient 12 will experience a seizure event during the particular sleep stage. In some examples, IMD 16 collects such seizure state data over 30 a period of time during which patient 12 experiences the particular sleep stage multiple different times in order to generate the seizure probability metric for the particular sleep stage, as described in further detail below with respect to FIG. 6. In some examples, IMD 16 may collect seizure state data 35 over an extended period of time, e.g., days, weeks, months, and the like, and generate a seizure probability metric for one or more sleep stages that is cumulative based on all or a portion of the collected data.”)
However, Giftakis does not explicitly teach:
and generating an output indicating the risk level.
However, Karoly does teach:
and generating an output indicating the risk level. (see fig. 25 and see [0184] discloses, “feedback provided by the one or more output devices 206 may include information concerning seizure likelihood in a subject, particularly a subject to which information recorded by the measurement unit 204 relates. Such information may include one or more of a seizure probability, a seizure risk rating, information concerning the cause of risk elevation (e.g. time of day, weather conditions, etc.). Such information may he portrayed graphically or through the use of auditory or haptic feedback (as discussed above).”)
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Giftakis’s teachings as previously cited with Karoly’s teachings as previously cited, the motivation being Giftakis teaches in Col. 21 and Col. 31 generating a seizure probability metric for each sleep stage and a user interface for a seizure probability profile for the patient, therefore it would be obvious to one of ordinary skill that a probability metric is a main input to a risk level and Giftakis also has hardware with user interface display therefore in combination with Karoly’s severity risk rating it would be obvious to display in the same manner without Giftakis becoming inoperable as well as improve further transparency and precision of data for patient care coordination.
As per claim 2, Giftakis further teaches:
The computer-implemented method of claim 1, wherein the at least one metric is an amount of time for a particular sleep state. (Col.7 lines 18-20 discloses, “IMD 16 may determine that patient 12 is in a particular sleep stage, e.g., REM sleep, during a particular period of time.”)
As per claim 3, Giftakis further teaches:
The computer-implemented method of claim 2, wherein the particular sleep state is a rapid eye movement (REM) state of sleep. (Col.7 lines 18-20 discloses, “IMD 16 may determine that patient 12 is in a particular sleep stage, e.g., REM sleep, during a particular period of time.”)
As per claim 4, Giftakis further teaches:
The computer-implemented method of claim 1, wherein the data is received from a RF transmitter-receiver associated with a multi-electrode device. (Col. 12 lines 58-61 discloses, “Programmer 14 may communicate via wireless communication with IMD 16 using radio frequency (RF) telemetry techniques known in the art.” And see Col. 5 lines 9-12 discloses, “Therapy system 10 includes external programmer 14, implantable medical device (IMD) 16, lead extension 18, and 10 one or more leads 20A and 20B with respective sets of electrodes 22A and 22B.” and Col. 9 lines 46-52 discloses, “For example, in some examples, at least some of the electrodes 22A, 22B of leads 20 have a complex electrode array geometry that is capable of producing shaped electrical fields. The complex electrode array geometry may include multiple electrodes (e.g., partial ring or segmented electrodes) around the outer perimeter of each lead 20, rather than one ring electrode.”)
As per claim 5, Giftakis further teaches:
The computer-implemented method of claim 1, wherein the particular time period is a first time period, and wherein the risk level is a prediction of a likelihood of the subject experiencing the seizure activity for a second time period, wherein the second time period occurs subsequent to the first time period. (see fig. 7 and fig. 8)
As per claim 6, Giftakis further teaches:
The computer-implemented method of claim 1, wherein the output is a first output and further comprising: identifying, based on the risk level, a treatment recommendation; and generating a second output indicating the treatment recommendation, the treatment recommendation usable to reduce the risk level. (Col. 8 lines 41-48 discloses, “As an illustration, if IMD 16 determines that patient 12 is experiencing a sleep stage where the seizure probability metric indicates a relatively high likelihood of patient 12 experiencing a seizure, IMD 16 may initiate the delivery of therapy to patient 12 or adjust one or more parameters of therapy being delivered to patient 12 to define a relatively aggressive therapy while patient 12 occupies the particular sleep stage.”)
As per claims 9-14, they are system claims which repeat the same limitations of claims 1-6 the corresponding method claims, as a collection of elements as opposed to a series of process steps. Since the teachings of Giftakis and Karoly as well as motivations to combine disclose the underlying process steps that constitute the methods of claims 1-6 it is respectfully submitted that they provide the underlying structural elements that perform the steps as well. As such, the limitations of claims 9-14 are rejected for the same reasons given above for claims 1-6.
As per claims 17-22 they are article of manufacture claims which repeats the same limitations of claim 1-6 the corresponding method claim, as a collection of executable instructions stored on machine readable media as opposed to a series of process steps. Since the teachings of Giftakis and Karoly as well as motivations to combine disclose the underlying process steps that constitute the method of claims 1-6 it is respectfully submitted that they likewise disclose the executable instructions that perform the steps as well. As such, the limitations of claims 17-22 are rejected for the same reasons given above for claims 1-6.
Claims 7, 15, and 23 are rejected under 35 U.S.C. 103 as being unpatentable over Giftakis et. al (hereinafter Giftakis) (US8812098B2) in view of Karoly et. al (hereinafter Karoly) (CA3070980C) and in further view of Blackwell et. al (hereinafter Blackwell) (US10827926B2)
As per claim 7, Giftakis does not teach:
The computer-implemented method of claim 1, wherein the at least one metric is a first metric and determining, based on the at least one metric, the risk level further comprises: determining a second metric for a healthy population based on historical data; identifying a statistically significant difference between the first metric and the second metric based on a comparison of the first metric and the second metric; and determining, based on the statistically significant difference, the risk level.
However, Karoly does teach the underlined portions:
The computer-implemented method of claim 1, wherein the at least one metric is a first metric and determining, based on the at least one metric, the risk level further comprises: determining a second metric for a healthy population based on historical data; identifying a statistically significant difference between the first metric and the second metric based on a comparison of the first metric and the second metric; and determining, based on the statistically significant difference, the risk level. ([0029] discloses, “ According to another aspect of the disclosure, there is provided a seizure advisory system, comprising: an input for receiving historical data associated with epileptic events experienced by the subject over a first time period, the historical data comprising physiological data associated with each epileptic event and a time at which each epileptic event occurred; a processor configured to:…[…]… epileptic eve the temporal probability model representing a probability of a future seizure occurrence over a set of time windows; generate a probabilistic model based on the physiological data associated with each epileptic event; weight the probabilistic model based on the temporal probability model to generate a weighted probabilistic model of future seizure activity; and output an estimate of seizure probability in the subject using the weighted probabilistic model.”)
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Giftakis’s teachings as previously cited with Karoly’s teachings as previously cited for the same reasons given in claim 1.
However, Karoly does not teach these underlined portions:
The computer-implemented method of claim 1, wherein the at least one metric is a first metric and determining, based on the at least one metric, the risk level further comprises: determining a second metric for a healthy population based on historical data; identifying a statistically significant difference between the first metric and the second metric based on a comparison of the first metric and the second metric; and determining, based on the statistically significant difference, the risk level
However, Blackwell does teach the underlined portions:
The computer-implemented method of claim 1, wherein the at least one metric is a first metric and determining, based on the at least one metric, the risk level further comprises: determining a second metric for a healthy population based on historical data; identifying a statistically significant difference between the first metric and the second metric based on a comparison of the first metric and the second metric; and determining, based on the statistically significant difference, the risk level (Col. 6 lines 5-10 discloses, “ The system can monitor the collective behavioural data in real time and compares the data against baselines which include one or more of: historic data of the user; relevant validated data sets for general populations; and relevant validated data sets for populations with specific neurological disorders.” And see Col. 7 lines 35-46 discloses, “Where the system identifies a risk to health or that the cognitive performance of the individual is outside normal values, the system can display relevant messages or information to the individual on the user interface and/or activate additional cognitive tests or questions through the user interface, preferably through a wearable device and/or a smartphone. The individual's response to such tests, taken together with all previous behavioural data, can be further analysed and compared against historic data of the user and relevant validated data sets for both the general populations and populations with neurological disorders.”)
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Giftakis’s teachings as previously cited and Karoly’s teachings as previously cited with Blackwell’s teachings as previously cited, the motivation being Giftakis (e.g. Col. 16) and Karoly (e.g. [0092]) both disclose utilizing historical data templates of known brain waveforms and clinical trial historical data used to determine statistically based risk respectively, therefore it would not be unpredictable to compare to a healthy full population of data as the hardware and analysis would remain the same with this additional data.
As per claim 15, they are system claims which repeat the same limitations of claim 7 the corresponding method claims, as a collection of elements as opposed to a series of process steps. Since the teachings of Giftakis, Karoly, and Blackwell as well as motivations to combine disclose the underlying process steps that constitute the methods of claim 7 it is respectfully submitted that they provide the underlying structural elements that perform the steps as well. As such, the limitations of claim 15 are rejected for the same reasons given above for claims 7.
As per claim 23 it is an article of manufacture claims which repeats the same limitations of claim 7 the corresponding method claim, as a collection of executable instructions stored on machine readable media as opposed to a series of process steps. Since the teachings of Giftakis, Karoly, and Blackwell as well as motivations to combine disclose the underlying process steps that constitute the method of claim 7 it is respectfully submitted that they likewise disclose the executable instructions that perform the steps as well. As such, the limitations of claim 23 is rejected for the same reasons given above for claim 7.
Claims 8, 16, and 24 are rejected under 35 U.S.C. 103 as being unpatentable over Giftakis et. al (hereinafter Giftakis) (US8812098B2) in view of Karoly et. al (hereinafter Karoly) (CA3070980C) and in further view of Roberson (US20130144652A1)
As per claim 8, Giftakis and Karoly do not explicitly teach:
The computer-implemented method of claim 1, wherein generating the output indicating the risk level further comprises: providing the output indicating a high-risk level in a first color; providing the output indicating a moderate risk level in a second color; and providing the output indicating a low risk level in a third color.
However, Roberson does teach:
The computer-implemented method of claim 1, wherein generating the output indicating the risk level further comprises: providing the output indicating a high-risk level in a first color; providing the output indicating a moderate risk level in a second color; and providing the output indicating a low risk level in a third color. ([0066] discloses, “In some embodiments, the complexity of the medical record may be used to identify different levels of a risk of an adverse event. The level of the risk may increase as the value of the complexity increases. In embodiments in which different levels of risk are determined, an indication of the determined level of risk may be output to a user in any suitable way. For example, in one implementation, a level of risk may be associated with a different color indicator displayed on a user interface of a computer. Exemplary color indicators may be a green indicator for low-risk patients, a yellow indicator for moderate risk patients, and a red indicator for high-risk patients.”)
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Giftakis’s teachings as previously cited and Karoly’s teachings as previously cited with Roberson’s teachings as previously cited, the motivation being Giftakis and Karoly both disclose interface and probabilities of seizure activity with Karoly additionally disclosing risk levels output on a user interface in terms of severity as previously aforementioned, therefore it would not be unpredictable to display further color related differentiation as this is a simple choice as the hardware and analysis would remain the same with this additional representation.
As per claim 16, they are system claims which repeat the same limitations of claim 8 the corresponding method claims, as a collection of elements as opposed to a series of process steps. Since the teachings of Giftakis, Karoly, and Roberson as well as motivations to combine disclose the underlying process steps that constitute the methods of claim 8 it is respectfully submitted that they provide the underlying structural elements that perform the steps as well. As such, the limitations of claim 16 are rejected for the same reasons given above for claims 8.
As per claim 24 it is an article of manufacture claims which repeats the same limitations of claim 8 the corresponding method claim, as a collection of executable instructions stored on machine readable media as opposed to a series of process steps. Since the teachings of Giftakis, Karoly, and Roberson as well as motivations to combine disclose the underlying process steps that constitute the method of claim 8 it is respectfully submitted that they likewise disclose the executable instructions that perform the steps as well. As such, the limitations of claim 24 is rejected for the same reasons given above for claim 8.
Prior Art not cited but made of record
US20230397876Al – VIELUF et. al
A Systems and methods of the present disclosure enable improved seizure detection and/or prediction using a seizure monitoring system. The system receives a data stream including wearable sensor data associated with a user, where the data stream includes electrodermal activity data and where the electrodermal activity data includes circadian rhythm-dependent amplitudes. The system receives a time associated with a seizure of the user. The system trains seizure machine learning model to identify a pre-ictal period associated with a time segment based on the circadian rhythm dependent amplitudes and the time associated with the seizure. The system deploys the seizure machine learning model to ingest a new data stream. Based on the new data stream, the seizure machine learning model predicts a seizure likelihood in a prediction period.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Ashley Elizabeth Evans whose telephone number is (571) 270-0110. The examiner can normally be reached Monday – Friday 8:00 AM – 5:00 PM.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Mamon Obeid can be reached on (571) 270-1813. The fax phone number for the organization where this application or proceeding is assigned 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. Should you have questions on access to the Patent Center, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free).
/ASHLEY ELIZABETH EVANS/Examiner, Art Unit 3687
/MAMON OBEID/Supervisory Patent Examiner, Art Unit 3687
Prosecution Insights