.
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 § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 21, 28, and 29 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 21 recites the limitation “the predetermined threshold range of one or more m(j) values is less than -15; and wherein the predetermined threshold range of the sum of all negative m(j) values is less than -15”. The claim mentions a predetermined threshold range but only gives one end of the threshold range. What is the threshold range? What are the units? Is it less than -15 millivolts? What is the value of -15 representing? It is unclear. Clarification is requested. For the purpose of examination, claim 21 is being interpreted such that the high probability of stroke is determined when one or more m(j) values is below -15.
Claim 28 recites the limitation “the size of the stroke is determined to be 100 ml or more based on an m(j) value of -20 or less, and the size of the stroke is determined to be less than 100 ml based on an m(j) value of greater than -20.”. What is m(j) referring to in this claim? Is it a value of the map matrix or something else? Also, what does it mean to determine the size of a stroke in milliliters? Clarification is requested.
Claim 29 recites the limitation “generating a combined relative electrical activity by combining the relative electrical activity from the EEG data from the first time period and the relative electrical activity from the EEG data from the first time period”. How can you combine relative electrical activity from the EEG from the first time period with itself? This is unclear. For the purpose of examination, claim 29 is being interpreted such that a combined relative electrical activity is generated by combining the relative electrical activity from the EEG data from the first time period and the relative electrical activity from the EEG from the second time period.
Claims not explicitly rejected above are rejected due to their dependence on a rejected base claim.
Claim Rejections - 35 USC § 101
Claims 1-5, 7-8, 12-21, 24-25, 27-30 and 58 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) as a whole, considering all claim elements both individually and in combination, do not amount to significantly more than an abstract idea. A streamlined analysis of claim 30 follows.
Step 1: Regarding claim 30, the claim recites a controller configured to perform a series of steps or acts, including obtaining electroencephalography data, determining relative electrical activity, determining the probability that a subject had a stroke, and instructing a communication device to communicate the determined probability. Thus, the claim is directed to a machine, which is one of the statutory categories of invention.
Step 2A, Prong One: The claim is then analyzed to determine whether it is directed to any judicial exception. The steps of determining relative electrical activity and determining the probability that a subject had a stroke set forth a judicial exception. The step of determining the probability that a subject had a stroke describes a concept performed in the human mind (including an observation, evaluation, judgment, opinion). The step of determining relative electrical activity describes mathematical relationships, mathematical formulas or equations, or mathematical calculations. Thus, the claim is drawn to a Mental Process and a Mathematical Concept, which are both an Abstract Idea. While the function is performed by a controller (a computer), according to section 2106.05(f) of the MPEP, merely using a computer as a tool to perform an Abstract Idea does not integrate the Abstract Idea into a practical application.
Step 2A, Prong Two: Next, the claim as a whole is analyzed to determine whether the claim recites additional elements that integrate the judicial exception into a practical application. The claim fails to recite an additional element or a combination of additional elements to apply, rely on, or use the judicial exception in a manner that imposes a meaningful limitation on the judicial exception. While claim 30 recites determining the probability that the subject experienced a stroke near one or more scalp locations, it fails to recite any practical application of determining the probability that the subject experienced a stroke. The determination of the probability that the subject experienced a stroke does not provide an improvement to the technological field, the method does not effect a particular treatment or effect a particular change based on the detection, nor does the controller use a particular machine to perform the Abstract Idea.
Step 2B: Next, the claim as a whole is analyzed to determine whether any element, or combination of elements, is sufficient to ensure that the claim amounts to significantly more than the exception. Besides the Abstract Idea, the claim recites obtaining electroencephalography data, electrodes positioned at scalp locations on the head of the subject, and instructing a communication device to communicate the determined probability. The electrodes and obtaining electroencephalography data are recited at a high level of generality such that it amounts to insignificant presolution activity e.g., mere data gathering step necessary to perform the Abstract Idea. Instructing a communication device to communicate the determined probability is merely adding insignificant extra solution activity to the Abstract Idea. When recited at this high level of generality, there is no meaningful limitation, such as a particular or unconventional function that distinguishes it from well-understood, routine, and conventional data gathering and comparing activity engaged in by medical professionals prior to Applicant's invention. Furthermore, it is well established that the mere physical or tangible nature of additional elements such as the electrodes do not automatically confer eligibility on a claim directed to an abstract idea (see, e.g., Alice Corp. v. CLS Bank Int'l, 134 S.Ct. 2347, 2358-59 (2014)).
Consideration of the additional elements as a combination also adds no other meaningful limitations to the exception not already present when the elements are considered separately. Unlike the eligible claim in Diehr in which the elements limiting the exception are individually conventional, but taken together act in concert to improve a technical field, the claim here does not provide an improvement to the technical field. Even when viewed as a combination, the additional elements fail to transform the exception into a patent-eligible application of that exception. Thus, the claim as a whole does not amount to significantly more than the exception itself. The claim is therefore drawn to non-statutory subject matter.
The dependent claim also fails to add something more to the abstract independent claim as it generally recites a generic device comprising generic components configured to perform the abstract idea. The recited communication device and alert device are generically claimed components configured to perform extra-solutional data communication. The electrodes are a generically claimed component configured to perform pre-solutional data gathering. The determining steps recited in the independent claims maintain a high level of generality even when considered in combination with the dependent claims.
The same rationale applies to claim 1. Claim 1 is directed to a method for performing the Abstract Idea. While claim 1 recites treating the subject for a high probability of stroke, it is noted that the treatment of the subject is not positively tied to any of the steps performed before it. The Abstract Idea itself is not tied to any of (1) an improvement to the technological field, (2) effecting a particular treatment or change based on the determined high probability or stroke, or (3) a particular machine.
The dependent claims fail to add something more to the abstract independent claim as they generally recite method steps pertaining to data gathering or steps capable of being performed mentally and/or by hand. The additional stroke detection measurement is insignificant extra-solution activity. The step of treating the subject for a high probability of stroke is not tied to a step performed before, such as a determination of a high risk of stroke. The determining steps recited in the independent claims maintain a high level of generality even when considered in combination with the dependent claims.
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.
Claims 1-5, 25, 29, 30, and 58 are rejected under 35 U.S.C. 103 as being unpatentable over Pulkit et al. (US 20210298659 A1 – Cited by Applicant), hereinafter referred to as Pulkit, in view of Schulhauser et al. (US 20220061678 A1) hereinafter referred to as Schulhauser.
Regarding claim 1, Pulkit discloses a method of assessing whether a subject had a stroke and treating the subject accordingly, the method comprising: (a) recording electroencephalography (EEG) data from electrodes positioned at scalp locations on the head of the subject (Figure 1(a), [0016]); (b) determining relative electrical activities from the EEG data, wherein the determining comprises: determining the relative electrical activity at each scalp location compared to electrical activity at all scalp locations; and determining the relative electrical activity at each scalp location compared to electrical activity at its corresponding contralateral scalp location ([0009], “By accounting for the contributions of different sources to the power of the recorded signals, and using a hemispheric baseline approach and a convex spectral clustering framework, the method permits rapid detection and localization of a single region or multiple regions of silence in the brain using a relatively small amount of EEG data (on the order of a few minutes)”). Pulkit does not disclose determining a high probability of stroke based on the determined relative electrical activities and treating the subject for a high probability of stroke. Schulhauser teaches determining a high probability of stroke ([0007], “the disclosure is directed to techniques for generating at least one of a detection, prediction, or a classification of a condition of the patient, such as stroke”, [0153], “processing circuitry 110 applies one or more detection, prediction, and/or classification algorithms to the parameter values and/or signals to detect, predict, and/or classify one or more patient conditions (708). In some examples, a result of the algorithm is a probability, e.g., risk of the condition”) and treating a subject for a high probability of stroke ([0193], “Server 604 may determine a preferential treatment pathway for the patient based on the emergency condition and location of the patient (1406). Certain patient conditions, such as LVO stroke, are best treated at particular hospitals or medical centers and by certain physicians... Server 604 may alert the medical center of the patient condition (1410), which may begin preparing appropriate treatments and equipment for the arrival of the patient in response to the notification.”). It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to have modified the method of Pulkit such that it includes determining a high probability of stroke and treating the subject for a high probability of stroke because treatment outcomes for stroke patients are highly time-dependent (Schulhauser, [0044]). Regarding claim 2, Pulkit further discloses that the scalp electrodes are positioned at four or more locations (Figure 1(a)).
Regarding claim 3, Pulkit discloses all of the limitations of the claim except performing an additional stroke detection measurement. Schulhauser teaches performing multiple measurements of a parameter, including electrical activity ([0066], “The plurality of parameter values may represent a sequence of parameter values over time, where each parameter value of the sequence of parameter values are collected by sensor device 106 for each time interval of a sequence of time intervals. For example, sensor device 106 may perform a parameter measurement in order to determine a parameter value of the sequence of parameter values according to a recurring time interval ”). It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to have modified the method of Pulkit such that it includes performing an additional stroke detection measurement because it allows for the tracking of the patient electrical activity over time (Schulhauser, [0066]).
Regarding claim 4, Pulkit further discloses that the additional stroke detection measurement is a brain magnetic resonance image (MRI) or head computed tomography (CT) scan (Figure 1(d), [0020]).
Regarding claim 5, Pulkit discloses all of the limitations of the claim as discussed above except that treating the subject for a high probability of stroke comprises medical or surgical intervention to reverse or minimize the effect of stroke; or wherein treating the subject for a high probability of stroke comprises transporting the subject to a medical facility, notifying the medical facility of a high probability of stroke, or a combination thereof. Schulhauser teaches a method where treating a subject for a high probability of stroke comprises medical intervention to reverse or minimize the effects of a stroke and transporting the subject to a hospital and alerting the medical facility of a high probability of stroke ([0193], “Server 604 may alert the medical center of the patient condition (1410), which may begin preparing appropriate treatments and equipment for the arrival of the patient in response to the notification.”). It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to have modified the method of Pulkit such that it includes treating the subject for a high probability of stroke comprises medical or surgical intervention to reverse or minimize the effect of stroke; or wherein treating the subject for a high probability of stroke comprises transporting the subject to a medical facility, notifying the medical facility of a high probability of stroke, or a combination thereof because it is important to treat the patient as soon as possible because treatment outcomes for stroke patients are highly time-dependent (Schulhauser, [0044]).
Regarding claim 25, Pulkit discloses all of the limitations of the claim as discussed above except that the probability of stroke is the probability of an ischemic stroke or hemorrhagic stroke. Schulhauser teaches using a classification algorithm to determine the type of stroke ([0154], “Classification algorithms may include an etiology classifier that can make a determination (probabilistic or definitive) of the origin or type of the condition (e.g., ischemic or hemorrhagic, or which hemisphere, for stroke).”). It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to have modified the method of Pulkit such that it includes that the probability of stroke is the probability of an ischemic stroke or hemorrhagic stroke because the different types of strokes have different treatments (Schulhauser, [0005]).
Regarding claim 29, Pulkit discloses all of the limitations of the claim as discussed above except repeating the recording of the EEG data during a second time period; determining the relative electrical activities from the EEG data from one or more additional time periods; generating a combined relative electrical activity by combining the relative electrical activity from the EEG data from the first time period and the relative electrical activity from the EEG data from the first time period; and determining a high probability of stroke based on the combined relative electrical activities. Schulhauser teaches a method where there is a learning period in the past and EEG recording is repeated, electrical activities are determined from the EEG data in another time period, and a combined relative electrical activity is generated from the activity of the first time period and the activity of the second time period which is used to determine a probability of stroke ([0153], [0157], “Processing circuitry 804 may further normalize one or more parameter values relative to a baseline value for the patient (804). The baseline value may be derived from values of the parameter determined for the patient in the past, such as an average of values preceding the current value by a certain amount of time, or from a certain baseline or learning period in the past. Normalizing may include any comparative or mathematical operation using the determined and baseline values, such as a difference operation. ”). It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to have modified the method of Pulkit such that it includes repeating the recording of the EEG data during a second time period; determining the relative electrical activities from the EEG data from one or more additional time periods; generating a combined relative electrical activity by combining the relative electrical activity from the EEG data from the first time period and the relative electrical activity from the EEG data from the first time period; and determining a high probability of stroke based on the combined relative electrical activities because it allows for accounting for patient to patient variation, which increases the sensitivity and specificity of detection of conditions, including stroke (Schulhauser, [0157]).
Regarding claim 30 Pulkit discloses obtaining electroencephalography (EEG) data from electrodes positioned at scalp locations on the head of the subject (Figure 1(a), [0016]); determining relative electrical activities from the EEG data, wherein the calculating comprises: determining the relative electrical activity at each scalp location compared to electrical activity at all scalp locations; and determining the relative electrical activity at each scalp location compared to electrical activity at its corresponding contralateral scalp location ([0009], “By accounting for the contributions of different sources to the power of the recorded signals, and using a hemispheric baseline approach and a convex spectral clustering framework, the method permits rapid detection and localization of a single region or multiple regions of silence in the brain using a relatively small amount of EEG data (on the order of a few minutes)”). Pulkit does not disclose a controller for assessing whether a subject had a stroke and communicating the results of the assessment, determining the probability that the subject experienced a stroke near one or more scalp locations based on the relative electrical activities, and electronically instructing a communication device to communicate the determined probabilities. Schulhauser teaches a method where a controller ([0119], “Processing circuitry 402 may include any one or more of a microprocessor, a GPU, a TPU, a controller, a DSP, an ASIC, an FPGA, or equivalent discrete or analog logic circuitry”) is configured to assess whether a subject had a stroke and communicate the results of the assessment, determine the probability that the subject experienced a stroke near one or more scalp locations based on the relative electrical activities ([0007], “the disclosure is directed to techniques for generating at least one of a detection, prediction, or a classification of a condition of the patient, such as stroke”, [0153], “processing circuitry 110 applies one or more detection, prediction, and/or classification algorithms to the parameter values and/or signals to detect, predict, and/or classify one or more patient conditions (708). In some examples, a result of the algorithm is a probability, e.g., risk of the condition”), and electronically instruct a communication device to communicate the determined probabilities ([0142], “In some examples, external device 500 may provide an alert to the patient or another entity (e.g., a call center) based on a condition detection, prediction, or classification provided by sensor device”). It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to have modified the system of Pulkit such that it includes a controller for assessing whether a subject had a stroke and communicating the results of the assessment, determining the probability that the subject experienced a stroke near one or more scalp locations based on the relative electrical activities, and electronically instructing a communication device to communicate the determined probabilities because treatment outcomes for stroke patients are highly time-dependent so communication of a prediction or classification is important (Schulhauser, [0044]).
Regarding claim 58, Pulkit discloses electrodes (Figure 1(a), [0012]). Pulkit does not disclose a controller; and one or more of the communication device, and an alert device. Schulhauser discloses a controller, a communication device , and an alert device ([0119], ““Processing circuitry 402 may include any one or more of a microprocessor, a GPU, a TPU, a controller, a DSP, an ASIC, an FPGA, or equivalent discrete or analog logic circuitry”, [0142], “In some examples, external device 500 may provide an alert to the patient or another entity (e.g., a call center) based on a condition detection, prediction, or classification provided by sensor device”). It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to have modified the system of Pulkit such that it includes a controller; and one or more of the communication device, an alert device because treatment outcomes for stroke patients are highly time-dependent so communication of a prediction or classification is important (Schulhauser, [0044]).
Claims 7, 8, 12, 13, 15, 27 are rejected under 35 U.S.C. 103 as being unpatentable over Pulkit in view of Schulhauser further in view of Shahaf et al. (US 20230240584 A1 ), hereinafter referred to as Shahaf.
Regarding claim 7, Pulkit in view of Schulhauser discloses all of the limitations of the claim as discussed above except that the subject had an elevated risk of stroke before the recording; or that the subject is unconscious. Shahaf teaches a method of monitoring and detecting stroke in patients who have risk of developing a stroke ([0082], “the device is used to monitor a clinical condition in a risk to develop stroke”) or patients who are unconscious (Figure 4A, block 402, [0050], “the at least one parameter of the penumbra is estimated while the subject is sedated and/or anesthetized, for example during a surgical procedure.”). It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to have modified the method of Pulkit in view of Schulhauser such that it includes that the subject had an elevated risk of stroke before the recording; or that the subject is unconscious because it allows for a surgical procedure to be modified based on the results of the recording (Shahaf, [0050]).
Regarding claim 8, Pulkit in view of Schulhauser discloses all of the limitations of the claim as discussed above except that the elevated risk of stroke comprises a risk selected from the group consisting of: altered mental status, loss of motor function, loss of sense of touch in a body part, dizziness, headache, and difficulty speaking; or wherein the elevated risk of stroke comprises a risk selected from the group consisting of: head trauma, hematoma, and subarachnoid hemorrhage; or wherein the elevated risk of stroke comprises a risk selected from the group consisting of: currently receiving surgery and receiving surgery within the past 30 days. Shahaf teaches a method of monitoring and detecting stroke in patients who are currently receiving surgery ([0050], “the at least one parameter of the penumbra is estimated while the subject is sedated and/or anesthetized, for example during a surgical procedure.”). It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to have modified the method of Pulkit in view of Schulhauser such that it includes that the elevated risk of stroke comprises a risk selected from the group consisting of: altered mental status, loss of motor function, loss of sense of touch in a body part, dizziness, headache, and difficulty speaking; or wherein the elevated risk of stroke comprises a risk selected from the group consisting of: head trauma, hematoma, and subarachnoid hemorrhage; or wherein the elevated risk of stroke comprises a risk selected from the group consisting of: currently receiving surgery and receiving surgery within the past 30 days because it allows for a surgical procedure to be modified based on the results of the recording (Shahaf, [0050]).
Regarding claim 12, Pulkit in view of Schulhauser discloses generating matrices of sources, measurements, and source signals (Pulkit [0019]). Pulkit in view of Schulhauser also discloses comparing the relative power of electrical activity at a frequency and scalp location to the power of electrical activity at all scalp locations (Schulhauser [0160]). Pulkit in view of Schulhauser does not disclose determining the relative electrical activities from the EEG data comprises: generating matrix A from the EEG data, wherein matrix A comprises elements a(t, j), wherein a(t, j) refers to the amplitude of electrical activity at time t and scalp location j generating matrix B from matrix A, wherein matrix B comprises elements a(f, j), wherein a(f, j) refers to the power of electrical activity at frequency f and scalp location generating symmetry matrix S comprising elements s(f, j), wherein s(f, j) refers to the relative power of electrical activity at frequency f and scalp location j compared to the power of electrical activity at frequency f and scalp location j* that is contralateral to scalp location j. Shahaf teaches a method of determining stroke where a relation is determined between the timing and duration of signals and the amplitude and frequency ([0069]). Shahaf also teaches using the power of the electrical activity as a way of detecting stroke ([0166]) and teaches comparing power of electrical activity between opposite sides of the brain ([0041], [0069]). It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to have modified the method of Pulkit in view of Schulhauser such that it includes generating matrix A from the EEG data, wherein matrix A comprises elements a(t, j), wherein a(t, j) refers to the amplitude of electrical activity at time t and scalp location j generating matrix B from matrix A, wherein matrix B comprises elements a(f, j), wherein a(f, j) refers to the power of electrical activity at frequency f and scalp location generating symmetry matrix S comprising elements s(f, j), wherein s(f, j) refers to the relative power of electrical activity at frequency f and scalp location j compared to the power of electrical activity at frequency f and scalp location j* that is contralateral to scalp location j because those parameters can be used to differentiate between healthy brain tissue and brain tissue affected by a stroke (Shahaf, [0070], [0166]).
Regarding claim 13, Pulkit in view of Schulhauser further discloses that each r(f, j) is generated by comparing a(f, j) to the mean of a(f) values from all scalp locations j (Schulhauser, [0157], “Processing circuitry 804 may further normalize one or more parameter values relative to a baseline value for the patient (804). The baseline value may be derived from values of the parameter determined for the patient in the past, such as an average of values preceding the current value by a certain amount of time…Normalizing may include any comparative or mathematical operation using the determined and baseline values, such as a difference operation”).
Regarding claim 15, Pulkit in view of Schulhauser further discloses dividing a(f,j) by a(f,j*) where j is a scalp location that is contralateral to scalp location j (Pulkit, [0011], “This motivates the use of a hemispheric baseline, i.e., instead of using β, {tilde over (β)} is defined as the ratio of β values of the mirrored sources from the opposite hemisphere of the brain, e.g., for source pair (A.sub.L, A.sub.R), which are remote from the region of silence(s), {tilde over (β)} is close to 1, shown as the red-colored areas, while for (B.sub.L, B.sub.R), where B.sub.R is located in the region of silences (see FIG. 1(d)), this ratio is close to zero (i.e., yellow-colored sources)”).
Regarding claim 27, Pulkit in view of Schulhauser discloses all of the elements of the claim as discussed above except determining the size of the stroke based on the relative electrical activities. Shahaf teaches a method where the size of the ischemic core is estimated based on EEG signals ([0047], “According to some embodiments, the at least one parameter of the stroke event comprises an occurrence of a stroke event, a location of an ischemic core in the brain and/or a size of the ischemic core.” [0048], “According to some embodiments, the at least one parameter of the stroke event is estimated based on EEG signals recorded by at least 2 EEG electrodes positioned in anterior locations on a scalp of a subject, where each of the anterior locations is above a different hemisphere of a brain of the subject”). It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to have modified the method of Pulkit in view of Schulhauser such that it includes determining the size of the stroke based on the relative electrical activities because it would merely be combining prior art elements according to known methods to yield predictable results. Knowing the size of the stroke allows clinicians to estimate the severity and alter their treatment accordingly.
Claims 14 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Pulkit in view of Schulhauser further in view of Shahaf further in view of Smulders et al. (Single-trial log transformation is optimal in frequency analysis of resting EEG alpha), hereinafter referred to as Smulders.
Regarding claim 14, Pulkit in view of Schulhauser discloses comparing an amplitude value to an average amplitude value using any comparative mathematical operation, which includes division, as discussed above. Pulkit in view of Schulhauser does not disclose that the normalization is log2 transformed. Smulders teaches that log transforms result in a less skewed distribution when normalizing values (Theoretical implications, paragraph 5, “In both cases, the log-transform performed best in transforming toward normality. Likewise, Davidson et al. (1990), comparing the log and square root (level-2) transform, concluded that the log-transform resulted in a less-skewed distribution. As argued above, our data suggest that the same transform on single epochs (level 1) is sufficient to achieve normality and is preferable.”) and that the base of the logarithm does not matter for a log transformation (Alpha magnitude: transformations, paragraph 2, “Fifth, the base of the log does not matter to the results of t-tests or ANOVAs, as log-transforms with a different base are linearly related, as shown by the change-of-base formula: loga(x) = logb(x)/logb(a).”). It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to have modified the method of Pulkit in view of Schulhauser in view of Shahaf such that it includes taking log2 of the amplitude at a frequency and location divided by the average of amplitudes because this allows for a less skewed normalization of the amplitude (Smulders) and because normalization allows for accounting for patient to patient variation, which increases the sensitivity and specificity of detection of conditions, including stroke (Schulhauser, [0157]).
Regarding claim 16, Pulkit in view of Schulhauser discloses dividing amplitude at a scalp location by amplitude at a contralateral scalp location, as discussed above. Pulkit in view of Schulhauser does not disclose taking log base 2 of the division between amplitudes between contralateral scalp locations. Smulders teaches that log transforms result in a less skewed distribution when normalizing values (Theoretical implications, paragraph 5, “In both cases, the log-transform performed best in transforming toward normality. Likewise, Davidson et al. (1990), comparing the log and square root (level-2) transform, concluded that the log-transform resulted in a less-skewed distribution. As argued above, our data suggest that the same transform on single epochs (level 1) is sufficient to achieve normality and is preferable.”) and that the base of the logarithm does not matter for a log transformation (Alpha magnitude: transformations, paragraph 2, “Fifth, the base of the log does not matter to the results of t-tests or ANOVAs, as log-transforms with a different base are linearly related, as shown by the change-of-base formula: loga(x) = logb(x)/logb(a).”). It would have been obvious to one of ordinary skill in the art at the time the invention was effectively filed to have modified the method of Pulkit in view of Schulhauser in view of Shahaf such that it includes taking log2 of the amplitude at a frequency and location divided by the amplitude at a contralateral location because it results in a less skewed distribution (Smulders).
Examiner’s note
The following is a statement of reasons for the lack of prior art rejections:
Regarding claim 17, none of the prior art discloses or suggests, either alone or in combination, a method of determining probability of stroke by generating a gating matrix by combining matrix R with matrix S, generating a map matrix by averaging gating matrix values for a scalp location at different frequencies, and determining a high probability of stroke based on the map matrix, in combination with the other claimed steps.
Claims 17-20 and 24 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure.
Asirvatham et al. (US 20140296680 A1 – Cited by Applicant) teaches a device which detects seizures and strokes using EEG and predicts stroke using historical data.
Doidge et al. (US 20120310107 A1) teaches a system and method which spatially maps electrical activity for each of a plurality of frequency intervals.
Schalk et al. (US 20100094154 A1) teaches a system and method for predicting abnormal brain activity (including stroke) using electrical activity detected by an EEG.
Li et al. (US 11771377 B1) teaches a system and method for identifying stroke patients using EEG data and generating mutual interaction feature matrices to identify features.
Fathieh (US 20230075570 A1) teaches a system and method for using power spectra from EEG signals to diagnose cardiac diseases and other conditions such as strokes.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to EMILY R UCHITEL whose telephone number is (571)305-5153. The examiner can normally be reached Mon-Fri from 8:30am – 5:00pm.
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/EMILY R UCHITEL/Examiner, Art Unit 3791
/ETSUB D BERHANU/Primary Examiner, Art Unit 3791
