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 .
DETAILED ACTION
In the Amendment dated 28 August 2025, the following occurred: Claims 1, 3, 5, 7, 9, 11, 13, 15, 17, 19 have been amended.
Claims 1-20 are pending.
Priority
This application claims priority to U.S. Provisional Patent Application No. 63/481,658 dated 26 January 2023.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-20 are rejected for lack of adequate written description.
Claims 1 and 11 recite functional steps for which the Applicant has not adequately described the steps in sufficient detail for one of ordinary skill in the art to conclude that the Applicant had possession of the invention at the time of filing. This is a new matter rejection.
Specifically, the claims recite (Claim 1 being representative) “convert one or more of the assessment data, the sensor data, and the potential neurological impairment into a standardized format.” The as-filed disclosure is silent as to converting data into a standardized format. Applicant cites to Spec. Para. 17, 21-22, 30, 33, and 37 as providing support. None of these paragraph mention converting the data to a format, much less a standardized format. The word “convert*” appears once in the specification in reference to analog to digital converters. The word “format” does not appear at all. The word “standard*” appears in reference to guidelines, web-browsers, and questionnaires, not collected data. As such, these features represent new matter.
By virtue of their dependence from Claim 1 or 11, this basis of rejection also applies to dependent Claims 2-10 and 12-20.
Claims 7 and 17 recite functional steps for which the Applicant has not adequately described the steps in sufficient detail for one of ordinary skill in the art to conclude that the Applicant had possession of the invention at the time of filing. This is a new matter rejection.
Specifically, the claims recite (Claim 7 being representative) “wherein determining the result comprises: determining that the result comprises the positive non-urgent result when one or more of the assessment data or the sensor data exceeds a first predetermined threshold; determining that the result comprises a negative non-urgent result when one or more of the assessment data or the sensor data does not exceed the first predetermined threshold; and determining that the result comprises an urgent result when one or more of the assessment data or the sensor data exceeds a second predetermined threshold.” This is not supported by the as-filed disclosure.
Specification Para. 0033 states:
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Specification Para. 0037 similarly states:
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As indicated by the Specification, the only support that is present with regard to urgent/non-urgent and thresholds is whether threshold numbers of factors are satisfied or not. This different than what is claimed which requires that the data itself exceeds a threshold, i.e., the difference between a temperature exceeding 100F (the data exceeding a threshold) and a patient having a high temperature and a cough (number of factors). As such, these features represent new matter.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Claims 1 and 11 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
The claim recites a method and system for neurological analysis of a patient, which are within a statutory category.
Step 2A1
The limitations of receiving a request for a neurological assessment; in response to the request, collecting assessment data from the patient and collecting sensor data related to the patient; automatically determining a result based on an analysis of the assessment data and the sensor data; and when the result comprises a positive non-urgent result: determining a potential neurological impairment of the patient and relevant provider information, based on the analysis of the assessment data and the sensor data; displaying a message related to the potential neurological impairment of the patient and the relevant provider information; converting one or more of the assessment data, the sensor data, and the potential neurological impairment into a standardized format; and transmitting the one or more of assessment data, the sensor data, and the potential neurological impairment in the standardized format, as drafted, is a process that, under the broadest reasonable interpretation, covers certain methods of organizing human activity (i.e., managing personal behavior including following rules or instructions) but for recitation of generic computer components. That is, other than reciting a processor or processor/interface, the claimed invention amounts to managing personal behavior or interaction between people. For example, but for the data processor and/or interface, this claim encompasses a person assessing patient data to determine whether a patient has a neurological impairment in the manner described in the identified abstract idea, supra. The Examiner notes that certain “method[s] of organizing human activity” includes a person’s interaction with a computer (see MPEP 2106.04(a)(2)(II)). If a claim limitation, under its broadest reasonable interpretation, covers managing personal behavior or interactions between people but for the recitation of generic computer components, then it falls within the “certain methods of organizing human activity” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Step 2A2
This judicial exception is not integrated into a practical application. In particular, the claims recite the additional element of an electronic device having a processor and/or a user interface that implements the identified abstract idea. The electronic device is not described by the applicant and is recited at a high-level of generality (i.e., a computer, see Spec. Para. 0014) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claims further recite the additional element of transmitting data to a database, a remote server, or a separate electronic device. The transmitting step is recited at a high level of generality (i.e., as a general means of transmitting data) and amounts to the mere transmission of data, which is a form of extra-solution activity. MPEP 2106.04(d)(I) indicates that extra-solution data gathering activity cannot provide a practical application. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application.
The claims further recite the additional element of one or more sensors. The one or more sensors merely generally links the abstract idea to a particular technological environment or field of use. MPEP 2106.04(d)(I) indicates that generally linking an abstract idea to a particular technological environment or field of use cannot provide a practical application.
The claims further recite the additional element of using an artificial intelligence algorithm to determine a result from analysis of assessment and sensor data. This represents mere instructions to implement the abstract idea on a generic computer. Implementing an abstract idea using a generic computer or components thereof does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. See, e.g., Recentive Analytics, Inc. v. Fox Corp., No. 2023-2437 at 10 (Fed. Cir. April 18, 2025) (finding that claims that do no more than apply established methods of machine learning to a new data environment are ineligible). Alternatively, or in addition, the implementation of the trained machine learning model to determine a result from analysis of assessment and sensor data merely confines the use of the abstract idea (i.e., the trained model) to a particular technological environment or field of use (artificial intelligence, the Examiner noting that there is no particular type of AI disclosed that performs the analysis) and thus fails to add an inventive concept to the claims. Accordingly, even in combination, this additional element does not integrate the abstract idea into a practical application.
Step 2B
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using an electronic device having a processor and/or a user interface to perform the noted steps amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept (“significantly more”).
Also, as discussed above with respect to integration of the abstract idea into a practical application, the additional element of transmitting data to a database or a remote server were considered extra-solution activity. This has been re-evaluated under the “significantly more” analysis and determined to be well-understood, routine, conventional activity in the field. MPEP 2016.05(d)(II) indicates that receiving and/or transmitting data over a network has been held by the courts to be well-understood, routine, conventional activity (citing Symantec, TLI Communications, OIP Techs., and buySAFE). Well-understood, routine, conventional activity cannot provide an inventive concept (“significantly more”). As such the claim is not patent eligible.
Also, as discussed above with respect to integration of the abstract idea into a practical application, the additional element of one or more sensors was determined to generally link the abstract idea to a particular technological environment or field of use. This has been re-evaluated under the “significantly more” analysis and has also been found insufficient to provide significantly more. MPEP 2106.05(A) indicates that generally linking an abstract idea to a particular technological environment or field of use cannot provide significantly more. Accordingly, even in combination, this additional element does not provide significantly more.
As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using an artificial intelligence algorithm to determine a result from analysis of assessment and sensor data was found to represent mere instructions to implement the abstract idea on a generic computer and/or confine the use of the abstract idea (i.e., the trained algorithm) to a particular technological environment or field of use (artificial intelligence). This has been re-evaluated under the “significantly more” analysis and determined to be insufficient to provide significantly more. MPEP 2106.05(I) indicates that mere instructions to implement the abstract idea on a generic computer and/or confining the use of the abstract idea to a particular technological environment or field of use cannot provide significantly more. See also Recentive Analytics, Inc. v. Fox Corp., No. 2023-2437 at 17 (Fed. Cir. April 18, 2025) (finding that applying machine learning to an abstract idea does not transform a claim into something significantly more). As such the claim is not patent eligible.
Claims 2-10 and 12-20 are similarly rejected because they either further define/narrow the abstract idea and/or do not further limit the claim to a practical application or provide as inventive concept such that the claims are subject matter eligible even when considered individually or as an ordered combination.
Claim(s) 2, 12 merely describe(s) displaying questions and receiving answers.
Claim(s) 3, 13 merely describe(s) determining the questions to display. Claim 3 also includes the additional element of an artificial intelligence algorithm. The artificial intelligence algorithm is evaluated in the same manner as the AI of claim 1 or 11 and does not provide a practical application or significantly more for the same reasons.
Claim(s) 4, 15 merely describe(s) how the questions are arrived at.
Claim(s) 5, 15 merely describe(s) how the sensor data is achieved.
Claim(s) 6, 16 merely describe(s) the type of sensor.
Claim(s) 7, 8, 17, 18 merely describe(s) how the result is arrived at.
Claim(s) 9, 19 merely describe(s) how data is displayed.
Claim(s) 10, 20 merely describe(s) determining a risk score.
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 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 of this title, 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.
Claim(s) 1, 2, 5, 6, 8-12, 15, 16, and 18-20 is/are rejected under 35 U.S.C. § 103 as being unpatentable over Handal (U.S. Pre-Grant Patent Publication No. 2020/0350056) in view of Jiang (U.S. Pre-Grant Patent Publication No. 2018/0263496) in view of Gonzales (U.S. Patent No. 11,348,689).
REGARDING CLAIM 1
Handal teaches the claimed method for neurological analysis of a patient, comprising:
receiving a request for a neurological assessment at a processor; [Para. 0036, 0061 teaches receiving a request for a concussion assessment (neurological assessment, see Spec. Para. 0003) at a central server.]
in response to receiving the request, collecting assessment data from the patient [Para. 0030, 0064, 0065 teaches that answers to a concussion questionnaire are received.] and collecting sensor data related to the patient detected by one or more sensors, using the processor; [Para. 0069 teaches that eye-tracking data from a camera (a sensor, see Claim 6). Para. 0071 also teaches accelerometer data.]
automatically determining […] a result based on an analysis of the assessment data and the sensor data, using the processor; and [Para. 0039, 0066, 0069 teaches that a clinical state score is determined using the questionnaire responses and the eye-tracking information.]
when the result comprises a positive non-urgent result: [Para. 0072 teaches that the beneficiary’s clinical state (result) of having a concussion is determined. Para. 0032, 0074 teaches that the beneficiary’s diagnosis is provided to a provider. This covers both urgent and non-urgent forms of a concussion (which is never determined in the claim nor defined by the Applicant) and therefore necessarily teaches that the following features occur for a positive non-urgent result. Para. 0102 also teaches a severity score describing the severity of the assessment (i.e., “Mild”).]
determining a potential neurological impairment of the patient and relevant provider information, based on the analysis of the assessment data and the sensor data, using the processor; [Para. 0072 teaches that the beneficiary is determined to have a concussion. Para. 0037 teaches that provider information is determined (relevant provider information, which is undefined) such as a username.]
displaying a message related to the potential neurological impairment of the patient […], using the processor; and [Para. 0072, 0082 teaches that the diagnosis of concussion is displayed on the mobile device and the server. See also Para. 0100, 0101.]
[…].
Handal may not explicitly teach displaying the relevant provider information; however, it would have been prima facie obvious to one of ordinary skill in the art at the time of filing to combine the provider information of Handal with the displayed data of Handal since the combination is merely combining prior art elements according to known methods to yield predictable results (KSR rationale A). It can be seen that each element claimed is present in Handal. Displaying provider information does not change or affect the normal display of information of Handal. Displaying diagnosis information would be performed the same way even with the addition of provider information. Since the functionalities of the elements in Handal do not interfere with each other, the results of the combination would be predictable.
Handal may not explicitly teach
using an artificial intelligence algorithm
Jiang at Para. 0018, 0019 teaches that it was known in the art of computerized healthcare, at the time of filing, to utilize machine leaning to analyze user data to determine a likelihood of concussion
using an artificial intelligence algorithm [Jiang at Para. 0018, 0019 teaches collecting eye movement and question response data and using a machine learning algorithm (an artificial intelligence algorithm) to determine the likelihood of a concussion.]
Therefore, it would have been prima facie obvious to one of ordinary skill in the art of computerized healthcare, at the time of filing, to modify the concussion determination system of Handal to utilize machine leaning to analyze user data to determine a likelihood of concussion at taught by Jiang, with the motivation of improving the accuracy of diagnosis (see Jiang at Para. 0004).
Handal/Jiang may not explicitly teach
converting one or more of the assessment data, the sensor data, and the potential neurological impairment into a standardized format; and
transmitting the one or more of the assessment data, the sensor data, and the potential neurological impairment in the standardized format from the processor to one or more of a database, a remote server, or a separate electronic device.
Gonzales at Col. 9, Lns. 36-41, Col. 12, Lns. 2-6, 44-67 teaches that it was known in the art of computerized healthcare, at the time of filing, to convert patient diagnosis data to a standardized format and transmit the data to a physician device, a server, and/or a database
converting one or more of the assessment data, the sensor data, and the potential neurological impairment into a standardized format; and [Gonzales at Col. 9, Lns. 36-41, Col. 12, Lns. 44-67 teaches converting a diagnosis (the assessment of Handel into a standardized data format.]
transmitting the one or more of the assessment data, the sensor data, and the potential neurological impairment in the standardized format from the processor to one or more of a database, a remote server, or a separate electronic device. [Gonzales at Col. 9, Lns. 36-41, Col. 12, Lns. 2-6, 44-67 teaches storing the diagnosis in the standardized format in a storage device (a d separate electronic device) and/or transmitting the data to physician devices (also a separate electronic device). Gonzales at Col. 9, Lns. 36-41, Col. 12, Lns. 2-6, 44-67 also teaches that the standardized data is stored in the collection of medical records, which a person having skill in the art would understand to be a database (i.e., an EMR) implemented on a server. See also Gonzales at Col. 1, Lns. 21-23.]
Therefore, it would have been prima facie obvious to one of ordinary skill in the art of computerized healthcare, at the time of filing, to modify the concussion determination system of Handal having the utilization of machine leaning to analyze user data to determine a likelihood of concussion of Jiang to convert patient diagnosis data to a standardized format and transmit the data to a physician device, a server, and/or a database as taught by Gonzales, with the motivation of improving patient care and increase overall hospital efficiency (see Gonzales at Col.8, Lns. 20-25).
REGARDING CLAIM 2
Handal/Jiang/Gonzales teaches the claimed method for neurological analysis of a patient of Claim 1. Handal/Jiang/Gonzales further teaches
wherein collecting the assessment data comprises:
displaying one or more questions to the patient on a user interface, using the processor; and [Handel at Fig. 4, Para. 0030, 0035, 0044 teaches that the server causes a questionnaire having questions to be displayed.]
receiving one or more responses to the one or more questions at the processor from the patient through the user interface. [Handel at Fig. 4, Para. 0030, 0064 teaches receiving responses to the questions are received via a touchscreen.]
REGARDING CLAIM 5
Handal/Jiang/Gonzales teaches the claimed method for neurological analysis of a patient of Claim 1. Handal/Jiang/Gonzales further teaches
further comprising receiving the sensor data from the one or more sensors that are in communication with the processor. [Handel at Para. 0069 teaches that eye-tracking data is received from a camera (a sensor, see Claim 6). Handel at Para. 0071 also teaches accelerometer data.]
REGARDING CLAIM 6
Handal/Jiang/Gonzales teaches the claimed method for neurological analysis of a patient of Claims 1 and 5. Handal/Jiang/Gonzales further teaches
wherein the one or more sensors comprise a camera, a microphone, or an accelerometer. [Handel at Para. 0069 teaches that eye-tracking data is from a camera. Handel at Para. 0071 also teaches accelerometer data.]
REGARDING CLAIM 8
Handal/Jiang/Gonzales teaches the claimed method for neurological analysis of a patient of Claim 1. Handal/Jiang/Gonzales further teaches
wherein determining the result comprises determining the result further based on existing medical data associated with the patient, using the processor. [Handel at Para. 0039 teaches that the beneficiary’s medical record (medical data) is accessed when performing the assessment.]
REGARDING CLAIM 9
Handal/Jiang/Gonzales teaches the claimed method for neurological analysis of a patient of Claim 1. Handal/Jiang/Gonzales further teaches
wherein displaying the message comprises generating and displaying a graphical representation of the result, using the processor. [Handel at Para. 0072, 0082 teaches that the diagnosis of concussion is displayed on the mobile device and the server, therefore the message is graphical (i.e., on a mobile phone display) representation. This means the displayed data is necessarily generated “using the processor.”]
REGARDING CLAIM 10
Handal/Jiang/Gonzales teaches the claimed method for neurological analysis of a patient of Claim 1. Handal/Jiang/Gonzales further teaches
further comprising generating a risk score based on one or more of the assessment data, the sensor data, existing medical data, or the potential neurological impairment, using the processor. [Handel at Para. 0062, 0066 teaches that a clinical score is calculated, which is interpreted as a score indicative of a risk of having a conduction. See also Handel at Para. 0040 where the clinical score threshold is a conditional risk.]
REGARDING CLAIM(S) 11
Claim(s) 11 is/are analogous to Claim(s) 1 and 5, thus Claim(s) 11 is/are similarly analyzed and rejected in a manner consistent with the rejection of Claim(s) 1 and 5.
REGARDING CLAIM(S) 12, 15, 16, AND 18-20
Claim(s) 12, 15, 16, and 18-20 is/are analogous to Claim(s) 2, 5, 6, and 8-10, thus Claim(s) 12, 15, 16, and 18-20 is/are similarly analyzed and rejected in a manner consistent with the rejection of Claim(s) 2, 5, 6, and 8-10.
Claim(s) 3, 4, 13, and 14 is/are rejected under 35 U.S.C. § 103 as being unpatentable over Handal (U.S. Pre-Grant Patent Publication No. 2020/0350056) in view of Jiang (U.S. Pre-Grant Patent Publication No. 2018/0263496) in view of Gonzales (U.S. Patent No. 11,348,689) in view of Goel et al. (U.S. Pre-Grant Patent Publication No. 2023/0154575).
REGARDING CLAIM 3
Handal/Jiang/Gonzales teaches the claimed method for neurological analysis of a patient of Claims 1 and 2. Handal/Jiang/Gonzales further teaches
wherein displaying the one or more questions comprises:
determining the one or more questions […]; and [Handel at Para. 0088 teaches that questions are determined. Para. 0116 also teaches generating the questionnaire.]
displaying the determined one or more questions, using the processor. [Handel at Fig. 4, Para. 0030, 0035, 0044 teaches that the server causes a questionnaire having questions to be displayed.]
Handal/Jiang/Gonzales may not explicitly teach
using the artificial intelligence algorithm
Goel at Para. 0005, 0048 teaches that it was known in the art of computerized healthcare, at the time of filing, to select questions for a questionnaire using artificial intelligence
using the artificial intelligence algorithm [Goel at Para. 0005, 0048 teaches selecting (generating) questions for a questionnaire using an artificial intelligence algorithm (interpreted to correspond to the artificial intelligence algorithm of Jiang).]
Therefore, it would have been prima facie obvious to one of ordinary skill in the art of computerized healthcare, at the time of filing, to modify the concussion determination system of Handal having the utilization of machine leaning to analyze user data to determine a likelihood of concussion of Jiang having the conversion of patient diagnosis data to a standardized format and transmission of the data to a physician device, a server, and/or a database of Gonzales to select questions for a questionnaire using artificial intelligence as taught by Goel, with the motivation of improving resources and timeliness (see Goel at Para. 0003).
REGARDING CLAIM 4
Handal/Jiang/Gonzales/Goel teaches the claimed method for neurological analysis of a patient of Claims 1-3. Handal/Jiang/Gonzales/Goel further teaches
wherein determining the one or more questions using the artificial intelligence algorithm comprises determining the one or more questions based on the received one or more responses, using the processor. [Handal at Para. 0088, 0089 teaches that questions are determined based on responses to general questionnaire. Goel at Para. 0048 teaches that the artificial intelligence algorithm bases its question selection on previous responses.]
REGARDING CLAIM(S) 13 AND 14
Claim(s) 13 and 14 is/are analogous to Claim(s) 3 and 4, thus Claim(s) 13 and 14 is/are similarly analyzed and rejected in a manner consistent with the rejection of Claim(s) 3 and 4.
Claim(s) 7 and 17 is/are rejected under 35 U.S.C. § 103 as being unpatentable over Handal (U.S. Pre-Grant Patent Publication No. 2020/0350056) in view of Jiang (U.S. Pre-Grant Patent Publication No. 2018/0263496) in view of Gonzales (U.S. Patent No. 11,348,689) in view of Subramaniam et al. (U.S. Pre-Grant Patent Publication No. 2020/0204631).
REGARDING CLAIM 7
Handal/Jiang/Gonzales teaches the claimed method for neurological analysis of a patient of Claim 1. Handal/Jiang/Gonzales may not explicitly teach
determining that the result comprises the positive non-urgent result when one or more of the assessment data or the sensor data exceeds a first predetermined threshold;
determining that the result comprises a negative non-urgent result when one or more of the assessment data or the sensor data does not exceed the first predetermined threshold; and
determining that the result comprises an urgent result when one or more of the assessment data or the sensor data exceeds a second predetermined threshold.
Subramaniam at Para. 0046, 0047, 0049 teaches that it was known in the art of computerized healthcare, at the time of filing, to compare patient sensor data to urgency tier levels and identify whether the patient has an urgent situation or not
determining that the result comprises the positive non-urgent result when one or more of the assessment data or the sensor data exceeds a first predetermined threshold; [Subramaniam at Para. 0046, 0047 teaches determining tier level alarm states based on analysis of sensor data and other information (the analysis of Handel). Para. 0049 teaches that if a tier 2 level is exceeded (a first predetermined threshold), the patient has a low urgency level (interpreted as a positive non-urgent result).]
determining that the result comprises a negative non-urgent result when one or more of the assessment data or the sensor data does not exceed the first predetermined threshold; and [Para. 0049 teaches that if the tier 2 level is not exceeded then there is no urgency issue (interpreted as negative non-urgent result).]
determining that the result comprises an urgent result when one or more of the assessment data or the sensor data exceeds a second predetermined threshold. [Para. 0049 teaches that if a tier 1 level (a second predetermined threshold) is exceeded, the patient has a high urgency level (interpreted as an urgent result).]
Therefore, it would have been prima facie obvious to one of ordinary skill in the art of computerized healthcare, at the time of filing, to modify the concussion determination system of Handal having the utilization of machine leaning to analyze user data to determine a likelihood of concussion of Jiang having the conversion of patient diagnosis data to a standardized format and transmission of the data to a physician device, a server, and/or a database of Gonzales to compare patient sensor data to urgency tier levels and identify whether the patient has an urgent situation or not as taught by Subramaniam, with the motivation of improving the compatibility and the flexibility to manage real-time medical data (see Subramaniam at Para. 0003).
Response to Arguments
Rejection under 35 U.S.C. § 101
Regarding the rejection of Claims 1-20, the Examiner has considered the Applicant’s arguments; however, the arguments are not persuasive. Any arguments inadvertently not addressed are unpersuasive for at least the following reasons. Applicant argues:
Similarly, the pending claims are directed to a method that, when viewed as a whole, clearly does not seek to tie up any judicial exception but rather, recites a specific, practical application sufficiently confined by meaningful limitations. […] the claims clearly do not seek to tie up the alleged abstract idea of "neurological analysis of a patient" such that others cannot practice it, nor do the claims encompass "a person assessing patient data to determine whether a patient has a neurological impairment".
Regarding (a), the Examiner respectfully disagrees. The claimed invention would pre-empt (tie up) the identified abstract idea by definition. The quoted portions of the rejection are a summary of the abstract idea/invention. The abstract idea is marked in bold and is clearly indicated in the basis of rejection.
That is, the claims are directed to clear improvements in technology, e.g., use of an electronic device for neurological analysis of a patient [recites features of the claim].
Regarding (b), the Examiner respectfully disagrees. There is no improvement to “technology” present. Any improvement is an improvement to the abstract idea. An improved abstract idea is still an abstract idea. See MPEP § 2106.05(a)(III) stating “it is important to keep in mind that an improvement in the abstract idea itself (e.g. a recited fundamental economic concept) is not an improvement in technology.” The Examiner further notes that “pathway A” is not a shortcut; if the claimed invention is eligible the same conclusion would be reached with either pathway.
The claimed steps of method claim 1, for example, do not recite any concepts for "managing personal behavior" or "organizing human activity" more generally. MPEP § 2106 identifies "managing personal behavior" in "methods of organizing human activity" as including "social activities, teaching, and following rules or instructions".
Regarding (c), the Examiner respectfully disagrees. The claimed invention represents a series of rule or instructions for a person or persons to follow, with or without the aid of a computer, to (to paraphrase) assess a patient data to determine whether a patient has a neurological impairment (see Spec. Para. 0002).
Similarly [to the claims in Diehr], in the pending claims, the totality of the claimed limitations act in concert to improve technology, e.g., use of an electronic device for neurological analysis of a patient.
Regarding (d), the Examiner respectfully disagrees. The claimed invention does not provide an improvement my any measure in MPEP 2106. With regard to the “improvement” analysis, there is no physical improvement to the computer nor is there an improvement to another technology (as in Diehr). None of the additional elements of the claim (the “another technology” of the claim; the rubber molding machine of Diehr) are improved in any way.
Moreover, the pending claims are similar to the patent-eligible claim described in Example 42 of the Subject Matter Eligibility Examples: Abstract Ideas document issued by the USPTO on January 7, 2019. Example 42 relates to a method for transmission of notifications when medical records are updated.
Regarding (e), the Examiner respectfully disagrees. Applicant’s claimed invention is nothing like those in Example 42. Even if they were, the claims in Example 42 were found to be eligible because they provided a technological solution to a technological problem. Example 42 was not eligible merely because it recited "converting" and "automatically generating and transmitting" data. Applicant has not identified nor can the Examiner find any technological problem caused by the technological environment to which the claims are confined (a general-purpose computer).
The Examiner cannot suggest a path forward with regard to the lack of subject matter eligibility.
Rejection under 35 U.S.C. § 103
Regarding the rejection of Claims 1-20, the Examiner has considered the Applicant’s arguments; however, the arguments are not persuasive. Applicant argues:
That is, Jiang only describes that the "machine learning annotated data" can be manually reviewed by a doctor at a later time. This is contrast to claim 1, which recites "automatically determining, using an artificial intelligence algorithm, a result based on an analysis of the assessment data and the sensor data". The other cited references are silent as to using an artificial intelligence algorithm for automatically determining a result, as in the claims.
Regarding (a), the Examiner respectfully disagrees. In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986). Here, Handel was relied upon to teach automatically analyzing assessment and sensor data of the patient, while Jiang was relied upon to that the analysis (of Handel) is via an artificial intelligence algorithm. That a doctor may or may not review the results of the AI analysis does not change this; the AI produces an analysis result. Further, the reference requires AI analysis to occur and thus it is automatic. Given the broadest reasonable interpretation, the requirement that a human does something does not mean that the thing does not automatically occur; the Examiner automatically puts his keys in the ignition when he drives his car.
However, there is no teaching or suggestion in Handal to convert any text or responses (much less the claimed assessment data, sensor data, and potential neurological impairment) into a standardized format, or to transmit any text of responses in a standardized format to a database, remote server, or electronic device.
Regarding (b), the Examiner has considered the Applicant’s arguments; however, these arguments are moot given the new grounds of rejection as necessitated by amendment.
Conclusion
Prior art made of record though not relied upon in the present basis of rejection are noted in the attached PTO 892 and include:
McNair et al. (U.S. Patent No. 11, 581,092) which discloses a clinical decision support system that includes conversion of patient data to a nomenclature.
Russell et al. (U.S. Pre-Grant Patent Publication No. 2007/0167850) which discloses a system for monitoring system errors when monitoring a patient.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/JASON S TIEDEMAN/Primary Examiner, Art Unit 3683