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 preliminary amendment dated 08/16/2024, the following occurred: Claims 1-7, 9-15 have been amended. Claims 16-22 are new. Specification at page 1, line 6 has been amended.
This is the first action on the merits. Claims 1-22 are currently pending.
Priority
This application claims priority from Provisional Application Nos. 63313084 dated 02/23/2022.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 08/16/2024 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Objections
Claim 6 is objected to because it recites the abbreviations ALS and ALSFRS without their full form. The first occurrence of an acronyms or abbreviations should be in parenthesis following the compound term, whether or not it may be considered well known. Appropriate corrections/clarification is required.
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 1-22 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 12-15are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites a method, system and a non-transitory computer readable medium for information processing.
Regarding claims 1 and 12-15, the limitation of (claim 1 being representative) acquire at least one neuromuscular disease-related user data a plurality of times in a predetermined period and generate to-be-provided information to be provided based on the user data, wherein the at least one neuromuscular disease-related user data includes at least one typing operation-related data selected from typing speed, accuracy, time and amount, at least one walking-related data selected from number of steps, walking speed, foot swing angle, ankle movement angle, stride length, arm swing, foot swing, lateral swing of the whole body and rate of falls during walking, at least one utterance-related data selected from voice data of conversation, call record, speaking speed, speaking time, sustained vocalization, number of words, language disorder, frequency of obscure language, pause period, non-speech sound and cough frequency, at least one sleep-related data selected from sleep time, sleep efficiency, eyeball movements, and frequency of awakening, at least one breathing-related data selected from vital capacity, forced vital capacity, dyspnea, orthopnea, respiratory failure, and frequency of coughing, at least one facial expression-related data selected from opening and width between upper and lower lips, lip movement, opening speed and acceleration, spasm, mouth surface, average symmetry ratio of left and right mouth surfaces, vertical positions of eyebrows, eye opening, parallel movement and rotation vector of head tilt, and eyeball movement, at least one fine motor movement-related data selected from user taps, inputs, swipes and draws entered into a digital device, at least one gross motor movement-related data selected from arm position-changing movements, going up and down stairs, standing up from a sitting position, and frequency of leg cramps, questionnaire answers regarding disease symptoms, information automatically collected with built-in sensors of devices, and data from medical institutions as drafted, is a process that, under the broadest reasonable interpretation, covers a method organizing human activity but for the recitation of generic computer components. That is other than reciting (in claims 1, 12 and 13) an information processing device and circuitry, (in claim 14) a method and (in claim 15) a non-transitory computer readable medium and computer, the claimed invention amounts to managing personal behavior or interaction between people (i.e., rules or instructions). For example, but for the information processing device, circuitry, non-transitory computer readable medium and computer, the claims encompass acquire at least one neuromuscular disease-related user data and generate to-be-provided information to be provided based on the user data in the manner described in the identified abstract idea, supra. 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 – Managing Personal Behavior Relationships, Interactions Between People (e.g. social activities, teaching, following rules or instructions)” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. Claim 14 is not tied to any particular technological environment that implements the identified abstract idea. In particular, claims 1, 12 and 13 recite the additional elements of an information processing device and circuitry. Claim 15 recites the additional element of a non-transitory computer readable medium and computer. These additional elements are not exclusively defined by the applicant and are recited at a high-level of generality (i.e., a generic server for enabling access to medical information or generic computer components for performing generic computer functions) such that they amounts to no more than mere instructions to apply the exception using a generic computer component. As set forth in MPEP 2106.04(d) “merely including instructions to implement an abstract idea on a computer” is an example of when an abstract idea has not been integrated into a practical application. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
Claims 1 and 12-15 further recite the additional element of a predetermined terminal. This additional element is recited at a high level of generality (i.e. a general means to provide data) and amount to extra solution activity. Accordingly, even in combination, this additional elements does not integrate the abstract idea into a practical application.
The claims do 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 elements of the information processing device, circuitry, non-transitory computer readable medium and computer 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”). Moreover, using generic computer components to perform abstract ideas does not provide a necessary inventive concept. See Alice, 573 U.S. at 223 (“mere recitation of a generic computer cannot transform a patent-ineligible abstract idea into a patent-eligible invention”). Therefore, whether considered alone or in combination, the additional elements do not amount to significantly more than the abstract idea.
Also as discussed with respect to integration of the abstract idea into a practical application, the additional element of a predetermined terminal was considered extra-solution activity. This has been re-evaluated under “significantly more” analysis and determined to be well-understood, routine and conventional in the field of healthcare Well-understood, routine and conventional activity cannot provide an inventive concept (“significantly more”). As such the claim is not patent eligible.
The examiner notes that: A well-known, general-purpose computer has been determined by the courts to be a well-understood, routine and conventional element (see, e.g., Alice Corp. v. CLS Bank; see also MPEP 2106.05(d)); Receiving and/or transmitting data over a network (“a communications network”) has also been recognized by the courts as a well - understood, routine and conventional function (see, e.g., buySAFE v. Google; MPEP 2016(d)(II)); and Performing repetitive calculations is/are also well-understood, routine and conventional computer functions when they are claimed in a merely generic manner (see, e.g., Parker v. Flook; MPEP 2016.05(d)).
Claims 2-11 and 16-22 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 further merely describe(s) continuously acquire user data. Claim(s) 3 and 16 further merely describe(s) passively or actively acquire the user data. Claim(s) 4 and 17 further merely describe(s) the to-be-provided information. Claim(s) 5 and 18 further merely describe(s) analyze the signs of the neuromuscular disease. Claim(s) 6, 7, 10, 19 and 20 further merely describe(s) the user data. Claim(s) 8 and 21 further merely describe(s) the self-reported information. Claim(s) 8 and 21 also include the additional element of “a user terminal” which is interpreted the same as a predetermined terminal and does not provide practical application or significantly more. Claim(s) 9 and 20 further merely describe(s) notify a terminal used by either the user, the user's family, or a doctor. Claim(s) 9 and 20 also include the additional element of “a terminal” which is interpreted the same as a predetermined terminal and does not provide practical application or significantly more. Claim(s) 11 further merely describe(s) the neuromuscular disease. Claims 2-11 and 16-22 further define the abstract idea and are rejected for the same reason presented above with respect to claims 1 and 12-15.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis 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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-22 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Baker (US 2020/0258631).
REGARDING CLAIM 1
Baker discloses an information processing device, comprising: circuitry configured to acquire at least one neuromuscular disease-related user data a plurality of times in a predetermined period and generate to-be-provided information to be provided to a predetermined terminal based on the user data ([0037] teaches determining at least one qualimetric activity parameter for cognition and/or fine motoric activity from a, typically preexisting, dataset of cognition and/or fine motoric activity measurements from said subject using a mobile device (interpreted by examiner as acquire at least one neuromuscular disease-related user data a plurality of times in a predetermined period). [0038] teaches b) comparing the determined at least one qualimetric activity parameter to a reference, whereby the cognition and movement disease or disorder will be assessed and [0383] teaches the said diagnosis, i.e., the identification of the subject as suffering from a cognition and movement disease or disorder, or not, is indicated to the subject or other person, such as a medical practitioner. Typically, this is achieved by displaying the assessment on a display of the mobile device or the evaluation device (interpreted by examiner as generate to-be-provided information to be provided to a predetermined terminal based on the user data)), wherein the at least one neuromuscular disease-related user data includes at least one typing operation-related data selected from typing speed, accuracy, time and amount, at least one walking-related data selected from number of steps, walking speed, foot swing angle, ankle movement angle, stride length, arm swing, foot swing, lateral swing of the whole body and rate of falls during walking, at least one utterance-related data selected from voice data of conversation, call record, speaking speed, speaking time, sustained vocalization, number of words, language disorder, frequency of obscure language, pause period, non-speech sound and cough frequency, at least one sleep-related data selected from sleep time, sleep efficiency, eyeball movements, and frequency of awakening, at least one breathing-related data selected from vital capacity, forced vital capacity, dyspnea, orthopnea, respiratory failure, and frequency of coughing, at least one facial expression-related data selected from opening and width between upper and lower lips, lip movement, opening speed and acceleration, spasm, mouth surface, average symmetry ratio of left and right mouth surfaces, vertical positions of eyebrows, eye opening, parallel movement and rotation vector of head tilt, and eyeball movement, at least one fine motor movement-related data selected from user taps, inputs, swipes and draws entered into a digital device, at least one gross motor movement-related data selected from arm position-changing movements, going up and down stairs, standing up from a sitting position, and frequency of leg cramps, questionnaire answers regarding disease symptoms, information automatically collected with built-in sensors of devices, and data from medical institutions ([0100] teaches typing data. [0170] teaches fine finger motor skill function parameters captured. [0275]-[0313] teaches a walking test. [0042] teaches sensors used for data acquisition are sensors such as gyroscope, magnetometer, accelerometer, proximity sensors, thermometer, humidity sensors, pedometer, heart rate detectors, fingerprint detectors, touch sensors, voice recorders, light sensors, pressure sensors, location data detectors, cameras, time recorders, sweat analysis sensors and the like. [0339] teaches information is typically derived from answering mood scale questions, answering questions on quality of life and disease symptoms, in particular, by performing the 29-Item Multiple Sclerosis Impact Scale (MSIS29) questionnaire and/or the Multiple Sclerosis Symptom Tracker (MSST). [0554] teaches acquiring data from Continuous Analysis of Gait (CAG). Continuous recording of gait feature data (step counts, duration, and asymmetry, as well as arm swing dynamic while walking) captured from sensors will allow passive monitoring of daily volume and quality of walking dynamics.).
REGARDING CLAIM 2
Baker disclose the limitation of claim 1.
Baker further discloses:
The information processing device according to claim 1, wherein the data acquisition par circuitry is configured to continuously acquire the user data in the predetermined period (Baker at (Baker at [0094] teaches the term “dataset of activity measurements” refers, in principle, to the entirety of data acquired by the mobile device from a subject (interpreted by examiner as continuously acquire the user data in the predetermined period)).
REGARDING CLAIM 3
Baker disclose the limitation of claim 1.
Baker further discloses:
The information processing device according to claim 1, wherein circuitry is configured to passively or actively acquire the user data (Baker at [0094] teaches the term “dataset of activity measurements” refers, in principle, to the entirety of data acquired by the mobile device from a subject (interpreted by examiner as passively or actively acquire the user data)).
REGARDING CLAIM 4
Baker disclose the limitation of claim 1.
Baker further discloses:
The information processing device according to claim 1, wherein the to-be-provided information is information related to at least one of signs of a neuromuscular disease, prediction of onset, prediction of progression, patient stratification, information related to consultation at a medical institution, and a score value related to progression of disease symptoms (Baker at [0056]-[0060] teach risk prediction models estimating probabilities of disability progression in patients with a diagnosis).
REGARDING CLAIM 5
Baker disclose the limitation of claim 1.
Baker further discloses:
The information processing device according to claim 1, wherein the circuitry is configured to analyze the signs of the neuromuscular disease from a fluctuation amount of the user data, and generate the signs as the to- be-provided information (Baker at ([0100] teaches typing data. [0170] teaches fine finger motor skill function parameters captured. [0275]-[0313] teaches a walking test. [0042] teaches sensors used for data acquisition are sensors such as gyroscope, magnetometer, accelerometer, proximity sensors, thermometer, humidity sensors, pedometer, heart rate detectors, fingerprint detectors, touch sensors, voice recorders, light sensors, pressure sensors, location data detectors, cameras, time recorders, sweat analysis sensors and the like. [0339] teaches information is typically derived from answering mood scale questions, answering questions on quality of life and disease symptoms, in particular, by performing the 29-Item Multiple Sclerosis Impact Scale (MSIS29) questionnaire and/or the Multiple Sclerosis Symptom Tracker (MSST). [0554] teaches acquiring data from Continuous Analysis of Gait (CAG). Continuous recording of gait feature data (step counts, duration, and asymmetry, as well as arm swing dynamic while walking) captured from sensors will allow passive monitoring of daily volume and quality of walking dynamics.) (all of these are interpreted by examiner as a fluctuation amount of the user data)).
REGARDING CLAIM 6
Baker disclose the limitation of claim 1.
Baker further discloses:
The information processing device according to claim 1, wherein the user data includes data related a motor function included in ALS function evaluation scale, ALSFRS (Baker at [0089 teaches diagnosing for ALS disease and that the method may be applied for assessing the disease, including the aspects described elsewhere in detail, making risk assessments, establishing risk prediction models and/or developing algorithmic solutions using, for instance, machine-learning and pattern recognition techniques.).
REGARDING CLAIM 7
Baker disclose the limitation of claim 1.
Baker further discloses:
The information processing device according to claim 1, wherein the user data includes self-reported information of a user (Baker at [0037] teaches determining at least one qualimetric activity parameter for cognition and/or fine motoric activity from a, typically preexisting, dataset of cognition and/or fine motoric activity measurements from said subject (interpreted by examiner as self-reported) using a mobile device).
REGARDING CLAIM 8
Baker disclose the limitation of claim 1.
Baker further discloses:
The information processing device according to claim 7, wherein the self-reported information is acquired from a user terminal used by the user (Baker at [0037] teaches determining at least one qualimetric activity parameter for cognition and/or fine motoric activity from a, typically preexisting, dataset of cognition and/or fine motoric activity measurements from said subject using a mobile device).
REGARDING CLAIM 9
Baker disclose the limitation of claim 1.
Baker further discloses:
The information processing device according to claim 1, wherein, the circuitry is configured to notify a terminal used by either the user, the user's family, or a doctor of the to-be-provided information. (Baker at [0042] teaches providing the result (interpreted by examiner as notify) of the analysis carried out by the evaluation unit to a user and [0383] teaches the said diagnosis, i.e., the identification of the subject as suffering from a cognition and movement disease or disorder, or not, is indicated to (also interpreted by examiner as notify) the subject or other person, such as a medical practitioner)
REGARDING CLAIM 10
Baker disclose the limitation of claim 1.
Baker further discloses:
The information processing device according to claim 1, wherein the user data is data related to a direct or indirect motor nervous system dysfunction (Baker at [0036] teaches fine motoric activity measurements from said subject).
REGARDING CLAIM 11
Baker disclose the limitation of claim 1.
Baker further discloses:
The information processing device according to claim 1, wherein the neuromuscular disease includes amyotrophic lateral sclerosis (Baker at [0005]).
REGARDING CLAIMS 12-22
Claims 12-22 are analogous to Claim 1-11 thus Claims 12-22 are similarly analyzed and rejected in a manner consistent with the rejection of Claim 1-11.
Conclusion
The prior art made of record though not relied upon in the present basis of rejection are noted in the attached PTO 892 and include:
Stanton (US 2007/0031853) discloses gene sequence variations with utility in determining the treatment of neurological or psychiatric disease.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to LIZA TONY KANAAN whose telephone number is (571)272-4664. The examiner can normally be reached on Mon-Thu 9:00am-6:00pm ET.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Robert Morgan can be reached on 571-272-6773. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from the 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 and https://www.uspto.gov/patents/docs for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/LIZA TONY KANAAN/Examiner, Art Unit 3683
/ROBERT W MORGAN/Supervisory Patent Examiner, Art Unit 3683