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 07/14/2026, the following occurred: Claims 1, 5, 9, 12, 13, 14, 15, 18 and 22 were amended. Claims 6, 11 and 19 were canceled. Claims 23-25 are new.
Claims 1-5, 7-10, 12-18 and 20-25 are currently pending.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 01/26/2026 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-5, 7-10, 12-18 and 20-25 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 user data related to amyotrophic lateral sclerosis and including a motor function included in Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised 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 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 2-5, 7-10, 16-18 and 20-25 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) 7, 10 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) 23 further merely describe(s) Claim(s) 24 further merely describe(s) Claim(s) 25 further merely describe(s) Claims 2-5, 7-10, 16-18 and 20-25 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 1-5, 7-10, 12-18 and 20-25 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 user data related to amyotrophic lateral sclerosis and including a motor function included in Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised 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 user data related to amyotrophic lateral sclerosis and including a motor function 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 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 discloses 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 discloses 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 discloses 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 discloses the limitation of claim 4.
Baker further discloses:
The information processing device according to claim 4, 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 7
Baker discloses 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 discloses 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 discloses 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, and 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 discloses 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 CLAIMS 12-18, 20-22, 24 and 25
Claims 12-18, 20-22, 24 and 25 analogous to Claim 1-5 and 7-10 thus Claims 12-18, 20-22, 24 and 25 are similarly analyzed and rejected in a manner consistent with the rejection of Claim 1-5 and 7-10.
REGARDING CLAIM 23
Baker discloses the limitation of claim 1.
Baker further discloses:
The information processing device according to claim 3, 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 [0005], also at [0037] teaches 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 wherein the to-be-provided information is information related to at least one of signs of a neuromuscular disease)).
Response to Arguments
Claim Objections
Regarding the claim objection(s), the Applicant has canceled claim 6 to overcome the basis/bases of objection.
Rejection under 35 U.S.C. § 101
Regarding the rejection of claims 1-5, 7-10, 12-18 and 20-25, the Examiner has considered the Applicant’s arguments, but does not find them persuasive. Applicant argues:
Specifically, the Office Action states that the claims fall within the abstract idea grouping of "Certain Methods of Organizing Human Activity - Managing Personal Behavior" (Office Action at 5). However, Claim 1 as currently amended is directed to a specialized, non-abstract medical information processing device that specifically monitors ALS patients by acquiring and analyzing physical sensor data mapped to the clinical ALSFRS motor function scale. Thus, Applicant respectfully submits that the pending claims do not recite a patent-ineligible abstract idea (Step 2A, Prong 1). Furthermore, the claimed device does not monitor "personal behavior" or "social interactions" in any generic sense. Rather, the circuitry captures objective, multi-modal physiological and motor-functional parameters (such as typing speed, walking stride length, voice pause periods, and vital breathing capacity) that directly correspond to the neurological degradation of ALS. These are physical, physiological measurements of a severe motor neuron disease, which cannot be characterized as an abstract method of organizing human activity..
Regarding 1, The Examiner respectfully disagrees. The claims under the broadest reasonable interpretation fall within certain methods of organizing human activity (i.e., managing personal behavior including following rules or instructions). The claims encompass a series of rules or instructions for a person or persons to follow, with or without the aid of a computer, to acquire data and generate information in the manner described in the identified abstract idea, supra. The rules or instructions are the claimed steps of “acquire…and generate..” as indicated supra. acquiring and generating data is an abstract idea. 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.
ALS is a rapidly progressive, fatal disease, and clinical assessments may be subjective and burdensome and conducted infrequently during in-person hospital visits. The claimed information processing device solves these specific clinical and technical problems by continuously and passively acquiring multi-modal physical data from a user device; and mapping and analyzing these physical data streams to the clinical motor function categories of the ALSFRS scale (e.g., matching typing speed to handwriting, voice data to speech, and accelerometer data to walking/climbing stairs). This specific integration provides a continuous, objective and non-invasive clinical monitoring feedback loop that improves medical informatics and patient-monitoring technology. The claimed device does not preempt the abstract concept of data analysis but rather provides a specific, clinically useful application. Therefore, Applicant respectfully submits that the pending claims are patent-eligible under Step 2A and are believed to be in compliance with the requirements of the statute.
Regarding 2, The Examiner respectfully disagrees. The claims acquire and generate data which is purely an abstract idea. There is no practical application in the claim. Providing a continuous, objective and non-invasive clinical monitoring feedback loop does not provide improvements in a technical field nor to the functioning of a computer. At best this is a medical improvement.
Rejection under 35 U.S.C. § 102
Regarding the rejection of claims 1-5, 7-10, 12-18 and 20-25, the Examiner has considered the Applicant’s arguments, but does not find them persuasive. Applicant argues:
Specifically, Claim 1 recites acquiring one or more ALS-related user data multiple times where the data includes data related to a motor function included in an ALSFRS-R. Baker et al., on the other hand, merely mentions ALS as one of many potential neurodegenerative diseases in a generic list and does not disclose or suggest a device that acquires and processes user data mapped to the clinical ALSFRS motor function scale… Baker et al. contains no disclosure of the ALSFRS scale, let alone any teaching of mapping daily smartphone sensor data to the specific clinical categories of the ALSFRS to objectively track ALS progression.
Regarding 1, The Examiner respectfully disagrees. The claim requires acquiring data where the data includes at least one of many types. Baker at [0032] teaches ALS is a neurodegenerative disease that involves cell death of the lower and upper motor neurons that control voluntary muscle contraction (Zarei 2015, Surgical Neurology International. 6: 171). ALS is characterized by stiff muscles, muscle twitching, amyotrophy, and gradually worsening weakness due to muscles decreasing in size resulting in difficulties in walking, speaking, swallowing, and breathing. Baker goes on to teach acquiring and providing data as the claim requires, see Baker at [0037], [0038], [0383], [0100], [0170], [0275]-[0313], [0042], [0339] and [0554]. Given the broadest reasonable interpretation, the cited reference teaches the claimed feature.
Conclusion
Applicant’s amendment necessitated the new grounds of rejection presented in this Office action. 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.
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:
Fallon (US 2010/0169409) discloses system and method employing remote data gathering and monitoring for diagnosis, staging, and treatment of Parkinson’s disease, movement and neurological disorders and chronic pain.
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/L.T.K./Examiner, Art Unit 3683
/ROBERT W MORGAN/Supervisory Patent Examiner, Art Unit 3683
