DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 11/29/2023 & 04/29/2024 was filed. The submission 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 1-6 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.
The Supreme Court has long held that “[l]aws of nature, natural phenomena, and abstract ideas are not patentable.” Alice Corp. Pty. Ltd. v. CLS Bank Int’l, 134 S. Ct. 2347, 2354 (2014) (quoting Assoc. for Molecular Pathology v. Myriad Genetics, Inc., 133 S. Ct. 2107, 2116 (2013) (internal quotation marks omitted)). The “abstract ideas” category embodies the longstanding rule that an idea, by itself, is not patentable. Alice Corp., 134S. Ct. at 2355 (quoting Gottschalk v. Benson, 409 U.S. 63, 67 (1972).
In Alice, the Supreme Court sets forth an analytical “framework for distinguishing patents that claim laws of nature, natural phenomena, and abstract ideas [or mental processes ] from those that claim patent-eligible applications of those concepts.” Id. at 2355 (citing Mayo Collaborative Servs. v. Prometheus Labs., Inc., 132 S. Ct. 1289, 1296–97 (2012)). The first step in the analysis is to “determine whether the claims at issue are directed to one of those patent-ineligible concepts.” Id. If the claims are directed to a patent-ineligible concept, the second step in the analysis is to consider the elements of the claims “individually and ‘as an ordered combination’” to determine whether there are additional elements that “‘transform the nature of the claim’ into a patent-eligible application.” Id. (quoting Mayo, 132 S. Ct. at 1298, 1297). In other words, the second step is to “search for an ‘inventive concept’—i.e., an element or combination of elements that is ‘sufficient to ensure that the patent in practice amounts to significantly more than a patent upon the [ineligible concept] itself’”. Id. (brackets in original) (quoting Mayo, 132 S. Ct. at 1294). The prohibition against patenting an abstract idea “‘cannot be circumvented by attempting to limit the use of the formula to a particular technological environment’ or adding ‘insignificant post-solution activity.’” Bilski v. Kappos, 561 U.S. 593, 610–11 (2010) (citation omitted).
Step 1: This part of the eligibility analysis evaluates whether the claim falls within any statutory category. See MPEP 2106.03. Independent Claim 1 recites the method of generating disease management data based on a received user’s voice data, and thus is a process (a series of steps or acts). A process is a statutory category of invention. Independent Claim 4 recites a voice based disease management device configured to execute steps similar to Claim 1. A device or apparatus is a Statutory category of invention. Dependent claims 2, 3, 5 and 6 are dependent on claims 1 and 4, respectively, and therefore recite their respective statutory classes.
Step 2A, Prong One: This part of the eligibility analysis evaluates whether the claim recites a judicial exception. As explained in MPEP 2106.04, subsection II, a claim “recites” a judicial exception when the judicial exception is “set forth” or “described” in the claim. In applying the framework set out in Alice, examiner found Applicant’s claims 1 and 4 are directed to a patent-ineligible abstract concept of generating disease management data based on a user’s voice. The steps of Applicant’s claims 1-6 are an abstract concept that would fall under the judicial exception of mental processes. Specifically, the claims recite the step of “receiving… user’s voice data.” The receiving may simply involve a human, such as a doctor, listening to another human’s voice, such as a patient. Therefore, this step is directed to a mental process. Furthermore, the step of “generating… disease management data based on the voice data” also falls under the mental processes grouping because the recitation does not place any limits on how the disease management data is generated. Thus, under broadest reasonable interpretation, the generating may simply involve a doctor producing a diagnosis and treatment based on listening to the patient’s voice by subjecting the patient to a series of vocal tests that may help the doctor in the accurate diagnosis. Therefore, the claims recite limitations that taken in combination, recite at least a series of mathematical concepts.
Step 2A, Prong Two: This part of the eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception into a practical application of the exception. This evaluation is performed by (1) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (2) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application. See MPEP 2106.04(d).
The claims recite “a voice based disease management device” as an additional element beyond the judicial exception. However, the additional elements do not amount to significantly more than the abstract idea because the additional elements constitute a generic computer environment. Alice, 134 S. Ct. at 2357. The Claims need meaningful limitations that go beyond generally linking the use of an abstract idea to a particular technological environment. Therefore, the steps are all abstract and the Claim as a whole is abstract. “[S]imply appending generic computer functionality to lend speed or efficiency to the performance of an otherwise abstract concept does not meaningfully limit claim scope for purposes of patent eligibility.” CLS Bank, 2013 U.S. App. LEXIS 9493, at *29 (citing Bancorp, 687 F.3d at 1278, and Dealertrack, Inc. v. Huber, 674 F.3d 1315, 1333-34 (Fed. Cir. 2012) (finding that the claimed computer-aided clearinghouse process is a patent-ineligible abstract idea)); SiRF Tech., Inc. v. Int'l Trade Comm'n, 601 F.3d 1319, 1333 (Fed. Cir. 2010) (“In order for the addition of a machine to impose a meaningful limit on the scope of a claim, it must play a significant part in permitting the claimed method to be performed, rather than function solely as an obvious mechanism for permitting a solution to be achieved more quickly, i.e., through the utilization of a computer for performing calculations.”). Additionally, dependent claims 2, 3, 5 and 6 do not provide any additional elements that integrate the judicial exception into a practical application. The claims simply describe that the disease management data is generated from “context” and “out-of-context” data and where the “context data is characteristic data generated on a context including sentence completeness, word composition, or a vocabulary, and the out-of-context data is characteristic data generated out of the context including a tone, a pitch, or a stuttering level.” The dependent claims fail to provide any additional elements because they simply describe vocal analysis parameters that would fall under the mental processes grouping, without significantly more.
Step 2B: This part of the eligibility analysis evaluates whether the claim as a whole amounts to significantly more than the recited exception, i.e., whether any additional element, or combination of additional elements, adds an inventive concept to the claim. See MPEP 2106.05.
At step 2A, prong two, the additional element of “a vocal based disease management device” was found to be a generic computer environment. At Step 2B, the re-evaluation of the generic computing environment consideration takes into account whether or not the generic computer environment is well understood, routine, and conventional in the field. See MPEP 2106.05(g). Here, the element of a voice based disease management device is recited at such a high level of generality and no detail is provided as to how this device would perform as a specialized “disease management” device, that the device would constitute a generic computer environment. Even when considered in combination, this additional element represents a generic computing environment, and therefore does not provide an inventive concept. Additionally, dependent claims 2, 3, 5 and 6 do not add an inventive concept.
In conclusion, Examiner notes that none of recited steps in Applicant's claims 1-6 refer to a specific machine by reciting structural limitations of any apparatus or to any specific operations that would cause a machine to be the mechanism to perform these steps. Although the claims may be processed by “voice based disease management” device, the device is merely a general purpose computing system. Therefore, all of the claims 1-6 are abstract.
Claim Rejections - 35 USC § 102
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 1-6 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Medan (US PG Pub 20210118329).
As per claims 1 and 4, Medan discloses: A method and a voice based disease management device for performing disease management using voice data (Medan; Fig. 1; p. 0038), comprising: receiving, by the voice based disease management device, user’s voice data (Medan; Fig. 2, item 204; p. 0041 - recording the user's vocal (which is also verbal) response to the stimulus and/or to instructions; see also Fig. 1, item 112 – vocal input module); and generating, by the voice based disease management device, disease management data based on the voice data (Medan; p. 0045 - computing a multi parametric vector, based at least on data resulted from the texts comparison and the measured/extracted/compute prosodic parameters, and providing an output signal indicative of one or more of the user's speech/lingual/qualities (disease management data); see also p. 0048 - …providing feedback to the user or to the SLP regarding the results of each recording session and may also provide speech quality trends or a trend of selected speech/language parameter(s); see also p. 0038 - Each determined speech quality may be assigned a score, for example 1-10 or 1-100, and may be displayed on display unit 110 for the user's consideration or for the consideration or follow-up of a caregiver such as a speech and language pathologist (SLP). Display unit 110 may also present a trend of improvement/deterioration, recommendations, suggestions for practice, etc). As per claims 2 and 5, Medan discloses: The method and the voice based disease management device of claims 1 and 4, wherein the generating of the disease management data includes: extracting, by the voice based disease management device, context data and out-of-context data based on the voice data (Medan; Fig. 2, item 205; p. 0042 - processing the user's recorded vocal response to measure/extract compute at least one prosodic (linguistics) parameter (context data)… see also p. 0025 - parameters related to the multi parametric vector may include phonetic transcription, part of speech, semantic class, intensity, pitch, loudness, intonation, tone, stress, rhythm number of correct words, percentage of time associated with correct words, degree of acoustic similarity, degree of semantic similarity, or any combination thereof. According to some embodiments, parameters related to the multi parametric vector comprise lingual (context) and acoustic parameters (out-of-context)); and generating, by the voice based disease management device, the disease management data based on the context data and out-of-context data extracted based on the voice data (Medan; p. 0049-0057; see also p. 0038).
As per claims 3 and 6, Medan discloses: The method and the voice based disease management device of claims 2 and 5, wherein the context data is characteristic data generated on a context including sentence completeness, word composition, or a vocabulary, and the out-of-context data is characteristic data generated out of the context including a tone, a pitch, or a stuttering level (Medan; Fig. 2, item 205; p. 0042 - processing the user's recorded vocal response to measure/extract compute at least one prosodic (linguistics) parameter (context data)… see also p. 0025 - parameters related to the multi parametric vector may include phonetic transcription, part of speech, semantic class, intensity, pitch, loudness, intonation, tone, stress, rhythm number of correct words, percentage of time associated with correct words, degree of acoustic similarity, degree of semantic similarity, or any combination thereof. According to some embodiments, parameters related to the multi parametric vector comprise lingual (context) and acoustic parameters (out-of-context)).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. The prior art made of record and not relied upon includes:
Gomory (US PG Pub 20160117940) discloses a system, method, and apparatus for treating a communication disorder includes a user input assembly, a central processing unit configured to analyze data entered into the input assembly, and a user output assembly configured to generate a report reflecting the analysis of the data (Gomory; Abstract). Provost (US PG Pub 20200075040) discloses a method of predicting a mood state of a user that may include recording an audio sample via a microphone of a mobile computing device of the user based on the occurrence of an event, extracting a set of acoustic features from the audio sample, generating one or more emotion values by analyzing the set of acoustic features using a trained machine learning model, and determining the mood state of the user, based on the one or more emotion values. In some embodiments, the audio sample may be ambient audio recorded periodically, and/or call data of the user recorded during clinical calls or personal calls (Provost; Abstract).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Rodrigo A Chavez whose telephone number is (571)270-0139. The examiner can normally be reached Monday - Friday 9-6 ET.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Richemond Dorvil can be reached at 5712727602. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/RODRIGO A CHAVEZ/Examiner, Art Unit 2658
/RICHEMOND DORVIL/Supervisory Patent Examiner, Art Unit 2658
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