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 .
Status of Claims
This action is pursuant to claims filed on 02/03/2023. Claims 1- 22 are pending. A first action on the merits of claims 1- 22 is as follows.
Priority
Priority acknowledgement is made regarding applicant’s claim to the instant application as a U.S. National Stage under 35 U.S.C. 371 of PCT/IB2021/057224 filed on 08/05/2021, which claims benefit to U.S. provisional application number 63/061,348 filed on 08/05/2020. Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Claim Objections
Claim 22 is objected to because of the following informalities:
Claim 14, lines 2-3: “…include data storage means configured to storage all the data…” should read “…include data storage means configured to store all the data…”.
Claim 22, line 22: MPEP 608.01(m) states: “Each claim begins with a capital letter and ends with a period. Periods may not be used elsewhere in the claims except for abbreviations”.
Appropriate correction is required.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
Because these claim limitations are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, they are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
Such claim limitations being interpreted under 35 U.S.C. 112(f), and the identified structure, material, or act disclosed in the specification that supports the recited functions, are as follows:
“…a sound detection means and an accelerometer registering sound signals and acceleration variations in the skin of a user…” of claim 1.
Corresponding structure: see specification [0014], “…the operation of the device of the present invention is based in the use of an accelerometer and a microphone simultaneously,…”.
“…the control device comprising processing means and data transmission means… wherein the control device is configured to receive and process the signals obtained by the sensor device and to transmit processed data to an external location” of claim 1.
Corresponding structure: see specification [0016], “…control device can be configured to transmit information in real time to a user interface, such as an app in a smartphone via Bluetooth…”.
“…wherein the sensor device further comprises adhesive means configured to allow a removable fixation of the sensor device in the skin of the user,…” of claim 6.
“…wherein the energy storage means is configured to provide an autonomous operation of more than 12 hours for continuous recording…” of claim 12.
Corresponding structure: see specification [0030], “…the energy storage means (124) preferably consist of a battery that allows the system to operate without a physical connection to an external source …”.
“…wherein the processing means is configured to process and deliver the signals to an external location…” of claim 13.
Corresponding structure: see specification [0016], “…control device can be configured to transmit information in real time to a user interface, such as an app in a smartphone via Bluetooth…”.
“…wherein the transmission means is configured to transmit the processed data to the external location, where it can be later analyzed by a specialist, in a post- processing or medical analysis…” of claim 15.
Corresponding structure: see specification [0016], “…control device can be configured to transmit information in real time to a user interface, such as an app in a smartphone via Bluetooth…”.
“…wherein the processing means is configured to implement a vocal analysis engine, comprising algorithms designed for the assessment of the vocal function, with an analysis module…” of claim 18.
Corresponding structure: see specification [0037], “…vocal analysis engine comprises several algorithms designed for the assessment of the vocal function, with two analysis modules that operates with a neck surface acceleration signal (ACC) and a sound signal obtained by the sound detecting means, preferably a microphone (MIC) …”.
“…wherein the processing means is configured to provide daily reports including data generated by the Vocal Analysis Engine, such as raw features, daily/weekly statistics, and daily biofeedback summary…” of claim 21.
Corresponding Structure: see specification [0055], “…the processing means is configured to provide daily reports. Once the vocal health indicators are calculated, the Vocal Analysis Engine generates a summary of the results. These results are saved and sent to both the users, for example via a mobile application or a web browser, and the Health Specialist…”.
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 6, 13-15, 18 and 21, and all claims dependent thereon, are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement.
The claims contain subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventors, at the time the application was filed, had possession of the claimed invention.
Claim 19 recites “…wherein the analysis module includes… MIC signal de-intelligibility, in which the high-bandwidth signal is transformed into selected features, such as SPL(Sound Pressure Level) via MIC RMS (Root Mean Squared) , magnitude of FFT (Fast Fourier Transform)…” in lines 2-6.
Claims 6, 13-15, 18, and 21 recite limitations which invoke 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function.
A claim limitation expressed in means- (or step-) plus-function language “shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.” 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. If the specification fails to disclose sufficient corresponding structure, materials, or acts that perform the entire claimed function, then the claim limitation is indefinite because applicant has in effect failed to particularly point out and distinctly claim the invention as required by 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph. In re Donaldson Co., 16 F.3d 1189, 1195, 29 USPQ2d 1845, 1850 (Fed. Cir. 1994) (en banc). Such a limitation also lacks an adequate written description as required by 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112, first paragraph, because an indefinite, unbounded functional limitation would cover all ways of performing a function and indicate that the inventor has not provided sufficient disclosure to show possession of the invention (see MPEP §2163.03(VI)).
Claim 6 recites “…wherein the sensor device further comprises adhesive means configured to allow a removable fixation of the sensor device in the skin of the user,…”. Applicant has not pointed out where this claim limitation is supported, nor does there appear to be a written description of the claim limitation “…adhesive means configured to allow a removable fixation of the sensor device in the skin of the user…”.” in the application as filed. The specification discloses an adhesive means (see [0028]), however, no support is provided in the description or figures of the disclosure regarding a structure allowing removable fixation of a sensor device in the skin of a user, or structural and functional equivalents of such. The lack of written description leads Examiner to interpret “ adhesive means” as any structure capable of allowing removable fixation of the sensor device in the skin of the user.
Claim 13-15 recite, inter alia, “processing means configured to process”, “data storage means configured to storage” and “transmission means configured to transmit” respectively. Applicant has not pointed out where this claim limitation is supported, nor does there appear to be a written description of “processing means configured to process”, “data storage means configured to storage” and “transmission means configured to transmit” in the application as filed. No support is provided in the description or figures regarding the recited limitations, or structural and functional equivalents of such. The lack of written description leads Examiner to interpret “processing means” as any structure capable of processing signals, “data storage means” as any structure capable of storing collected data, and “transmission means” as any structure capable of transmitting data.
Claim 18 recites “…wherein the processing means is configured to implement a vocal analysis engine, comprising algorithms designed for the assessment of the vocal function…with an analysis module…” in lines 1-3. Applicant has not pointed out where this claim limitation is supported, nor does there appear to be a written description of “…processing means is configured to implement a vocal analysis engine… with an analysis module…” in the application as filed. No support is provided in the description or figures regarding the recited limitation, or structural and functional equivalents of such. The lack of written description leads Examiner to interpret “processing means” as any structure capable of performing vocal analysis.
Claim 21 recites “…wherein the processing means is configured to provide daily reports including data generated by the Vocal Analysis Engine, such as raw features, daily/weekly statistics, and daily biofeedback summary…”. Applicant has not pointed out where this claim limitation is supported, nor does there appear to be a written description of “…processing means…configured to provide daily reports…” in the application as filed. . No support is provided in the description or figures regarding the recited limitation, or structural and functional equivalents of such. The lack of written description leads Examiner to interpret “processing means” as any structure capable of providing daily reports.
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 6, 10, 11, 13-15, 18-22, and all claims dependent thereon, are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 10, 11, 19, 21, and 22 recite inter alia the phrase “such as”. The phrase "such as" renders the claims indefinite because it is unclear whether the limitations following the phrase are part of the claimed invention. See MPEP § 2173.05(d).
Claim 19 recites “…wherein the analysis module includes… MIC signal de-intelligibility, in which the high-bandwidth signal is transformed into selected features…” in lines 2-4. Where applicant acts as his or her own lexicographer to specifically define a term of a claim contrary to its ordinary meaning, the written description must clearly redefine the claim term and set forth the uncommon definition so as to put one reasonably skilled in the art on notice that the applicant intended to so redefine that claim term. Process Control Corp. v. HydReclaim Corp., 190 F.3d 1350, 1357, 52 USPQ2d 1029, 1033 (Fed. Cir. 1999). It is unclear what applicant intends the phrase “MIC signal de-intelligibility” to mean, and the specification does not clearly redefine the term. This renders the scope of the claim unclear, as there is ambiguity regarding how applicant intends to manipulate the microphone signals. For examination purposes, Examiner is interpreting “MIC signal de-intelligibility” as any transformation of microphone signals.
Claim 19 further recites “…MIC signal de-intelligibility, in which the high-bandwidth signal is transformed into selected features such as SPL (sound pressure level) via MIC RMS (root mean squared), magnitude of FFT (fast Fourier transform)…” in lines 3-6. There is insufficient antecedent basis for this limitation in the claim. Claims 1 and 18, from which claim 19 depends, does not recite a selection of features. According to the specification (see [0054]), it appears that SPL is an estimated parameter indicating an assessment of vocal function. It is unclear whether applicant intends for SPL to be a feature selected for analysis, or a parameter estimated by the analysis module. Additionally, it is unclear whether applicant intends to apply both RMS and FFT to sound signals obtained by the MIC, or if a magnitude of FFT is an alternatively recited feature. This renders the scope of the claim unclear, as there is ambiguity regarding what features applicant intends to select and how applicant intends to select them. For examination purposes, Examiner is interpreting “…in which the high-bandwidth signal is transformed into selected features such as SPL (sound pressure level) via MIC RMS (root mean squared), magnitude of FFT (fast Fourier transform)…” as any transformation of microphone signal data to sound pressure level, utilizing Fast Fourier Transform and Root Mean Squared.
Claim 19 further recites “…robust vocal activity detection on the ACC signal and related VAD features, using ACC and MIC correlation…” in lines 9-10. The term “robust” is a relative term which renders the scope of the claim unclear. The term “robust” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. This renders the claim indefinite, as there is ambiguity regarding what data applicant intends to manipulate.
Claim 19 further recites “…robust vocal activity detection on the ACC signal and related VAD features, using ACC and MIC correlation…” in lines 9-10. There is insufficient antecedent basis for this limitation in the claim. Claims 18/1 from which claim 19 depends, do not recite “related VAD features”. Additionally, what does applicant define as a “related” feature? This renders the scope of the claim unclear, as there is ambiguity regarding what features applicant intends to manipulate to perform vocal activity detection. For examination purposes, Examiner is interpreting “related VAD features” as any feature related to vocal activity detection.
Claim 19 further recites “…wherein the analysis module includes…acoustic dosimeter, including a background noise level detection via VAD and MIC signal processing…” in lines 15-16. According to the specification (see [0037]-[0038]), it would appear that the “analysis module” is referring to a structure implemented by a processor that analyzes signals obtained by the accelerometer and microphone. It is unclear how an acoustic dosimeter, a physical object, can be implemented by a processor for signal processing. This renders the scope of the claim unclear, as there is ambiguity regarding how applicant intends to manipulate collected data. Examiner recommends amending claim 19 to recite “…acoustic dosimetry including a background noise level detection…”.
Claim 20 recites “…aerodynamic features like AC flow…MFDR…SQ…obtained via the IBIF…algorithm from the ACC signal, including a calibration scheme to obtain robust subject-specific IBIF parameters using MIC inverse filtering…” in lines 4-10. The phrase "aerodynamic features like" renders the claim indefinite because it is unclear whether the limitations following the phrase are part of the claimed invention. See MPEP § 2173.05(d). For examination purposes, Examiner is interpreting features following the phrase “aerodynamic features like…” as a list of alternatives.
Claim 20 further recites “…SQ…obtained via the IBIF…algorithm…” in lines 6-8. There is insufficient antecedent basis for this limitation in the claim. Claim 18, from which claim 20 depends, recites “…a vocal analysis engine, comprising algorithms designed for the assessment of vocal function…” in lines 2-3. However, it is unclear if the IBIF algorithm recited in claim 20 is an algorithm recited in claim 18, or a new algorithm. This renders the scope of the claim unclear, as there is ambiguity regarding what data applicant intends to manipulate.
Claim 20 further recites “…robust subject-specific IBIF parameters…” in lines 9-10. The term “robust” is a relative term which renders the scope of the claim unclear. The term “robust” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. This renders the claim indefinite, as there is ambiguity regarding what data applicant intends to manipulate.
Claim 20 further recites “…subglottal pressure obtained by using multivariate linear regression (using the prior aerodynamic features, ACC, and IBIF features) using SPL from the MIC signal…” in lines 11-13. As described above, it is unclear which features following the phrase “aerodynamic features like” recited in line 4 of claim 20 are included in the claimed invention. Additionally, there is insufficient antecedent basis for this limitation in the claim, as it is unclear what IBIF features applicant is referring to. This renders the scope of the claim unclear, as there is ambiguity regarding what data applicant intends to manipulate to obtain subglottal pressure. For examination purposes, Examiner is interpreting the recited limitation as obtaining subglottal pressure using multivariate linear regression (using any of the recited aerodynamic features, ACC, and any IBIF feature) using SPL from the MIC signal.
Claims 21 and 22 recite “daily/weekly” and “and/or” respectively. It is unclear if this is meant to be inclusive of daily and weekly, or if it is meant to be an alternative of daily or weekly. This renders the scope of the claim unclear, as there is ambiguity regarding whether applicant intends for the recited limitations to represent an inclusive list, or a list of alternatives.
Claim 22 recites the phrase “such as for example” (see lines 21-22). The phrase "such as for example" renders the claim indefinite because it is unclear whether the limitation(s) following the phrase are part of the claimed invention. See MPEP § 2173.05(d).
Claim 22 further recites “..wherein the Vocal Analysis Engine is also capable of generating graphic information based on the daily reports and user-requested analyses, and provide a correlation between the obtained parameters and habits of the user and environmental characteristics…” in lines 1-5. Claim 22 further recites “…a comparison of the parameters in the same time window between the different days of the analysis…” in lines 13-14, further recites “…correlate alterations in the parameters obtained with the user's habits and environmental variables…” in lines 15-16, and further recites “…estimating parameters to identify and support the diagnosis of different pathologies…” in lines 20-21. There is insufficient antecedent basis for this limitation in the claim. Claims 21/18/1, from which claim 22 depends, do not define “parameters” as recited in claim 22. This renders the scope of the claim unclear, as there is ambiguity regarding what data applicant intends to manipulate to provide a correlation. For examination purposes, Examiner is interpreting “parameters” as any feature related to vocal activity detection.
Claim 22 further recites “…waveform and spectral visualization across time with user defined window time…” in lines 6-7, and further recites “…multiple vocal health measures across time with smoothing and user defined window time…” in lines 8-9. There is insufficient antecedent basis for this limitation in the claim. It is unclear if the “user defined window time” recited in lines 6-7 and 8-9 are the same user defined window time, or different user defined window times. This renders the scope of the claim unclear, as there is ambiguity regarding what data applicant intends to manipulate.
Claim 22 further recites “…uni- and bi-dimensional histograms for any of the standard or advanced vocal measures…” in lines 10-11. There is insufficient antecedent basis for this limitation in the claim. Claims 21/18/1, from which claim 22 depends, do not recite “standard vocal measures” or “advanced vocal measures”. This renders the scope of the claim unclear, as there is ambiguity regarding what data applicant intends to manipulate to produce uni- and bi-directional histograms. For examination purposes, Examiner is interpreting “any of the standard or advanced vocal measures” as any measure of vocal function.
Claim 22 further recites “…visualization with the UMAP dimensionality reduction technique…” in lines 12-13. There is insufficient antecedent basis for this limitation in the claim. Claims 21/18/1, from which claim 22 depends, do not recite “a UMAP dimensionality reduction technique” and additionally fail to define “UMAP” . This renders the scope of the claim unclear, as there is ambiguity regarding how applicant intends to manipulate collected data.
Claims 6, 13-15, 18, and 21 recite limitations which invoke 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function, rendering the scope of the claims, and all claims dependent thereon, indefinite.
The primary purpose of this requirement of definiteness of claim language is to ensure that the scope of the claims is clear so the public is informed of the boundaries of what constitutes infringement of the patent. See MPEP 2173. Claims invoking § 112, sixth paragraph, must have some structure to "avoid pure functional claiming.” Aristocrat Techs. Australia Pty Ltd. v. Int'l Game Tech., 521 F.3d 1328, 1333 (Fed. Cir. 2008). For a computer-implemented means plus function claim limitation invoking § 112, sixth paragraph, the corresponding structure must be more than simply a general purpose computer or microprocessor because these components can be programmed to perform very different functions in very different ways. Id. The structure must include the algorithm needed to transform the general purpose computer or microprocessor into a structure that is a special purpose computer. Id.at 1338.
A rejection under § 112, second paragraph, is appropriate if the specification discloses no corresponding algorithm associated with a computer or microprocessor. Id.at 1337-38. The specification must explicitly disclose the algorithm, and simply reciting the claimed function in the specification will not be a sufficient disclosure for an algorithm. Blackboard, Inc. v. Design2Learn, Inc., 574 F.3d 1371, 1384 (stating that language that simply describes the function to be performed describes an outcome, not a means for achieving that outcome).
Claim 6 recites “…wherein the sensor device further comprises adhesive means configured to allow a removable fixation of the sensor device in the skin of the user,…”. The specification discloses an adhesive means (see [0028]), however, the disclosure fails to disclose any structure that performs the entire claimed function allowing removable fixation of the sensor device in the skin of the user, rendering the scope of the claim unclear.
Claim 13-15 recite, inter alia, “processing means configured to process”, “data storage means configured to storage” and “transmission means configured to transmit” respectively. Merely restating a function associated with a means-plus-function limitation is insufficient to provide the corresponding structure for definiteness. See, e.g., Noah, 675 F.3d at 1317, 102 USPQ2d at 1419; Blackboard, 574 F.3d at 1384, 91 USPQ2d at 1491; Aristocrat, 521 F.3d at 1334, 86 USPQ2d at 1239.
Claim 18 recites “…wherein the processing means is configured to implement a vocal analysis engine, comprising algorithms designed for the assessment of the vocal function…with an analysis module…” in lines 1-3. However, the disclosure fails to disclose any structure or algorithm that performs the entire claimed function (i.e., implementing a vocal analysis engine with an analysis module). The specification must explicitly disclose the algorithm for performing the claimed function, and simply reciting the claimed function in the specification will not be a sufficient disclosure for an algorithm which, by definition, must contain a sequence of steps. Blackboard, 574 F.3d at 1384, 91 USPQ2d at 1492.
Claim 19 recites “…wherein the analysis module includes… MIC signal de-intelligibility, in which the high-bandwidth signal is transformed into selected features, such as SPL(Sound Pressure Level) via MIC RMS (Root Mean Squared) , magnitude of FFT (Fast Fourier Transform)…” in lines 2-6.
Claim 21 recites “…wherein the processing means is configured to provide daily reports including data generated by the Vocal Analysis Engine, such as raw features, daily/weekly statistics, and daily biofeedback summary…” However, the disclosure fails to disclose any structure or algorithm that performs the entire claimed function (i.e., providing daily reports). The specification must explicitly disclose the algorithm for performing the claimed function, and simply reciting the claimed function in the specification will not be a sufficient disclosure for an algorithm which, by definition, must contain a sequence of steps. Blackboard, 574 F.3d at 1384, 91 USPQ2d at 1492.
Therefore, these claims are indefinite and is rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph.
Applicant may:
(a) Amend the claim so that the claim limitation will no longer be interpreted as a limitation under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph;
(b) Amend the written description of the specification such that it expressly recites what structure, material, or acts perform the entire claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(c) Amend the written description of the specification such that it clearly links the structure, material, or acts disclosed therein to the function recited in the claim, without introducing any new matter (35 U.S.C. 132(a)).
If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure, material, or acts and clearly links them to the function so that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed function, applicant should clarify the record by either:
(a) Amending the written description of the specification such that it expressly recites the corresponding structure, material, or acts for performing the claimed function and clearly links or associates the structure, material, or acts to the claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(b) Stating on the record what the corresponding structure, material, or acts, which are implicitly or inherently set forth in the written description of the specification, perform the claimed function. For more information, see 37 CFR 1.75(d) and MPEP §§ 608.01(o) and 2181.
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 (i.e., changing from AIA to pre-AIA ) 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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-6, 8-10, 13-16, and 18 are rejected under 35 U.S.C. 102(a)(1) and 102(a)(2) as being anticipated by US 2020/0128317 to Feldman.
Regarding independent claim 1: Feldman discloses a wearable voice detection system in the form of a necklace (see abstract and Figs. 9A-9D, “…throat microphone system and method… microphone unit may attach to the neck of the wearer and may encircle the neck…”) comprising:
A sensor device comprising a sound detection means and an accelerometer registering sound signals and acceleration variations in the skin of a user (see [0069], “…sensor may comprise a contact microphone, accelerometer, or other type of vibrational sensor mounted against a part of the body of the wearer (such as against the neck of the wearer)…”, sound detection means (i.e., microphone registering sound signals) and accelerometer mounted to the neck of a user to sense vibrational changes);
a control device in electrical communication with the sensor device , the control device comprising processing means and data transmission means (see Figs. 3A-3B and [0101]-[0103], “…audio module 304 (configured to communicate wirelessly with receiver unit 112)… wireless audio module 304 may comprise a 2.4 GHz transceiver module (e.g., non-Bluetooth)…wireless audio module 304 may comprise Bluetooth communication in order to communicate directly with mobile electronic device 114 … used in order to process the sound data, such as to voice unvoiced speech…”,audio module 304 (i.e., control device) electrically communicates with sensor device and has processing and data transmission means (i.e., Bluetooth)) ;
wherein the control device is configured to receive and process the signals obtained by the sensor device and to transmit processed data to an external location (see Figs. 3A-3B and [0104], “…the data from the various sensors, including the voice stream and/or the pulse data, may be transmitted wirelessly to one or more electronic devices external to the microphone unit”).
Regarding claim 2: Feldman discloses a wearable voice detection system according to claim 1, as discussed above. Feldman further discloses wherein the control device and the sensor device are connected by means of an electrical connection that allows the transfer of the signals captured by the sensor device to the control device to be processed (see Figs. 3A-3B and [0104], “…data from the various sensors, including the voice stream and/or the pulse data, may be transmitted wirelessly to one or more electronic devices external to the microphone unit”).
Regarding claim 3: Feldman discloses a wearable voice detection system according to claim 1, as discussed above. Feldman further discloses wherein the control device is located on the back of the neck and the sensor device in the frontal area, close to the trachea to allow a more accurate reception of the signals (see Fig. 9C and [0141], “…microphone unit that houses that battery and transmitter is positioned below (such as approximately 3 inches below) the ear of the wearer, as shown in FIGS. 9A and 9C. Further, when the microphone unit 900, 950 is attached to the wearer, the microphone of the microphone unit may be positioned proximate to the larynx”).
Regarding claim 4: Feldman discloses a wearable voice detection system according to claim 3/1, as discussed above. Feldman further discloses wherein the sensor device locates on the neck skin between the sternal notch and the thyroid prominence (see [0068], “…sensor may be positioned in or on any one, any combination, or all of: on the throat (e.g., on or proximate to the hyoid bone; on or proximate to the thyroid cartilage; on or proximate to the cricoid cartilage…”, location on the cricoid cartilage locates the device between the sternal notch and the thyroid prominence ).
Regarding claim 5: Feldman discloses a wearable voice detection system according to claim 1, as discussed above. Feldman further discloses wherein the sensor device comprises the sound detecting means , an accelerometer housing , the accelerometer , a front casing and back cover configured to couple and provide a housing for the sensor device (see [0072], “…the vibration sensor…positioned in the same housing as the microphone, with the housing configured for attachment on the throat of the person…”See also [0172], “…some, or all of microphone unit 800 may be encased in a rubber, such as silicone rubber. For example, in one implementation, each of the microphone unit (which may include one PCB), the flex ribbon cable, and the transmitter (which may include a second PCB and a battery) may be encased in an enclosure…”).
Regarding claim 6: Feldman discloses a wearable voice detection system according to claim 5/1, as discussed above. Feldman further discloses wherein the sensor device further comprises adhesive means configured to allow a removable fixation of the sensor device in the skin of the user (see [0138], “…microphone unit 800 may use an adhesive (such as die-cut double-sided adhesive) to adhere the microphone unit 800 to the neck of the wearer…”), and a rubber or silicone pad selected such to not affect the capture of the signals (see [0172], “…some, or all of microphone unit 800 may be encased in a rubber, such as silicone rubber. For example, in one implementation, each of the microphone unit (which may include one PCB), the flex ribbon cable, and the transmitter (which may include a second PCB and a battery) may be encased in an enclosure…”).
Regarding claim 8: Feldman discloses a wearable voice detection system according to claim 1, as discussed above. Feldman further discloses wherein the control device comprises a control means , front casing , the processing means , energy storage means and a back cover (see [0133], “…microphone unit 800 may be encased in a rubber, such as silicone rubber. For example, in one implementation, each of the microphone unit (which may include one PCB), the flex ribbon cable, and the transmitter (which may include a second PCB and a battery) may be encased in an enclosure…”).
Regarding claim 9: Feldman discloses a wearable voice detection system according to claim 8/1, as discussed above. Feldman further discloses wherein the control means includes one or more buttons to allow the control of some operational features of the system (see [0132], “…buttons 804, 806 are resident on main unit 802. In one implementation, button 804 comprises an on/off button, and button 806 comprises a feature button…”).
Regarding claim 10: Feldman discloses a wearable voice detection system according to claim 8/1, as discussed above. Feldman further discloses wherein the control means includes a keypad having one or more buttons or a touchpad, and is configured to provide basic commands for the operation of the system, such as turning the system on and off, among others (see Fig. 8A and [0132], “…buttons 804, 806 are resident on main unit 802. In one implementation, button 804 comprises an on/off button, and button 806 comprises a feature button, such as a mute button…”, front face of main unit 802 includes buttons 804 and 806 (i.e., a keypad having one or more buttons) which turn the system on and off and mute the system (i.e., turning the system on and off and providing commands for control of the system).
Regarding claim 13: Feldman discloses a wearable voice detection system according to claim 1, as discussed above. Feldman further discloses wherein the processing means is configured to process and deliver the signals to an external location (see Figs. 3A-3B and [0104], “…the data from the various sensors, including the voice stream and/or the pulse data, may be transmitted wirelessly to one or more electronic devices external to the microphone unit”)..
Regarding claim 14: Feldman discloses a wearable voice detection system according to claim 1, as discussed above. Feldman further discloses wherein the processing means include data storage means configured to storage all the data that is being processed by the system (see [0149], “…computer-readable medium can include a magneto-optical or optical medium, such as a disk or tapes or other storage device to capture carrier wave signals such as a signal communicated over a transmission medium…”).
Regarding claim 15: Feldman discloses a wearable voice detection system according to claim 1, as discussed above. Feldman further discloses wherein the transmission means is configured to transmit the processed data to the external location, where it can be later analyzed by a specialist, in a post- processing or medical analysis (see Figs. 3A-3B and [0101]-[0104], “…audio module 304 (configured to communicate wirelessly with receiver unit 112)… wireless audio module 304 may comprise a 2.4 GHz transceiver module (e.g., non-Bluetooth)…wireless audio module 304 may comprise Bluetooth communication in order to communicate directly with mobile electronic device 114 … used in order to process the sound data … data from the various sensors, including the voice stream and/or the pulse data, may be transmitted wirelessly to one or more electronic devices external to the microphone unit…”,audio module 304 (i.e., control device) electrically communicates with sensor device and has processing and data transmission means (i.e., Bluetooth) to transmit data to an external location).
Regarding claim 16: Feldman discloses a wearable voice detection system according to claim 15/1, as discussed above. Feldman further discloses wherein the processed data is preferably transmitted to a user interface, which is configured to visualize and analyze the data in a corresponding software (see [0084], “…throat microphone application 175 (the functionality being discussed further below), input/output device(s) 173 (such as touch sensitive displays, keyboards, or the like), and a communication interface 172 (which may include any one, any combination, or all of: near-field communication (e.g., Bluetooth)…application 175 may be a representation of software, hardware, firmware, and/or middleware configured to implement functionality of the throat microphone system…”, user interface (i.e., throat microphone application) processes and displays information (i.e., visualizes and analyzes data)).
Regarding claim 18: Feldman discloses a wearable voice detection system according to claim 1, as discussed above. Feldman further discloses wherein the processing means is configured to implement a vocal analysis engine, comprising algorithms designed for the assessment of the vocal function, with an analysis module that operates with a neck surface acceleration signal (ACC) and a sound signal obtained by the sound detecting means, preferably a microphone (MIC) (see [0069], “…sensor may comprise a contact microphone, accelerometer, or other type of vibrational sensor mounted against a part of the body of the wearer (such as against the neck of the wearer)…”, see also [0073], “…the processor analyzing one or both of the non-audio data or the voice activity detector may employ…artificial intelligence algorithms in order to assemble the proper vibrational profile to detect when the wearer is actually speaking…”, microphone (i.e., MIC) detects sound signals (i.e., sound detection means) and an accelerometer mounted to the neck of a user senses vibrational changes (i.e., ACC, neck surface acceleration signal), which are analyzed by a processor (i.e., vocal analysis engine) using artificial intelligence algorithms (i.e., an analysis module) to detect when a user is speaking (i.e., assess a user’s vocal function)).
Claims 7, 11, and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Feldman.
Regarding claim 7: Feldman discloses a wearable voice detection system according to claim 5/1, as discussed above. Feldman further discloses an accelerometer mounted against the skin of a wearer (see [0069], “the sensor may comprise a contact microphone, accelerometer, or other type of vibrational sensor mounted against a part of the body of the wearer (such as against the neck of the wearer)…”) and an accelerometer and microphone located in the same housing (see [0072], “…the non-audio data sensor and the microphone are in the same housing and positioned on the same part of the body of the person…”).
However, although Feldman fails to explicitly disclose wherein the back cover includes a hole to allow a communication between the accelerometer and skin of the user, such modification would have been obvious to one of ordinary skill in the art at the time the invention was made since it has been held that omission of an element and its function in a combination where the remaining elements perform the same functions as before involves only routine skill in the art. In re Karlson, 136 USPQ 184.
Regarding claim 11: Feldman discloses a wearable voice detection system according to claim 8/1, as discussed above. Feldman further discloses touch sensitive displays for displaying information (see [0084], “…well known computing systems, environments, and/or configurations that may be suitable for implementing features of the throat microphone application 175 such as, but are not limited to, smartphones, tablet computers, personal computers (PCs), server computers, handheld or laptop devices, multiprocessor systems, microprocessor-based systems, network PCs, or devices… input/output device(s) 173 (such as touch sensitive displays, keyboards, or the like), and a communication interface…”).
However, Feldman fails to explicitly disclose wherein the control means includes displaying means, such as a screen or lights to provide basic information about the status of the operation, like the battery level, or other operation features.
Although Feldman fails to explicitly disclose the control means including a displaying means, such modification would have been obvious to one of ordinary skill in the art at the time the invention was filed since it has been held that providing a mechanical or automatic means to replace manual activity, which accomplishes the same result, is within the ambit of a person of ordinary skill in the art. See In re Venner, 120 USPQ 192 (CCPA 1958) (see MPEP § 2144.04).
Regarding claim 17: Feldman discloses a wearable voice detection system according to claim 1, as discussed above. Feldman further discloses wherein the processing means is configured to implement treatments or algorithms to the input signal (see [0114], “…mobile computing device processes the audio data in preparation for output…mobile computing device causes the processed audio data to be used in some form, such as transmitted to another device for output…”, processing for output (i.e., treatment of input signal)), including filtering by hardware to precondition the signal (see [0116], “…app on the smartphone may use a rumble filter…eliminating the noise resident in the lower end frequencies of the audio input, …”, application on smartphone (i.e., hardware based application) filters input signals to eliminate noise (i.e., precondition signals)).
However, Feldman fails to explicitly disclose use of an audio codec to further process the signals.
Feldman further discloses signal encoding executed by a processor (see [0148], “…medium that can be capable of storing, encoding or carrying a set of instructions for execution by a processor…”), and an analog to digital converter to perform digital signal processing (see [0143], “…enable different parts of the circuit, such as filtering 1004 (configured to filter the audio signal generated by microphone 1002), analog-to-digital conversion (ADC) 1006, and signal processing 1008 (such as digital signal processing)…”).
Although Feldman fails to explicitly disclose an audio codec to further process signals, Feldman teaches signal processing using encoding. Therefore, such modification (use of an audio codec) would have been obvious to one of ordinary skill in the art at the time the invention was made, since it has been held that providing a mechanical or automatic means to replace manual activity, which accomplishes the same result, is within the ambit of a person of ordinary skill in the art. See In re Venner, 120 USPQ 192 (CCPA 1958) (see MPEP § 2144.04).
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over Feldman in view of US 2021/0113099 A1 to Rogers et al. (“Rogers”).
Regarding claim 12: Feldman discloses a wearable voice detection system according to claim 8/1, as discussed above. Feldman further discloses wherein the energy storage means is configured to provide an autonomous operation (see [0101], “…battery 314 (such as a Lithium Polymer battery)….”, battery (i.e., energy storage means) providing power to device (i.e., autonomous operation)).
However, Feldman is silent regarding providing an autonomous operation of more than 12 hours for continuous recording.
Rogers teaches systems and methods for wearable mechano-acoustic electrophysiological sensing (see [0002], “…Systems and methods are provided for mechano-acoustic electrophysiological sensing electronics derived from the body…devices are referred herein as soft, flexible, and wearable…”) including continuous recording of mechano-acoustic signals for 48 hours (see [0259], “…suitable for use in a continuous, wearable mode of operation in recording mechano-acoustic signals originated from human physiological activities… recording continues for 48 hours…”).
Feldman discloses a battery operated device providing autonomous operation, but fails to explicitly disclose a length of operational time. Rogers teaches continuous recording operation for a period of 48 hours. Therefore, it would have been obvious to one of ordinary skill in the art at the time the invention was filed to modify Feldman (to provide autonomous operation for more than 12 hours) for the purpose of recording large volumes of data over a period of time to advance clinical assessment and monitoring of patients, as evidence by Rogers (see [0204]). Furthermore, one of ordinary skill in the art would have had predictable success combining the teachings of Feldman and Rogers since both teachings relate to the same narrow field of endeavor, i.e., mechano-acoustic patient monitoring.
Additionally, although Feldman is silent regarding more than 12 hours for continuous recording, such modification (optimization of battery life) would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention since it has been held that where the general conditions of a claim are disclosed in the prior art, discovering the optimum or workable ranges involves only routine skill in the art. In re Aller, 105 USPQ 233.
Claim 19 is rejected under 35 U.S.C. 103 as being unpatentable over Feldman in view of US 2019/0231233 A1 to Turner et al. (“Turner”), further in view of Rogers, and further in view of a research article entitled “Comparison of Vocal Vibration-Dose Measures for Potential-Damage Risk Criteria” by Titze et al. (“Titze”).
Regarding claim 19: Feldman discloses a wearable voice detection system according to claim 18/1, as discussed above. Feldman further discloses MIC signal de-intelligibility (i.e., processing microphone data, see 112(b) section above) by transforming high bandwidth acoustic signals using FFT (see [0033], “…Processing of the sound data… filtering (e.g., high pass filtering)…controlled using one or more parameters inputs for voice spectrum analysis and/or fast Fourier transforms…”, performing high pass filtering on input microphone signals (i.e., transforming high-bandwidth signals into selected features)), using Fast Fourier Transform parameters (i.e., FFT)).
vocal activity detection using microphone and accelerometer signals (see [0145], “…VAD 1054 is configured to perform voice activity detection, also known as speech activity detection or speech detection…detect human speech by band-limiting the analog audio input signal from microphone 1002, compute signal energy within a given time window…”, )
- robust vocal activity detection on the ACC signal and related VAD features, using ACC and MIC correlation (see [0144]-[0145], “…a voice detector 1052 that uses non-audio data to detect whether voice is in data generated by a microphone 1002. … discriminate between ambient noise and human speech… signal sampled at the same rate as the corresponding acoustic signals, with a zero value representing that no speech has occurred during the corresponding time sample, and a unity value indicating that speech has occurred during the corresponding time sample…” non-audio data (i.e., neck accelerometer data) and acoustic signals (i.e., microphone audio data) are used perform vocal activity detection by determining if a relationship (i.e., correlation) exists between the non-audio data and microphone acoustic signal in a given period of time),
- vocal intensity that is made via both MIC and ACC data after VAD (see [0044], “…parameter(s) may be tailored to the speaker based on analysis of the processed sound data… In particular… speech intensity level…” speech intensity level (i.e., vocal intensity) determined using processed sound data (i.e., microphone and accelerometer data));
- acoustic monitoring including a background noise level detection via VAD and MIC signal processing (see [0066], “…By way of background…only process audio data that is generated by vocal sounds of the person (as opposed to audio data that is generated by other sounds, such as other speakers, other external noises, or the like)… a voice activity detector (alternatively known as voice activity detection) may analyze the voice stream…”, differentiating between vocal sounds and background noise (i.e., background noise level detection) using microphone signals and voice activity detection) ;
However, Feldman fails to explicitly disclose “…MIC signal de-intelligibility in which the high bandwidth signal is transformed into SPL (sound pressure level) via MIC RMS (Root Mean Squared)…”.
Turner teaches modification of speech audio signals by measuring sound pressure level (see [0001], “…relates to the modification of audio signals, for example speech and music, using results of the hearing test…”, see also [0165], “…a sound pressure level indicative of the sound volume …”) using RMS and FFT processing (see [0217], “…correction factor…when a 65-dB SPL speech noise is applied…done in the FFT domain, in preferred embodiments it is completed with a signal file with the same digital RMS as the level at which the insertion gains are specified…”).
Feldman discloses a wearable voice detection system (see abstract) and processing microphone data (i.e., MIC signal de-intelligibility, see 112(b) section above) by transforming high bandwidth acoustic signals using FFT (see [0033]), but fails to explicitly disclose transforming microphone signals to Sound Pressure Level using Root Mean Squared and FFT. Turner teaches sound pressure level audio signal transformation using RMS and FFT parameters (see [0217]).
Therefore, it would have been prima facie obvious to one having ordinary skill in the art at the time the invention was filed to modify Feldman (to transform microphone signals to sound pressure level using root mean squared and fast Fourier transform) for the purpose of enhancing audio signals, as evidence by Turner (see [0001]). Furthermore, one of ordinary skill in the art would have had predictable success combining Feldman and Turner since both teachings relate to the same narrow field of endeavor, i.e., audio data processing.
Additionally, Feldman fails to explicitly disclose “… daily ACC placement calibration check, which is made via both MIC RMS and ACC data after VAD (vocal activity detection)…”
Feldman further discloses a local adjustment of system parameters (see [0029], “…allow for the remote or even local adjustment of configuration & parameters…”, local adjustment of parameters (i.e., calibration check)), daily voice biomarker analysis (see [0064], “…voice biomarker analysis…analyzed at multiple points in time (such as daily, weekly, monthly, etc.)…”), and using an accelerometer mounted to the neck of a user to detect movement (see [0069], “…a sensor configured to sense muscle movement in order to generate muscle movement data.…sensor may comprise…accelerometer…mounted against a part of the body of the wearer (such as against the neck of the wearer)…”). Turner further teaches initial and on-going calibration of sound processing parameters (see [0115], “…initial and on-going calibration as well as parameters for sound processing algorithms…”). However, the Feldman/Turner combination fails to explicitly teach a daily neck surface acceleration signal placement calibration check made via both microphone RMS data and ACC data.
Rogers teaches systems and methods for wearable mechano-acoustic electrophysiological sensing (see [0002], “…Systems and methods are provided for mechano-acoustic electrophysiological sensing electronics derived from the body…devices are referred herein as soft, flexible, and wearable…”) including processing filtered acoustic signals using RMS values (see [0230], “…filtered signal is then passed through a root-means square value threshold…”). Rogers further teaches system calibration using reinforced learning (see [0180], “Reinforced Learning…enables the system to auto-adjust and calibrate…”).
The Feldman/Turner combination teaches daily parameter analysis, a calibration check, adjusting system parameters, and using data from a neck mounted accelerometer to detect movement, but fails to disclose a calibration check using both RMS and a neck acceleration signal. Rogers teaches microphone system calibration and acoustic signal processing using RMS.
Therefore, it would have been prima facie obvious to one having ordinary skill in the art at the time the invention was filed to modify the Feldman/Turner combination (to perform a daily ACC placement calibration check using microphone ACC and RMS) for the purpose of improving sensor performance parameters, as evidence by Rogers (see [0015]). Furthermore, one of ordinary skill in the art would have had predictable success combining Feldman, Turner, and Rogers, since their teachings relate to the same narrow field of endeavor, i.e., audio data processing.
Additionally, although Feldman fails to explicitly disclose “…vocal intensity that is made via both MIC RMS and ACC data after VAD…”, Rogers further teaches processing filtered acoustic signals using RMS values (see [0230], “…filtered signal is then passed through a root-means square value threshold…”).
Therefore, it would have been prima facie obvious to one having ordinary skill in the art at the time the invention was filed to modify the Feldman/Turner/Rogers combination (to determine vocal intensity using microphone RMS and ACC data) for the purpose of improving data parsing to differentiate physiological information, as evidence by Rogers (see [0262]).
Additionally, Feldman fails to explicitly disclose “…fundamental frequency f0, from the ACC signal using autocorrelation…”.
Rogers teaches a range of vibrational fundamental frequency harmonics for talking adults (see [0108], “… Vibration frequencies of vocal folds in humans range from 90 to 2000 Hz. With an average fundamental frequency of ˜116 Hz (male, mean age, 19.5), ˜217 Hz (female; mean age, 19.5), and ˜226 Hz (child, age 9 to 11) during conversation…”) and further teaches automatic distinction of speech using harmonics of the fundamental frequency of the human voice (see [0275], “…Talking signals are distinguishable by the presence of a second harmonics of the fundamental frequency F0 as a local maxima of power spectral density in the range of human voice…”, vibrational fundamental frequency harmonics of the human voice used to distinguish speech (i.e., autocorrelation of vibrational signals to harmonics of vocal fundamental frequencies)).
Therefore, it would have been prima facie obvious to one having ordinary skill in the art at the time the invention was filed to modify the Feldman/Turner/Rogers combination (to determine fundamental frequency of neck acceleration signals using autocorrelation) for the purpose of differentiating between speaking and non-speaking events of a subject, as evidence by Rogers (see [0275]).
Additionally, Feldman fails to explicitly disclose “…vocal dose (SPL and f0 from the ACC signal) including cycle and distance dose…”,
The Feldman/Turner/Rogers combination teaches determining sound pressure level (see Turner [0165], “…threshold axis represents a sound pressure level indicative of the sound volume…”) and determining fundamental frequency from a neck acceleration signal (of the Feldman/Turner/Rogers combination) (see Rogers [0275], “…the fundamental frequency F0…”), but fails to explicitly disclose a vocal dose including cycle and distance dose.
Titze teaches vocal vibration dosimetry analysis (see abstract) by measuring vibrational acceleration signals at the neck of a user (see pg. 1428, col. 1, “…estimate vibration amplitude from skin acceleration measured on the neck…”), and determining vibrational dose using fundamental frequency and SPL (see Fig. 4 and page 1432 col. 1, “…all of the dose measures are dependent on basic measures such as f0 and SPL…”) including cycle and distance dose (see pg. 1426, col. 1, “…four vibration-dose calculations (time dose, cycle dose, distance dose, and energy dose)…”).
Therefore, it would have been prima facie obvious to one having ordinary skill in the art at the time the invention was filed to modify the Feldman/Turner/Rogers combination (to determine vocal dose including cycle and distance dose) for the purpose of determining tradeoffs between various parameters of vocal loading analysis, as evidence by Titze (see pg. 1426, col. 1). Furthermore, one of ordinary skill in the art would have had predictable success combining Feldman/Turner/Rogers and Titze since their teachings relate to the same narrow field of endeavor, i.e., vocal analysis.
Additionally, Feldman fails to explicitly disclose “…acoustic dosimeter, including a background noise level detection via VAD and MIC signal processing…”.
Feldman further discloses background noise level detection using microphone signal processing and VAD (see [0066]), but fails to explicitly disclose an acoustic dosimeter.
Titze further teaches a vocal dosimeter (see pg.1425 col. 2 – 1426 col. 1, “…dose calculations are performed in ambulatory phonation monitoring devices and voice dosimeters…”).
Therefore, it would have been prima facie obvious to one having ordinary skill in the art at the time the invention was filed to modify the Feldman/Turner/Rogers/Titze combination (to use an acoustic dosimeter to determine background noise level) for the purpose of noninvasively collecting acoustic data, as evidence by Titze (see pg. 1425).
Additionally, Feldman fails to explicitly disclose “…vocal efficiency (SPL vs. ACC)…”.
Titze further teaches a comparison of skin acceleration and SPL measurements (see Fig. 2 and pg. 1428, col. 2, “…comparison of amplitude estimation from SPL measurements…and from tissue acceleration…from visual and SAL measurements…”).
Therefore, it would have been prima facie obvious to one having ordinary skill in the art at the time the invention was filed to modify the Feldman/Turner/Rogers/Titze combination (to use an acoustic dosimeter to determine background noise level) for the purpose of comparison between vocal dose calculations, as evidence by Titze (see pg. 1428).
Additionally, Feldman fails to explicitly disclose “…- H1-H2, ratio between the first and the second harmonic, FFT base on ACC signal…”.
The Feldman/Turner/Rogers/Titze combination further teaches determining a ratio based on input signals (see Feldman [0040], “…Compression ratio may specify the amount of attenuation to be applied to the signal. A wide range of ratios may be available (and may be selected based on the profile)…”) and further teaches additional harmonics of the fundamental frequency in the range of the human voice (see Rogers [0275], “…presence of a second harmonics of the fundamental frequency F0 as a local maxima of power spectral density in the range of human voice…”).
Although the Feldman/Turner/Rogers/Titze combination is silent regarding a ratio between the first and second harmonic FFT based on the neck acceleration signal, Feldman discloses using signal data to determine a ratio (see Feldman [0040]), and Rogers teaches speech differentiation using harmonics of the fundamental frequency of the human voice (see Rogers [0275]). Therefore, it would have been prima facie obvious to one having ordinary skill in the art at the time the invention was filed to modify the Feldman/Turner/Rogers/Titze combination (to determine a ratio between the first and second harmonic FFT of the ACC signal) for the purpose of reducing signal artifacts and deriving additional information from signal data, as evidence by Rogers (see [0173]-[0174]).
Additionally, Feldman fails to explicitly disclose “…spectral tilt, High resolution filtering on FFT of ACC signal…”.
Feldman further teaches filtering a voice spectrum to determine a power spectrum at varying frequencies (see [0122], “…examining the power spectrum… may map out the speech…examine the strength in certain frequencies and/or certain key frequency ranges that are triggered when the sound is vocalized versus non-vocalized… tends to have more power on the higher frequency ranges versus lower frequency ranges”).
Although Feldman fails to explicitly disclose “spectral tilt”, Feldman teaches determining a power spectrum based on high resolution filtering of signals. Therefore, it would have been prima facie obvious to one having ordinary skill in the art at the time the invention was filed to modify the Feldman/Turner/Rogers/Titze combination (to determine spectral tilt) for the purpose of differentiating between vocalized and non-vocalized speech, as evidence by Feldman (see [0122]).
Additionally, Feldman fails to disclose “… CPP (central peak prominence) on ACC and MIC signals…”
Rogers further teaches identifying a local maximum in a frequency banded time series signal (see [0273], “…local maxima in the time series of band-passed signal, given a minimum peak height…”).
Therefore, it would have been prima facie obvious to one having ordinary skill in the art at the time the invention was filed to modify the Feldman/Turner/Rogers/Titze combination (to determine CPP) for the purpose of analyzing running series data, as evidence by Rogers (see [0273]).
Claim 20 is rejected under 35 U.S.C. 103 as being unpatentable over Feldman in view of Rogers, further in view of Turner, and further in view of US 2018/0090158 A1 to Jensen et al. (“Jensen”).
Regarding claim 20: Feldman discloses a wearable voice detection system according to claim 18/1, as discussed above. Feldman further discloses wherein the vocal analysis engine (of Feldman, as discussed above) further comprises advanced features directed to better identify vocal hyperfunctional behaviors (see [0061]-[0064], “…a biological marker (or other medical sign) gleaned or deduced from a voice stream of a person… may detect certain diseases… than in other conventional ways…”, detection of non-conventional vocal behaviors (i.e., features directed to identify hyperfunctional behaviors)), including:
Feldman further discloses inverse filtering (see [0128], “…signal may be inverted (e.g., flipped 180°) for feedback suppression…”).
However, Feldman fails to disclose “…including: aerodynamic features like AC flow (unsteady flow of air) , MFDR (maximum flow declination rate), OQ (open quotient, ratio of the open period to the entire glottal cycle’s duration) , SQ (speed quotient, ratio between the opening and the closing phase of the vocal folds) obtained via the IBIF (impedance based inverse filtering) algorithm from the ACC signal, including a calibration scheme to obtain robust subject-specific IBIF parameters using MIC inverse filtering…”.
Rogers teaches a wearable sensing system operating with an accelerometer an microphone to determine airflow parameters (see [0214], “…controlled release of airflow from a user that can then be measured by the sensing elements within the sensor system (e.g. accelerometer or microphone). This enables the quantification of airflow (volume over time)…”) including variations in airflow (see [0215], “…distinguish mouth breathing from nose breathing by variations in throat vibration or airflow…can also time the length of inspiration and expiration…”, variations in airflow indicative of unsteady flow of air (i.e., AC flow aerodynamic feature)).
Feldman discloses a vocal analysis engine (see [0073]) and analysis of advanced features directed to vocal hyperfunctional behaviors (see [0061]-[0064]), but fails to explicitly disclose aerodynamic features. Rogers teaches a vocal analysis system, operating with a microphone and accelerometer, indicating aerodynamic features (i.e., unsteady flow of air) (see [0214]-[0215]).
Therefore, it would have been prima facie obvious to one having ordinary skill in the art at the time the invention was filed to modify Feldman (to determine aerodynamic features (i.e., AC flow)) for the purpose of determining signs of patient deterioration, as evidence by Rogers (see [0214]). Furthermore, one of ordinary skill in the art would have had predictable success combining the teachings of Feldman and Rogers since both teachings relate to the same narrow field of endeavor, i.e., mechano-acoustic patient monitoring.
Additionally, Feldman fails to disclose “…subglottal pressure obtained by using multivariate linear regression (using the prior aerodynamic features, ACC and IBIF features) using SPL from the MIC signal…”.
Turner teaches modification of speech audio signals by measuring sound pressure level (see [0001], “…relates to the modification of audio signals, for example speech and music, using results of the hearing test…”, see also [0165], “…a sound pressure level indicative of the sound volume …”) and further teaches multivariable linear interpolation of audio signals using SPL from measured audio signals (see [0206]-[0207], “…Insertion gain (IG) for “65” dB SPL speech, IG65, as a function of FFT frequency…value of gain as a function of frequency is calculated via the audiogram measure…first method is to interpolate the linear gain on a linear frequency scale…”).
Therefore, it would have been prima facie obvious to one having ordinary skill in the art at the time the invention was filed to modify the Feldman/Rogers combination (to apply multivariate linear regression using SPL from MIC signals) for the purpose of obtaining a pressure level indicative of sound volume, as evidence by Turner (see [0165]). Furthermore, one of ordinary skill in the art would have had predictable success combining the teachings of Feldman/Rogers and Turner since their teachings relate to the same narrow field of endeavor, i.e., mechano-acoustic audio detection.
Additionally, the Feldman/Rogers/Turner combination is silent regarding “…subglottal pressure obtained by using multivariate linear regression (using the prior aerodynamic features, ACC and IBIF features) using SPL from the MIC signal…”.
Rogers further teaches a deflection membrane associated with a pressure required to transfer a volume of air during exhalation (see [0150], “…deflection associated to a specific pressure. The amount of deflection of the membrane using the device defines the amount of volume of the air transferred during the period of expiration…”).
Although the Feldman/Rogers/Turner combination fails to explicitly disclose determining subglottal pressure, the Feldman/Rogers/Turner combination teaches determining a sound pressure level indicative of sound volume (see Turner [0165]) and further teaches determining a pressure specific to exhalation (see Rogers [0150]). Therefore, it would have been prima facie obvious to one having ordinary skill in the art at the time the invention was filed to modify the Feldman/Rogers/Turner combination (to determine a subglottal pressure) for the purpose of monitoring disease indicating markers, as evidence by Rogers (see [0198]).
Additionally, Feldman fails to disclose “…singing detection using both ACC and MIC signal”.
Feldman further discloses vocal analysis using a neck surface acceleration signal and a microphone signal (see [0069], “…sensor may comprise a contact microphone, accelerometer, or other type of vibrational sensor mounted against a part of the body of the wearer (such as against the neck of the wearer)…”, see also [0073], “…the processor analyzing one or both of the non-audio data or the voice activity detector may employ…artificial intelligence algorithms in order to assemble the proper vibrational profile to detect when the wearer is actually speaking…”), but fails to explicitly disclose singing detection.
Jensen teaches a voice activity detection unit (see abstract) estimating vocal activities of a user, including singing (see [0006], “…the voice activity detection estimate is indicative of speech, or other human utterances involving speech-like elements, e.g. singing or screaming…”).
Therefore, it would have been prima facie obvious to one having ordinary skill in the art at the time the invention was filed to modify the Feldman/Rogers/Turner combination (to detect singing) for the purpose of differentiating speech-like elements, as evidence by Jensen (see [0029]). Furthermore, one of ordinary skill in the art would have had predictable success combining the teachings of Feldman/Rogers/Turner and Jensen since their teachings relate to the same narrow field of endeavor, i.e., mechano-acoustic vocal detection.
Claim 21 is rejected under 35 U.S.C. 103 as being unpatentable over Feldman in view of US 2020/0098376 A1 to Tas et al. (“Tas”).
Regarding claim 21: Feldman discloses a wearable voice detection system according to claim 18/1, as discussed above.
Feldman further discloses daily analysis of voice biomarkers (see [0064], “…voice biomarker analysis may be performed in one of several ways… the person's voice stream…may be analyzed at multiple points in time (such as daily, weekly, monthly, etc.)…”, daily analysis of voice biomarkers by processor (i.e., vocal analysis engine of Feldman, as discussed above regarding claim 18)) .
However, Feldman fails to explicitly disclose “…wherein the processing means is configured to provide daily reports including data generated by the Vocal Analysis Engine, such as raw features, daily/weekly statistics, and daily biofeedback summary”.
Tas teaches a biomarker tracking system for Parkinson’s patients (see [0006], “…a system for tracking biomarkers in a Parkinson's patient…”) including generating disease state reports based on data collected by a processor (see [0008], “…electronic processor is also configured to generate a disease state report based at least in part on the speech data deviation model… electronic processor collects data over at least one week…”).
Feldman discloses a vocal analysis engine generating data (see [0069] and [0073]) and a daily analysis of vocal biomarkers (see [0064]), but fails to explicitly disclose providing daily reports. Tas teaches a vocal analysis processor generating a disease state report (see [0008]).
Therefore, it would have been prima facie obvious to one having ordinary skill in the art at the time the invention was filed to modify Feldman (to provide daily reports) for the purpose of monitoring patient disease progression, as evidence by Tas (see [0011]). Furthermore, one of ordinary skill in the art would have had predictable success combining the teachings of Feldman and Tas, since their teachings relate to the same narrow field of endeavor, i.e., diagnostic vocal detection.
Claim 22 is rejected under 35 U.S.C. 103 as being unpatentable over Feldman in view of Tas, and further in view of Rogers.
Regarding claim 22: The Feldman/Tas combination discloses a wearable voice detection system according to claim 21/18/1, as discussed above. The Feldman/Tas combination further discloses wherein the Vocal Analysis Engine (of Feldman, as discussed above) is also capable of generating graphic information (see Feldman [0098], “…Output device 210 is configured to present information to the user…device 210 may be a display such as a liquid crystal display (LCD), a gas or plasma-based flat-panel display, or a traditional cathode-ray tube (CRT) display or other well-known type of display…”, output display indicates generation and display of graphic information) including:
- waveform and spectral visualization across time with user defined window time (see Feldman [0122], “…map out the speech in 2 dimensions and examine the voice spectrum (e.g., examine the strength in certain frequencies and/or certain key frequency ranges that are triggered…” see also [0044], “…parameter(s) may be tailored to the speaker… such as, without limitation, start/stop time of usage…”, power spectrum mapping (i.e., visualization of vocal waveform and spectrum across time) tailored to a user (i.e., during a user defined time window));
- multiple vocal health measures across time with filtering and user defined window time (see Feldman [0044]-[0045], “…parameter(s) may be tailored to the speaker… log various metrics related to the usage of the microphone, such as, without limitation, start/stop time of usage average speech intensity level, voice commands used, and others.…”, see also [0116], “…use a rumble filter (e.g., a high-pass filter), thereby eliminating the noise resident in the lower end frequencies of the audio input…example parameter for the profile may include the cutoff frequency for the rumble filter…”, metrics (i.e., vocal health measures) recorded over time with a user defined time window, and processed using filters to remove noise (i.e., smoothing));
- a comparison of the parameters between different periods of analysis (see Tas [0011], “…comparing the collected and stored data…”, see also [0045], “…session record is stored…such that it can be later accessed for review, analysis, or comparison to other session records…”)
- estimating parameters to identify and support the diagnosis of different pathologies and/or health conditions, even beyond the voice, such as for example Parkinson's (see Feldman [0061], “…Voice biomarkers (also known as vocal biomarkers) is a biological marker (or other medical sign)…may detect certain diseases (such as Alzheimer's disease, Parkinson's disease, or coronary artery disease)…”, determined voice biomarkers (i.e., estimated parameters) detect Parkinson’s disease (i.e., identify and support diagnosis of different pathologies and/or health conditions, specifically Parkinson’s)).
However, Feldman fails to explicitly disclose “…wherein the Vocal Analysis Engine is also capable of generating graphic information based on the daily reports and user-requested analyses, and provide a correlation between the obtained parameters and habits of the user and environmental characteristics…”.
The Feldman/Tas combination teaches daily reports (as discussed above in relation to claim 21). Tas further teaches detecting correlations between parameters and patient events (see Tas [0009]- [0010], “…system may detect and/or track significant “events” in the patient data… changes in sleep patterns or changes in physical, mental, or social parameters associated with a patient may be detected and tracked as noteworthy events…system may detect correlations between parameters… a system may unilaterally detect events and/or correlations and choose which ones to track or report, for example by applying machine learning or other computing techniques to the gathered data…”, user events and deviations in normal user patterns (i.e., user habits and environmental characteristics) are compared to gathered user data (i.e., correlated to obtained parameters)).
Therefore, it would have been prima facie obvious to one having ordinary skill in the art at the time the invention was filed to modify the Feldman/Tas combination (to provide a correlation between obtained parameters, user habits, and environmental characteristics) for the purpose of reporting deviations to a patient or physician, as evidence by Tas (see [0010]).
Additionally, the Feldman/Tas combination fails to explicitly disclose “…multiple vocal health measures across time with smoothing and user defined window time…”.
Rogers teaches audio signal processing including smoothing filtered data (see [0157], “…smoothing the data contains the normalized filtered signal…”).
Therefore, it would have been prima facie obvious to one having ordinary skill in the art at the time the invention was filed to modify the Feldman/Tas combination (to smooth data) for the purpose of representing the signal in a simpler way, as evidence by Rogers (see [0157]). Furthermore, one of ordinary skill in the art would have had predictable success combining the teachings of Feldman/Tas, and Rogers since their teachings relate to the same narrow field of endeavor, i.e., vocal detection and processing.
Additionally, the Feldman/Tas combination fails to explicitly disclose “…- uni- and bi-dimensional histograms for any of the standard or advanced vocal measures…”.
Rogers teaches normalization of audio data (see Rogers [0157], “…Normalization of each filtered data…”) including generating histograms (see [0157], “…using histogram, or automatic threshold setting algorithm…”).
Therefore, it would have been prima facie obvious to one having ordinary skill in the art at the time the invention was filed to further modify the Feldman/Tas/Rogers combination (to include histograms for vocal measures) for the purpose of determining and classifying vocal activity, as evidence by Rogers (see [0157]). Furthermore, it would have been prima facie obvious to one having ordinary skill in the art at the time the invention was filed to further modify the Feldman/Tas/Rogers combination (to include uni- and bi-directional histograms) since it has been held that where the general conditions of a claim are disclosed in the prior art, discovering the optimum or workable ranges involves only routine skill in the art. In re Aller, 105 USPQ 233.
Additionally, the Feldman/Tas/Rogers combination fails to explicitly disclose “… visualization with the UMAP dimensionality reduction technique…”.
Feldman discloses data mapping in two dimensions (see [0122], “…may map out the speech in 2 dimensions and examine the voice spectrum…”). Rogers further teaches dimension reduction methods (see [0162], “…includes dimension reduction methods such as Latent Dirichlet for obtaining predictors. Then, clustering methods including but not limited to k-modes and DBSCAN…”).
Although Rogers fails to explicitly teach the UMAP dimensionality reduction technique, such modification would have been obvious to one of ordinary skill in the art at the time the invention was filed, since it has been held that where the general conditions of a claim are disclosed in the prior art, discovering the optimum or workable ranges involves only routine skill in the art. In re Aller, 105 USPQ 233.
Additionally, the Feldman/Tas/Rogers combination fails to explicitly disclose “…a comparison of the parameters in the same time window between the different days of the analysis…”.
The Feldman/Tas combination discloses daily analysis of voice biomarkers (see Feldman [0064], “…voice biomarker analysis may be performed in one of several ways… the person's voice stream…may be analyzed at multiple points in time (such as daily, weekly, monthly, etc.)…”) and providing a daily analysis of voice biomarkers (see Tas [0008], “…electronic processor is also configured to generate a disease state report based at least in part on the speech data deviation model… electronic processor collects data over at least one week…”).
Tas further teaches comparing measured vocal metrics to previously measured and recorded values (see Tas [0053], “…determines the subject's functional state by comparing the set of attributes determined for the subject's current performance of the vocal exercise with a set of attributes determined for a prior performance of the vocal exercise by the subject…”).
Although the Feldman/Tas/Rogers combination fails to explicitly disclose a parameter comparison in the same time window between different days, the Feldman/Tas/Rogers combination teaches daily parameter data collection (see Feldman [0008]), and parameter comparison against previously collected values (see Tas [0053]). Therefore, it would have been obvious to one having ordinary skill in the art at the time the invention was made to modify the Feldman/Tas/Rogers combination (to compare parameters in the same time window across different days) since it has been held that where the general conditions of a claim are disclosed in the prior art, discovering the optimum or workable ranges involves only routine skill in the art. In re Aller, 105 USPQ 233.
Additionally, the Feldman/Tas/Rogers combination fails to explicitly disclose “…correlate alterations in the parameters obtained with the user's habits (smoking, eating, screaming, etc.) and environmental variables…”.
The Feldman/Tas combination teaches detecting correlations between parameters and patient events and habits (see Tas [0009]- [0010]), but fails to explicitly disclose smoking, eating, screaming, etc.
Rogers further teaches generating a clinical metric based on physiological user behaviors (see [0014], “…clinical metric may be selected from the group consisting of a swallowing parameter, a respiration parameter, an aspiration parameter, a coughing parameter, a sneezing parameter, a temperature, a heart rate, a sleep parameter, pulse oximetry, a snoring parameter, body movement, scratching parameter, bowel movement parameter, a neonate subject diagnostic parameter; a cerebral palsy diagnostic parameter, and any combination thereof…”, see also [0057], “…social metric may be selected from the group consisting of: talking time, number of words, phonatory parameter, linguistic discourse parameter, conversation parameter, sleep quality, eating behavior, physical activity parameter, and any combination thereof…”, metrics monitored include eating behavior (i.e., eating habit), a respiration and coughing parameter (i.e., indicative of a smoking habit) a heart rate and body movement parameter (i.e., indicative of a screaming habit and an environmental variable)).
Therefore, it would have been prima facie obvious to one having ordinary skill in the art at the time the invention was filed to modify the Feldman/Tas/Rogers combination (to provide a correlation between an alteration in obtained parameters with alterations is user habits and environmental variables) for the purpose of quantifying physical parameters to determine a level of social interaction, as evidence by Rogers (see [0199]).
Additionally, the Feldman/Tas/Rogers combination fails to explicitly disclose “…obtaining vocal efficiency level indicators, which correspond to indicators that describe a "voice quality". These indicators allow the patients to notice their improvement.”.
Rogers further teaches using phonatory features to quantify linguistic interactions of patients (see [0199], “…recorded signal can be used to extract additional data including phonatory features (e.g., F0, spectral peak, voice onset time, temporal features of speech) as well as linguistic discourse markers (e.g. pausing, verbal disfluencies)…”).
Therefore, it would have been prima facie obvious to one having ordinary skill in the art at the time the invention was filed to modify the Feldman/Tas/Rogers combination (to obtain vocal efficiency level indicators corresponding to a voice quality) for the purpose of quantifying physical parameters to quantify physiological parameters of social interaction, as evidence by Rogers (see [0199]).
Conclusion
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/ALYSSA PAIGE NOVAK/Examiner, Art Unit 3791
/ERIC J MESSERSMITH/Primary Examiner, Art Unit 3791
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