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 .
Claim Rejections - 35 USC § 101
Claims 1-18 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.
Each of Claims 1-18 has been analyzed to determine whether it is directed to any judicial exceptions.
Step 2A, Prong 1
Each of Claims 1-18 recites at least one step or instruction for observing, judging or evaluating data, which is grouped as a mental process under the 2019 PEG. Accordingly, each of Claims 1-18 recites an abstract idea.
Specifically, Claim 1 recites A digestive canal scanning device comprising:
a sensor module comprising multiple microphones attached to multiple sites separated from each other on the abdomen of a patient (additional element) to detect sounds from the abdomen after the patient swallows food;
a data processing unit (additional element) converting analog signals generated from the multiple microphones (additional element) into digital audio signals; and
an analysis unit (additional element) classifying a digestive canal sound among multiple audio signals converted by the data processing unit (additional element) and recognizing that a location of a microphone (additional element) detecting a signal classified as the digestive canal sound is a location at which the digestive canal sound is generated.
Claim 6 recites A body scanning device comprising:
a sensor module comprising multiple microphones attached to multiple sites separated from each other on a patient body (additional element) to collect an internal body sound from the patient body (observation, which is a mental process under the 2019 PEG);
a data processing unit (additional element) converting audio signals collected by the multiple microphones (additional element) into digital signals and obtaining frequency information of the audio signals through fast Fourier transform (judgement or evaluation, which is a mental process under the 2019 PEG) and
an analysis unit (additional element) classifying the internal body sound generated from the patient body among multiple audio signals generated from the multiple microphones based on the frequency information (judgement or evaluation, which is a mental process under the 2019 PEG) provided by the data processing unit (additional element) and recognizing that a location of a microphone detecting the internal body sound is a location at which the internal body sound is generated (observation, which is a mental process under the 2019 PEG);
[Claim 13] (Original) A body scanning method of a body scanning device comprising:
attaching multiple microphones (additional element) to a scanning target region on a patient body to be separated from each other on the patient body, followed by collecting internal body sounds of the patient body (observation, which is a mental process under the 2019 PEG);
converting, by a data processing unit (additional element), audio signals collected by the multiple microphones into digital signals to obtain frequency information of the audio signals through fast Fourier transform of the audio signals (judgement or evaluation, which is a mental process under the 2019 PEG); and
classifying, by an analysis unit (additional element), an internal body sound among the audio signals generated from the multiple microphones using the frequency information to recognize that a location of a microphone detecting the internal body sound is a location at which the internal body sound is generated (judgement or evaluation, which is a mental process under the 2019 PEG).
[Claim 17] (Original) An acoustic digestive organ monitoring system comprising:
multiple auscultation units attached to various locations on a patient abdomen (additional element) to collect a biological sound group generated from the patient digestive system (observation, which is a mental process under the 2019 PEG);
at least one artifact collection unit attached to the patient abdomen (additional element) to collect an artifact group generated outside the patient (observation, which is a mental process under the 2019 PEG);
a signal extraction unit (additional element) comparing the biological sound group collected by the auscultation unit with the artifact group collected by the artifact collection unit to filter noise from the biological sound group after removing the artifact group from the biological sound group (judgement or evaluation, which is a mental process under the 2019 PEG);
a feature extraction unit (additional element) extracting the biological sound group into multiple biological sound sources through division of the biological sound group, from which the artifact group is removed by the signal extraction unit, using spatial features of the patient digestive system (judgement or evaluation, which is a mental process under the 2019 PEG);
a database to which the biological sources extracted by the feature extraction unit are input (observation, which is a mental process under the 2019 PEG);
an artificial neural network (additional element) monitoring the biological sources input to the database to output a biological sound target corresponding to a digestive system disease as a diagnosis result among the biological sound sources input to the database; and
a wireless communication unit (additional element) sending the diagnosis result to a control server (observation, which is a mental process under the 2019 PEG).
Accordingly, as indicated above, each of the above-identified claims recites an abstract idea.
Further, dependent Claims 1-18 merely include limitations that either further define the abstract idea (and thus don’t make the abstract idea any less abstract) or amount to no more than generally linking the use of the abstract idea to a particular technological environment or field of use because they’re merely incidental or token additions to the claims that do not alter or affect how the process steps are performed.
Step 2A, Prong 2
The above-identified abstract idea in independent Claim 1, 6, 13, 17 (and its respective dependent claims) are not integrated into a practical application under 2019 PEG because the additional elements (identified above in independent Claim 1, 6, 13, 17), either alone or in combination, generally link the use of the above-identified abstract idea to a particular technological environment or field of use. More specifically, the additional elements of: a sensor module, a data processing unit, an analysis unit, a sensor module, microphones, multiple auscultation units, artifact collection unit, feature extraction unit, a database, an artificial neural network, a wireless communication unit, are generically recited computer elements in independent Claim 1, 6, 13, 17 (and its respective dependent claims) which do not improve the functioning of a computer, or any other technology or technical field. Nor do these above-identified additional elements serve to apply the above-identified abstract idea with, or by use of, a particular machine, effect a transformation or apply or use the above-identified abstract idea in some other meaningful way beyond generally linking the use thereof to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception. Furthermore, the above-identified additional elements do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer. For at least these reasons, the abstract idea identified above in independent Claim 1, 6, 13, 17 (and its respective dependent claims) is not integrated into a practical application under 2019 PEG.
Moreover, the above-identified abstract idea is not integrated into a practical application under 2019 PEG because the claimed system merely implements the above-identified abstract idea (e.g., mental process) using rules (e.g., computer instructions) executed by a computer. In other words, independent Claims and its dependent claims are merely directed to an abstract idea with additional generic computer elements which do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer and insignificant extra-solution activity related to a sensing unit collecting data. Additionally, Applicant’s specification does not include any discussion of how the claimed invention provides a technical improvement realized by these claims over the prior art or any explanation of a technical problem having an unconventional technical solution that is expressed in these claims. That is, like Affinity Labs of Tex. v. DirecTV, LLC, the specification fails to provide sufficient details regarding the manner in which the claimed invention accomplishes any technical improvement or solution. Thus, for these additional reasons, the abstract idea identified above in independent Claims (and its dependent claims) is not integrated into a practical application under the 2019 PEG.
Accordingly, independent Claims (and its dependent claims) are each directed to an abstract idea under 2019 PEG.
Step 2B
None of Claims include additional elements that are sufficient to amount to significantly more than the abstract idea for at least the following reasons.
These claims require the additional elements of: a sensor module, a data processing unit, an analysis unit, a sensor module, microphones, multiple auscultation units, artifact collection unit, feature extraction unit, a database, an artificial neural network, a wireless communication unit.
The above-identified additional elements are generically claimed computer components which enable the above-identified abstract idea(s) to be conducted by performing the basic functions of automating mental tasks. The courts have recognized such computer functions as well understood, routine, and conventional functions when claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity. See, Versata Dev. Group, Inc. v. SAP Am., Inc. , 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); and OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93.
Furthermore, Applicant’s specification does not describe any special programming or algorithms required for the additional elements. This lack of disclosure is acceptable under 35 U.S.C. §112(a) since this hardware performs non-specialized functions known by those of ordinary skill in the computer arts. By omitting any specialized programming or algorithms, Applicant's specification essentially admits that this hardware is conventional and performs well understood, routine and conventional activities in the computer industry or arts. In other words, Applicant’s specification demonstrates the well-understood, routine, conventional nature of the above-identified additional elements because it describes these additional elements in a manner that indicates that the additional elements are sufficiently well-known that the specification does not need to describe the particulars of such additional elements to satisfy 35 U.S.C. § 112(a) (see Berkheimer memo from April 19, 2018, (III)(A)(1) on page 3). Furthermore, Meron et al. (U.S. Patent Application Publication No. 20170056451) discloses a sensor module, a data processing unit, an analysis unit, a sensor module, microphones, multiple auscultation units, artifact collection unit, feature extraction unit, a database, an artificial neural network, a wireless communication unit (paragraph 0029-0030, 0041-0042, 0045-0046).
The recitation of the above-identified additional limitations in Claims 1-18 amounts to mere instructions to collect data with extra-solution activity and implement the abstract idea on a computer. Simply using a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); and TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Moreover, implementing an abstract idea on a generic computer, does not add significantly more, similar to how the recitation of the computer in the claim in Alice amounted to mere instructions to apply the abstract idea of intermediated settlement on a generic computer.
A claim that purports to improve computer capabilities or to improve an existing technology may provide significantly more. McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314-15, 120 USPQ2d 1091, 1101-02 (Fed. Cir. 2016); and Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1335-36, 118 USPQ2d 1684, 1688-89 (Fed. Cir. 2016). However, a technical explanation as to how to implement the invention should be present in the specification for any assertion that the invention improves upon conventional functioning of a computer, or upon conventional technology or technological processes. That is, the disclosure must provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. Here, Applicant’s specification does not include any discussion of how the claimed invention provides a technical improvement realized by these claims over the prior art or any explanation of a technical problem having an unconventional technical solution that is expressed in these claims. Instead, as in Affinity Labs of Tex. v. DirecTV, LLC 838 F.3d 1253, 1263-64, 120 USPQ2d 1201, 1207-08 (Fed. Cir. 2016), the specification fails to provide sufficient details regarding the manner in which the claimed invention accomplishes any technical improvement or solution.
For at least the above reasons, the system of Claims 1 to 18 are directed to applying an abstract idea (e.g., mental process) on a general purpose computer without (i) improving the performance of the computer itself (as in McRO, Bascom and Enfish), or (ii) providing a technical solution to a problem in a technical field (as in DDR). In other words, none of Claims 1 to 18 provides meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that these claims amount to significantly more than the abstract idea itself.
Taking the additional elements individually and in combination, the additional elements do not provide significantly more. Specifically, when viewed individually, the above-identified additional elements in independent Claim 1 (and its dependent claims) do not add significantly more because they are simply an attempt to limit the abstract idea to a particular technological environment. That is, neither the general computer elements nor any other additional element adds meaningful limitations to the abstract idea because these additional elements represent insignificant extra-solution activity. When viewed as a combination, these above-identified additional elements simply instruct the practitioner to implement the claimed functions with well-understood, routine and conventional activity specified at a high level of generality in a particular technological environment. As such, there is no inventive concept sufficient to transform the claimed subject matter into a patent-eligible application. As such, the above-identified additional elements, when viewed as whole, do not provide meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that the claims amount to significantly more than the abstract idea itself. Thus, Claims 1 to 18 merely apply an abstract idea to a computer and do not (i) improve the performance of the computer itself (as in Bascom and Enfish), or (ii) provide a technical solution to a problem in a technical field (as in DDR).
Therefore, none of the Claims 1 to 18 amounts to significantly more than the abstract idea itself. Accordingly, Claims 1 to 18 are not patent eligible and rejected under 35 U.S.C. 101 as being directed to abstract ideas implemented on a generic computer in view of the Supreme Court Decision in Alice Corporation Pty. Ltd. v. CLS Bank International, et al. and 2019 PEG.
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.
Claim(s) 1-4, 17 is/are rejected under 35 U.S.C. 102(a(1)) as being anticipated by Meron (US 20170367642)
[Claim 1] Meron discloses A digestive canal scanning device (abstract) comprising:
a sensor module comprising multiple microphones (110) attached to multiple sites separated from each other on the abdomen of a patient to detect sounds from the abdomen after the patient swallows food (paragraph 0038, 0043) (Fig 2b);
a data processing unit (paragraph 0018, 0053) converting analog signals generated from the multiple microphones into digital audio signals (paragraph 0038-0042); and
an analysis unit (120) classifying a digestive canal sound among multiple audio signals converted by the data processing unit and recognizing that a location of a microphone detecting a signal classified as the digestive canal sound is a location at which the digestive canal sound is generated (paragraph 0035, 0037, 0042).
[Claim 2] Meron discloses The digestive canal scanning device according to claim 1, wherein the sensor module comprises multiple unidirectional microphones (110); and an attachment pad attached to the patient abdomen and receiving the multiple microphones to be separated from each other (paragraph 0044) (Fig 2b).
[Claim 3] Meron discloses The digestive canal scanning device according to claim 2, wherein the sensor module comprises a soundproof pad coupled to an inner surface of the attachment pad (paragraph 0044) (Fig 2b).
[Claim 4] Meron discloses The digestive canal scanning device according to claim 1, wherein the analysis unit extracts locations, at which the multiple audio signals are generated, and treats an audio signal generated from a location separated a predetermined distance from locations at which other audio signals are generated, as noise (paragraph 0041).
[Claim 17] Meron discloses An acoustic digestive organ monitoring system comprising:
multiple auscultation units (110) attached to various locations on a patient abdomen to collect a biological sound group generated from the patient digestive system (paragraph 0038, 0043) (Fig 2b);
at least one artifact collection unit attached to the patient abdomen to collect an artifact group (“noise”) generated outside the patient (paragraph 0038);
a signal extraction unit comparing the biological sound group collected by the auscultation unit with the artifact group collected by the artifact collection unit to filter noise from the biological sound group after removing the artifact group from the biological sound group (paragraph 0038, 0041-0042);
a feature extraction unit extracting the biological sound group into multiple biological sound sources through division of the biological sound group, from which the artifact group is removed by the signal extraction unit, using spatial features of the patient digestive system (paragraph 0042, 0052);
a database to which the biological sources extracted by the feature extraction unit are input (paragraph 0045-0047, 0056, 0058);
an artificial neural network monitoring the biological sources input to the database to output a biological sound target corresponding to a digestive system disease as a diagnosis result among the biological sound sources input to the database (paragraph 0045-0047, 0056, 0058); and
a wireless communication unit sending the diagnosis result to a control server (paragraph 0039, 0046).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (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 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 5-6, 10-13, 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Meron (US 20170367642) in view of Satoshi (JP 2000262523)
[Claim 5] Meron discloses all of the limitations of the claim except The digestive canal scanning device according to claim 1, wherein the analysis unit is provided with characteristic data exclusive to the digestive canal sound to classify an audio signal having the same characteristics as the characteristic data as the digestive canal sound through spectrum analysis of each of the multiple audio signals, the characteristic data being a combination of frequencies unique to the digestive canal sound. Satoshi teaches wherein the analysis unit is provided with characteristic data exclusive to the digestive canal sound to classify an audio signal having the same characteristics as the characteristic data as the digestive canal sound through spectrum analysis of each of the multiple audio signals, the characteristic data being a combination of frequencies unique to the digestive canal sound (paragraphs 0033-0036). Therefore, it would have been obvious at the effective filing date of the invention to modify Meron’s acoustic large intestine detection device by Satoshi’s gastrointestinal activity acoustic monitor for the purpose of utilizing a well-known signal analysis method to efficiently detect an occurrence of a peristaltic sound and easily estimating the condition of the digestive system.
[Claim 6] Meron discloses A body scanning device (abstract) comprising:
a sensor module comprising multiple microphones (110) attached to multiple sites separated from each other on a patient body to collect an internal body sound from the patient body (paragraph 0038, 0043) (Fig 2b);
a data processing unit (paragraph 0018, 0053) converting audio signals collected by the multiple microphones into digital signals (paragraph 0038-0042); and
an analysis unit (120) classifying the internal body sound generated from the patient body among multiple audio signals generated from the multiple microphones (110) provided by the data processing unit and recognizing that a location of a microphone detecting the internal body sound is a location at which the internal body sound is generated (paragraph 0019, 0035, 0037, 0042).
Meron discloses of the limitations in the claim except obtaining frequency information of the audio signals through fast Fourier transform and based on the frequency information provided by the data processing unit. Satoshi teaches obtaining frequency information of the audio signals through fast Fourier transform and based on the frequency information provided by the data processing unit (page 2, page 3, paragraph 0026-0036). Therefore, it would have been obvious at the effective filing date of the invention to modify Meron’s acoustic large intestine detection device by Satoshi’s gastrointestinal activity acoustic monitor for the purpose of utilizing a well-known signal analysis method to efficiently detect an occurrence of a peristaltic sound and easily estimating the condition of the digestive system.
[Claim 10] (Original) Meron discloses The body scanning device according to claim 6, wherein the sensor module comprises: multiple unidirectional microphones (110); and an attachment pad attached to the patient abdomen and receiving the multiple microphones to be separated from each other (paragraph 0044).
[Claim 11] Meron discloses The body scanning device according to claim 10, wherein the sensor module further comprises a soundproof pad coupled to an inner surface of the attachment pad (paragraph 0044) (Fig 2b).
[Claim 12] Meron discloses The body scanning device according to claim 6, wherein the analysis unit extracts locations, at which the multiple audio signals are generated, and treats an audio signal generated from a location separated a predetermined distance from locations at which other audio signals are generated, as noise (paragraph 0041).
[Claim 13] (Original) Meron discloses A body scanning method of a body scanning device comprising:
attaching multiple microphones (110) to a scanning target region on a patient body to be separated from each other on the patient body, followed by collecting internal body sounds of the patient body (paragraph 0038, 0043) (Fig 2b);
converting, by a data processing unit, audio signals collected by the multiple microphones into digital signals (paragraph 0018, 0038-0043); and
classifying, by an analysis unit, an internal body sound among the audio signals generated from the multiple microphones (paragraph 0035, 0037, 0042) to recognize that a location of a microphone detecting the internal body sound is a location at which the internal body sound is generated (paragraph 0035, 0037, 0042).
Meron discloses all of the limitations in the claim except obtain frequency information of the audio signals through fast Fourier transform of the audio signals, using frequency information. Satoshi teaches obtain frequency information of the audio signals through fast Fourier transform of the audio signals (page 2, page 3, paragraph 0026-0033). Therefore, it would have been obvious at the effective filing date of the invention to modify Meron’s acoustic large intestine detection device by Satoshi’s gastrointestinal activity acoustic monitor for the purpose of utilizing a well-known signal analysis method to efficiently detect an occurrence of a peristaltic sound and easily estimating the condition of the digestive system.
[Claim 15] Meron discloses all of the limitations of the claim except the body scanning method according to claim 13, wherein classifying the internal body sound comprises obtaining the preset frequency characteristics by learning frequency characteristics of the internal body sound based on frequency information obtained through fast Fourier transform of the multiple audio signals provided as learning data. Satoshi teaches wherein classifying the internal body sound comprises obtaining the preset frequency characteristics by learning frequency characteristics of the internal body sound based on frequency information obtained through fast Fourier transform of the multiple audio signals provided as learning data (paragraph 0033-0036). Therefore, it would have been obvious at the effective filing date of the invention to modify Meron’s acoustic large intestine detection device by Satoshi’s gastrointestinal activity acoustic monitor for the purpose of utilizing a well-known signal analysis method to efficiently detect an occurrence of a peristaltic sound and easily estimating the condition of the digestive system.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to YASMEEN S WARSI whose telephone number is (571)272-9942. The examiner can normally be reached Monday-Friday 9 am to 5 pm.
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/YASMEEN S WARSI/Examiner, Art Unit 3791
/MAY A ABOUELELA/Primary Examiner, Art Unit 3791