DETAILED ACTION
Remarks
This office action is issued in response to communication filed on 7/15/2022. Claims 1-17 are pending in this Office 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 Objections
Claims 5-7 and 13-15 are objected to because of the following informalities: Claims 5-7 and 13-15 recite the term "and/or", which is selective language, the examiner suggests using either the "and" term or the "or" term, otherwise the claims should be worded in a clearer fashion to claim both terms. For the purpose of this examination the examiner is selecting the "or" term from this selective language. Appropriate correction is required.
Claims 1-3 and 8-11 include plurality of bullet points. Appropriate correction is required.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
2. Claims 1-17 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim 1:
Step 1: Statutory Category ?: Yes. Claim 1 recites a method which is a statutory category.
Step 2A-Prong 1: Judicial Exception Recited ?: Yes.
The limitations: "applying to said signal (1) a target parameter set, which is indicative for a plurality of reference target signal segments that are obtained from reference single- channel EEG-recordings, to detect a first signal segment of said signal (1) and to classify the detected first signal segment as a target signal segment”; " assigning a first time stamp (t1) to the detected first signal segment; " applying to said signal (1) a non-target parameter set, which is indicative for a plurality of reference non-target signal segments that are obtained from reference single-channel EEG-recordings, to detect a second signal segment of said signal (1) and to classify the detected second signal segment as a non-target signal segment ; " assigning a second time stamp (t2) to the detected second signal segment; " determining a temporal proximity of the first time stamp (t1) and the second time stamp (t2); " based on said determined temporal proximity, determining if a voting process is required to determine whether classification of the detected first signal segment as a target signal segment or classification of the detected second signal segment as a non-target signal segment is correct; and " upon establishing that said voting process is required, performing said voting process” are processes that that can be performed in the human mind using observation, evaluation, judgment and opinion including with the help with a pen and paper.
The limitations: “wherein the target parameter set comprises wavelet coefficients that are determined using wavelet decomposition of the plurality of reference target signal segments” ; “wherein the non-target parameter set comprises wavelet coefficients that are determined using wavelet decomposition of the plurality of reference non- target signal segments” are mathematical calculations that falls under mathematical concepts of the abstract idea groupings.
Step 2A-Prong 2: Integrated into a practical application? No.
Claim 1 recites additional limitation : “providing a signal (1) that is obtained from a single-channel EEG-recording” which is mere data gathering and thus is insignificant extra solution activity. (See MPEP 2106.05(g))
Step 2B: Recites additional elements that amount to significantly more than the judicial exception? No.
Claim 1 does not include additional elements that are sufficient to amount to significantly more than judicial exception. The additional limitation of “providing a signal (1) that is obtained from a single-channel EEG-recording” is mere data gathering and is well-understood, routine conventional activities previously known to the industry and therefore does not amount to significantly more than the judicial exception. (See MPEP 2106.05(d)), subsection II. Even when considered in combination, the additional element does not provide an inventive concept, claim 1 therefore is ineligible.
Claim 2 recites additional elements of “generating a first signal sample (10) that comprises the detected first signal segment; matching the first signal sample (10) with the plurality of reference target signal segments to determine a best target match; generating a second signal sample (12) that comprises the detected second signal segment; matching the second signal sample with the plurality of reference non-target signal segments to determine a best non-target match; applying metrics to the first signal sample (10), the best target match, the second signal sample (12) and the best non-target match to determine: whether the classification of the detected first signal segment as a target signal segment is correct; or - whether the classification of the detected second signal segment as a non- target signal segment is correct.” which are mental processes that can be performed in the human mind using observation, evaluation, judgment and opinion including with the help with a pen and paper. Claim 2 does not include any additional element that integrates the abstract idea into practical application in step 2A-Prong 2 and amounts to significantly more than the judicial exception in step 2B. Claim 2 is not patent eligible.
Claim 3 recites additional elements of “wherein performing the voting process comprises: generating a first signal sample (10) that comprises the detected first signal segment; matching the first signal sample (10) with a set of reference target signal segments that is based on the plurality of reference target signal segments to determine a best target match; generating a second signal sample (12) that comprises the detected second signal segment; matching the second signal sample (12) with a set of reference non-target signal segments that is based on the plurality of reference non-target signal segments to determine a best non-target match; applying metrics to the first signal sample (10), the best target match, the second signal sample (12) and the best non-target match to determine: whether the classification of the detected first signal segment as a target signal segment is correct; or whether the classification of the detected second signal segment as a non- target signal segment is correct” are mental processes that can be performed in the human mind using observation, evaluation, judgment and opinion including with the help with a pen and paper. Claim 3 does not include any additional element that integrates the abstract idea into practical application in step 2A-Prong 2 and amounts to significantly more than the judicial exception in step 2B. Claim 3 is not patent eligible.
Claim 4 recites additional elements of “removing the classification of the detected first signal segment or the classification of the detected second signal segment that based on the voting process is incorrect” which is mental process that can be performed in the human mind using observation, evaluation, judgment and opinion including with the help with a pen and paper. Claim 4 does not include any additional element that integrates the abstract idea into practical application in step 2A-Prong 2 and amounts to significantly more than the judicial exception in step 2B. Claim 4 is not patent eligible.
Claim 5 recites additional elements of “wherein a predetermined detection boundary, which is determined based on the target parameter set and/or the non-target parameter set, is applied that allows classification of detected signal segments as target signal segments or as non-target signal segments” which is mental process that can be performed in the human mind using observation, evaluation, judgment and opinion including with the help with a pen and paper. Claim 5 does not include any additional element that integrates the abstract idea into practical application in step 2A-Prong 2 and amounts to significantly more than the judicial exception in step 2B. Claim 5 is not patent eligible.
Claim 6 recites additional elements of “determining an optimized target parameter set that comprises wavelet coefficients that are indicative specifically for the plurality of reference target signal segments and/or an optimized non-target parameter set that comprises wavelet coefficients that are indicative specifically for the plurality of reference non-target signal segments” which is mental process that can be performed in the human mind using observation, evaluation, judgment and opinion including with the help with a pen and paper. Claim 6 does not include any additional element that integrates the abstract idea into practical application in step 2A-Prong 2 and amounts to significantly more than the judicial exception in step 2B. Claim 6 is not patent eligible.
Claim 7 recites additional elements of “wherein based on the optimized target parameter set and/or the optimized non-target parameter set a detection boundary is determined that allows improved classification of detected signal segments as target signal segments or as non-target signal segments” which is mental process that can be performed in the human mind using observation, evaluation, judgment and opinion including with the help with a pen and paper. Claim 7 does not include any additional element that integrates the abstract idea into practical application in step 2A-Prong 2 and amounts to significantly more than the judicial exception in step 2B. Claim 7 is not patent eligible.
Claim 8 recites additional element of a system “ the detector (2) having a database (4)comprising at least one of: " a plurality of reference target signal segments that are obtained from reference single-channel EEG-recordings; a set of reference target signal segments that is based on the plurality of reference target signal segments; a plurality of reference non-target signal segments that are obtained from reference single-channel EEG-recordings; a set of reference non-target signal segments that is based on the plurality of reference non-target signal segments; a target parameter set that is indicative for the plurality of reference target signal segments, wherein the target parameter set comprises wavelet coefficients that are determined using wavelet decomposition of the plurality of 35 reference target signal segments; and a non-target parameter set that is indicative for a plurality of reference non- target signal segments, wherein the non-target parameter set comprises wavelet coefficients that are determined using wavelet decomposition of the plurality of reference non-target signal segments”. The additional “detector and database” which is recited at the very high level of generality such that it amounts no more than mere instructions to apply the exception using generic computer components . Claim 8 does not include additional elements that are sufficient to amount to significantly more than judicial exception. As indicates above, the additional element of additional “detector and database” is at best the equivalent of merely adding the words “apply it” to the exception. Even when considered in combination, the additional elements do not provide an inventive concept, claim 8 therefore is ineligible.
Claim 9:
Step 1: Statutory Category ?: Yes. Claim 9 recites a system which is a statutory category.
Step 2A-Prong 1: Judicial Exception Recited ?: Yes.
The limitations: "applying to said signal (1) a target parameter set, which is indicative for a plurality of reference target signal segments that are obtained from reference single- channel EEG-recordings, to detect a first signal segment of said signal (1) and to classify the detected first signal segment as a target signal segment”; " assigning a first time stamp (t1) to the detected first signal segment; " applying to said signal (1) a non-target parameter set, which is indicative for a plurality of reference non-target signal segments that are obtained from reference single-channel EEG-recordings, to detect a second signal segment of said signal (1) and to classify the detected second signal segment as a non-target signal segment ; " assigning a second time stamp (t2) to the detected second signal segment; " determining a temporal proximity of the first time stamp (t1) and the second time stamp (t2); " based on said determined temporal proximity, determining if a voting process is required to determine whether classification of the detected first signal segment as a target signal segment or classification of the detected second signal segment as a non-target signal segment is correct; and " upon establishing that said voting process is required, performing said voting process” are processes that that can be performed in the human mind using observation, evaluation, judgment and opinion including with the help with a pen and paper.
The limitations: “wherein the target parameter set comprises wavelet coefficients that are determined using wavelet decomposition of the plurality of reference target signal segments” ; “wherein the non-target parameter set comprises wavelet coefficients that are determined using wavelet decomposition of the plurality of reference non- target signal segments” are mathematical calculations that falls under mathematical concepts of the abstract idea groupings.
Step 2A-Prong 2: Integrated into a practical application? No.
Claim 9 recites additional limitation : “providing a signal (1) that is obtained from a single-channel EEG-recording” which is mere data gathering and thus is insignificant extra solution activity.(See MPEP 2106.05(g))
The additional element of “ a processor” which is recited at the very high level of generality such that it amounts no more than mere instructions to apply the exception using generic computer component.
Step 2B: Recites additional elements that amount to significantly more than the judicial exception? No.
Claim 9 does not include additional elements that are sufficient to amount to significantly more than judicial exception. The additional limitation of “providing a signal (1) that is obtained from a single-channel EEG-recording” is mere data gathering and is well-understood, routine conventional activities previously known to the industry and therefore does not amount to significantly more than the judicial exception. (See MPEP 2106.05(d)), subsection II. The “processor” is at best the equivalent of merely adding the words “apply it” to the exception. Even when considered in combination, the additional elements do not provide an inventive concept, claim 9 therefore is ineligible.
Claim 10 recites additional elements of " generating a first signal sample (10) that comprises the detected first signal segment; matching the first signal sample (10) with the plurality of reference target signal segments to determine a best target match; generating a second signal sample (12) that comprises the detected second signal segment; matching the second signal sample with the plurality of reference non-target signal segments to determine a best non-target match; applying metrics to the first signal sample (10), the best target match, the second signal sample (12) and the best non-target match to determine: whether the classification of the detected first signal segment as a target signal segment is correct; or - whether the classification of the detected second signal segment as a non- target signal segment is correct” which are mental processes that can be performed in the human mind using observation, evaluation, judgment and opinion including with the help with a pen and paper. Claim 10 does not include any additional element that integrates the abstract idea into practical application in step 2A-Prong 2 and amounts to significantly more than the judicial exception in step 2B. Claim 10 is not patent eligible.
Claim 11 recites additional elements of " generating a first signal sample (10) that comprises the detected first signal segment; matching the first signal sample (10) with a set of reference target signal segments that is based on the plurality of reference target signal segments to determine a best target match; " generating a second signal sample (12) that comprises the detected second signal segment; * matching the second signal sample (12) with a set of reference non-target signal segments that is based on the plurality of reference non-target signal segments to determine a best non-target match; " applying metrics to the first signal sample (10), the best target match, the second signal sample (12) and the best non-target match to determine: - whether the classification of the detected first signal segment as a target signal segment is correct; or whether the classification of the detected second signal segment as a non target signal segment is correct” which are mental processes that can be performed in the human mind using observation, evaluation, judgment and opinion including with the help with a pen and paper. Claim 11 does not include any additional element that integrates the abstract idea into practical application in step 2A-Prong 2 and amounts to significantly more than the judicial exception in step 2B. Claim 11 is not patent eligible.
Claim 12 recites additional elements of “remove the classification of the detected first signal segment or the classification of the detected second signal segment that based on the voting process is incorrect” which is mental process that can be performed in the human mind using observation, evaluation, judgment and opinion including with the help with a pen and paper. Claim 12 does not include any additional element that integrates the abstract idea into practical application in step 2A-Prong 2 and amounts to significantly more than the judicial exception in step 2B. Claim 12 is not patent eligible.
Claim 13 recites additional elements of “apply a predetermined detection boundary that is determined based on the target parameter set and/or the non-target parameter set, the detection boundary allowing a classification of detected signal segments as target signal segments or as non-target signal segments” which is mental process that can be performed in the human mind using observation, evaluation, judgment and opinion including with the help with a pen and paper. Claim 13 does not include any additional element that integrates the abstract idea into practical application in step 2A-Prong 2 and amounts to significantly more than the judicial exception in step 2B. Claim 13 is not patent eligible.
Claim 14 recites additional elements of “determine an optimized target parameter set that comprises wavelet coefficients that are indicative specifically for the plurality of reference target signal segments and/or an optimized non-target parameter set that comprises wavelet coefficients that are indicative specifically for the plurality of reference non-target signal segments” which is mental process that can be performed in the human mind using observation, evaluation, judgment and opinion including with the help with a pen and paper. Claim 14 does not include any additional element that integrates the abstract idea into practical application in step 2A-Prong 2 and amounts to significantly more than the judicial exception in step 2B. Claim 14 is not patent eligible.
Claim 15 recites additional elements of “apply a predetermined detection boundary that is determined based on the optimized target parameter set and/or the optimized non-target parameter set, the detection boundary allowing an improved classification of detected signal segments as target signal segments or as non-target signal segments” which is mental process that can be performed in the human mind using observation, evaluation, judgment and opinion including with the help with a pen and paper. Claim 15 does not include any additional element that integrates the abstract idea into practical application in step 2A-Prong 2 and amounts to significantly more than the judicial exception in step 2B. Claim 15 is not patent eligible.
Claim 16 recites additional elements of “a data storage unit (6) that is operatively connected to the processor (5), wherein the data storage unit (6) is configured and arranged to store at least one of the single-channel EEG-recording and the signal obtained from the single-channel EEG-recording, and a classification of a detected signal segment of said signal as a target signal segment or as a non-target signal segment as a result of the method performed by the processor (5)”. The “ data storage unit” which is recited at the very high level of generality such that it amounts no more than mere instructions to apply the exception using generic computer component . Claim 16 does not include additional elements that are sufficient to amount to significantly more than judicial exception. As indicates above, the additional element of additional “data storage unit” is at best the equivalent of merely adding the words “apply it” to the exception. Even when considered in combination, the additional elements do not provide an inventive concept, claim 16 therefore is ineligible.
Claim 17 recites additional elements of “wherein the system (3) is configured and arranged to be connectable with two electrodes (7) that are arrangeable on a subject's scalp and are configured to record the single-channel EEG-recording and transfer the single-channel EEG-recording to the data storage unit (6)” which is simply data gathering step and therefore are insignificant extra-solution activities. (See MPEP 2106.05(g)). Mere data gathering and is well-understood, routine conventional activities previously known to the industry and therefore does not amount to significantly more than the judicial exception. (See MPEP 2106.05(d)), subsection II) Even when considered in combination, the additional elements do not provide an inventive concept, claim 17 therefore is ineligible.
Allowable Subject Matter
Claims 2-3 and 10-11 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1,4-9 and 12-17 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Li et al.(US Patent Application Publication 2019/0167143 A1, hereinafter “Li”)
As to claim 1, Li teaches a data processing method for detecting and classifying a segment of a signal (1) that is obtained from a single-channel EEG-recording as a target signal segment or as a non-target signal segment, the method comprising:
providing a signal (1) that is obtained from a single-channel EEG-recording;(Li par [0042] teaches receiving ECG data from a sensing device)
applying to said signal (1) a target parameter set, which is indicative for a plurality of reference target signal segments that are obtained from reference single- channel EEG-recordings, to detect a first signal segment of said signal (1) and to classify the detected first signal segment as a target signal segment,(Li par [0042] teaches the output of the first and/or second neural networks may be processed by the ECG platform to achieve delineation and classification of the ECG data) wherein the target parameter set comprises wavelet coefficients that are determined using wavelet decomposition of the plurality of reference target signal segments;(Li par [0008] teaches concerning delineation, two main approaches are used for finding waves of cardiac signals. The first approach is based on a multiscale wavelet analysis. This approach looks for wavelet coefficients reaching predefined thresholds at specified scales)
assigning a first time stamp (t1) to the detected first signal segment;(Li par [0066] teaches delineator 39 causes the first neural network to read each time point of the cardiac signal , spatio-temporally analyze each time point of the cardiac signal and assign a score at each time point corresponding to one or more types of waves)
applying to said signal (1) a non-target parameter set, which is indicative for a plurality of reference non-target signal segments that are obtained from reference single-channel EEG-recordings, to detect a second signal segment of said signal (1) and to classify the detected second signal segment as a non-target signal segment (Li par [0042] teaches the output of the first and/or second neural networks may be processed by the ECG platform to achieve delineation and classification of the ECG data),
wherein the non-target parameter set comprises wavelet coefficients that are determined using wavelet decomposition of the plurality of reference non- target signal segments(Li par [0008] teaches concerning delineation, two main approaches are used for finding waves of cardiac signals. The first approach is based on a multiscale wavelet analysis. This approach looks for wavelet coefficients reaching predefined thresholds at specified scales);
assigning a second time stamp (t2) to the detected second signal segment; (Li par [0066] teaches delineator 39 causes the first neural network to read each time point of the cardiac signal , spatio-temporally analyze each time point of the cardiac signal and assign a score at each time point corresponding to one or more types of waves)
determining a temporal proximity of the first time stamp (t1) and the second time stamp (t2); (Li par [0066] teaches spatio-temporally analyze each time point of the cardiac signal and assign a score at each time point corresponding to one or more types of waves)
based on said determined temporal proximity, determining if a voting process is required to determine whether classification of the detected first signal segment as a target signal segment or classification of the detected second signal segment as a non-target signal segment is correct (Li par [0070] teaches as the cardiac signal processed by the delineation network involves a high sample rate and the delineation network generates data for each wave type at each time point, the output recovered is robust enough to identify two waves occurring at the same time such as the case with hidden P-waves); and
upon establishing that said voting process is required, performing said voting process (Li par [0071] teaches using the scored assigned to each time point corresponding to each wave type, delineator 39 may post process the cardiac signal. Post processing involves , assigning to each time point, none, one, or several waves, calculating the onset and offset of each of the identified waves and optionally determining the characterization of the waves) .
As to claim 4, Li teaches the data processing method according to any one of the preceding claims, further comprises removing the classification of the detected first signal segment or the classification of the detected second signal segment that based on the voting process is incorrect. (Li par [0071] teaches using the scored assigned to each time point corresponding to each wave type, delineator 39 may post process the cardiac signal. Post processing involves , assigning to each time point, none, one, or several waves, calculating the onset and offset of each of the identified waves and optionally determining the characterization of the waves) .
As to claim 5, Li teaches the data processing method according to any one of the preceding claims, wherein a predetermined detection boundary, which is determined based on the target parameter set and/or the non-target parameter set, is applied that allows classification of detected signal segments as target signal segments or as non-target signal segments.( Li par [0071] teaches calculating the onset and offset of each of the identified waves . Computing the “onset” and “offset” of each waves involves computing the time points of the beginning and the end of each wave in the cardiac signal)
As to claim 6, Li teaches the data processing method according to any one of the preceding claims, further comprises determining an optimized target parameter set that comprises wavelet coefficients that are indicative specifically for the plurality of reference target signal segments and/or an optimized non-target parameter set that comprises wavelet coefficients that are indicative specifically for the plurality of reference non-target signal segments. (Li par [0008] teaches concerning delineation, two main approaches are used for finding waves of cardiac signals. The first approach is based on a multiscale wavelet analysis. This approach looks for wavelet coefficients reaching predefined thresholds at specified scales)
As to claim 7, Li teaches the data processing method according to claim 6, wherein based on the optimized target parameter set and/or the optimized non-target parameter set a detection boundary is determined that allows improved classification of detected signal segments as target signal segments or as non-target signal segments. (Li par [0008] teaches concerning delineation, two main approaches are used for finding waves of cardiac signals. The first approach is based on a multiscale wavelet analysis. This approach looks for wavelet coefficients reaching predefined thresholds at specified scales . Li par [0071] teaches computing the “onset” and “offset” of each waves involves computing the time points of the beginning and the end of each wave in the cardiac signal)
As to claim 8, Li teaches a detector (2) that is configured and arranged to cooperate with a system (3) that is configured and arranged to perform the data processing method according to any one of the claims 1-7 for detecting and classifying a segment of a signal (1) that is obtained from a single-channel EEG-recording as a target signal segment or as a non-target signal segment,(Li Fig.2, and par [0043]-[0044] teaches ECG processing system includes sensing device 13, system device 14 and server 15, as well as drive 16)
the detector (2) having a database (4) (Li par [0051] teaches ECG application 29 may be stored in storage 27) comprising at least one of:
a plurality of reference target signal segments that are obtained from reference single-channel EEG-recordings; (ECG application 29 may cause the system device 14 to receive ECG data from sensing device 13, to record ECG data from sensing device 13)
a set of reference target signal segments that is based on the plurality of reference target signal segments; a plurality of reference non-target signal segments that are obtained from reference single-channel EEG-recordings; a set of reference non-target signal segments that is based on the plurality of reference non-target signal segments; a target parameter set that is indicative for the plurality of reference target signal segments, wherein the target parameter set comprises wavelet coefficients that are determined using wavelet decomposition of the plurality of 35 reference target signal segments; and a non-target parameter set that is indicative for a plurality of reference non- target signal segments, wherein the non-target parameter set comprises wavelet coefficients that are determined using wavelet decomposition of the plurality of reference non-target signal segments.
Claims 9 and 12-16 merely recite a system to perform the method of claims 1 and 4-8 respectively. Accordingly, Li teaches every limitation of claims 9 and 12-16 as indicates in the above rejection of claims 1 and 4-8 respectively.
As to claim 17, Li teaches the system (3) according to claim 16, wherein the system (3) is configured and arranged to be connectable with two electrodes (7) that are arrangeable on a subject's scalp and are configured to record the single-channel EEG-recording and transfer the single-channel EEG-recording to the data storage unit (6).(Li par [003] teaches ECG typically is generated from cardiac signals sensed by a number of electrodes placed in specific areas on a patient)
Conclusion
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/HIEN L DUONG/Primary Examiner, Art Unit 2147