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
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-22 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an
abstract idea without significantly more. Claims 1 and 12 recite an apparatus and a method with instructions for performing operations of the device comprising:
calculating variance of the respiration signal to generate a variance degree;
performing a first changepoint detection on the variance degree to obtain a first interval;
capturing a first interval signal from the respiration signal according to the first interval;
detecting the first interval signal to generate a detection result corresponding to at least one periodic breathing;
and outputting the detection result.
To determine whether a claim satisfies the criteria for subject matter eligibility, the claim is
evaluated according to a stepwise process as described in MPEP 2106(III) and 2106.03-2106.05. The instant claims are evaluated according to such analysis.
Step 1: Is the claim to a process, machine, manufacture or composition of matter?
Claim 1 is directed to an apparatus, claim 12 is directed to a method and thus meet the
requirements for step 1.
Step 2A (Prong 1): Does the claim recite an abstract idea, law of nature, or natural
phenomenon?
Claims 1 and 12 recite an apparatus an a method with instructions for performing operations of
the device comprising:
calculating variance of the respiration signal to generate a variance degree;
performing a first changepoint detection on the variance degree to obtain a first interval;
capturing a first interval signal from the respiration signal according to the first interval;
detecting the first interval signal to generate a detection result corresponding to at least one periodic breathing;
and outputting the detection result.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the
limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Therefore, claims 1 and 12 recite an abstract idea of a mental process.
Claims 1 and 12 recite the abstract idea of a mental process. The limitations as drafted in the
claims, under its broadest reasonable interpretation, covers performance of the claimed steps in the mind, but for the recitation of a generic processor. Other than reciting a generic processing system and memory, nothing in the elements of the claims precludes the step from practically being performed in the mind or manually by a clinician. For example:
“Calculating variance of the respiration signal to generate a variance degree;” A physician may use mathematical equations to calculate a degree of variance for a respiration signal.
“Performing a first changepoint detection on the variance degree to obtain a first interval;” A physician separate the waveforms to separate a first and second interval and perform a first changepoint.
“Capturing a first interval signal from the respiration signal according to the first interval;” I physician may identify a first interval signal and capture the signal by recording it using a pen and paper.
“Detecting the first interval signal to generate a detection result corresponding to at least one periodic breathing;” A physician may generate a detection result to periodic breathing by observing signal, using equations, and comparing signals with a threshold value.
“And outputting the detection result.” A physician may give a diagnosis verbally or visually to a patient.
Furthermore claims 2, 4, 6, 8, 10, 13, 15, 17, 19, and 21 recite additional steps that can be manually performed by the clinician.
Claims 2 and 13
“Performing a fast Fourier transform on the first interval signal to generate a conversion signal; performing a second changepoint detection on the conversion signal to obtain a second interval; capturing a second interval signal from the respiration signal according to the second interval; and determining whether the second interval signal corresponds to the periodic breathing to generate the detection result.” A physician may convert the signal using the Fourier transform equation. The physician may also separate the signals into a first and second interval. A second respiration signal may be captured with pen and paper to generate a detection result for periodic breathing.
Claims 4 and 15
“Determining whether a first feature value of the second interval signal matches a first condition to calculate a first score corresponding to the second interval signal; and determining whether the second interval signal corresponds to the periodic breathing according to the first score.” A physician may observe or examine the signal to determine a first feature of the second interval signal. The feature may be compared to match with a first condition to calculate a first score using equations and observation. This may be used to determine whether the second interval signal corresponds to the periodic breathing.
Claims 6 and 17
“Performing the second changepoint detection on the conversion signal to obtain a third interval adjacent to the second interval; capturing a third interval signal from the respiration signal according to the second interval and the third interval; and determining whether a second feature value of the third interval signal matches a second condition to calculate the first score.” A physician may convert the signal using the Fourier transform equation. The physician may also separate the signals into a first, second, and third interval. A second and third respiration signal may be captured with pen and paper to generate a detection result for periodic breathing. A feature may be compared to match with a second condition to calculate a first score using equations and observation. This may be used to determine whether the second interval signal corresponds to the periodic breathing.
Claims 8 and 19
“Capturing a fourth interval signal from the conversion signal according to the second interval; determining whether a second feature value of the fourth interval signal matches a second condition to calculate a second score corresponding to the fourth interval signal; and determining whether the second interval signal corresponds to the periodic breathing according to the first score and the second score.” A physician may convert the signal using the Fourier transform equation. The physician may also separate the signals into a first, second, third, and fourth interval. A fourth respiration signal may be captured with pen and paper to generate a detection result for periodic breathing. A second feature may be compared to match with a second condition to calculate a second score using equations and observation. This may be used to determine whether the second interval signal corresponds to the periodic.
Claims 10 and 21
“Performing the second changepoint detection on the conversion signal to obtain a third interval adjacent to the second interval; capturing a fifth interval signal from the conversion signal according to the second interval and the third interval; and determining whether a third feature value of the fifth interval signal matches a third condition to calculate the second score.” A physician may convert the signal using the Fourier transform equation. The physician may also separate the signals into a first, second, third, fourth, and fifth interval. A fifth respiration signal may be captured with pen and paper to generate a detection result for periodic breathing. A third feature may be compared to match with a third condition to calculate a second score using equations and observation. This may be used to determine whether the second interval signal corresponds to the periodic.
Step 2A (Prong 2): Does the claim recite additional elements that integrate the judicial
exception into a practical application?
Claims 1 and 12 recite the additional elements of a “a transceiver” and a “processor” which are being interpreted as a processor of a data gathering device.
“A transceiver, receiving a respiration signal,” is recited as pre-solution activity to the step of data gathering.
However, these elements are recited at a high level of generality performing the function of generic data processing such that they amount to no more than mere instructions to simply implement the abstract idea using generic computer components. See MPEP 2106.05(b) and (f).
Accordingly, the additional elements do not integrate the abstract idea into a practical
application.
Step 2B: Does the claim recite additional elements that amount to significantly more than the
judicial exception?
The additional elements when considered individually and in combination are not enough to
qualify as significantly more than the abstract idea.
“A transceiver, receiving a respiration signal,” is recited as pre-solution activity to the step of data gathering.
As discussed above with respect to integration of the abstract idea into a practical application, “a transceiver” and a “processor” which are being interpreted as a processor of a data gathering device as recited to perform the steps of:
calculating variance of the respiration signal to generate a variance degree;
performing a first changepoint detection on the variance degree to obtain a first interval;
capturing a first interval signal from the respiration signal according to the first interval;
detecting the first interval signal to generate a detection result corresponding to at least one periodic breathing;
and outputting the detection result.
amount to no more than mere instructions to apply the exception using generic computer
components. Mere instructions to apply an exception using generic components cannot provide an inventive concept. These additional elements are well‐understood, routine (For example Droitcour et al. US Pub.: US 20100152600 A1, hereinafter Droitcour) teaches a data gathering device with a processor and memory, and conventional limitations that amount to mere instructions or elements to implement the abstract idea. In addition, the end result of the system/method, the essence of the whole, is a patent-ineligible concept. Therefore, the claims are not patent eligible.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-22 are rejected under 35 U.S.C. 102(a)(1) as being unpatentable by Droitcour et al. US
Pub.: US 20100152600 A1, hereinafter Droitcour.
Regarding claim 1, Droitcour teaches an electronic device for detecting a periodic breathing,
comprising: a transceiver (2201), receiving a respiration signal (fig. 7 and 22; paragraph 246 and 639);
and a processor (2202), coupled to the transceiver (2201) and configured to perform: calculating a variance degree of the respiration signal (fig. 7 and 22; paragraph 246, 609, and 639); It is disclosed an indication of level of variability of the measured rate, i.e., how much the rate varied during the measurement interval.
performing a first changepoint detection on the variance degree to obtain a first interval (fig. 7 and 22; paragraph 609-610); The time domain and the frequency domain rate estimates can be compared. The processor may determine the difference between the two results, which can indicate the degree to which the signal does not fit the assumptions of either the time or frequency domain approaches. Different interval timings are disclosed to be used based on this comparison. Therefore, a first interval and changepoint is disclosed.
capturing a first interval signal from the respiration signal according to the first interval (fig. 7 and 22; paragraph 609-610); A plurality of intervals are disclosed and captured.
detecting the first interval signal to generate a detection result corresponding to at least one periodic breathing (paragraph 412-415); An irregularity index value from 0-6 is used as detection results for periodic breathing for each intervals.
and outputting the detection result through the transceiver (fig. 7 and 22; paragraph 246 and 412-415); The irregularity index value may be displayed or alerted to the patient.
Regarding claims 2 and 13, Droitcour teaches wherein the processor (2202) is further configured
to perform: performing a fast Fourier transform on the first interval signal to generate a conversion signal (fig. 22; paragraph 421 and 609); A Fourier transform is computed on all the samples to provide the signal spectrum.
performing a second changepoint detection on the conversion signal to obtain a second interval and capturing a second interval signal from the respiration signal according to the second interval (fig. 7 and 22; paragraph 609-610); The time domain and the frequency domain rate estimates can be compared. The processor may determine the difference between the two results, which can indicate the degree to which the signal does not fit the assumptions of either the time or frequency domain approaches. Different interval timings are disclosed to be used based on this comparison. Therefore, a second interval and changepoint is disclosed.
and determining whether the second interval signal corresponds to the periodic breathing to generate the detection result (paragraph 412-415); An irregularity index value from 0-6 is used as detection results for periodic breathing for each intervals.
Regarding claims 3 and 14, Droitcour teaches wherein the processor (2202) is further configured
to perform: inputting the second interval signal to a machine learning model to determine whether the second interval signal corresponds to the periodic breathing (fig. 22; paragraph 412-415, 421 and 609). A Fourier transform is as a machine learning tool for waveform conversion and analysis.
Regarding claims 4 and 15, Droitcour teaches wherein the processor (2202) is further configured
to perform: determining whether a first feature value of the second interval signal matches a first condition to calculate a first score corresponding to the second interval signal (paragraph 372, 412-415, and 496); Features may be compared to with conditions or threshold to help calculate irregularity index, which equates to a first score.
and determining whether the second interval signal corresponds to the periodic breathing according to the first score (paragraph 372, 412-415, and 609-610); An irregularity index value from 0-6 is used as detection results for periodic breathing for each intervals. This index equates to a first score.
Regarding claims 5 and 16, Droitcour teaches wherein the first feature value is associated with
one of the following features: power spectral density, variance, median, first quartile, third quartile, and maximum value (paragraph 372, 378, and 496).
Regarding claims 6 and 17, Droitcour teaches wherein the processor is further configured to
perform: performing the second changepoint detection on the conversion signal to obtain a third interval adjacent to the second interval (fig. 7 and 22; paragraph 609-610); The time domain and the frequency domain rate estimates can be compared. The processor may determine the difference between the two results, which can indicate the degree to which the signal does not fit the assumptions of either the time or frequency domain approaches. Different interval timings are disclosed to be used based on this comparison. Therefore, a second and third interval is disclosed, and are adjacent to one another. This refers to a second changepoint.
capturing a third interval signal from the respiration signal according to the second interval and the third interval (fig. 7 and 22; paragraph 609-610); A plurality of intervals are disclosed and captured.
and determining whether a second feature value of the third interval signal matches a second condition to calculate the first score (paragraph 372, 412-415, and 496); A second feature may be compared to with different conditions or threshold to help calculate irregularity index, which equates to a first score.
Regarding claims 7 and 18, Droitcour teaches wherein the second feature value is associated
with one of the following features: variance, median, first quartile, third quartile, and maximum value (paragraph 372, 378, and 496).
Regarding claims 8 and 19, Droitcour teaches wherein the processor is further configured to
perform: capturing a fourth interval signal from the conversion signal according to the second interval (fig. 7 and 22; paragraph 609-610); A plurality of intervals are disclosed and captured.
determining whether a second feature value of the fourth interval signal matches a second condition to calculate a second score corresponding to the fourth interval signal (paragraph 372, 412-415, and 496); A second feature may be compared to with different conditions or threshold to help calculate irregularity index, which equates to a second score. This may be done for all interval signals for analysis.
and determining whether the second interval signal corresponds to the periodic breathing according to the first score and the second score (paragraph 372, 412-415, and 609-610); An irregularity index value from 0-6 is used as detection results for periodic breathing for each intervals. This index equates to both a first score and second score.
Regarding claims 9 and 20, Droitcour teaches wherein the second feature value is associated
with one of the following features: variance, median, first quartile, third quartile, maximum value, peak width, peak count, skewness, and kurtosis (paragraph 372, 378, and 496).
Regarding claims 10 and 21, Droitcour teaches wherein the processor (2202) is further
configured to perform: performing the second changepoint detection on the conversion signal to obtain a third interval adjacent to the second interval (fig. 7 and 22; paragraph 609-610); The time domain and the frequency domain rate estimates can be compared. The processor may determine the difference between the two results, which can indicate the degree to which the signal does not fit the assumptions of either the time or frequency domain approaches. Different interval timings are disclosed to be used based on this comparison. Therefore, a second and third interval is disclosed, and are adjacent to one another. This refers to a second changepoint.
capturing a fifth interval signal from the conversion signal according to the second interval and the third interval (fig. 7 and 22; paragraph 609-610); A plurality of intervals are disclosed and captured.
and determining whether a third feature value of the fifth interval signal matches a third condition to calculate the second score (paragraph 372, 412-415, and 496); A third feature may be compared to with different conditions or threshold to help calculate irregularity index, which equates to a second score. This may be done for all interval signals for analysis.
Regarding claims 11 and 22, Droitcour teaches wherein the third feature value is associated with
one of the following features: variance, median, first quartile, third quartile, and maximum value (paragraph 372, 378, and 496).
Regarding claim 12, Droitcour teaches a method of detecting a periodic breathing for an
electronic device detecting the periodic breathing, comprising: receiving a respiration signal through the electronic device (fig. 7 and 22; paragraph 246 and 639);
calculating variance of the respiration signal to generate a variance degree (fig. 7 and 22; paragraph 246, 609, and 639); It is disclosed an indication of level of variability of the measured rate, i.e., how much the rate varied during the measurement interval.
performing a first changepoint detection on the variance degree to obtain a first interval (fig. 7 and 22; paragraph 609-610); The time domain and the frequency domain rate estimates can be compared. The processor may determine the difference between the two results, which can indicate the degree to which the signal does not fit the assumptions of either the time or frequency domain approaches. Different interval timings are disclosed to be used based on this comparison. Therefore, a first interval and changepoint is disclosed.
capturing a first interval signal from the respiration signal according to the first interval (fig. 7 and 22; paragraph 609-610); A plurality of intervals are disclosed and captured.
detecting the first interval signal to generate a detection result corresponding to at least one periodic breathing (paragraph 412-415); An irregularity index value from 0-6 is used as detection results for periodic breathing for each intervals.
and outputting the detection result (fig. 7 and 22; paragraph 246 and 412-415); The irregularity index value may be displayed or alerted to the patient.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to THIEN J TRAN whose telephone number is (571)272-0486. The examiner can normally be reached M-F. 8:30 am - 5:30 pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Benjamin Klein can be reached at 571-270-5213. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/T.J.T./Examiner, Art Unit 3792
/Benjamin J Klein/Supervisory Patent Examiner, Art Unit 3792