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 Objections
Claim 15 is objected to because of the following informalities: The claim language “Computer program with program code to perform…” should be changed to “A non-transitory computer program with program code to perform…” 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.
Claims 1-15, specifically independent claims 1 & 13, are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception without significantly more. Please see the below analysis providing the details as to why the invention is directed towards non-statutory subject matter.
Step 1:
Claim 1 is directed to a method. Therefore, the claim falls within a statutory category of invention.
Claim 13 is directed to a system, which is a product. Therefore, the claim falls within a statutory category of invention.
Step 2A, prong 1:
Claim 1 recites a method comprising:
“…providing a plurality of biosignal curves…”
“…storing the detected biosignal curves…”
“…applying an algorithm to the plurality of biosignal curves…”
“…classifying biosignal curves…”
Claim 13 recites a method steps (by an implantable medical device) comprising:
“…providing a plurality of biosignal curves…”
“…storing the detected biosignal curves…”
“…applying an algorithm to the plurality of biosignal curves…”
“…classifying biosignal curves…”
Under the broadest reasonable interpretation, claims 1 & 13, recites a series of steps practically performed in the human mind. A human could provide, store, apply and classify a plurality of biosignal curves. Therefore, it would be practical to perform the steps in a human’s mind, or with a pen and paper.
Therefore, claims 1 & 13, recite method steps comprising mental processes (i.e. providing, storing) and mathematical concepts (i.e. applying, classifying). Since claims 1 & 13 recite limitations that fall within the mental processes and mathematical concepts of abstract ideas, and the claims are therefore directed to an abstract idea.
Step 2A, prong 2:
Claims 1 & 13 recites the following additional elements, which for the reasons set forth below, do not integrate the abstract idea into a practical application:
“…implantable medical device…” which is directed to data output, see MPEP 2106.05(g).
“…a storage medium…” which is directed to mere instructions to apply an exception, see MPEP 2106.05(f).
Therefore, the claims fail to integrate the abstract idea into a practical application. The examiner also notes that the additional elements recited in claims 1, 8 & 15 do not apply or use the judicial exception to affect a particular treatment or prophylaxis for a disease or medical condition. The claims are silent to providing any treatment at all to a patient.
Step 2B:
The claims as a whole fails to recite an inventive concept. The additional elements, when considered individually and in combination, do not recite significantly more than the abstract idea for the reasons as set forth above in Step 2A, Prong 2. Upon re-evaluating the limitation that was previously identified as insignificant extra-solution activity in Step 2A, Prong 2, the following evidence to show that the limitation is well-understood, routine and conventional:
real-time discrete data obtained from a medical device/data previously collected from a medical device (i.e. body surface/unipolar electrodes) Presenting offers and gathering statistics, OIP Techs., 788 F.3d at 1362-63, 115 USPQ2d at 1092-93; Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network).
producing at said computer processor a human-readable output (i.e. processor) of the analysis of the gathered data, this is also WURC, as evidenced by Electric Power Group, LLC v. Alstom S.A., 830F.3d 1350, 119 USPQ2d 1739 (Fed.Cir. 2016), which discusses “conventional computer, network, and display technology” and states that “nothing in the patent contains any suggestion that the displays needed for that purpose are anything but readily available. We have repeatedly held that such invocations of computers and networks that are not even arguably inventive are “insufficient to pass the test of an inventive concept in the application” of an abstract idea”.” Similarly, there is nothing in Applicant’s specification that indicates that the device that is “producing at said computer processor a human-readable output indicating” the findings of the analysis is anything but readily available.
Therefore, the claims fail to recite significantly more than the abstract idea and claims 1-15 are rejected under 35 U.S.C 101.
The limitations of the dependent claims 2-12 & 14-15 further define the biosignal curves, the algorithm, and the classification, which further limit claim limitations already indicated above as being directed to an abstract idea. Therefore, the dependent claims are also directed to patient-ineligible subject matter.
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) 1-15 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Carlson (US 2003/0204146).
1.
Computer-implemented method for classification of similar biosignal curves detected by an implantable medical device, comprising the following steps: providing a plurality of biosignal curves by the implantable medical device; storing the detected biosignal curves in a storage medium;
E.G. via the disclosed computer implemented method 200 that retrieves EGM data, i.e. an array of amplitude data for cardiac cycles, from an implanted device, via step 204, wherein beat segments are extracted and stored {[0033]-[0034], [0038], [0040] & (Fig 2A)}.
applying an algorithm (A) to the plurality of biosignal curves to determine a similarity of each of the plurality of biosignal curves with the plurality of biosignal curves with respect to at least one signal feature according to predetermined similarity criteria;
E.G. via the disclosed step 216 of organizing similar waveform segments into ‘contiguous’ morphology group memberships via a clustering step 212 {[0037]-[0039], [0063] & (Fig 2A)}
*Note that the examiner is interpreting the clustering step used to ‘identify’ and extract similar groups from a data set as being the claimed algorithm applies to determine similarity [0037].
and classifying biosignal curves matching the predetermined similarity criteria.
E.G. via disclosed step 220, which marks the group membership with some ‘indicia’ [0040] and the step of providing final classification, step 428, that generates an annotated segment [0088].
2.
Computer-implemented method of claim 1, wherein the biosignal curves are at least one of ECG and/or IEGM signal curves, respiratory signal curves, in particular a respiratory rhythm and/or a respiratory depth, pressure waveform signal curves, temperature waveform signal curves, tissue and body inductance signal curves and blood flow signal curves.
E.G. [0034].
3.
Computer-implemented method of claim 1, wherein the algorithm (A) for determining the similarity of the biosignal curves performs at least one of a cross-correlation function and an image processing technique with respect to the at least one signal feature (SF), wherein the at least one signal feature (SF) is a morphology of a QRS complex, a morphology of a T-wave and/or a morphology of a P- wave of an ECG-signal curve.
E.G. ([0061]-[0064])
4.
Computer-implemented method claim 1, wherein the algorithm, in particular a machine learning algorithm, for determining the similarity of the biosignal curves is configured to classify the biosignal curves matching the predetermined similarity criteria.
E.G. via the disclosed method 400 {[0055] & (Fig 3)}.
5.
Computer-implemented method of claim 1, wherein the similarity of the biosignal curves is determined by a first algorithm, and wherein a classification of biosignal curves matching the predetermined similarity criteria (SC) is performed by a second algorithm.
E.G. via the disclosed grouping based on waveform morphology being via clustering, step 408, and the step of finding contiguous, similar beats incorporates a FFRW algorithm {[0061]-[0063], [0068]-[0069] & (Fig 3)}
6.
Computer-implemented method of claim 1, wherein the predetermined similarity criteria (SC) are met if a numeric value of the at least one signal feature (SF) of a first biosignal curve and at least a second biosignal curve of the plurality of biosignal curves is within a predetermined numeric range.
E.G. based on the disclosed identity threshold output 410A and a second similarity threshold 410C {[0065]-[0066] & (Fig 3)}.
7.
Computer-implemented method of claim 1, wherein a classification result of biosignal curves matching the predetermined similarity criteria is sent to a communication device of a healthcare provider, wherein the classification result comprises at least one designated class, a number of similar episodes of the classified biosignal curves and a time interval, in which the classified number of similar episodes occurred.
E.G. via the disclosed ‘subtree membership’ associated with each EGM heartbeat being stored for storage, transmission or visual display, wherein at step 428 the final classification is generated to annotate the segment of the episode and outputted {[0066], [0088] & (Fig 3)}.
8.
Computer-implemented method of claim 1, wherein the application of the algorithm to the plurality of biosignal curves and/or the classification of the biosignal curves matching the predetermined similarity criteria (SC) is performed by an executable program embedded within the implantable medical device and/or operating on a remote server, and wherein the biosignal curves are transmitted to the remote server a patient communication device or smartphone.
E.G. via the disclosed data associated with the computer implemented method being retrieved over a data communications network at a location remote to the IMD, wherein an annotated and processed segment is outputted via a visual display ([0007] & [0088]).
9.
Computer-implemented method of claim 1, wherein the biosignal curves are acquired by the implantable medical device at predetermined intervals and/or on request, in particular as a wide-field ECG between electrodes and a housing of the implantable medical device.
E.G. {[0032]-[0033] & (Fig. 1)}
10.
Computer-implemented method of claim 1, wherein the implantable medical device is a diagnostic implant, in particular a cardiac rhythm monitor, a pressure sensor implant or a vital sign acquisition implant for acquiring respiratory data and/or temperature data, a therapeutic implant, in particular a cardiac pacemaker or a defibrillator, or a neurostimulator.
E.G. {[0033] & (Fig. 1)}.
11.
Computer-implemented method of claim 8, wherein at least one classification result of biosignal curves matching the predetermined similarity criteria is sent to the patient communication device or smartphone, in particular by the implantable medical device or the remote server, wherein the at least one classification result is accessible to a user of the implantable medical device via the patient communication device or smartphone.
E.G. ([0007] & [0088]).
12.
Computer-implemented method of claim 1, wherein based on the classification of the biosignal curves matching the predetermined similarity criteria (SC), operating parameters of the implantable medical device are adjusted.
E.G. via the disclosed implantable device utilizing the EGM waveform data to provide ‘corrective’ action by said implantable device ([0033]-[0035).
13.
System for classification of similar biosignal curves detected by an implantable medical device, comprising: an implantable medical device for providing a plurality of biosignal curves; a storage medium for storing the detected biosignal curves;
E.G. via the disclosed computer implemented method 200 that retrieves EGM data, i.e. an array of amplitude data for cardiac cycles, from an implanted device, via step 204, wherein beat segments are extracted and stored {[0033]-[0034], [0038], [0040] & (Fig 2A)}.
means for applying an algorithm (A) to the plurality of biosignal curves to determine a similarity of each of the plurality of biosignal curves with the plurality of biosignal curves with respect to at least one signal feature (SF) according to predetermined similarity criteria (SC);
E.G. via the disclosed step 216 of organizing similar waveform segments into ‘contiguous’ morphology group memberships via a clustering step 212 {[0037]-[0039], [0063] & (Fig 2A)}
*Note that the examiner is interpreting the clustering step used to ‘identify’ and extract similar groups from a data set as being the claimed algorithm applies to determine similarity [0037].
and means for classifying biosignal curves matching the predetermined similarity criteria.
E.G. via disclosed step 220, which marks the group membership with some ‘indicia’ [0040] and the step of providing final classification, step 428, that generates an annotated segment [0088].
14.
System of claim 13, wherein the storage medium for storing the detected biosignal curves is arranged in the implantable medical device and/or in a remote server, wherein the biosignal curves are transmittable to the remote server via a patient communication device or smartphone.
E.G. ([0007] & [0088]).
15.
Computer program with program code to perform the method of claim 1 when the computer program is executed on a computer.
E.G. [0034].
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to NICOLE F JOHNSON whose telephone number is (571)270-5040. The examiner can normally be reached Monday-Friday 8:00am-5:00pm EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, David Hamaoui can be reached at 571-270-5625. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/NICOLE F JOHNSON/Primary Examiner, Art Unit 3796