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 § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-19 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding claim 1, the terms “slow-moving average” and “fast-moving average” are a relative term which renders the claim indefinite. The terms “slow-moving average” and “fast-moving average” are not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. One of ordinary skill would not be able to ascertain which averages count as “slow-moving“ or “fast-moving.” For Examination purposes, it will be interpreted that slow-moving is an average taken over a long time period, and fast-moving is an average taken over a long time period.
Claims 4, 13, 15, and 17 are rejected for using the same recited terms detailed above.
Claims 2-12 are rejected for their dependency on claim 1; Claims 5 and 6 are rejected for their dependency on claim 4; Claims 14-19 are rejected for their dependency on claim 13; And claim 19 is rejected for its dependency on claim 17.
Regarding claims 2 and 20, the claims recite, “obtain the plurality of heartbeat intervals at a respective particular time of day…”. The recitation of “a respective particular time of day” is indefinite because it is not clear based on the language of the claim if the intervals are taken at the same time each day, or if each day has a time in which the heart beat sample is taken, but does not have to be the same time each day. For this reason, the claims are rendered indefinite. For examination purposes, the claims will be interpreted as obtaining a plurality of heartbeat intervals at a time each day, but it does not have to be at the same time each day.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed inventions are directed towards a judicial exception without significantly more.
Step 1 – Is the claim to a statutory category of invention?
Claims 1-12 recite a machine (i.e., a system). Claims 13, 14, and 16-20 recite a method. Claim 15 recites a machine (system). Therefore, the claims are to a statutory category of invention.
Step 2A, prong 1 – Does the claim recite a judicial exception?
Independent claim 1 recites: “…determine a slow-moving average for each sample point parameter of respective heartbeat intervals during a first period of time; determine a fast-moving average for each sample point parameter of respective heartbeat intervals during a second period of time, the second period of time being less than the first period of time; determine a difference between the slow-moving average and the fast-moving average for each sample point parameter; and determine a risk level of a health event for the patient based on the determined differences.” The limitations recite both mathematical concept abstract ideas and mental process abstract ideas. The steps of determining fast-moving and slow-moving averages, and differences between those averages, are all based on mathematical concepts in that they are no more than applying basic mathematical principles to data. Further, determining a risk level of a health event is a mental process in that one of ordinary skill in the art, such as a physician, could make this judgement in their head based on differences between ECG readings. As recited in MPEP 2106.04(a)(2)(III): “Accordingly, the "mental processes" abstract idea grouping is defined as concepts performed in the human mind, and examples of mental processes include observations, evaluations, judgments, and opinions.” A physician could make a judgement or opinion on the risk of a health event based on differences in ECG data. For these reasons, the recited limitations are mathematical concept abstract ideas and mental process abstract ideas.
Independent claim 13 recites: “…determining a slow-moving average for each sample point parameter of respective heartbeat intervals during a first period of time; determine a fast-moving average for each sample point parameter of respective heartbeat intervals during a second period of time, the second period of time being less than the first period of time; determine a difference between the slow-moving average and the fast-moving average for each sample point parameter; and determine a risk level of a health event for the patient based on the determined differences.” The limitations recite both mathematical concept abstract ideas and mental process abstract ideas. The steps of determining fast-moving and slow-moving averages, and differences between those averages, are all based on mathematical concepts in that they are no more than applying basic mathematical principles to data. Further, determining a risk level of a health event is a mental process in that one of ordinary skill in the art, such as a physician, could make this judgement in their head based on differences between ECG readings. As recited in MPEP 2106.04(a)(2)(III): “Accordingly, the "mental processes" abstract idea grouping is defined as concepts performed in the human mind, and examples of mental processes include observations, evaluations, judgments, and opinions.” A physician could make a judgement or opinion on the risk of a health event based on differences in ECG data. For these reasons, the recited limitations are mathematical concept abstract ideas and mental process abstract ideas.
Independent claim 15 recites: “…determine a slow-moving metric based on the heart beat data during a first period of time; determine a fast-moving metric based on the heart beat data during a second period of time, the second period of time being less than the first period of time; determine a risk level of a health event for the patient based on the slow-moving metric and fast-moving metric.” The limitations recite both mathematical concept abstract ideas and mental process abstract ideas. The steps of determining fast-moving and slow-moving metric are based on mathematical concepts in that they are no more than applying basic mathematical principles and calculations to data. Further, determining a risk level of a health event is a mental process in that one of ordinary skill in the art, such as a physician, could make this judgement in their head based on the calculated metrics. As recited in MPEP 2106.04(a)(2)(III): “Accordingly, the "mental processes" abstract idea grouping is defined as concepts performed in the human mind, and examples of mental processes include observations, evaluations, judgments, and opinions.” A physician could make a judgement or opinion on the risk of a health event based on differences in ECG data. For these reasons, the recited limitations are mathematical concept abstract ideas and mental process abstract ideas.
Step 2A prong 2 – Does the claim recite additional elements that integrate the judicial exception into a
practical application?
In addition to the judicial exceptions recited above, claim 1 recites: “A system comprising: a memory; and processing circuitry coupled to the memory…”. A memory and processing circuitry are generic computer structures that do not integrate the judicial exception into a practical application.
Claim 1 further recites: “…receive electrocardiogram (ECG) data of a patient, wherein the ECG data is generated by one or more sensing devices of the patient based on physiological signals of the patient sensed by the one or more sensing devices; obtain a plurality of heartbeat intervals from the ECG data; sample a plurality of points for each respective heartbeat interval of the plurality of intervals…” Receiving, obtaining, and sampling ECG data is insignificant extra-solution activity data gathering in that it recites general steps for measuring and obtaining heart beat data. One of ordinary skill would recognize that the general steps of recording ECG data are known in the art, and that the recitation of these steps are merely gathering ECG data. Therefore, the limitations in addition to the recited judicial exception do not integrate the judicial exception into a practical application.
In addition to the judicial exceptions recited above, claim 13 recites: “receiving electrocardiogram (ECG) data of a patient, wherein the ECG data is generated by one or more sensing devices of the patient based on physiological signals of the patient sensed by the one or more sensing devices; obtaining a plurality of heartbeat intervals from the ECG data; sampling a plurality of points for each respective heartbeat interval of the plurality of intervals.” Receiving, obtaining, and sampling ECG data is insignificant extra-solution activity data gathering in that it recites general steps for measuring and obtaining heart beat data. One of ordinary skill would recognize that the general steps of recording ECG data are known in the art, and that the recitation of these steps are merely gathering ECG data. Therefore, the limitations in addition to the recited judicial exception do not integrate the judicial exception into a practical application.
In addition to the judicial exceptions recited above, claim 15 recites: “A system comprising: a memory; and processing circuitry coupled to the memory…”. A memory and processing circuitry are generic computer structures that do not integrate the judicial exception into a practical application.
Claim 15 further recites: “receive electrocardiogram (ECG) data of a patient, wherein the ECG data is generated by one or more sensing devices of the patient based on physiological signals of the patient sensed by the one or more sensing devices; obtain a plurality of heartbeat intervals from the ECG data.” Receiving and obtaining ECG data is insignificant extra-solution activity data gathering in that it recites general steps for measuring and obtaining heart beat data. One of ordinary skill would recognize that the general steps of recording ECG data are known in the art, and that the recitation of these steps are merely gathering ECG data. Therefore, the limitations in addition to the recited judicial exception do not integrate the judicial exception into a practical application.
Step 2B – Do the additional elements add significantly more to the judicial exception?
In addition to the judicial exceptions recited above, claim 1 recites: “A system comprising: a memory; and processing circuitry coupled to the memory…”. A memory and processing circuitry are generic computer structures that do add significantly more to the judicial exception.
Claim 1 further recites: “…receive electrocardiogram (ECG) data of a patient, wherein the ECG data is generated by one or more sensing devices of the patient based on physiological signals of the patient sensed by the one or more sensing devices; obtain a plurality of heartbeat intervals from the ECG data; sample a plurality of points for each respective heartbeat interval of the plurality of intervals…”. Receiving, obtaining, and sampling ECG data is insignificant extra-solution activity data gathering in that it recites general steps for measuring and obtaining heart beat data. One of ordinary skill would recognize that the general steps of recording ECG data are known in the art, and that the recitation of these steps are merely gathering ECG data. Therefore, the limitations in addition to the recited judicial exception do not add significantly more to the judicial exception.
In addition to the judicial exceptions recited above, claim 13 recites: “receiving electrocardiogram (ECG) data of a patient, wherein the ECG data is generated by one or more sensing devices of the patient based on physiological signals of the patient sensed by the one or more sensing devices; obtaining a plurality of heartbeat intervals from the ECG data; sampling a plurality of points for each respective heartbeat interval of the plurality of intervals.” Receiving, obtaining, and sampling ECG data is insignificant extra-solution activity data gathering in that it recites general steps for measuring and obtaining heart beat data. One of ordinary skill would recognize that the general steps of recording ECG data are known in the art, and that the recitation of these steps are merely gathering ECG data. Therefore, the limitations in addition to the recited judicial exception do not add significantly more to the judicial exception.
In addition to the judicial exceptions recited above, claim 15 recites: “A system comprising: a memory; and processing circuitry coupled to the memory…”. A memory and processing circuitry are generic computer structures that do not add significantly more to the judicial exception.
Claim 15 further recites: “receive electrocardiogram (ECG) data of a patient, wherein the ECG data is generated by one or more sensing devices of the patient based on physiological signals of the patient sensed by the one or more sensing devices; obtain a plurality of heartbeat intervals from the ECG data.” Receiving and obtaining ECG data is insignificant extra-solution activity data gathering in that it recites general steps for measuring and obtaining heart beat data. One of ordinary skill would recognize that the general steps of recording ECG data are known in the art, and that the recitation of these steps are merely gathering ECG data. Therefore, the limitations in addition to the recited judicial exception do not add significantly more to the judicial exception.
Dependent claims
Claims 2 and 20 further limits insignificant, extra-solution activity.
Claims 3-6, 10, and 16-19 recite a mathematical concept abstract idea.
Claims 7-9 further limits an abstract idea mental process.
Claim 11 further limits an abstract idea mathematical concept and mental process.
Claim 14 recites generic computer structure for executing the abstract ideas of claim 13.
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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1, 2, 4-6, 8, 10, 13-15, and 17-20 are rejected under 35 U.S.C. 102(a)(1)/(a)(2) as being anticipated by Gill et al. (US 20110004111 A1, "Gill").
Regarding independent claim 1, Gill teaches a system comprising: a memory (Fig. 2; memory 260); and processing circuitry (Fig. 2; microcontroller 220) coupled to the memory (para. [0047]: "The microcontroller 220 is further coupled to a memory 260 by a suitable data/address bus 262") and configured to: receive electrocardiogram (ECG) data of a patient (para. [0064] discloses obtaining segments of an IEGM (a type of ECG) from electrodes to detect ischemia), wherein the ECG data is generated by one or more sensing devices of the patient based on physiological signals of the patient sensed by the one or more sensing devices (para. [0064]: "At step 700, ventricular activity is detected using one or more electrode pairs as described above. At step 702, a detection window is opened for a predetermined time after the ventricular activity is detected. In one embodiment, the window is opened for about 50 milliseconds following the onset of ventricular activity. It will be understood that the window may be opened for a predetermined time following detection of the R-wave peak, or following the end of the QRS complex, or any other suitable event."); obtain a plurality of heartbeat intervals from the ECG data (para. [0065] mentions a window, which is an interval: "At step 704, the portion of the IEGM signal within the window is sensed, and the amplitude of the IEGM signal is determined"); Para. [0069] also mentions segments, which are intervals); sample a plurality of points for each respective heartbeat interval of the plurality of intervals (para. [0065]: "…the values sensed within the window"; para. [0069]: "amplitudes"); determine a slow-moving average for each sample point parameter of respective heartbeat intervals during a first period of time (para. [0070]: "To support ischemia detection, in one embodiment the STn values may be measured periodically on an ensemble-average of several (e.g. 8-16) consecutive or closely occurring QRST complexes (e.g., within a few minutes of each other)."; [0071]: " Alternately, the STn values may be measured periodically for each of several individual consecutive or approximately consecutive complexes and statistics calculated on the several measurements. Statistical parameters to be estimated may include the mean and the variance, or any other suitable parameter to determine an average ST segment value for purposes of monitoring for ischemia."; para. [0075]: "short-term average value"); determine a fast-moving average for each sample point parameter of respective heartbeat intervals during a second period of time (para. [0075]), the second period of time being less than the first period of time (para. [0075]: "In another embodiment, the implanted device 100 may compute a short-term average value (e.g., taken over a plurality of cycles within the last few minutes) as well as a long-term average value (e.g., taken over a period of weeks, months, etc.)"); determine a difference between the slow-moving average and the fast-moving average for each sample point parameter (para. [0075]: "In this embodiment, if a short-term average value exceeds a long-term average value by more than a threshold amount (or alternately by more than a percentage of the long-term average value).” A slow-moving average is interpreted as an average taken over a long period of time; a fast-moving average is interpreted as an average taken over a short period of time); and determine a risk level of a health event for the patient based on the determined differences (para. [0075]: "if a short-term average value exceeds a long-term average value by more than a threshold amount (or alternately by more than a percentage of the long-term average value), then ischemia is indicated."; para. [0093]: "The burden metric may include measures of certainty and/or severity of ischemia."; para. [0094]: "In one embodiment for example, the degree by which a feature exceeds its threshold for ischemia detection may mapped to a severity/likelihood index which can take values from 1-5…").
Regarding independent claim 13, Gill teaches a method comprising: receiving electrocardiogram (ECG) data of a patient (para. [0064] discloses obtaining segments of an IEGM (a type of ECG) from electrodes to detect ischemia), wherein the ECG data is generated by one or more sensing devices of the patient based on physiological signals of the patient sensed by the one or more sensing devices (para. [0064]: "At step 700, ventricular activity is detected using one or more electrode pairs as described above. At step 702, a detection window is opened for a predetermined time after the ventricular activity is detected. In one embodiment, the window is opened for about 50 milliseconds following the onset of ventricular activity. It will be understood that the window may be opened for a predetermined time following detection of the R-wave peak, or following the end of the QRS complex, or any other suitable event."); obtaining a plurality of heartbeat intervals from the ECG data (para. [0065] mentions a window, which is an interval: "At step 704, the portion of the IEGM signal within the window is sensed, and the amplitude of the IEGM signal is determined"); Para. [0069] also mentions segments, which are intervals); sampling a plurality of points for each respective heartbeat interval of the plurality of intervals (para. [0065]: "…the values sensed within the window"; para. [0069]: "amplitudes"); determining a slow-moving average for each sample point parameter of respective heartbeat intervals during a first period of time (para. [0070]: "To support ischemia detection, in one embodiment the STn values may be measured periodically on an ensemble-average of several (e.g. 8-16) consecutive or closely occurring QRST complexes (e.g., within a few minutes of each other)."; [0071]: " Alternately, the STn values may be measured periodically for each of several individual consecutive or approximately consecutive complexes and statistics calculated on the several measurements. Statistical parameters to be estimated may include the mean and the variance, or any other suitable parameter to determine an average ST segment value for purposes of monitoring for ischemia."; para. [0075]: "short-term average value"); determining a fast-moving average for each sample point parameter of respective heartbeat intervals during a second period of time (para. [0075]), the second period of time being less than the first period of time (para. [0075]: "In another embodiment, the implanted device 100 may compute a short-term average value (e.g., taken over a plurality of cycles within the last few minutes) as well as a long-term average value (e.g., taken over a period of weeks, months, etc.)"); determining a difference between the slow-moving average and the fast-moving average for each sample point parameter (para. [0075]: "In this embodiment, if a short-term average value exceeds a long-term average value by more than a threshold amount (or alternately by more than a percentage of the long-term average value)"; A slow-moving average is interpreted as an average taken over a long period of time; a fast-moving average is interpreted as an average taken over a short period of time); and determining a risk level of a health event for the patient based on the determined differences (para. [0075]: "if a short-term average value exceeds a long-term average value by more than a threshold amount (or alternately by more than a percentage of the long-term average value), then ischemia is indicated."; para. [0093]: "The burden metric may include measures of certainty and/or severity of ischemia."; para. [0094]: "In one embodiment for example, the degree by which a feature exceeds its threshold for ischemia detection may mapped to a severity/likelihood index which can take values from 1-5…").
Regarding independent claim 15, Gill teaches a system comprising: a memory (Fig. 2; memory 260); and processing circuitry (Fig. 2; microcontroller 220) coupled to the memory (para. [0047]: "The microcontroller 220 is further coupled to a memory 260 by a suitable data/address bus 262") and configured to: receive electrocardiogram (ECG) data of a patient (para. [0064] discloses obtaining segments of an IEGM (a type of ECG) from electrodes to detect ischemia), wherein the ECG data is generated by one or more sensing devices of the patient based on physiological signals of the patient sensed by the one or more sensing devices (para. [0064]: "At step 700, ventricular activity is detected using one or more electrode pairs as described above. At step 702, a detection window is opened for a predetermined time after the ventricular activity is detected. In one embodiment, the window is opened for about 50 milliseconds following the onset of ventricular activity. It will be understood that the window may be opened for a predetermined time following detection of the R-wave peak, or following the end of the QRS complex, or any other suitable event."); obtain a plurality of heartbeat intervals from the ECG data (para. [0065] mentions a window, which is an interval: "At step 704, the portion of the IEGM signal within the window is sensed, and the amplitude of the IEGM signal is determined"); Para. [0069] also mentions segments, which are intervals); determine a slow-moving metric based on the heartbeat data during a first period of time (para. [0075]: " In another embodiment, the implanted device 100 may compute a short-term average value (e.g., taken over a plurality of cycles within the last few minutes) as well as a long-term average value (e.g., taken over a period of weeks, months, etc.)…. The long-term average value accounts for slowly evolving shifts in the ST segment."); determine a fast-moving metric based on the heartbeat data during a second period of time (para. [0075]), the second period of time being less than the first period of time (para. [0075]; weeks and months are longer than minutes); and determine a risk level of a health event for the patient based on the slow-moving metric and the fast-moving metric. (para. [0075]: " In this embodiment, if a short-term average value exceeds a long-term average value by more than a threshold amount (or alternately by more than a percentage of the long-term average value), then ischemia is indicated.").
Regarding claims 2, Gill teaches the system of claim 1 (see above), wherein the processing circuitry is configured to obtain the plurality of heartbeat intervals at a respective particular time of day over a plurality of days (para. [0076]: " In this application, STn and/or .DELTA.STn might be measured every ten minutes with historical baseline values for .DELTA.STn determined at a single point in time (e.g. at implant or at the command of a clinician) or to the long-term average value determined over a relatively long period of time (e.g. over the previous week)."; para. [0096]: "In the above examples, Y may represent all the measurements made since the last follow-up. Preferably, the metric will be recorded periodically by the device so that changes over time can be observed. Ideally, X would be stored for every measurement. More X/Y would be stored periodically, e.g. every day or every week.").
Regarding claim 4, Gill teaches the system of claim 1 (see above), wherein the processing circuitry is further configured to: determine a comparison value (para. [0075]; difference in short-term average value and long-term average value) for each sample point parameter by comparing an absolute value of the difference between the slow-moving average and the fast-moving average for each sample point parameter to a risk threshold (para. [0075]: “ In this embodiment, if a short-term average value exceeds a long-term average value by more than a threshold amount (or alternately by more than a percentage of the long-term average value), then ischemia is indicated.” “The difference” would imply an absolute value since it is a positive integer between numbers.); and determine the risk level of the health event for the patient based on the comparison values for each sample point parameter (para. [0075]: "In this embodiment, if a short-term average value exceeds a long-term average value by more than a threshold amount (or alternately by more than a percentage of the long-term average value), then ischemia is indicated. The long-term average value accounts for slowly evolving shifts in the ST segment."; Additionally, see para. [0066]).
Regarding claim 5, Gill teaches the system of claim 4 (see above), wherein the processing circuitry is further configured to determine the risk level of the health event for the patient based on a number of consecutive parameter points having the respective comparison value above or equal to the comparison threshold. (para. [0079]: "In one embodiment, implanted device 100 might detect ischemia based on a single STn or .DELTA.STn measurement that exceeds a corresponding threshold. It might be required that several (e.g. 3) consecutive measurements exceed threshold. It might be required that the rate of measurements exceeding threshold exceed a second threshold, e.g. at least 3 of 5 consecutive measurements. Alternately, it might be required that a measure of statistical significance (e.g. T-value) between a set of historical baseline measurements and subsequent set of measurements exceed a threshold.").
Regarding claim 6, Gill teaches the system of claim 4 (see above), wherein the processing circuitry is further configured to determine the risk level of the health event for the patient based on an amount of the comparison value. (para. [0094]: "[0094] In one embodiment for example, the degree by which a feature exceeds its threshold for ischemia detection may mapped to a severity/likelihood index which can take values from 1-5 where 1 indicates the threshold for detection was barely exceeded and 5 indicates it was exceeded by at least 100%. Then the burden metric above would keep a count of detections of each severity level (e.g. Xn/Y where n=1-5).").
Regarding claim 8, Gill teaches the system of claim 1 (see above), wherein the health event comprises a health care utilization event (Gill discloses using the device for detecting myocardial ischemia (para. [0008]), which would require hospitalization/surgical intervention and use of a health care facility and personnel).
Regarding claim 10, Gill teaches the system of claim 1 (see above), wherein, to determine the risk level of the health event, the processing circuitry is configured to determine a probability of an occurrence of the health event. (para. [0093]: " The burden metric may include measures of certainty and/or severity of ischemia. This could lead to a multi-dimensional burden metric.").
Regarding claim 12, Gill teaches the system of claim 1 (see above), wherein, to determine the risk level of the health event, the processing circuitry is configured to determine a probability of an occurrence of the health event. (para. [0093]: " The burden metric may include measures of certainty and/or severity of ischemia. This could lead to a multi-dimensional burden metric.").
Regarding claim 14, Gill teaches a computer-readable medium storing instructions that when executed by one or more processors cause the one or more processors to perform the method of claim 13. (para. [0038]: " The aforementioned components may be implemented in hardware as part of the microcontroller 220, or as software/firmware instructions programmed into the device and executed on the microcontroller 220 during certain modes of operation.").
Regarding claim 17, Gill teaches the method of claim 13 (see above), further comprising: determining a comparison value (para. [0075]; difference in short-term average value and long-term average value) for each sample point parameter by comparing an absolute value of the difference between the slow-moving average and the fast-moving average for each sample point parameter to a risk threshold (para. [0075]: “ In this embodiment, if a short-term average value exceeds a long-term average value by more than a threshold amount (or alternately by more than a percentage of the long-term average value), then ischemia is indicated.” “The difference” would imply an absolute value since it is a positive integer between numbers.); and determining the risk level of the health event for the patient based on the comparison values for each sample point parameter (para. [0075]: "In this embodiment, if a short-term average value exceeds a long-term average value by more than a threshold amount (or alternately by more than a percentage of the long-term average value), then ischemia is indicated. The long-term average value accounts for slowly evolving shifts in the ST segment."; Additionally, see para. [0066]).
Regarding claim 18, Gill teaches the method of claim 17 (see above), further comprising: determining the risk level of the health event for the patient based on a number of consecutive parameter points having the respective comparison value above or equal to the comparison threshold. (para. [0079]: "In one embodiment, implanted device 100 might detect ischemia based on a single STn or .DELTA.STn measurement that exceeds a corresponding threshold. It might be required that several (e.g. 3) consecutive measurements exceed threshold. It might be required that the rate of measurements exceeding threshold exceed a second threshold, e.g. at least 3 of 5 consecutive measurements. Alternately, it might be required that a measure of statistical significance (e.g. T-value) between a set of historical baseline measurements and subsequent set of measurements exceed a threshold.").
Regarding claim 19, Gill teaches the method of claim 17 (see above), further comprising: determining the risk level of the health event for the patient based on an amount of the comparison value. (para. [0094]: "[0094] In one embodiment for example, the degree by which a feature exceeds its threshold for ischemia detection may mapped to a severity/likelihood index which can take values from 1-5 where 1 indicates the threshold for detection was barely exceeded and 5 indicates it was exceeded by at least 100%. Then the burden metric above would keep a count of detections of each severity level (e.g. Xn/Y where n=1-5).")
Regarding claims 20, Gill teaches the method of claim 13 (see above), wherein the plurality of heartbeat intervals are obtained at a respective particular time of day over a plurality of days (para. [0076]: " In this application, STn and/or .DELTA.STn might be measured every ten minutes with historical baseline values for .DELTA.STn determined at a single point in time (e.g. at implant or at the command of a clinician) or to the long-term average value determined over a relatively long period of time (e.g. over the previous week)."; para. [0096]: "In the above examples, Y may represent all the measurements made since the last follow-up. Preferably, the metric will be recorded periodically by the device so that changes over time can be observed. Ideally, X would be stored for every measurement. More X/Y would be stored periodically, e.g. every day or every week.").
Claim Rejections - 35 USC § 103
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.
Claims 3 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Gill et al. (US 20110004111 A1, "Gill") in view of Zhang et al. (US 20170001005 A1, "Zhang").
Regarding claims 3 and 16, Gill teaches the system of claim 1 and the method of claim 13 (see 102 rejections above). However, Gill does not expressly teach normalizing the plurality of sampled points for each respective heartbeat interval of the plurality of intervals.
Zhang, in the same field of monitoring cardiac health events, discloses a system and method for heart event detection. Zhang discloses normalizing the plurality of sampled points for each respective heartbeat interval of the plurality of intervals. (para. [0075]: "In an example, a signal can include a normalized difference, such as a difference between an average of the cardiac interval information in the long-term window 610 and an average of the cardiac interval information in the short-term window 620, such as normalized by an average of the cardiac interval information in the long-term window 610, or by a baseline value.").
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system (specifically the processor) and method of Gill to include the normalizing technique, as disclosed by Zhang. One of ordinary skill in the art would recognize that the techniques of Zhang would improve prognoses and patient outcomes while avoiding unnecessary medical intervention and reducing healthcare costs. Further, by there would be a reasonable expectation of success in determining health event risks by normalizing the sample points for heart beat intervals, as Zhang discloses using the normalization technique for this purpose. Therefore, it would have been obvious to include the technique of Zhang in the system and method of Gill.
Claims 7 and 9 are rejected under 35 U.S.C. 103 as being unpatentable over Gill et al. (US 20110004111 A1, "Gill") in view of Bouguerra et al. (US 20200093388 A1, “Bouguerra”).
Regarding claim 7, Gill teaches the system of claim 1 (see 102 rejection above). However, Gill does not teach wherein the health event comprises a stroke.
Bouguerra, in the same field of endeavor of monitoring and predicting health events, discloses a system and method for detecting atrial fibrillation events. Bouguerra discloses wherein the health event comprises stroke. (para. [0001]: "AF has been associated with cardiac disease as well as stroke."; para. [0044]: ". One type of risk event listed in the report section 314 is the pause events in pause event section 342, which represent periods in which the heart does not generate the requisite electrical impulses for at least a brief period (e.g., 2 seconds or more). Pause events can cause a temporary lack of blood flow that may increase the likelihood of the formation of blood clots (thrombi) and may lead to ischemic stroke.").
It would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Gill to include stroke detection, as disclosed by Bouguerra. One of ordinary skill in the art would recognize that stroke can be caused by ischemia, and that Bouguerra discloses how monitoring cardiac events can be indicative of ischemic stroke. It would have been obvious for one of ordinary skill in the art that the system of Gill could be modified for detection of strokes since it already detects a variation of ischemia (myocardial). Since Bouguerra suggests using a similar system to detect strokes, and that cardiac ischemia is indicative of strokes, it would have been obvious to use the system of Gill to detect strokes.
Regarding claim 9, Gill teaches the system of claim 1 (see 102 rejection above). Although Gill does not explicitly disclose detecting sudden cardiac arrest, one of ordinary skill in the art would recognize that myocardial ischemia is directly related to cardiac arrest as a cause of cardiac arrest. Therefore, it would have been obvious to one of ordinary skill that if the device of skill determines myocardial ischemia, it is also determining cardiac arrest.
Additionally, Bouguerra discloses wherein the health event comprises sudden cardiac arrest (para. [0005]: “By determining whether the one or more patient-initiated events are concurrent with detected cardiac arrhythmia, the system may distinguish between neurally mediated disease and cardiac disease. For example, fainting (syncope) can be neurally mediated or caused by cardiac arrhythmia, such as a cardiac pause event or a ventricular fibrillation (VF) event. Cardiac pause (also known as sinoatrial arrest, sinus arrest, or sinus pause) occurs when the sinoatrial node of the heart transiently ceases to generate the electrical impulses that normally stimulate the cardiac tissues to contract.”).
It would have been obvious for one of ordinary skill in the art to configure the device of Gill to detect cardiac arrest, as disclosed by Bouguerra. One of ordinary skill would recognize that detecting cardiac arrest would be useful in improving prognosis and early detection. Since Bougerra discloses that cardiac arrests can be detecting with ECG health monitoring, it would have been obvious to configure Gill’s system to also detect cardiac arrests as a health event.
Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over Gill et al. (US 20110004111 A1, "Gill") in view of Selker et al. (US 20170196505 A1, "Selker").
Regarding claim 11, Gill teaches the system of claim 1 (see above). However, Gill does not expressly teach wherein the risk level comprises a risk that the health event will occur within a predetermined time period.
Selker, in the same field of endeavor of monitoring physiological parameters to predict or detect health events, discloses a predictive instrument for administration of cardiac metabolic support. Selker discloses wherein the risk level comprises a risk that the health event will occur within a predetermined time period. (para. [0003]: " Other prior uses of predictive instruments have focused on prediction of the patient's future clinical outcomes, such as a probability of death within 30 days, or a probability of cardiac arrest within the next two days.").
It would have been obvious for one of ordinary skill in the art to modify the device of Gill to include a risk level in a predetermined time period. One of ordinary skill would recognize that predicting events within a time period is known in the art, as Selker discloses that there are prior uses of predictive instruments for indicating the probability of a medical condition, such as ischemia or arrest, in a predetermined time period (see Selker para. [0003]). It would have been obvious to include the predetermined time periods since Selker’s system also uses predetermined time periods for detecting adverse events.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Chauha et al. (US 20180125385 A1) and Snell et al. (US 7647104 B1) are pertinent to independent claims 1, 13, and 15.
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/O.L.M./Examiner, Art Unit 3796
/ALLEN PORTER/Primary Examiner, Art Unit 3796
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