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 .
DETAILED ACTION
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-11 and 13-17 are rejected under 35 U.S.C. 103 as being unpatentable over Ghosh et al (US 2020/0352470).
Regarding claim 1, Ghosh discloses a method for generating an electrophysiological parameter, the method comprising:
Gosh discloses descriptors comprising an atrial sensing channel 87 and a ventricular sensing channel 89. A selected subset comprises either channel 87 or channel 89. External electrodes 112 are configured to be wrapped around the torso of a patient 114. The signals sensed by electrodes 112 comprise channels of data, see paragraph [0049]. Gosh teaches selecting subsets of electrophysiological descriptors from predefined electrophysiological descriptors, see paragraph [ 0049]. The signal sensed in atrial channel 87 or ventricular sensing channel 89 comprises a signal type, ie, cardiac. A signal marker comprises a selected atrial or ventricular signal. Gosh discloses statistical modalities comprising standard deviation of activation times, average left ventricular or thoracic surrogate electrical activation times and a difference between average left surrogate and average right surrogate activation times. These surrogate activation times are related to the sensed signals sensed at electrodes 112 for the sensed atrial channel 87 and sensed ventricular channel 89. This follows from Gosh disclosing the electrodes 112 monitor electrical signals representative of measured surrogate cardiac electrical activation times representative of the patient’s heart. See paragraph [0049]. Clearly, Gosh discloses marking a signal type, the atrial channel 87, which is a subset of both the atrial channel and the ventricular channel, and preforming a statistical modality comprising at least a standard deviation of activation time, see paragraph [0037]. Selecting a subset of first electrophysiological descriptors from a set of first predefined electrophysiological descriptors from electrodes 112, according to an input parameter defining a measurement context, each first electrophysiological descriptor of the subset being associated with at least one channel, a signal type, a signal marker and a statistical modality for calculation; at least one first descriptor of the subset being associated with a statistical modality different to that of another first descriptor of the subset and a signal marker different to that of the other first descriptor, see paragraph [0052];
arranging a plurality of surface electrodes on a patient's body, see Fig. 3;
recording of a plurality of cardiac electrical activities defining said channels, each channel being obtained by the recordings of at least two electrodes, see paragraph [0055];
estimating the set of electrophysiological descriptors of the subset, each electrophysiological descriptor being calculated from the statistical modality that is applied to the signal marker of the acquired signal according to the signal type on a selected channel associated with said electrophysiological descriptor, see paragraph [0066];
comparing the value of the set of electrophysiological descriptors with at least one threshold value specific to the set of electrophysiological descriptors, said at least one threshold value being defined by a statistical distribution comprising at least a mean posterior activation time or MPAT of said descriptors of a set of patients of a reference group, see paragraphs [0071] and [0072], and
Ghosh does not disclose calculating a score defining an electrophysiological parameter as a function of the exceeding of the at least one threshold value.
Ghosh teaches: cardiac cycles may be scored and ranked 200 based one or more metrics generated thereon. For example, peak times, maximum amplitude, minimum amplitudes, amplitude sums of all valid electrode signals, various intervals such as R-wave to R-wave interval, etc. with respect to various fiducial points within electrical activity may be determined for each cardiac cycle, see paragraph [0080].
One of ordinary skill in the art would have found it obvious to calculate a score defining an electrophysiological parameter as a function of the exceeding of the at least one threshold value because Ghosh suggests removing cycles having a score less than scoring threshold, see paragraphs [0070] and [0071]. To calculate a score defining an electrophysiological parameter as a function of exceeding a threshold is equivalent to determining whether a posterior electrode, or activation monitored by the posterior electrode, constitutes early activation, the activation time being compared to an early-activation threshold. A comparison is a process that does not require undue experimentation and Ghosh provides a similar example in discriminating a P-wave or R-wave from background electrical noise, the sensing circuit compares processed signals to a threshold which is similar to calculating a score that is representative of a patient’s cardiac activity, by comparing values with a control population, see paragraph [0091].
Regarding claim 2, Ghosh discloses the comparing is performed by comparing the value of the set of descriptors with the threshold value defined by a statistical distribution comprising medians, modes, averages, (see paragraph [0044]) of said descriptors of the set of patients of the reference group of dimension equal to the number of descriptors of the subset, see paragraphs [0071] and [0072].
Regarding claim 3, Ghosh discloses the comparing is performed by comparing the value of each electrophysiological descriptor with at least one threshold value specific to said electrophysiological descriptor, said at least one threshold value comprising maximum or minimum value, (see paragraph [0044]) being defined by a statistical distribution of said descriptor of a set of patients of the reference group, and calculating the score defining the electrophysiological parameter is performed by incrementing said score each time an electrophysiological descriptor exceeds the at least one threshold value specific to it, see paragraphs [0071] and [0072].
Regarding claim 4, Ghosh discloses the subset comprises at least one geographical descriptor comprising locations on the surface of the torso of the patient 114 which is associated with several channels and several geographical groups, see paragraph [0056], each geographical group being formed by a central channel and the at least four channels adjacent to the central channel, the value of the electrophysiological descriptor being determined, see Fig. 3:
by comparing the value, for each geographical group, of the measurement of each channel according to the signal type and the signal marker selected with at least one geographical threshold value specific to said electrophysiological descriptor and said channel;
by counting the number of geographical groups for which the value of at least three channels exceeds the geographical threshold value that is specific to it, see paragraphs [0046] and [0047].
Regarding claim 5, Ghosh discloses the input parameter defining the measurement context defines a subset of characteristic descriptors:
of a given cardiac pathology which determines the degree of posterior left bundle branch engagement, see paragraph [0053].
Regarding claim 6, Ghosh discloses each first electrophysiological descriptor of the subset is associated with at least one channel of a predefined area of the patient's body 114 from a set of predefined areas collected using electrode apparatus 110 and in that wherein for each electrophysiological descriptor, the predefined area on the patient's body is chosen from:
an upper right area of the torso;
an upper left area of the torso;
a lower right area of the torso;
a lower left area of the torso; and
an entire torso of the patient, see Fig. 3.
Regarding claim 7, Ghosh discloses each electrophysiological descriptor, the signal type analyzed is chosen from:
a vertical bipolar signal taken between two electrodes of the given area where 12 to 50 electrodes are positioned, one of the two electrodes being offset along a vertical line leading from the feet to the head of the patient with respect to the other electrode, see paragraph [0051]
.
Regarding claim 8, Ghosh discloses at least one electrophysiological descriptor, the heterogeneity signal marker is the measurement of the voltage of an averaged signal, see paragraph [0067].
Regarding claim 9, Ghosh teaches the control circuit 80 may control various parameters of the electrical stimulus delivered by the therapy delivery module 84 such as, frequency, see paragraph [0120]. One of ordinary skill in the art would have found it obvious to provide at least one electrophysiological descriptor, where the marker is the measurement, on the averaged and filtered signal between 40 and 250 Hertz, of the duration of depolarization of the ventricles (QRS) or fragmentation of the signal during depolarization of the ventricles because the range between 40 and 250 Hertz is within the range for the stimulation of the ventricles for the pacing therapy provided in the Ghosh device.
Regarding claim 10, Ghosh discloses at least one electrophysiological descriptor, the signal marker is the measurement on the discrete wavelet decomposition of the signal:
of the energy of the sum of the wavelets of the multiphasic waveforms, see paragraph [0090]
or
of the number of local minima.
Regarding claim 11, Ghosh discloses at least one electrophysiological descriptor, the signal marker is the measurement on the continuous wavelet decomposition of the signal of the number of chains of local maxima of the multiphasic waveforms, see paragraph [0080].
Regarding claim 13, Ghosh discloses for at least one electrophysiological descriptor, the statistical modality is chosen from:
the standard deviation of the measured values of the signal on each electrode of the predefined area, see paragraph [0036]
.
Regarding claim 14, Ghosh discloses a device for generating an electrophysiological parameter, the device comprising:
a plurality of surface electrodes 112 configured to be deposited on a patient's body and to measure an electrical potential of the surface of the patient's body, each surface electrode defining a channel, see paragraph [0049];
a means of measuring the signal of each channel comprising computing device 160 and torso-surface potential signals sensed by electrodes 112, see paragraph [0052];
a calculation means comprising computing apparatus 140 configured to:
select a subset of descriptors channel 87 or channel 89 from a set of predefined descriptors according to an input parameter defining a measurement context, each electrophysiological descriptor of the subset being associated with at least one channel, a signal type, a signal marker and a statistical modality for calculation from electrodes 112; at least one descriptor of the subset being associated with a statistical modality comprising at least a mean posterior activation time or MPAT different to that of a second descriptor, acoustic sensors 120 of the subset and a signal marker different to that of the second descriptor, see paragraph [0051];
record a plurality of cardiac electrical activities defining said channels, each channel being obtained by the recordings of at least two electrodes, see paragraph [0052];
estimate the set of electrophysiological descriptors of the subset, each electrophysiological descriptor being calculated from the statistical modality that is applied to the signal marker of the acquired signal according to the signal type on a selected channel associated with said electrophysiological descriptor, see paragraph [0067];
compare the value of the set of electrophysiological descriptors with at least one threshold value specific to the set of electrophysiological descriptors, said at least one threshold value being defined by a statistical distribution comprising at least a mean posterior activation time or MPAT of said descriptors of a set of patients, see paragraphs [0071] and [0072].
Gosh discloses descriptors comprising an atrial sensing channel 87 and a ventricular sensing channel 89. A selected subset comprises either channel 87 or channel 89. External electrodes 112 are configured to be wrapped around the torso of a patient 114. The signals sensed by electrodes 112 comprise channels of data, see paragraph [0049]. Gosh teaches selecting subsets of electrophysiological descriptors from predefined electrophysiological descriptors, see paragraph [0049]. Gosh teaches selecting subsets of electrophysiological descriptors from predefined electrophysiological descriptors, see paragraph [ 0049]. The signal sensed in atrial channel 87 or ventricular sensing channel 89 comprises a signal type, ie, cardiac. A signal marker comprises a selected atrial or ventricular signal. Gosh discloses statistical modalities comprising standard deviation of activation times, average left ventricular or thoracic surrogate electrical activation times and a difference between average left surrogate and average right surrogate activation times. These surrogate activation times are related to the sensed signals sensed at electrodes 112 for the sensed atrial channel 87 and sensed ventricular channel 89. This follows from Gosh disclosing the electrodes 112 monitor electrical signals representative of measured surrogate cardiac electrical activation times representative of the patient’s heart. See paragraph [0049]. Clearly, Gosh discloses marking a signal type, the atrial channel 87, which is a subset of both the atrial channel and the ventricular channel, and preforming a statistical modality comprising at least a standard deviation of activation time, see paragraph [0037].
Ghosh does not disclose calculating a score defining an electrophysiological parameter as a function of the exceeding of the at least one threshold value defined by the statistical distribution MPAT.
Gosh suggests the display apparatus 130, 170 may include any apparatus capable of displaying information to a user, such as a graphical user interface 132, 172 including electrode status information and various rankings of cardiac therapy scenarios, see paragraph [0039].
The evaluation method 200 evaluates posterior left bundle branch engagement and cardiac therapy adjustment. The method 200 includes measuring electrical activity from external electrodes 112 and generating surrogate activation times.Ghosh teaches: cardiac cycles may be scored and ranked 200 based one or more metrics generated thereon. For example, peak times, maximum amplitude, minimum amplitudes, amplitude sums of all valid electrode signals, various intervals such as R-wave to R-wave interval, etc. with respect to various fiducial points within electrical activity may be determined for each cardiac cycle, see paragraphs [0036] and [0080].
Gosh teaches if the MPAT is less than or equal to 30 milliseconds, then it may be determined that the left bundle branch is sufficiently engaged. Further, if the MPAT is greater than 30 milliseconds and less than 50 milliseconds, then it may be determined that the left bundle branch is partially engaged. Still further, for example, if the MPAT is greater than or equal to 50 milliseconds, then it may be determined that the left bundle branch is insufficiently engaged, see paragraph [0072]. Gosh discloses these ranges are only example ranges.
Gosh teaches selected pacing settings for the cardiac conduction therapy may, in some embodiments, be referred to as the “optimal” pacing settings as, for example, the pacing settings providing the most complete posterior left bundle branch engagement may be selected. It is to be understood, however, the pacing settings providing the most complete posterior left bundle branch engagement may not necessarily be the pacing settings that would be selected as considerations other than posterior left bundle branch engagement exist such as, for example, battery life of the device performing the therapy. Thus, the selected, or optimal, pacing settings for the cardiac pacing therapy may represent a balance of many factors including posterior left bundle branch engagement, see paragraph [0082].
One of ordinary skill in the art would have found it obvious to calculate a score defining an electrophysiological parameter as a function of the exceeding of the at least one threshold value defined by the statistical distribution MPAT because Ghosh suggests removing cycles having a score less than scoring threshold for engagement, see step 200 in Fig. 4. To calculate a score defining an electrophysiological parameter as a function of exceeding a threshold is process that does not require undue experimentation and Ghosh provides a similar example in discriminating a P-wave or R-wave from background electrical noise, see paragraph [0116].
Regarding claim 15, Ghosh teaches acoustic sensors 120 may be integrated in an elastic band 113, see paragraph [0049]. One of ordinary skill in the art would have found it obvious to substitute a plethysmography belt for the strap 113 or vest 114 because the belt provides a similar function of holding an acoustic sensor next to the patient for detecting a patient's respiration phases.
Regarding claim 16, Ghosh discloses a device for generating an electrophysiological parameters comprising a plurality of electrodes 112, a receiver of signals measured by the electrodes 116, a memory for recording the measured data and a calculator making it possible to perform operations and processings on the measured data 140, said device comprising means configured to implement the method of claim 1.
Regarding claim 17, Ghosh teaches acoustic sensors 120 may be integrated in an elastic band 113, see paragraph [0049]. One of ordinary skill in the art would have found it obvious to substitute a plethysmography belt for the strap 113 or vest 114 because the belt provides a similar function of holding an acoustic sensor next to the patient for detecting patient sound signals for detecting a patient's respiration phases.
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over Ghosh et al (US 2020/0352470) in view of Bonner et al (US 2020/0155845).
Regarding claim 12, Ghosh teaches if a second dart electrode assembly 12 is employed, its length may be unequal to the expected pacing site depth and may be configured to act as an indifferent electrode for delivering of pacing energy to and/or sensing signals from the tissue.
Bonner teaches heart sound S1 generally has a duration of about 150 ms and a frequency on the order of about 20 to 250 Hz, see paragraph [0127].
One of ordinary skill in the art would have found it obvious to combine the teaching of Bonner with the system and method of Ghosh for at least one descriptor where the signal marker is the measurement on the wavelet taken between 128 and 256 Hertz of the signal of the number of areas of reduced amplitude because Ghosh suggests combining acoustic sensors 120 with electrodes 112 for sensing acoustic energy and electrical signals from a pacing site associated with the vest 114.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Werneth et al (US 10,828,011) disclose a related cardiac surface electrode device with electrodes integrated into a piece of clothing worn by a patient. Chen et al (US 9,538,930) disclose an ECG waveform measuring system and method comprising different frequency domain waveforms.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to George Manuel whose telephone number is (571) 272-4952.
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/George Manuel/
Primary Examiner
Art Unit: 3792
1/27/2026