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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 08 October 2025 has been entered. Claims 1 and 23 are currently amended. Claim 2 is canceled, and claim 30 is new. Claims 1, 3, 5-11, 13-16, 20, 22-23, and 25-30 are pending in the application.
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 1, 3, 5, 8, 13-16, 20, 22-23, and 25-29 are rejected under 35 U.S.C. 103 as being unpatentable over Atsmon (WO 03103484) in view of Srivastava (US PGPub No. 2015/0066006), and further in view of Single et al. (US PGPub No. 2014/0194772), hereinafter Single.
Regarding claims 1 and 23, Atsmon teaches a method and system for detecting neural activity in a nerve (Fig. 1 and page 3, lines 22-23: “a method and apparatus for measuring in the non-stimulated activity of a plurality of sensory nerve fibers”), comprising:
a first electrode and a second electrode (Fig. 1: first and second electrodes 108);
and a processing apparatus (Fig. 1: pattern recognition device 118) configured to receive a first electrical signal from the first electrode and a second electrical signal from a second electrode, wherein the second electrode is spaced from the first electrode along the nerve (Fig. 1: second electrode 108 spaced from first electrode 108 along nerve 104; page 9, lines 7-10: “a method and apparatus for measuring the nerve signal on at least two sensor in proximity to the nerve fiber, the sensors are spaced apart such that the measurements can be correlated […] The present invention also provides electrodes and a processing unit in order to measure the action potentials progressing through a nerve fiber along its pathway and enable to measure the level of nerve activity”);
apply a correlation analysis between the first and second electrical signals, including for at least one non-zero lag time, to obtain correlation data (page 9, lines 10-12: “The correlation between the two measured signals in a time difference reflecting a predetermined velocity range and then summing all the correlation value points measured and calculated”);
and detect, from an analysis of the correlation data to locate a correlation between the first and second signals at the at least one non-zero lag time, at least one neural signal indicative of neural activity in the nerve (Figs. 3A-5C; page 9, line 29 – page 10, line 3: “placing, relatively close two or more electrodes and measuring the traveling signals using multiple electrodes along the nerve pathway. The use of a correlation function between the detected signal of relatively close electrodes may overcome the lower amplitude of a lower conduction velocity nerve signals and make such signals detectable;” page 14, lines 15-29: “There is a time shift 421 between the two detected main peaks from electrodes 401 and 403. […] Another possible manner for calculating the shift is to detect peaks 410 and 420 and measure the time difference between the said peaks. Another possible way is to calculate the cross correlation between the signals in Fig. 4B and Fig. 4C. The maximum peak of the cross correlation function versus time shift appears at the time shift 421;” and claim 13: “determining and storing the signal associated with sensory nerve signals from the signals filtered by cross correlating between two predetermined signal; and calculating the activity of the signal associated with sensory nerve signals through the use of an operator for determining that a sensory nerve action potential is present;” examiner interprets determining the presence of a sensory nerve action potential as detecting a neural signal indicative of neural activity in the nerve).
Atsmon does not explicitly teach wherein the first electrical signal is received from a first pair of electrodes and the second electrical signal is received from a second pair of electrodes. However, in an analogous art, Srivastava teaches a method of measuring neural activity using bipolar pairs of electrodes (par. 0038: “pairs of the energy delivery element 124 can be configured to provide multi-polar (e.g., bipolar) recording of nerve activity proximate to a target site in a vessel and/or deliver bipolar energy to nerves proximate to the target site. The energy delivery elements 124 can be paired in various different configurations, such as the first and second energy delivery elements 124a and 124b, the first and third energy delivery elements 124a and 124c, the first and fourth energy delivery elements 124a and 124d, the second and fourth energy delivery elements 124b and 124d, and/or other suitable pairs of energy delivery elements 124 depending on the number of energy delivery elements”), which has the advantage of reducing noise relative to recordings obtained with single electrodes (par. 0038: “Multi-polar recording is expected to reduce noise that would otherwise be collected via a single electrode because differential amplification of multi-polar recordings can selectively amplify the difference in the signal (the nerve action potential, i.e., the electrical activity developed in a nerve cell during activity), while suppressing the common signal (e.g., the background noise)”). It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the method and system of Atsmon by using bipolar electrodes (that is, pairs of electrodes) at each recording site, as suggested by Srivastava, in order to reduce noise relative to recordings obtained with single electrodes, as taught by Srivastava.
Atsmon teaches wherein the first or second electrical signal may have a low amplitude that is difficult to detect (page 9, lines 24-27: “the sum of the signals in a low conduction velocity nerve fiber has a lower amplitude than the compound signal in a higher conduction velocity nerve fiber, due to out of phase's summation. The low amplitude turns such signals to be undetectable in current methods”), but the combination does not explicitly teach wherein the correlation analysis is applied over a period of one second or longer, and wherein the first or second electrical signal has a negative signal-to-noise ratio.
However, in an analogous art, Single teaches a method and system for detecting neural onset responses from a signal with negative signal-to-noise ratio (Figs. 10a, 11a, 12a; par. 0045: “in both the single-shot and 200-shot approaches the aligned mean trace makes it possible to find responses which otherwise would be indistinguishable from the sources of background noise”) using correlation analysis over an extended period (par. 0044: “FIGS. 10-12 show data obtained by: application of 200 consecutive stimuli at the nominated amplitude”), which makes it possible to detect signals resulting from a lower stimulus level (par. 0045: “For the recordings over 200 shots in FIGS. 10-12, the aligned mean trace elicits the onset of neural response at an even lower stimulus level”). It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the method and system of the combined reference to apply the correlation analysis over an extended period for a signal with negative signal-to-noise ratio, as suggested by Single, in order to detect signals at a lower stimulus level, as taught by Single. It would further have been obvious to select a period of one second or longer for the correlation analysis, since Single teaches that the length of the correlation analysis is a result effective variable (namely, that a longer recording results in better detection at lower stimulus levels), and since it has been held that discovering an optimum value of a result effective variable involves only routine skill in the art. In re Boesch, 617 F.2d 272, 205 USPQ 215 (CCPA 1980).
Regarding claim 3, the combination teaches the method of claim 1 as described previously. Atsmon further teaches wherein the at least one non-zero lag time is preselected based on at least one of: a distance between the first pair of electrodes and the second pair of electrodes; and a fiber type of the nerve (Fig. 3B and page 6, lines 15-19: “calculating the expected time difference for a signal to arrive in a predetermined velocity range wherein the maximal time difference is equal to the time difference divided by the maximum predetermined speed range for the signal while the minimal time difference is equal to the time difference divided by the minimum predetermined speed range for the signal;” page 9, lines 2-5: “a method and apparatus for detecting and measuring electrical activity of nerve signals in nerve fibers having a slow or a predetermined conduction velocity, for example C nerve fibers in a human being or an animal”).
Regarding claim 5, the combination teaches the method of claim 1 as described previously. Atsmon further teaches wherein the correlation analysis is applied for a plurality of non-zero lag times (Fig. 3B: step 304; page 13, lines 12-18: “the maximal time difference dtmax is equal to dx v.sup.'min while the minimal time difference dtmin is equal to dx/vmax. […] In step 304 the cross correlation (X) between measurements si and s2 is calculated. The cross correlation (X) is calculated for dtmin and dtmax”).
Regarding claim 8, the combination teaches the method of claim 5 as described previously. Atsmon further teaches further comprising categorising a fibre type of the nerve based on the magnitude of a lag time at which the neural signal is detected (page 11, lines 25-28: “a pattern recognition device determines the relevant signal associated with sensory nerve signals from the signals filtered. For example, the pattern recognition step determines which signals are C nerve signals or A nerve signals and the like;” see also Figs. 5A-5C and page 15, lines 3-17: “Fig. 5A, presents a schematic drawing of an example of a C nerve signal, in accordance with the present invention. The width 501 of the signal is defined as the time difference between the two closest points of the same signal having a value about above the base (resting potential); Fig. 5B, presents a schematic drawing of an example of an A nerve signal, in accordance with the present invention. The width of the signal in Fig. 5B is marked 502. Width 501 is larger than width 502 […] Person skilled in the art will appreciate that filtering out C nerve fiber action potentials can be done by choosing the action potentials that create a maximal cross correlation with a predetermined C nerve action potential”).
Regarding claims 13 and 28, the combination teaches the method of claim 1 and system of claim 23 as described previously. Atsmon further teaches wherein the neural signal corresponds to one or more distinct regions of correlation between the first and second signals at the at least one non-zero lag time (Fig. 3A: step 284 and page 12, lines 27-30: “In step 284 the cross correlation between the signals measured from the at least two or more close electrodes is calculated. The area of the cross correlation in the range which corresponds to the interested nerve fiber conduction average velocity is calculated”).
Regarding claims 14 and 29, the combination teaches the method of claim 13 and system of claim 28 as described previously. Atsmon further teaches wherein the one or more distinct regions of correlation in the correlation data at the at least one non-zero lag time include one or more peaks in correlation between the first and second signals, the peaks being centered at the at least one non-zero lag time (Figs. 4B-4C and page 14, lines 27-29: “calculate the cross correlation between the signals in Fig. 4B and Fig. 4C. The maximum peak of the cross correlation function versus time shift appears at the time shift 421”).
Regarding claim 15, the combination teaches the method of claim 1 as described previously. Atsmon further teaches wherein each of the first and second pairs of electrodes are located outside a perineurium of the nerve (Fig. 1: electrodes 108 located outside nerve 104). Examiner interprets electrodes located on the body surface, as taught by Atsmon, to be located outside a perineurium of a nerve, as broadly as claimed.
Regarding claim 16, the combination teaches the method of claim 1 as described previously. Atsmon further teaches wherein: the nerve is a peripheral nerve; or the nerve is an autonomic nervous system nerve; or the nerve is myelinated; or the nerve is non-myelinated (Fig. 1: peripheral nerve 104).
Regarding claims 20 and 22, the combination teaches the method of claim 1 as described previously. Atsmon further teaches a processing apparatus configured to carry out the method of claim 1, and a non-transitory computer-readable memory medium comprising instructions to cause a processing apparatus to perform the method of claim 1 (Fig. 1: pattern recognition device 118; claim 1: “a pattern recognition device for correlating the measurements in a time difference or time difference range reflecting a predetermined velocity range”).
Regarding claims 25-26, the combination teaches the system of claim 23 as described previously. As the combination modifies the system of Atsmon by replacing each recording electrode (Fig. 1: electrodes 108) with a pair of electrodes, as suggested by Srivastava, the combination also teaches further comprising an electrode array (examiner interprets the first and second pairs of electrodes positioned along the nerve to be an electrode array, as broadly as claimed), the electrode array comprising the first pair of electrodes and the second pair of electrodes, wherein the first two electrodes are positioned proximate each other along the electrode array, the two second electrodes are positioned proximate each other along the electrode array, and the first pair of electrodes is spaced from the second pair of electrodes along the electrode array.
Regarding claim 27, the combination teaches the system of claim 26 as described previously. Atsmon teaches wherein the longitude distance between two adjacent sensors along a nerve is calculated so as to enable the first and second electrical signals to be correlated (page 13, lines 6-9: “the variable dx is calculated as the longitude distance between the at least two sensors in close proximity along a nerve fiber bundle direction. The variable dx should be such to enable the expected signal received in the two sensors to be correlated”), but the combined reference does not explicitly teach wherein the distance between electrode pairs is greater than the distance between the two electrodes within one pair. However, the specific distances between electrodes would have been an obvious matter of design choice to one having ordinary skill in the art before the effective filing date of the claimed invention, since Atsmon teaches that the distance between sensors is a variable to be chosen according to the particular application, and Applicant has not disclosed that the specific ratio of distance between electrode pairs to the distance between the two electrodes within one pair solves any stated problem or is for any particular purpose, and it appears that the invention would perform equally as well with any ratio determined by one of ordinary skill in the art to produce first and second electrical signals capable of being correlated.
Claims 6-7 and 30 are rejected under 35 U.S.C. 103 as being unpatentable over Atsmon in view of Srivastava and Single and further in view of Eder et al. (US PGPub No. 2014/0249647), hereinafter Eder ‘647.
Atsmon in view of Srivastava and Single teaches the method of claim 5 as described previously but does not explicitly teach wherein the plurality of non-zero lag times includes negative and positive sign lag times, or further comprising categorizing the neural signal as afferent or efferent based on a sign of a lag time at which the neural signal is detected, wherein afferent and efferent signals are detected simultaneously.
However, in an analogous art, Eder ‘647 teaches a method of applying correlation analysis to recorded neural signals (par. 0027: “directly incorporating the delay and sum operations into a cross correlation operation, where the cross correlation between the two un-delayed bipolar channels is calculated with a time lag corresponding to the desired delay between the channels”) including categorizing the neural signal as afferent or efferent based on a sign of a lag time at which the neural signal is detected and detecting afferent and efferent signals simultaneously in order to separate them (Fig. 5 and par. 0043: “the present invention provides an implantable system for sensing and recording of nerve signals in which the signals can be separated by their propagation direction along the longitudinal nerve axis, by which it becomes possible to discriminate between sensory or motor related activity;” par. 0045: “Here, electrode 1a is closer to the spinal cord than electrode 1c, which means that action potentials traveling from electrode 1a to electrode 1c are `efferent` (motor commands), and action potentials traveling the opposite directions are `afferent` (sensory signals);” examiner notes that one of ordinary skill in the art would understand that action potentials traveling in opposite directions would generate signals with opposite signs in the disclosed recording configuration).
Eder ‘647 further teaches that discriminating between afferent and efferent signals is useful because only either type of signal is usually essential for a particular application, and the other constitutes an undesired interference signal (par. 0043). It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the method of the combined reference to include negative and positive sign lag times and further to categorize the neural signal as afferent or efferent based on a sign of a lag time while detecting afferent and efferent signals simultaneously, as suggested by Eder ‘647, because Eder ‘647 teaches the usefulness of discriminating between afferent and efferent signals in that one of the types of signal may constitute an undesired interference signal.
Claims 9-11 are rejected under 35 U.S.C. 103 as being unpatentable over Atsmon in view of Srivastava and Single and further in view of Eder et al. (US PGPub No. 2014/0249646), hereinafter Eder ‘646.
Atsmon in view of Srivastava and Single teaches the method of claim 1 as described previously. The combination does not explicitly teach applying the correlation analysis for a zero lag time to obtain the correlation data, or detecting, from the correlation data, at least one alternative signal indicative of electrical activity, the alternative signal corresponding to positive correlation between the first and second signals at a substantially zero lag time, wherein the alternative signal is indicative of muscle movement; or the alternative signal is an evoked neural response to stimulation.
However, Eder ‘646 teaches that bioelectric interference (that is, an alternative signal indicative of muscle movement) is instantaneously present on adjacent bipolar channels and therefore has positive correlation across the bipolar channels at a substantially zero lag time (Fig. 3 and par. 0020: “The interference is instantaneously present on all electrodes, and is therefore positively correlated across the individual bipolar channels. The nerve signals are however negatively correlated, since two adjacent bipolar channels are presented with a rising and a falling phase of the same action potential. This makes it possible to create a model of the interference by adding two bipolar channels together, therefore increasing the interferential component while nullifying the--ideally equal--neural component. The interference model is thus independent from the signal and can be applied to the adaptive filter. The reference signal can therefore be derived by adding the signals from two or more bipolar channels”). Eder ‘646 teaches that creating a model of the interference allows for filtering the interference out of the recorded signal (par. 0017: “Once an independent model of the interference can be obtained such that it is uncorrelated to the signal of interest, it can be applied to an adaptive filter before subtracting the filter output from the primary signal”). It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the method of the combined reference by applying a correlation analysis and detecting a signal indicative of electrical activity at a substantially zero lag time, the signal being indicative of muscle movement, as suggested by Eder ‘646, in order to create a model of the interference and filter the interference out of the recorded signal, as taught by Eder ‘646.
Response to Arguments
Applicant’s arguments, filed 08 October 2025, with respect to the rejection(s) of claim(s) 1 and 23 under 35 U.S.C. 103 have been fully considered and are persuasive. Therefore, in light of the amendments to the claims, the previous rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Single. As described previously, Single teaches an extended period of time for applying correlation analysis to a neural signal with negative signal-to-noise ratio.
Conclusion
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/LINDA C DVORAK/Primary Examiner, Art Unit 3794
/D.E.L./Examiner, Art Unit 3794