The present invention relates generally to medical device systems, and more particularly to pulse generator systems operable to measure an Evoked Compound Action Potential (ECAP) that can be used to adjust stimulation therapy.
Implantable stimulation devices deliver electrical stimuli to nerves and tissues for the therapy of various biological disorders, such as pacemakers to treat cardiac arrhythmia, defibrillators to treat cardiac fibrillation, cochlear stimulators to treat deafness, retinal stimulators to treat blindness, muscle stimulators to produce coordinated limb movement, spinal cord stimulators to treat chronic pain, cortical and Deep Brain Stimulators (DBS) to treat different neurological conditions including movement disorders, psychological disorders, migraine disorders, and epilepsy among others, and other neural stimulators to treat urinary incontinence, sleep apnea, shoulder subluxation, etc. The description that follows will generally focus on the use of the invention within a Spinal Cord Stimulation (SCS) system, such as that disclosed in U.S. Pat. No. 6,516,227. However, the present invention may find applicability with any Implantable Medical Device (IPG) or in any IPG system, such as in a Deep Brain Stimulation (DBS) system as disclosed in U.S. Pat. No. 9,119,964.
An SCS system typically includes an Implantable Pulse Generator (IPG) 10 shown in plan and cross-sectional views in
In the illustrated IPG 10, there are thirty-two lead electrodes (E1-E32) split between four leads 14, with the header 28 containing a 2×2 array of lead connectors 24 to receive the leads' proximal ends. However, the number of leads and electrodes in an IPG is application specific and therefore can vary. In a SCS application, the electrode leads 14 are typically implanted proximate to the dura in a patient's spinal cord, and when a four-lead IPG 10 is used, these leads can be split with two on each of the right and left sides. Two 16-electrode leads could also be used with each having a splitter allowing the leads to be connected to two lead connectors 24. Each of the IPG's lead connectors 24 can also support for example 12 or 16 electrodes. The proximal contacts 22 are tunneled through the patient's tissue to a distant location such as the buttocks where the IPG case 30 is implanted, at which point they are coupled to the lead connectors 24. As also shown in
As shown in the cross section of
The IPG 10 also includes one or more antennas 42a and 42b for transcutaneously communicating with external programming devices, such as a patient external controller 50 (
Implantation of IPG 10 in a patient is normally a multi-step process, as explained with reference to
The ETS 70 essentially mimics operation of the IPG 10 to provide stimulation to the implanted electrodes 16, and thus includes contains a battery within its housing along with stimulation and communication circuitry similar to that provided in the IPG 10. Thus, the ETS 70 allows the effectiveness of stimulation therapy to be verified for the patient, such as whether therapy has alleviated the patient's symptoms (e.g., pain). Trial stimulation using the ETS 70 further allows for the determination of particular stimulation program(s) that seems promising for the patient to use once the IPG 10 is later implanted into the patient. A stimulation program may include stimulation parameters that specify for example: which of the electrodes 16 are to be active and used to issue stimulation pulses; the polarity of those active electrodes (whether they are to act as anodes or cathodes); the current or voltage amplitude (A) of the stimulation pulses; the pulse width (PW) of the stimulation pulses; the frequency (f) of the stimulation pulses; the duty cycle (DC) of the stimulation pulses (i.e., the percentage of time that the pulses are asserted relative to the period of the pulses) the shape of the stimulation waveform (e.g., one or more square pulses, one or more ramped pulses, one or more sinusoidal pulses, or even non-pulse-based waveforms, etc.); and other parameters related to issuing a burst of pulses, such as the number of pulses; etc.
At the end of the trial stimulation phase, a decision is made whether to abandon stimulation therapy, or whether to provide the patient with a permanent IPG 10 such as that shown in
An example of stimulation pulses as prescribed by a particular stimulation program and as executable by the IPG or ETS 70 is illustrated in
Biphasic pulses are useful because the second pulse phase can actively recover any charge build up after the first pulse phase residing on capacitances (such as the DC-blocking capacitors 107 discussed later with respect to
The stimulation program executed by the IPG 10 and ETS 70 can be set or adjusted via a communication link from the external controller (
When a neural fiber is recruited by electrical stimulation, it will issue an action potential—that is, the neural fiber will “fire.” An action potential for a typical neural fiber is shown in
Neural fibers recruited and that fire within volume 95 create a cumulative response called an Evoked Compound Action Potential, or ECAP, which is shown in
The IPG 100 (or ETS 170) includes control circuitry 102 into which an ECAP algorithm 124a can be programmed. Control circuitry 102 may comprise a microcontroller for example such as Part Number MSP430, manufactured by Texas Instruments, which is described in data sheets at http://www.ti.com/lsds/ti/microcontroller/16-bit_msp430/overview.page?DCMP=MCU_other& HQS=msp430, which is incorporated herein by reference. Other types of control circuitry may be used in lieu of a microcontroller as well, such as microprocessors, FPGAs, DSPs, or combinations of these, etc. Control circuitry 102 may also be formed in whole or in part in one or more Application Specific Integrated Circuits (ASICs), as described in U.S. Patent Application Publication 2012/0095529 and U.S. Pat. Nos. 9,061,140 and 8,768,453, which are incorporated herein by reference.
In the IPG 100 (or ETS 170) a bus 118 provides digital control signals to one or more Digital-to-Analog converters (DACs) 104, which are used to produce currents or voltages of prescribed amplitudes (A) for the stimulation pulses, and with the correct timing (PW, f). As shown, the DACs include both PDACs which source current to one or more selected anode electrodes, and NDACs which sink current from one or more selected cathode electrodes. In this example, a switch matrix 106 under control of bus 116 is used to route the output of one or more PDACs and one or more NDACs to any of the electrodes, which effectively selects the anode and cathode electrodes. Buses 118 and 116 thus generally set the stimulation program the IPG 100 is running. The illustrated circuitry for producing stimulation pulses and delivering them to the electrodes is merely one example. Other approaches may be found for example in U.S. Pat. Nos. 8,606,362 and 8,620,436, and U.S. Patent Application Publication 2018/0071520. Note that a switch matrix 106 isn't required, and instead a PDAC and NDAC can be dedicated to (e.g., wired to) each electrode.
Notice that the current paths to the electrodes 16 include the DC-blocking capacitors 107 alluded to earlier, which provide additional safety by preventing the inadvertent supply of DC current to an electrode and to a patient's tissue. As discussed earlier, capacitances such as these can become charged as stimulation currents are provided, providing an impetus for the use of biphasic pulses.
One or more of the electrodes 16 can be used to sense the ECAP described earlier, and thus each electrode is further coupleable to at least one sense amp 110. In the example shown, there are four sense amps 110 each corresponding to a particular timing channel in which stimulation can be issued. Under control by bus 114, a multiplexer 108 can couple any of the electrodes to any of the sense amps 110 at a given time. This is however not strictly necessary, and instead each electrode can be coupleable to its own dedicated sense amp 110, or all electrodes can be selected for sensing at different times and presented by MUX 108 to a single sense amp 110. The analog waveform comprising the ECAP, described further below, is preferably converted to digital signals by one or more Analog-to-Digital converters (ADC(s)) 112, which may sample the waveform at 50 kHz for example. The ADC(s) may also reside within the control circuitry 102, particularly if the control circuitry 102 has A/D inputs.
Notice that connection of the electrodes 16 to the sense amp(s) 110 preferably occurs through the DC-blocking capacitors 107, such that capacitors are between the electrodes and the sense amp(s) 110. This is preferred so as to not undermine the safety provided by the DC-blocking capacitors 107.
Once the digitized ECAP is received at the control circuitry 102, it is processed by the ECAP algorithm 124a to determine one or more ECAP features that describe the basic shape and size of the ECAP(s), as explained further below with reference to
The amplitude of an ECAP will depend on how many neural fibers are firing. Generally speaking, a primary ECAP response, e.g., the height of peak N1, can vary, usually between microVolts to tens of milliVolts. Note that the DC blocking capacitor 107 through which the ECAPs pass will remove any DC components in the signal, which is thus referenced to 0 Volts. If necessary, the sensed ECAP signal can be amplified and level-shifted by the sense amp(s) 110 so that its voltage is brought within a range that the control circuitry 102 and/or ADCs 112 can handle, such as between 3 Volts and ground.
In the example shown, the pulses are defined with respect to a total anodic and cathodic current (collectively, Itot) that the electrodes will provide at any given time. This is desirable so that the patient's tissue will not receive a net amount of charge. The sole cathode electrode E4 provides all of the total cathodic current (−Itot), and so provides 100*−Itot, or −A. The two anode electrodes E3 and E5 must together issue the total anodic current (+Itot), and in this example each provides 50%*+Itot, or +½A. The anode electrodes can issue any anodic currents that together will equal +Itot (e.g., 70%*+Itot and 30%*+Itot. It is assumed that this particular stimulation program has been chosen as one that generally provides good therapeutic results for a particular patient.
Once stimulation begins (at time=0), an ECAP will be produced comprising the sum of the action potentials of neural fibers recruited and hence firing in volume 95. As shown in
A single sense electrode (S) has been chosen to sense the ECAP as it moves past, which in this example is electrode E8. Selection of an appropriate sense electrode can be determined by the ECAP algorithm 124a operable in the control circuitry 102 based on a number of factors. For example, it is preferable that a sense electrode S be sensibly chosen with respect to the active electrodes, such that the EM field produced around the active electrodes will dissipate (or more preferably, cease) at the sense electrode by the time the ECAP arrives. This simplifies ECAP detection at the sense electrode, because voltages present in the EM field will not interfere with and potentially mask the ECAP at the sense electrode. (Note that the stimulation artifact resulting from the EM field is not shown at the sense electrode in
In
Note that the ECAP algorithm 124a can enable measurement of an ECAP after a single pulse, or after a burst of (higher-frequency) pulses, such as is shown in
It is not strictly necessary that sensing occur at an electrode that would not experience interference from the EM field produced by the active electrodes, because masking techniques can be used to subtract voltages present in the EM field. Such masking techniques are described for example in M. Hughes, “Fundamentals of Clinical ECAP Measures in Cochlear Implants: Part 1: Use of the ECAP in Speech Processor Programming (2nd Ed.),” Audiology Online (Nov. 8, 2010) (http://www.audiologyonline.com/articles/fundamental sclinicalecapmeasuresin846); and I. Akhoun et al., “Electrically evoked compound action potential artifact rejection by independent component analysis: Technique validation,” Hearing Research 302 pp. 60-73 (2013), which are both incorporated herein by reference. In fact, an active electrode can be used for ECAP sensing, which would involve quickly disconnecting the stimulation circuitry from the electrodes (e.g., at the switch matrix 106,
The ECAP algorithm 124a could choose more than one electrode to act as a sense electrode. For example, ECAP algorithm 124a may sense the traveling ECAP at electrodes E6, E7, E8, E9, etc. This would require timing control, because E6 would sense before E7, etc., and might further require circuitry changes to accommodate sensing the ECAP at different electrodes at overlapping points in time. For example, each electrode might in this example require its own timing control (mux 108), and its own sense amp 110 and ADC 112, although this isn't illustrated in
A practical aspect that could affect sensing ECAPs in IPG 100 (or ETS 170) relates to passive charge recovery. As discussed earlier, the use of biphasic pulses are preferred in an IPG to actively recover charge during the second pulse phase that may have built up across capacitive elements (such as the DC blocking capacitors 107) during the first pulse phase. Because active charge recovery may not be perfect, IPG 100 may additionally include passive charge recovery as implemented by switches 122 shown in
As discussed earlier, it is important to determine a stimulation program that will best alleviate a patient's symptoms. Part of this “fitting” process includes determining which electrodes should be activated by the IPG 100 (or the ETS 170); the polarity of these active electrodes; the amplitude of stimulation; (if stimulation is issued in pulses) the pulse width, frequency, the duty cycle (DC), and shape of the waveform (e.g., pulses); etc. Initial fitting of a patient to determine a stimulation program that is effective usually occurs using a clinician programmer 90 (
Of particular importance during fitting is determining an electrode configuration, i.e., the electrodes that should be active, their polarities, and the percentage of the total anodic or cathodic current that each active electrode will receive. The electrode configuration defines a Central Point of Stimulation (CPS) at a location in the patient's tissue, and one can be determined from the other: the CPS can be calculated using the electrode configuration, and a preset CPS can be used to calculate an appropriate electrode configuration centered at the CPS. CPS can be defined in different manners, as explained further below with reference to
Simulation 1 shows the tripolar stimulation program discussed earlier (
Simulation 2 adjusts the electrode configuration while keeping the CPS the same (centered at cathode electrode E4). In this example, additional anode electrodes (E2, E6) are activated, with anode electrodes E2, E3, E5, and E6 respectively providing 27%, 22%, 22%, and 27% of the total anodic current, +Itot. As seen, the different distribution of the anodic current affects the number of volume elements x expected to be recruited. At amplitude Itot=A, 22x volume elements are recruited; at amplitude 1.4 A, 62x volume elements are recruited; and at amplitude 2 A, 113x volume elements are recruited. Notice that the number of volume elements x recruited in Simulation 2 increases compared to Simulation 1 at the same current amplitudes due to the different electrode configuration used.
Simulation 3 also keeps the location of the CPS constant (centered at cathode electrode E4), but as compared to Simulation 1 changes the active anode electrodes to electrodes that are farther away from cathode E4. Specifically, electrodes E2 and E6 are selected as anode electrodes (each providing 50% of the total anodic current, +Itot). This different distribution of the anodic current also affects the number of volume elements x expected to be recruited. At amplitude Itot=A, 50x volume elements are recruited; at amplitude 1.4 A, 103x volume elements are recruited; and at amplitude 2 A, 156x volume elements are recruited. Notice that the number of volume elements x recruited in Simulation 3 increases compared to Simulations 1 and 2 at the same current amplitudes, again due to the different electrode configuration used.
These simulations indicate that useful adjustment to therapy—recruiting a larger or smaller number or neural fibers, and perhaps different types of fibers—can be made by adjusting the electrode configuration while keeping the location of the CPS constant. This is beneficial, because the CPS, once determined, is generally indicative of the location of a patient's symptoms (e.g., pain), and thus stimulation logically continues to be centered around that point.
There are different manners in which electrode configurations needed to achieve a desired location of the desired Central Point of Stimulation can be defined in three-dimensional space, some of which are shown in the examples of
The CPS can comprise a midpoint between a (virtual) anode and a (virtual) cathode.
In
Other more-sophisticated techniques for defining CPS can involve analysis of the voltages or electric field (E=dV/dx) that would be expected at various locations in the patient's tissue given the electrode configuration. This may involve modeling the tissue environment in which the electrodes are placed, and may take into account the different conductivities and locations of specific tissues in that environment (such as the spinal cord, the cerebrospinal fluid (CSF) surrounding the spinal cord, vertebrae bone tissue, etc.).
In any of these examples for defining the position of the CPS, it should be noted that the CPS can be input, and then the electrode configuration computed (the electrodes that should be active, their polarities, and the percentage of the total anodic or cathodic current that each active electrode will receive. Conversely the CPS can be calculated from the electrode configuration that is specified. A clinician for example can enter an electrode configuration using the user interface of his clinician programmer 90, which can in turn calculate or determine CPS position in any of the ways specified in
In an actual implementation, the extent of neural recruitment can be determined by measuring the ECAP at the IPG 100 (or ETS 170), and ECAP algorithm 124a is useful in this regard.
Prior to operation of the ECAP algorithm 124a in
Once a stimulation program is chosen, the ECAP algorithm 124a can choose one or more electrodes to act as a sense electrode (S) (step 142), as described above. Stimulation can then be provided using the stimulation program (step 144). At this point, the algorithm may undertake certain pre-processing steps (145) in preparation for an upcoming ECAP measurement (146). Because the ECAP is generally a small voltage signal, it may be advisable for example to quantify any background “noise” inherent at the sense electrode so that it can be subtracted out of the ECAP measurement. Such noise may include background neural activity not related to the stimulation that the IPG 100 (or ETS 170) provides. Also, if sensing at the sense electrode occurs during a time when the EM fields related to stimulation have not dissipated, it can be advisable to quantify such stimulation artifacts at the sense electrode so that they may also be subtracted from the ECAP measurement.
Thereafter, ECAP algorithm 124a can measure one or more ECAPs at the sense electrode(s) (step 146) as described earlier. A plurality of ECAPs can be measured as explained above and averaged if necessary to improve the fidelity of the resulting signal.
Next, at least one ECAP feature is determined (step 148) from the measured ECAP(s) indicative of the size and shape of the ECAP. Various features for an ECAP are shown in
Next the ECAP algorithm 124a assesses the one or more features of the ECAP to determine whether they are acceptable, which can include comparing the feature(s) to one or more thresholds or ranges (step 150). In this regard, the ECAP algorithm 124a is flexible, and what is deemed acceptable can vary depending on the circumstances. For example, at times it may be desirable that the ECAP have a large magnitude, such as H_N1 greater than a threshold, which might indicate a strong neural response effective for therapy. At other times, it may be desirable that the ECAP have a small magnitude not exceeding a threshold, which might indicate that the neural tissue is not being over-stimulated. Alternatively, an ECAP can be deemed acceptable if one or more of its features hasn't changed significantly (is within a range) compared to past ECAP measurements; this might indicate that the patient is receiving the desired amount of neural recruitment, and that neural recruitment isn't being affected by variances such as patient movement, scarring of tissue, etc. ECAP features can be indicative of the neural fibers that are recruited, and thus acceptable thresholds or ranges may be set so as to active activate or inhibit different fibers.
Step 150 can also be used to calibrate the algorithm 124a, and in particular can be used to determine which the types of stimulation adjustments that have had a marked effect on the sensed ECAP, which can in turn adjust the manner in which the ECAP algorithm iteratively operates as it learns which adjustments the ECAPs are sensitive to. This can also involve assessing the sensitivity of various ECAP features. For example, assume that adjusting from a first electrode configuration (such as shown in Simulation 1 in
Moreover, and as explained further below, the ECAP algorithm 124a may at least for some iterations change stimulation parameters other than the electrode configuration—such as Itot, pulse width, frequency, duty cycle, waveform shape, various burst parameters, etc. (see step 154). Should adjustment of one of those parameters significantly change a particular ECAP feature—i.e., that feature is sensitive to the changed parameter—the ECAP algorithm 124a may in future iterations focus on adjusting that parameters and ignoring adjustment of others parameters to which the ECAP is less sensitive. In short, the ECAP algorithm 124a has the capability to learn and to change its operation and what it adjusts based on the sensitivity of the ECAP feature(s) it determines. Patient feedback—whether adjustments are helping the patient's symptoms or creating unwanted side effects—in addition to the sensed ECAPs can also be useful to algorithm learning.
If the ECAP feature(s) are acceptable, the ECAP algorithm 124a can eventually repeat, perhaps after a time delay (step 156) such as every minute or so, to allow the algorithm to gradually adjust the stimulation program the IPG 100 (or ETS 170) is running, as discussed next.
If the ECAP feature(s) are not acceptable (150), the ECAP algorithm 124a can adjust the electrode configuration—the active electrodes, their polarities, and relative amplitudes—of the stimulation program while keeping the location of the Central Point of Stimulation (CPS) constant (step 152). As explained earlier, this can involve choosing new (
However, if desired, other stimulation parameters can also be adjusted in addition to the electrode configuration, as set forth in optional step 154. For example, the pulse width of the pulses (PW), the frequency of the pulses (F), the duty cycle (DC), the waveform shape, and various burst parameters (such as number and duration of pulses) can be changed. However, it is preferred for at least some iterations of the ECAP algorithm 124a that these other stimulation parameters remain constant, so that only the effect of the change of the electrode configuration on the ECAP (152) can be analyzed in subsequent steps. It should be noted that these other stimulation parameters can be changed outside of the use of ECAP algorithm 124a; for example, they may be changed when selecting the stimulation program (140) prior to beginning execution of the ECAP algorithm 124a. Furthermore, there may be other reasons not related to ECAP generation or detection that warrant changing of stimulation parameters. For one, the patient or clinician using their external devices 50 or 90 may simply desire to change the amplitude of simulation or other pulse parameters.
The total anodic and cathodic current amplitude Itot can also be changed at optional step 154, although again it is preferred for at least some iterations of the ECAP algorithm 124a that Itot remain constant, so that only the effect of the change of the electrode configuration on the ECAP (152) can be analyzed in subsequent steps. Nonetheless, the utility of adjusting Itot is suggested as reasonable in the simulations of
If ECAP feature(s) are not acceptable (150), it is not necessary that every iteration of ECAP algorithm 124a adjust the electrode configuration (152). As shown by optional path 153, the algorithm may sometimes proceed to optional step 154 to allow other stimulation parameters to be adjusted, as discussed above.
After adjustment, the ECAP algorithm 124a largely repeats—which will involve for at least some iterations applying stimulation with new electrode configurations, and measuring the resulting ECAP to see if the ECAP feature(s) are can be rendered acceptable. While it would be expected that the sense electrode(s) chosen earlier would remain the same, they could be adjusted (142). This could be sensible in case the new electrode configuration chosen places newly-active electrodes too close to the sense electrode(s) picked earlier.
As noted above, the ECAP algorithm can alternatively operate with the assistance of external devices, as shown in
The ECAP algorithm 124a in the IPG 100 (or ETS 170) next performs many of the same steps described earlier, such as executing the stimulation program (186); pre-processing for the upcoming ECAP measurement (188); and measuring the ECAP(s) at the prescribed sense electrode(s) (190). At this point (192), the ECAP algorithm 124a will telemeter at least some information regarding the measured ECAP(s) from the IPG 100 (or ETS 170) to the external device (to algorithm 124b). For example, the entire ECAP waveform(s) can be telemetered (e.g., preferably after being digitized; see ADCs 112,
Once at received at the external device, ECAP algorithm 124b will process the received ECAP information as necessary (194). For example, the ECAP feature(s) can now be determined from the telemetered waveform information, or even further ECAP features can be determined if desired. Then, acceptability of the ECAP feature(s) are determined as described earlier (196). If the features are acceptable, and assuming the patient reports good therapeutic result (204), the ECAP algorithm 124b can terminate. (ECAP algorithm 124a can continue to run in the IPG 100 (or ETS 170) as described earlier in
If the ECAP feature(s) are not acceptable (196), ECAP algorithm 124b can as before adjust the electrode configuration of the stimulation program, preferably keeping for at least some iterations of the algorithm the CPS (recorded earlier) and total anodic and cathodic current Itot constant (198). This adjustment can occur automatically at the external device, or may involve clinician input. As before, other stimulation parameters can optionally be adjusted (199, 200). Once the stimulation program has been so adjusted, the sense electrode(s) can be adjusted if necessary (201), and then the adjusted stimulation program (and adjusted sense electrode(s) information if necessary) is telemetered to the IPG 100 (or ETS 170) (202), where the adjusted stimulation program is then executed (ECAP algorithm 124a). ECAP measurements can be taken again, with results telemetered to the external device to see if the adjustment has rendered ECAP feature(s) that are now acceptable.
In this example of ECAP algorithm 124a, X different electrode configurations creating stimulation located at a constant CPS and with a constant total anodic and cathodic current amplitude Itot are pre-selected (210). As explained further below, each are tried in succession to determine which results in most favorable ECAP feature(s). The X different electrode configurations can be selected in any number of ways: they may be automatically generated by the external device or the IPG 100 (or ETS 170) once the CPS and Itot are known, or the clinician for example can manually specify the electrode configurations at the external device. In just one example the three different electrode configurations depicted in Simulations 1-3 in
One or more sense electrodes are chosen as before (212), and X is set to 1 (214), selecting electrode configuration 1, which is used to provide stimulation (216). Pre-processing prior to an ECAP measurement can be performed as described earlier (218), and one or more ECAPs produced by the electrode configuration 1 are measured at the sense electrode(s) (220). One or more features for the ECAP(s) are determined and stored (222). If this electrode configuration is not the last electrode configuration to be tested (224), X is incremented (226), effectively selecting electrode configuration 2, which is tested next. Once all X electrode configurations have been tested (224), the previously-stored ECAP feature(s) for each of the electrode configurations are assessed (230), and the electrode configuration having the best ECAP feature(s) is chosen for stimulation (232).
One skilled in the art will understand that the ECAP algorithm 124a and 124b and/or any supporting user interface program will comprise instructions that can be stored on non-transitory machine-readable media, such as magnetic, optical, or solid-state memories. Such memories may be within the IPG or ETS itself (i.e., stored in association with control circuitry 102), within the external system (e.g., 50 or 90), or readable by the external system (e.g., memory sticks or disks). Such memories may also include those within Internet or other network servers, such as an implantable medical device manufacturer's server or an app store server, which may be downloaded to the external system.
Although particular embodiments have been shown and described, the above discussion should not limit the present invention to these embodiments. Various changes and modifications may be made without departing from the spirit and scope of the present invention. Thus, the present invention is intended to cover equivalent embodiments that may fall within the scope of the present invention as defined by the claims.
This is a non-provisional application of U.S. Provisional Patent Application Ser. No. 62/568,211, filed Oct. 4, 2017, which is incorporated herein by reference in its entirety, and to which priority is claimed.
Number | Name | Date | Kind |
---|---|---|---|
5697958 | Paul et al. | Dec 1997 | A |
5702429 | King | Dec 1997 | A |
5814092 | King | Sep 1998 | A |
5902236 | Iversen | May 1999 | A |
5902249 | Lyster | May 1999 | A |
5913882 | King | Jun 1999 | A |
6078838 | Rubenstein | Jun 2000 | A |
6181969 | Gord et al. | Jan 2001 | B1 |
6516227 | Meadows et al. | Feb 2003 | B1 |
6907130 | Rubernstein | Jun 2005 | B1 |
7024247 | Gliner et al. | Apr 2006 | B2 |
7424322 | Lombardi et al. | Sep 2008 | B2 |
7450992 | Cameron | Nov 2008 | B1 |
8255057 | Fang et al. | Aug 2012 | B2 |
8335664 | Eberle | Dec 2012 | B2 |
8352030 | Denison | Jan 2013 | B2 |
8412345 | Moffitt | Apr 2013 | B2 |
8463400 | Hegi et al. | Jun 2013 | B2 |
8594797 | Lee | Nov 2013 | B2 |
8606362 | He et al. | Dec 2013 | B2 |
8620436 | Parramon et al. | Dec 2013 | B2 |
8768453 | Parramon et al. | Jul 2014 | B2 |
8825169 | Zhu et al. | Sep 2014 | B2 |
8909350 | Lee | Dec 2014 | B2 |
8913804 | Blum et al. | Dec 2014 | B2 |
9014820 | Lee et al. | Apr 2015 | B2 |
9044155 | Strahl | Jun 2015 | B2 |
9061140 | Shi et al. | Jun 2015 | B2 |
9119964 | Marnfeldt | Sep 2015 | B2 |
9149636 | Moffitt et al. | Oct 2015 | B2 |
9155892 | Parker et al. | Oct 2015 | B2 |
9248274 | Troosters et al. | Feb 2016 | B2 |
9248279 | Chen et al. | Feb 2016 | B2 |
9265431 | Hincapie Ordonez et al. | Feb 2016 | B2 |
9302112 | Bornzin et al. | Apr 2016 | B2 |
9381356 | Parker et al. | Jul 2016 | B2 |
9386934 | Parker et al. | Jul 2016 | B2 |
9387334 | Lee et al. | Jul 2016 | B2 |
9403013 | Walker et al. | Aug 2016 | B2 |
9409020 | Parker | Aug 2016 | B2 |
9526897 | Chen et al. | Dec 2016 | B2 |
9533148 | Carcieri et al. | Jan 2017 | B2 |
9731116 | Chen | Aug 2017 | B2 |
9872990 | Parker et al. | Jan 2018 | B2 |
9974455 | Parker et al. | May 2018 | B2 |
10076667 | Kaula et al. | Sep 2018 | B2 |
20020156513 | Borkan | Oct 2002 | A1 |
20050246004 | Cameron et al. | Nov 2005 | A1 |
20080146894 | Bulkes et al. | Jun 2008 | A1 |
20120092031 | Shi et al. | Apr 2012 | A1 |
20120095519 | Parramon et al. | Apr 2012 | A1 |
20120095529 | Parramon et al. | Apr 2012 | A1 |
20120116475 | Nelson et al. | May 2012 | A1 |
20130035745 | Ahmed | Feb 2013 | A1 |
20130053926 | Hincapie | Feb 2013 | A1 |
20130289665 | Marnfeldt et al. | Oct 2013 | A1 |
20140100632 | Rao et al. | Apr 2014 | A1 |
20140180361 | Burdick | Jun 2014 | A1 |
20140194772 | Single et al. | Jul 2014 | A1 |
20140236042 | Parker et al. | Aug 2014 | A1 |
20140296737 | Parker et al. | Oct 2014 | A1 |
20150018898 | Tass | Jan 2015 | A1 |
20150032181 | Baynham et al. | Jan 2015 | A1 |
20150080982 | Funderburk | Mar 2015 | A1 |
20150157861 | Aghassian et al. | Jun 2015 | A1 |
20150246230 | Litvak | Sep 2015 | A1 |
20150282725 | Single et al. | Oct 2015 | A1 |
20150313487 | Single et al. | Nov 2015 | A1 |
20150360038 | Zottola et al. | Dec 2015 | A1 |
20150374999 | Parker et al. | Dec 2015 | A1 |
20160166164 | Obradovic et al. | Jun 2016 | A1 |
20160287126 | Parker et al. | Oct 2016 | A1 |
20160287182 | Single et al. | Oct 2016 | A1 |
20160303368 | Parramon et al. | Oct 2016 | A1 |
20170049345 | Single et al. | Feb 2017 | A1 |
20170071490 | Parker et al. | Mar 2017 | A1 |
20170135624 | Parker et al. | May 2017 | A1 |
20170216587 | Parker et al. | Aug 2017 | A1 |
20170281958 | Serrano Carmona et al. | Oct 2017 | A1 |
20170296823 | Hershey et al. | Oct 2017 | A1 |
20170361101 | Single et al. | Dec 2017 | A1 |
20180056068 | Zhang et al. | Mar 2018 | A1 |
20180071520 | Weerakoon et al. | Mar 2018 | A1 |
20180071527 | Feldman et al. | Mar 2018 | A1 |
20180110987 | Parker et al. | Apr 2018 | A1 |
20180117335 | Parker et al. | May 2018 | A1 |
20180132747 | Parker et al. | May 2018 | A1 |
20180132760 | Parker et al. | May 2018 | A1 |
20180133459 | Parker et al. | May 2018 | A1 |
20180140831 | Feldman et al. | May 2018 | A1 |
20180228391 | Parker et al. | Aug 2018 | A1 |
20180228547 | Parker et al. | Aug 2018 | A1 |
20180256052 | Parker et al. | Sep 2018 | A1 |
20190099602 | Esteller et al. | Apr 2019 | A1 |
Number | Date | Country |
---|---|---|
2709721 | Sep 2016 | EP |
2006029090 | Mar 2006 | WO |
2015077362 | May 2015 | WO |
2017100866 | Jun 2017 | WO |
2017173493 | Oct 2017 | WO |
2017210352 | Dec 2017 | WO |
2017219096 | Dec 2017 | WO |
Entry |
---|
International Search Report and Written Opinion regarding corresponding PCT Application No. PCT/US2018/051783, dated Dec. 20, 2018. |
Precision Spectra™ System Programming Manual, Boston Scientific Corp., 90834018-18 Rev A (2016). |
E. Viezi et al., “Spinal Cord Stimulation (SCS) with Anatomically Guided (3D) Neural Targeting Shows Superior Chronic Axial Low Back Pain Relief Compared to Traditional SCS—LUMINA Study,” Pain Medicine, pp. 1-15 (2017). |
J. Parker et al., “Electrically Evoked Compound Action Potential Recorded From the Sheep Spinal Cord”, Neuromodulation, 16:295-303 (2013). |
J. Parker, et al., “Compound Action Potentials Recorded in Human Spinal Cord During Neurostimulation for Pain Relief,” PAIN, vol. 153(3), pp. 593-601 (Mar. 2012). |
W.D. Willis, Jr. et al., “Sensory Mechanisms of the Spinal Cord: Volume 2 Ascending Sensory Tracts and Their Descending Control: Third Edition,” Springer Science & Business Media, Chap. 7, p. 278 (2013). |
M. Hughes, “Fundamentals of Clinical ECAP Measures in Cochlear Implants: Part 1: Use of the ECAP in Speech Processor Programming (2nd Ed.),” Audiology Online (Nov. 8, 2010) (http://www.audiologyonline.com/ articles/ fundamentalsclinicalecapmeasuresin846). |
I. Akhoun et al., “Electrically evoked compound action potential artifact rejection by independent component analysis: Technique validation,” Hearing Research 302 pp. 60-73 (2013). |
M. Moffit et al., A Novel 3-Dimensional Algorithm for Model-Based Programming in Spinal Cord Stimuation (SCS): Illumina-3D™ , presentation (2013). |
T. Kano et al., “Evoked Spinal Cord Potentials: An Illustrated Guide to Physiology, Pharmacology, and Recording Techniques,” To Print ISBN 978-4-431-24026-6, Chapter 4, pp. 40-49 (2006). |
U.S. Appl. No. 62/641,748, Zhu et al. |
U.S. Appl. No. 62/648,231, Esteller et al. |
U.S. Appl. No. 62/650,844, Marnfeldt et al. |
U.S. Appl. No. 62/679,259, Esteller et al. |
U.S. Appl. No. 62/768,617, Esteller et al. |
U.S. Appl. No. 62/825,982, Wagenbach et al. |
U.S. Appl. No. 16/210,794, Brill et al. |
U.S. Appl. No. 16/238,151, Esteller et al. |
H. Mino & J. Rubenstein, “Effects of Neural Refractoriness on Spatio-Temporal Variability in Spike Initiations with Eletrical Stimulation,” IEEE Trans. On Neural Sys. & Rehabilitation Eng., vol. 14, No. 3, pp. 273-280 (2006). |
J. Rubinstein et al., “Pseudospontaneous activity: stochastic independence of auditory nerve fibers with electrical stimulation,” Hear Res., 127(1-2), pp. 108-118 (1999) (abstract only). |
J. Paz, “Physiological Midline Mapping Based on Spinal Cord Stimulation (SCS) Response Using the 32-Contact Paddle Lead,” 19th NANS Annual Meeting (Dec. 13-15, 2015). |
E.L. Air et al., “Electrophysiologic Monitoring for Placement of Laminectomy Leads for Spinal Cord Stimulation Under General Anesthesia,” Neuromodulation: Technology at the Neural Interface, vol. 15(6), pp. 573-580 (2012). |
J.L. Shils et al., “Intraoperative Neurophysiologic Methods for Spinal Cord Stimulator Placement Under General Anesthesia,” Neuromodulation: Technology at the Neural Interface, vol. 15(6), pp. 560-572 (2012). |
A. Taghva et al., “Intraoperative Electromyography as an Adjunct to Sacral Neuromodulation for Chronic Pelvic Pain,” Neuromodulation: Technology at the Neural Interface, vol. 18(1), pp. 62-66 (2015). |
Number | Date | Country | |
---|---|---|---|
20190099602 A1 | Apr 2019 | US |
Number | Date | Country | |
---|---|---|---|
62568211 | Oct 2017 | US |