Automatic Calibration in an Implantable Stimulator Device Having Neural Sensing Capability

FIELD OF THE INVENTION

This application relates to Implantable Medical Devices (IMDs), and more specifically to circuitry to assist with calibrating stimulation in an implantable stimulator device.

INTRODUCTION

Implantable neurostimulator devices are devices that generate and deliver electrical stimuli to body 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 to treat motor and psychological disorders, 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 neurostimulator device system.

An SCS system typically includes an Implantable Pulse Generator (IPG) 10 shown in FIG. 1. The IPG 10 includes a biocompatible device case 12 that holds the circuitry and a battery 14 for providing power for the IPG to function. The IPG 10 is coupled to tissue-stimulating electrodes 16 via one or more electrode leads that form an electrode array 17. For example, one or more percutaneous leads 15 can be used having ring-shaped or split-ring electrodes 16 carried on a flexible body 18. In another example, a paddle lead 19 provides electrodes 16 positioned on one of its generally flat surfaces. Lead wires 20 within the leads are coupled to the electrodes 16 and to proximal contacts 21 insertable into lead connectors 22 fixed in a header 23 on the IPG 10, which header can comprise an epoxy for example. Once inserted, the proximal contacts 21 connect to header contacts 24 within the lead connectors 22, which are in turn coupled by feedthrough pins 25 through a case feedthrough 26 to stimulation circuitry 28 within the case 12.

In the illustrated IPG 10, there are thirty-two electrodes (E1-E32), split between four percutaneous leads 15, or contained on a single paddle lead 19, and thus the header 23 may include a 2×2 array of eight-electrode lead connectors 22. However, the type and number of leads, and the number of electrodes, in an IPG is application specific and therefore can vary. The conductive case 12 can also comprise an electrode (Ec). In a SCS application, the electrode lead(s) are typically implanted in the spinal column proximate to the dura in a patient's spinal cord, preferably spanning left and right of the patient's spinal column. The proximal contacts 21 are tunneled through the patient's tissue to a distant location such as the buttocks where the IPG case 12 is implanted, at which point they are coupled to the lead connectors 22. In other IPG examples designed for implantation directly at a site requiring stimulation, the IPG can be lead-less, having electrodes 16 instead appearing on the body of the IPG 10 for contacting the patient's tissue. The IPG lead(s) can be integrated with and permanently connected to the IPG 10 in other solutions. The goal of SCS therapy is to provide electrical stimulation from the electrodes 16 to alleviate a patient's symptoms, such as chronic back pain.

IPG 10 can include an antenna 27a allowing it to communicate bi-directionally with a number of external devices discussed subsequently. Antenna 27a as shown comprises a conductive coil within the case 12, although the coil antenna 27a can also appear in the header 23. When antenna 27a is configured as a coil, communication with external devices preferably occurs using near-field magnetic induction. IPG 10 may also include a Radio-Frequency (RF) antenna 27b. In FIG. 1, RF antenna 27b is shown within the header 23, but it may also be within the case 12. RF antenna 27b may comprise a patch, slot, or wire, and may operate as a monopole or dipole. RF antenna 27b preferably communicates using far-field electromagnetic waves, and may operate in accordance with any number of known RF communication standards, such as Bluetooth, Zigbee, WiFi, MICS, and the like.

Stimulation in IPG 10 is typically provided by pulses each of which may include a number of phases such as 30a and 30b, as shown in the example of FIG. 2A. Stimulation parameters typically include amplitude (current I, although a voltage amplitude V can also be used); frequency (F); pulse width (PW) of the pulses or of its individual phases such as 30a and 30b; the electrodes 16 selected to provide the stimulation; and the polarity of such selected electrodes, i.e., whether they act as anodes that source current to the tissue or cathodes that sink current from the tissue. These and possibly other stimulation parameters taken together comprise a stimulation program that the stimulation circuitry 28 in the IPG 10 can execute to provide therapeutic stimulation to a patient.

In the example of FIG. 2A, electrode E1 has been selected as an anode (during its first phase 30a), and thus provides pulses which source a positive current of amplitude +I to the tissue. Electrode E2 has been selected as a cathode (again during first phase 30a), and thus provides pulses which sink a corresponding negative current of amplitude −I from the tissue. This is an example of bipolar stimulation, in which only two lead-based electrodes are used to provide stimulation to the tissue (one anode, one cathode). However, more than one electrode may be selected to act as an anode at a given time, and more than one electrode may be selected to act as a cathode at a given time.

IPG 10 as mentioned includes stimulation circuitry 28 to form prescribed stimulation at a patient's tissue. FIG. 3 shows an example of stimulation circuitry 28, which includes one or more current source circuits and one or more current sink circuits. The sources and sinks can comprise Digital-to-Analog converters (DACs), and may be referred to as PDACs and NDACs in accordance with the Positive (sourced, anodic) and Negative (sunk, cathodic) currents they respectively issue. In the example shown, a NDACi/PDACi pair is dedicated (hardwired) to a particular electrode node ei 39. Each electrode node ei 39 is connected to an electrode Ei 16 via a DC-blocking capacitor Ci 38, for the reasons explained below. The stimulation circuitry 28 in this example also supports selection of the conductive case 12 as an electrode (Ec 12), which case electrode is typically selected for monopolar stimulation. The PDACs and NDACs can also comprise voltage sources.

Proper control of the PDACs and NDACs allows any of the electrodes 16 to act as anodes or cathodes to create a current through a patient's tissue, R, hopefully with good therapeutic effect. In the example shown, electrode E1 has been selected as an anode electrode to source current to the tissue R and E2 as a cathode electrode to sink current from the tissue R. Thus PDAC1 and NDAC2 are activated and digitally programmed to produce the desired current, I, with the correct timing (e.g., in accordance with the prescribed frequency F and pulse widths PWa and PWb). Power for the stimulation circuitry 28 is provided by a compliance voltage VH, as described in further detail in U.S. Patent Application Publication 2013/0289665. As shown the compliance voltage may be coupled to the source circuitry (e.g., the PDAC(s)), while ground may be coupled to the sink circuitry (e.g., the NDAC(s)), such that the stimulation circuitry is coupled to and powered between the compliance voltage and ground. More than one anode electrode and more than one cathode electrode may be selected at one time, and thus current can flow through the tissue R between two or more of the electrodes 16. Stimulation circuitry 28 can differ. In an example not shown, a switching matrix can intervene between the one or more PDACs and the electrode nodes ei 39, and between the one or more NDACs and the electrode nodes, to allow any of the PDACs or NDACs to be connected to any of the electrode nodes. Various examples of stimulation circuitries can be found in U.S. Pat. Nos. 6,181,969, 8,606,362, 8,620,436, 10,912,942, and U.S. Patent Application Publication 2018/0071520. Much of the stimulation circuitry 28 of FIG. 3, including the PDACs and NDACs, the switch matrices (if present), and the electrode nodes ei 39 can be integrated on one or more Application Specific Integrated Circuits (ASICs), which may also contain other circuitry useful in the IPG 10, such as telemetry circuitry (for interfacing off chip with telemetry antennas 27a and/or 27b), circuitry for generating the compliance voltage VH, various measurement circuits, etc.

Also shown in FIG. 3 are DC-blocking capacitors Ci 38 placed in series in the electrode current paths between each of the electrode nodes ei 39 and the electrodes Ei 16 (including the case electrode Ec 12). The DC-blocking capacitors 38 act as a safety measure to prevent DC current injection into the patient, as could occur for example if there is a circuit fault in the stimulation circuitry 28, and also generally comprise part of the IPG's charge balancing mechanism. The DC-blocking capacitors 38 are typically provided off-chip (off of the ASIC(s)), and instead may be provided in or on a circuit board in the IPG 10 used to integrate its various components, as explained in U.S. Patent Application Publication 2015/0157861.

Referring again to FIG. 2A, the stimulation pulses as shown are biphasic, with each pulse comprising a first phase 30a followed thereafter by a second phase 30b of opposite polarity. Biphasic pulses are useful to actively recover any charge that might be stored on capacitive elements in the electrode current paths, such as on the DC-blocking capacitors 38. Charge recovery is shown with reference to both FIGS. 2A and 2B. During the first pulse phase 30a, charge will (primarily) build up across the DC-blockings capacitors C1 and C2 associated with the electrodes E1 and E2 used to produce the current, giving rise to voltages Vc1 and Vc2 (I=C*dV/dt). During the second pulse phase 30b, when the polarity of the current I is reversed at the selected electrodes E1 and E2, the stored charge on capacitors C1 and C2 is recovered, and thus voltages Vc1 and Vc2 hopefully return to 0V at the end the second pulse phase 30b. To recover all charge by the end of the second pulse phase 30b of each pulse (Vc1=Vc2=0V), the first and second phases 30a and 30b are charged balanced at each electrode, with the phases comprising an equal amount of charge but of the opposite polarity. Passive charge recovery can also occur after the active pulse phases such as 30a and 30b. This can occur during periods 30c, when passive charge recovery switches 41 (FIG. 3) are closed. Passive charge recovery is explained further in U.S. Pat. No. 10,716,937 and 10,792,491.

FIG. 4 shows various external devices that can wirelessly communicate data with the IPG 10, including a patient, hand-held external controller 60, and a clinician programmer 70. Both of devices 60 and 70 can be used to wirelessly transmit a stimulation program to the IPG 10—that is, to program its stimulation circuitry 28 to produce stimulation with desired amplitudes and timings as described earlier. Both devices 60 and 70 may also be used to adjust one or more stimulation parameters of a stimulation program that the IPG 10 is currently executing. Devices 60 and 70 may also wirelessly receive information from the IPG 10, such as various status information, etc. Devices 60 and 70 may additionally communicate with an External Trial Stimulator (ETS) which is used to mimic operation of the IPG 10 during a trial period and prior to the IPG's implantation, as explained in U.S. Pat. Nos. 9,724,508 and 9,259,574.

External controller 60 can be as described in U.S. Patent Application Publication 2015/0080982 for example, and may comprise a controller dedicated to work with the IPG 10. External controller 60 may also comprise a general purpose mobile electronics device such as a mobile phone which has been programmed with a Medical Device Application (MDA) allowing it to work as a wireless controller for the IPG 10, as described in U.S. Patent Application Publication 2015/0231402. External controller 60 includes a user interface, preferably including means for entering commands (e.g., buttons or selectable graphical icons) and a display 62. The external controller 60's user interface enables a patient to adjust stimulation parameters, although it may have limited functionality when compared to the more-powerful clinician programmer 70, described shortly. The external controller 60 can have one or more antennas capable of communicating with the IPG 10. For example, the external controller 60 can have a near-field magnetic-induction coil antenna 64a capable of wirelessly communicating with the coil antenna 27a in the IPG 10. The external controller 60 can also have a far-field RF antenna 64b capable of wirelessly communicating with the RF antenna 27b in the IPG 10.

Clinician programmer 70 is described further in U.S. Patent Application Publication 2015/0360038, and can comprise a computing device 72, such as a desktop, laptop, or notebook computer, a tablet, a mobile smart phone, a Personal Data Assistant (PDA)-type mobile computing device, etc. In FIG. 4, computing device 72 is shown as a laptop computer that includes typical computer user interface means such as a screen 74, a mouse, a keyboard, speakers, a stylus, a printer, etc., not all of which are shown for convenience. Also shown in FIG. 4 are accessory devices for the clinician programmer 70 that are usually specific to its operation as a stimulation controller, such as a communication “wand” 76 coupleable to suitable ports on the computing device 72, such as USB ports 79 for example. The antenna used in the clinician programmer 70 to communicate with the IPG 10 can depend on the type of antennas included in the IPG 10. If the patient's IPG 10 includes a coil antenna 27a, wand 76 can likewise include a coil antenna 80a to establish near-filed magnetic-induction communications at small distances. In this instance, the wand 76 may be affixed in close proximity to the patient, such as by placing the wand 76 in a belt or holster wearable by the patient and proximate to the patient's IPG 10. If the IPG 10 includes an RF antenna 27b, the wand 76, the computing device 72, or both, can likewise include an RF antenna 80b to establish communication with the IPG 10 at larger distances. The clinician programmer 70 can also communicate with other devices and networks, such as the Internet, either wirelessly or via a wired link provided at an Ethernet or network port.

To program stimulation programs or parameters for the IPG 10, the clinician interfaces with a clinician programmer graphical user interface (GUI) 82 provided on the display 74 of the computing device 72. As one skilled in the art understands, the GUI 82 can be rendered by execution of clinician programmer software 84 stored in the computing device 72, which software may be stored in the device's non-volatile memory 86. Execution of the clinician programmer software 84 in the computing device 72 can be facilitated by control circuitry 88 such as one or more microprocessors, microcomputers, FPGAs, DSPs, other digital logic structures, etc., which are capable of executing programs in a computing device, and which may comprise their own memories. Such control circuitry 88, in addition to executing the clinician programmer software 84 and rendering the GUI 82, can also enable communications via antennas 80a or 80b to communicate stimulation parameters chosen through the GUI 82 to the patient's IPG 10.

The user interface of the external controller 60 may provide similar functionality because the external controller 60 can include similar hardware and software programming as the clinician programmer. For example, the external controller 60 includes control circuitry 66 similar to the control circuitry 88 in the clinician programmer 70, and may similarly be programmed with external controller software stored in device memory.

SUMMARY

A method is disclosed for determining one or more first thresholds for therapeutic stimulation provided to a patient by an implantable neurostimulator. The method may comprise: (a) providing the therapeutic stimulation to the patient via the implantable neurostimulator, wherein the therapeutic stimulation comprises a plurality of stimulation parameters; (b) determining a value for a neural response, wherein the neural response is formed in response to the therapeutic stimulation; and (c) determining one or more first thresholds for the therapeutic stimulation using the determined value for the neural response, wherein each first threshold is determined using a first mathematical relationship that models each first threshold as a function of values of the neural response.

In one example, the one or more first thresholds comprise thresholds for one of the stimulation parameters that causes a physiological response in the patient. In one example, the physiological response comprises one or more of paresthesia and discomfort. In one example, the one or more first thresholds comprise physiological thresholds. In one example, the one or more physiological thresholds comprise one or more of a perception threshold and a discomfort threshold. In one example, the one or more first thresholds comprise thresholds for an amplitude of the therapeutic stimulation. In one example, the therapeutic stimulation is provided to the spinal column of the patient, and wherein the neural response comprises an Evoked Compound Action Potential. In one example, the value for the neural response comprises a value of one of the stimulation parameters. In one example, the value for the neural response comprises a minimum value of the one of the stimulation parameters at which the neural response is detectable. In one example, the one of the stimulation parameters comprises an amplitude of the therapeutic stimulation. In one example, the first mathematical relationship that models each first threshold is a linear function of the values of the neural response. In one example, the value for the neural response comprises an extracted neural threshold. In one example, an external device communicates with the implantable neurostimulator. In one example, the value for the neural response is determined in the external device. In one example, the method is initiated at a user interface of the external device. In one example, the first mathematical relationship for each of the first thresholds is stored in the external device. In one example, the one or more first thresholds is determined in the external device. In one example, the method may further comprise transmitting the one or more first thresholds to the implantable neurostimulator or to another external device. In one example, the method may further comprise prior to step (a), providing test stimulation to the patient via the implantable neurostimulator, wherein the test stimulation is provided at a plurality of different test pulse widths. In one example, the method may further comprise determining values for a neural response at each of the test pulse widths, wherein the neural response is formed in response to the test stimulation. In one example, the method may further comprise determining a second mathematical relationship that models values for the neural response as a function of pulse width using the values for the neural response as determined at each of the test pulse widths. In one example, in step (a) the therapeutic stimulation is provided to the patient at a therapeutic pulse width. In one example, in step (b) the value for the neural response is determined using the second mathematical relationship determined at the therapeutic pulse width.

A system is disclosed which may comprise: an external device configured to communicate with an implantable neurostimulator, wherein the external device is configured to: (a) program the implantable neurostimulator to provide therapeutic stimulation to a patient, wherein the therapeutic stimulation comprises a plurality of stimulation parameters; (b) determine a value for a neural response, wherein the neural response is formed in response to the therapeutic stimulation; and (c) determine one or more first thresholds for the therapeutic stimulation using the determined value for the neural response, wherein each first threshold is determined using a first mathematical relationship that models each first threshold as a function of values of the neural response.

In one example, the one or more first thresholds comprise thresholds for one of the stimulation parameters that causes a physiological response in the patient. In one example, the physiological response comprises one or more of paresthesia and discomfort. In one example, the one or more first thresholds comprise physiological thresholds. In one example, the one or more physiological thresholds comprise one or more of a perception threshold and a discomfort threshold. In one example, the one or more first thresholds comprise thresholds for an amplitude of the therapeutic stimulation. In one example, the therapeutic stimulation is provided to the spinal column of the patient, and wherein the neural response comprises an Evoked Compound Action Potential. In one example, the value for the neural response comprises a value of one of the stimulation parameters. In one example, the value for the neural response comprises a minimum value of the one of the stimulation parameters at which the neural response is detectable. In one example, the one of the stimulation parameters comprises an amplitude of the therapeutic stimulation. In one example, the first mathematical relationship that models each first threshold is a linear function of the values of the neural response. In one example, the value for the neural response comprises an extracted neural threshold. In one example, the system may further comprise the implantable neurostimulator. In one example, the implantable neurostimulator is configured to sense the neural response. In one example, the implantable neurostimulator is configured transmit information indicative of the sensed neural response to the external device. In one example, the first mathematical relationship for each of the first thresholds is stored in the external device. In one example, the external device is further configured to transmit the one or more first thresholds to the implantable neurostimulator or to another external device. In one example, the external device is further configured, prior to step (a), to program the implantable neurostimulator to provide test stimulation to the patient via the implantable neurostimulator, wherein the test stimulation is provided at a plurality of different test pulse widths. In one example, the external device is further configured to determinize values for a neural response at each of the test pulse widths, wherein the neural response is formed in response to the test stimulation. In one example, the external device is further configured to determine a second mathematical relationship that models values for the neural response as a function of pulse width using the values for the neural response as determined at each of the test pulse widths. In one example, in step (a) the therapeutic stimulation is provided to the patient at a therapeutic pulse width. In one example, in step (b) the value for the neural response is determined using the second mathematical relationship determined at the therapeutic pulse width.

A non-transitory computer readable medium is disclosed which may comprise instructions executable on an external device configured to communicate with an implantable neurostimulator, wherein the instructions are configured to: (a) render a user interface on the external device to allow a user program the implantable neurostimulator to provide therapeutic stimulation to a patient, wherein the therapeutic stimulation comprises a plurality of stimulation parameters; (b) determine a value for a neural response, wherein the neural response is formed in response to the therapeutic stimulation; and (c) determine one or more first thresholds for the therapeutic stimulation using the determined value for the neural response, wherein each first threshold is determined using a first mathematical relationship that models each first threshold as a function of values of the neural response.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows an Implantable Pulse Generator (IPG), in accordance with the prior art.

FIGS. 2A and 2B show an example of stimulation pulses producible by the IPG, in accordance with the prior art.

FIG. 3 shows stimulation circuitry useable in the IPG, in accordance with the prior art.

FIG. 4 shows various external devices capable of communicating with and programming stimulation in an IPG, in accordance with the prior art.

FIG. 5 shows an improved IPG having neural response sensing, and the ability to adjust stimulation dependent on such sensing.

FIG. 6 shows stimulation producing a neural response, and the sensing of that neural response at at least one electrode of the IPG.

FIG. 7 shows different physiological thresholds such as pth and dth, and how they relate to amplitude I of stimulation.

FIG. 8 shows a Graphical User Interface (GUI) of an external device such as a clinician programmer, and use of the interface to set stimulation for a patient and to determine physiological thresholds for that stimulation.

FIG. 9 shows graphs relating physiological thresholds such as pth and dth to extracted neural thresholds (ENTs).

FIG. 10 shows an algorithm using measured ENTs to determine physiological thresholds using the relationships of FIG. 9.

FIG. 11 shows strength-duration curves, and modeling ENTs in accordance with such curves to establish ENTs as a function of duration (pulse width).

FIG. 12 shows an algorithm using ENTs measured at different pulse widths to determine physiological thresholds using the relationships of FIG. 9 and the ENT modelling of FIG. 11.

DETAILED DESCRIPTION

An increasingly interesting development in pulse generator systems, and in Spinal Cord Stimulator (SCS) pulse generator systems specifically, is the addition of sensing capability to complement the stimulation that such systems provide. For example, and as explained in U.S. Patent Application Publication 2017/0296823, it can be beneficial to sense a neural response in neural tissue that has received stimulation from an SCS pulse generator.

FIG. 5 shows circuitry for an SCS IPG 100 having neural response sensing capability. The IPG 100 includes control circuitry 102, which 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. 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) in the IPG 100 as described earlier, which ASIC(s) may additionally include the other circuitry shown in FIG. 5.

FIG. 5 includes the stimulation circuitry 28 described earlier (FIG. 3), including one or more DACs (PDACs and NDACs). A bus 118 provides digital control signals to the DACs to produce currents or voltages of prescribed amplitudes (I) and with the correct timing (PW, F) at the electrodes selected for stimulation. The electrode current paths to the electrodes 16 include the DC-blocking capacitors 38 described earlier.

The control circuitry 102 is programmed with a neural response algorithm 124 to evaluate a neural response of neurons that fire (are recruited) by the stimulation that the IPG 100 provides. One such neural response depicted in FIGS. 5 and 6 is an Evoked Compound Action Potential, or “ECAP,” although other types of neural responses also exist and can be sensed by the IPG 100. As its name implies, an ECAP comprises a compound (summation) of various action potentials issued from a plurality of recruited neurons, and its amplitude and shape varies depending on the number and type of neural fibers that are firing. Generally speaking, an ECAP can vary between tens of microVolts to tens of milliVolts. The neural response algorithm 124 assesses the ECAP and can, for example, adjust the stimulation program in a closed loop fashion. In this regard, the neural response algorithm 124 can attempt to remove other signals that may be present at the sensing electrode (stimulation artifacts, background signals and noise) and determine one of more features indicative of the size and shape of the ECAP (e.g., peak-to-peak heights, peak areas, line lengths, etc.). Such ECAP features are described in further details in U.S. Patent Application Publication 2020/0305744, which is incorporated herein by reference in its entirety.

The control circuitry 102 and/or the neural response algorithm 124 can also enable one or more sense electrodes (S) to sense the ECAP, either automatically or based on a user selection of the sense electrode(s) as entered into an external device (see FIG. 4). As shown in FIG. 6, the ECAP will be initiated upon stimulation of neural fibers in a recruited neural population 95 proximate to the electrodes chosen for stimulation (e.g., E1 and E2), and will move through the patient's tissue via neural conduction. In the simple example of FIG. 6, electrode E6 is chosen as a sense electrode S, and thus this electrode will detect the ECAP as it moves past. The speed at which the ECAP moves depends on the several factors, and is variable.

To assist with selection of the sensing electrode(s), and referring again to FIG. 5, each electrode node ei 39 is made coupleable to at least one sense amp 110. In this example, for simplicity, all of the electrode nodes are shown as sharing a single sense amp 110. Thus, any one sensing electrode (e.g., electrode node e6) can be coupled to the sense amp 110 (e.g., Ve6) at a given time per multiplexer 108, as controlled by bus 114. However, although not shown, each electrode node can also be coupleable to its own dedicated sense amp 110. ECAP sensing can also involve differential sensing of the ECAP at more than one electrode (e.g., at electrodes E5 and E6), and thus two electrode nodes (e.g., Ve5 and Ve6) can be input to a differential sense amp 110, as explained for example in U.S. Patent Application Publication 2020/0305744. After the ECAP is sensed, the analog waveform comprising the ECAP is preferably converted to digital signals by an Analog-to-Digital converter 112, which may also reside within the control circuitry 102. The neural response algorithm 124 can then assess the size and shape of the ECAP as already described, and if necessary, make adjustments to stimulation via bus 118. In an alternative, the neural response algorithm 124 may also transmit data to an external device such as the clinician programmer 70 or the patient external controller 60 (FIG. 4), which permits those external systems to perform some of the processing. For example, the algorithm 124 can cause the IPG 100 to transmit digital or analog representations of the waveforms, leaving the external system to determine ECAP features from the waveforms. The algorithm 124 may also cause the IPG 100 to transmit determined ECAP features to the external systems for analysis. In this regard, notice that all or a portion of the neural sensing algorithm 124 can operate in an external system, such as in conjunction with the clinician programmer's software 84 (FIG. 4).

Stimulation in IPG 100 can be provided with reference to a number of different physiological thresholds, which will different from patient to patient. Generally speaking, a physiological threshold comprises a threshold that causes a physiological response in the patient. Reaching a physiological threshold may be perceptible to the patient, such as paresthesia or discomfort. FIG. 7 shows an example of two particular physiological thresholds, which are called the perception threshold (pth) and the discomfort threshold (dth). Other physiological thresholds also exist, but are not shown for simplicity. In this example, the physiological thresholds are expressed in terms of current amplitude I of the stimulation therapy that is provided to the patient, although other parameters of the stimulation therapy (e.g., pulse width, frequency) could be used to define these thresholds as well. The perception threshold pth comprises a lowest amplitude at which the patient can still feel the stimulation (as paresthesia), or as a highest amplitude at which the patient cannot feel the stimulation. As such, the perception threshold pth demarks a boundary between sub-perception stimulation therapy (I<pth) and supra-perception stimulation therapy (I>pth). The discomfort threshold dth comprises a highest amplitude at which stimulation is still comfortable for the patient. In other words, stimulation amplitudes above dth (I>dth) are uncomfortable for the patient, and thus these higher amplitudes are generally avoided.

It is normally useful for the clinician to determine at least one of these physiological thresholds for a given patient, because this can be useful to programming or controlling the patient's stimulation therapy. For example, pth can be important to determine if it is desired that a patient receive sub-perception stimulation therapy or supra-perception therapy. dth can be important to determine to ensure that stimulation therapy does not cause patient discomfort. Physiological thresholds can be determined by the clinician using the GUI 82 of the clinician programmer 70 as shown in FIG. 8, which can also be used to generally determine optimal stimulation parameters for the patient. The GUI 82 as shown in FIG. 8 is fairly basic, and an actual implementation can be more complicated and can provide more options to tailor stimulation and/or to provide active or passive charge recovery schemes, although these more advanced details aren't shown. In this example, the GUI 82 includes a lead interface 130 which shows the electrode array 17 as implanted in the patient. The lead interface 130 can show the relative positions of the leads in the electrode array to each other, and can also show the position of the leads relative to the patient's tissue. For example, although not shown, the locations of the patient's vertebrae can also be displayed in the leads interface 130.

The GUI 82 can also include a stimulation parameters interface 132 which is used to set the stimulation parameters of the stimulation that the patient will receives. This can include means to adjust the amplitude (I), pulse width (PW) and frequency (F) of the stimulation pulses. The GUI can also include means to set the location of stimulation in the electrode array 17. This can involve selecting active electrodes (E), the polarity of those active electrodes (P; anode or cathode), and the percentage of amplitude I (X %) that each active electrode should receive. In this example, electrode E1 has been selected as an anode and E2 as a cathode, with each receiving 100% of current amplitude I as an anodic current (+I) and as a cathodic current (−I). However, and as mentioned earlier, more than one electrode can be selected as an anode and more than one electrode can be selected as a cathode at a given time by sharing the anodic or cathodic current between those anode/cathode electrodes, as dictated by percentage X %. Sharing the anodic and cathodic currents between different numbers of electrodes can set the position of anode and cathode poles (+ and −) as virtual poles between the physical location of the electrodes, as is known. Typically, the location of the stimulation in the electrode array 17 can be manipulated by the clinician, such as by using a computer mouse to move the location of the stimulation within the leads interface 130, and this is done with the goal of locating a position that treats the patient's symptoms (e.g., pain). Note that an electrode configuration algorithm can be used to automatically determine active electrodes (E), polarities (P), and percentages (X %) as the clinician positions the stimulation in the electrode array, as explained further in U.S. Pat. No. 10,881,859, which is incorporated herein by reference in its entirety. GUI 82 can also include a program interface 134 to allow a clinician to store and load stimulation programs for the patient.

Once generally optimal stimulation parameters (I, PW, F, E, P, X) have been determined for the patient, the clinician can determine one or more physiological thresholds discussed earlier. This can generally involve an amplitude “sweep” where the amplitude is set to 0 and is gradually increased until the patient first starts to perceive the stimulation (which establishes pth). Further increasing the amplitude until the patient experiences discomfort similarly establishes dth. Once these thresholds have been determined in this manner, they can be stored by the clinician in a threshold interface 136 in the GUI 82 along with the other stimulation parameters, which then allows these physiological thresholds to be used in setting or controlling the patient's stimulation. For example, once dth is set, the GUI 82 may set this as a maximum value for amplitude I, and may limit amplitude I adjustments to values lower than this maximum for patient safety. In another example, if the clinician decides that the patient should receive paresthesia-based therapy (i.e., supra-perception therapy where the patient perceives a sensation produced by the stimulation), the GUI 82 may set pth as an amplitude minimum, while also setting dth as an amplitude maximum for safety. Percentages of these values can be used as well. For example, the maximum amplitude may be set to 90% of dth to ensure some guardband against patient discomfort. Likewise, if the clinician decides that the patient should receive paresthesia-free (sub-perception) therapy, the GUI 82 may set pth as an amplitude maximum. Again, the maximum amplitude may be limited to a percentage of pth, such as 90% of pth to guardband against the possibility that the patient may feel the stimulation. The optimal stimulation parameters and any relevant physiological thresholds such as pth and/or dth can also be transmitted to and stored in the patient's external controller 60 and/or the patient's IPG 100, as shown in FIG. 8. Having the physiological thresholds transmitted to such patient devices is useful to control the extent to which a patient can adjust his situation therapy, such as by limiting amplitude adjustments to different treatment regimes (supra-perception, sub-perception, sub-discomfort, etc.) as just described.

While establishing physiological thresholds such as pth and dth can be useful, it does take some time for the clinician to perform. This can create problems for the clinician when trying to determine optimal stimulation parameters for the patient. As noted above, the clinician can attempt to move the location of the stimulation in the electrode array to try and find a location that best treats the patient's symptoms. Typically, the values of physiological thresholds such as pth and dth will change as the location of the stimulation changes. This can mean that the clinician may need to determine these thresholds at each new stimulation location, which as noted takes some time to manually establish.

Another shortcoming to determining pth and dth as described is that these thresholds are typically set once at the beginning of stimulation therapy, and may thereafter only be altered by the clinician from time to time. This is unfortunate, because it may be useful to adjust such thresholds in between clinician visits. In this regard, it is known that it can be necessary to adjust a patient's stimulation, because the stimulation environment has changed. If a patient changes position, such as going from sitting to standing, this can bring the electrodes closer to or farther from the spinal neural tissue. This would suggest that the intensity of stimulation (e.g., amplitude) may need to be decreased or increased to bring about the same therapeutic effect when treating a patient's symptoms. Scar tissue or changes to the electrode/tissue interface may also naturally change over time, which would also suggest that it may be beneficial to adjust a patient's stimulation. It would be expected that such changes to the stimulation environment would suggest the need to adjust the physiological thresholds. For example, if it is necessary to generally increase the amplitude of simulation given such environmental changes, it would be expected that pth and dth should also increase. However, pth and dth as just discussed are typically set or adjusted by the clinician only infrequently, as described above.

It would be beneficial to automatically change or update physiological thresholds such as pth and dth using measurements taken from the patient. This would allow clinician to more quickly establish values for such thresholds, and would allow such thresholds to be adjusted even after leaving a clinician's office. In this disclosure, neural response measurements are used to estimate, adjust, and set therapeutic thresholds. More specifically, extracted neural thresholds (ENTs) are determined. An ENT may be expressed in terms of current amplitude I of the stimulation therapy that is provided to the patient, and comprises the minimum amplitude at which a neural response can be reliably detected, as described further below. The inventors have noticed a correlation between ENTs and physiological thresholds such as pth and dth, which allows such thresholds to be estimated and updated using measured ENT values. In particular, the inventors have noticed a parallel between the strength-duration curves for ENTs and physiological thresholds such as pth and dth, which again allows physiological thresholds to be estimated and updated using measured ENT values. This is beneficial, because ENTs can be objectively measured, which allows physiological thresholds to be automatically and quickly adjusted on the fly. This both assists the clinician in determining physiological thresholds, and also allows for updating of these thresholds without a clinician's assistance.

An extracted neural threshold (ENT) as just noted may be expressed in terms of current amplitude I of the stimulation therapy that is provided to the patient, as shown in FIG. 7, and comprises the smallest amplitude at which an neural response to the stimulation can be reliably detected. One such neural response comprises an ECAP, which as mentioned above is a small signal which may be difficult to detect. The ability to detect an ECAP—and thus determine an ENT value (in mA)—depends on many factors, such as the design of the sense amp(s) 110 (FIG. 5), the resolution with which the sensed ECAP is sampled (via ADC 112), and the particulars of the neural response algorithm 124 (which as noted above can operate at least in part in external systems as well). Furthermore, sensing an ECAP is made difficult because the voltage in a patient's tissue can vary, both as a result of the stimulation and background noise in the tissue. See, e.g., U.S. Patent Application Publications 2020/0305744 and PCT (Int'l) Publication WO 2020/251899. Still further, the sensing electrode(s) used to sense ECAPs may not be constant with respect to stimulation provided in different patients; the distance between the stimulating and sensing electrodes may vary for example. Adding further variability is the fact that the ECAPs can be detected in different ways. For example, an ENT can be determined by the neural response algorithm 124 using signal averaging. See, e.g., U.S. Pat. No. 10,926,092. An ENT can also be determined “visually”—i.e., as a lowest amplitude at which an ECAP (e.g., its shape) can be visually noticed by a clinician and input into the GUI. (Normally it would be expected that ENT extracted mathematically would be lower than an ENT extracted visually).

For these reasons, an ENT, although measured objectively, does not comprise an absolute value, but instead has a value that may be system and/or patient dependent. In this regard, and referring again to FIG. 7, an ENT may have an uncertain relationship to other therapeutic thresholds such as the perception threshold pth. For example, ECAPs are present in sub-perception stimulation therapy, and so one could expect ENTs to be of lower values than pth. However, such ENTs could be higher than pth depending on how ENTs are measured by the system, and depending on the specific patient lead implantation location and its distance to the spinal cord. Note that ECAPs comprise only one type neural response to stimulation, and that other types of neural responses exist for which extracted thresholds can be determined. For example, in Deep Brain Stimulation, stimulation of brain tissue can give rise to Evoked Resonant Neural Activity (ERNA) responses, as explained in U.S. patent application Ser. No. 17/388,818, filed Jul. 29, 2021. Neural thresholds of still evoked potentials are possible. Note also that ENTs as described here also comprise a type of physiological threshold in that it comprises a threshold (e.g., of current amplitude) that causes a physiological response (a detectable ECAP response) in the patient.

Even though ENT values may have some variability, the inventors have noticed based on empirical measurements that ENTs as measured in a given system vary predictably with physiological thresholds such as pth and dth otherwise determined by the system. This is shown in FIG. 9, which shows data taken from different patients. For each patient, an extracted neural threshold (ENT) was measured. Each patient's perception threshold pth (top graph) and discomfort threshold dth (bottom graph) were also determined as described above. As the figures shown, both pth and dth show a significant correlation to ENT. Specifically, using curve fitting (e.g., least squared) techniques, a mathematical relationship 140a between pth and ENT has been determined, and a mathematical relationship 140b between dth and ENT has been determined. Notice that these relationships 140a and 140b do not comprise a mere scalar between ENT as measured and the therapeutic thresholds pth and dth (i.e., pth and dth are not just equal to c*ENT, where c is a constant). In this example, the relationships 140a and 140b are linear, but could be modelled as different functions (e.g., exponential s, logarithms, polynomials, etc.).

FIG. 10 shows a first algorithm 150 which can be used to measure ENTs, and to automatically estimate or calibrate one or more physiological thresholds such as pth or dth using the relationships 140a or 140b. In the example of FIG. 10, certain steps in the algorithm 150 are performed by an external device, such as a clinician programmer 70 or patient external controller 60. However, this is not strictly necessary, and instead the entirety of algorithm 150 can be performed within the IPG 100 itself (as programmed in its control circuitry 102), particularly if the relationships 140a or 140b are stored in the IPG 100. It is assumed here that algorithm 150 is initiated by the GUI at option 148 (FIG. 148). Note that aspects of algorithm 150 may be embodied in instructions stored in non-transitory computer readable media such as solid state, optical or magnetic memories, which may be included whole or in part in the external device or the IPG 100. Algorithm 150 may comprise part of the external device's software (e.g., 84, FIG. 4), and may be integrated with the software used to render the GUI 82.

In step 152, an ENT value is measured using stimulation parameters determined earlier for the patient. Specifically, and assuming option 148 is used to start the algorithm 150, the external device causes the IPG 100 to increase the amplitude I starting from zero, until a neural response such as an ECAP is detectable (either using extraction or visualization). The ENT could also be determined by decreasing I until ECAPs are no longer detectable. Because step 152 implicates use of the neural response algorithm 124, and because this algorithm 124 can also operate in part in the external device, step 152 may be performed at least in part in the external device or wholly within the IPG 100. Again, the neural response algorithm 124 can determine the ENT value using extraction or visualization techniques as described earlier.

In step 154, the determined ENT value is used to determine at least one neural threshold, such as pth (using relationship 140a) or dth (using relationship 140b). These relationships may be stored in the external device in conjunction with other aspects of algorithm 150. One skilled will understand that the physiological thresholds can be determined by entering the ENT value into the relationships 140a and 140b and solving for pth and/or dth. Again, if the relationships 140a and 140b are stored in the IPG 100, this step 154 can also be performed entirely within the IPG 100.

In step 156, the physiological thresholds pth and/or dth determined in step 156 are stored in the external device. In particular, the algorithm 150 may automatically populated these determined physiological thresholds into the threshold interface 136 of the GUI (FIG. 8).

At this point, an optional step 158 may be performed to confirm that the determined physiological thresholds are at proper values by testing them on the patient. This is simpler and faster than determining these thresholds as described above using a full amplitude sweep. For example, in a manual mode, the amplitude value is set to the determined pth value (say pth=I=4.8 mA) and tested on the patient, perhaps by manually moving the amplitude up and down a slight amount from this value. From this, a slightly different value for pth may be determined (e.g., pth=4.9 mA or 4.7 mA), and this would occur more quickly because a full range of amplitude values is not tested. This example in effect provides an estimated pth value, which can then be quickly updated based on testing. dth may be similarly tested and confirmed. In a more automated approach, a small range of amplitude values is swept around the determined thresholds (e.g., from 4.5 mA to 5.1 mA), with the patient pressing a button (e.g., at I=4.9 mA) when (in this example) he can first start to feel paresthesia. pth in this example would be calibrated from 4.8 to 4.9 mA.

At step 160, the physiological thresholds as so determined (and perhaps confirmed at step 158) are transmitted to the patient's external controller 60 or to the patient's IPG 10 directly. As noted above, these thresholds can be put to useful ends in controlling patient stimulation therapy. If algorithm 150 runs exclusively in the IPG 100, such transmission of the determined physiological thresholds would not be necessary.

FIG. 11 illustrates a manner in which the disclosed technique for determining physiological thresholds using ENT can be extended to include consideration of other stimulation parameters. The left graph in FIG. 11 shows a well-known strength-duration curve, which generally shows a relation between strength (e.g., amplitude I) and the duration (e.g., pulse width PW) necessary to recruit neural tissue and generate an action potential. This curve is typically defined by the rheobase (Irb) which generally comprises the minimal current amplitude that results in depolarization, and a chronaxie time (c) which essentially sets the time constant of the displayed curve. This strength-duration curve has been modeled in the literature using different mathematical equations, and two of them (Weiss-Lapicque, and Lapicque-Blair) are shown. ECAPs are the result of multiple action potentials triggered almost at the same time and added together to form the evoked compound action potential. It stands to reason that recruited neural tissue would cause ECAPs to issue, and therefore that ENTs (also measured in intensity or amplitude) would follow these same curves, as shown in the right graph of FIG. 11. As such, ENTs can be modelled as a function of duration (pulse width), using the same constants (Irh, c) present in the strength-duration equations.

This suggests to the inventor that it may be beneficial to measure ENTs at more than one pulse width. Doing so allows a mathematical relationship 170 to be determined relating ENT values and pulse widths (i.e., ENT=f(PW)). This is shown in further detail in FIG. 12, where ENT values have been measured for different pulse widths: (PW, ENT)=(50 μs, 5 mA), (100 μs, 3 mA), and (300 μs, 1 mA). Using the Weiss-Lapicque equation and curve fitting techniques, values for the rheobase (Irh=0.2 mA) and the chronaxie time (c=1200 μs) can be determined. In other words, a relationship 170 is determined for the patient which relates ENTs to various pulse widths for their stimulation—i.e., ENT=0.2 (1+1200/PW).

Establishing relationship 170 is useful in the context of the disclosed technique, because it allows physiological thresholds like pth and dth to be estimated for different pulse widths, and algorithm 180 in FIG. 12 shows an example of the use of such information. In the example of FIG. 12, certain steps in the algorithm 180 are performed by an external device, such as a clinician programmer 70 or patient external controller 60. However, this is not strictly necessary, and instead the entirety of algorithm 180 can be performed within the IPG 100 itself (as programmed in its control circuitry 102), particularly if the relationships 140a, 140b, and 170 are stored in the IPG 100. It is again assumed here that algorithm 180 is initiated by the GUI at option 148 (FIG. 148). Like algorithm 150, algorithm 180 may be embodied in instructions stored in non-transitory computer readable media.

In step 182, an ENT value is measured using stimulation parameters determined earlier for the patient, but with different pulse widths. Specifically, and assuming option 148 is used to start the algorithm 150, the external device may provide an instruction 200 on the GUI 82 instructing the clinician to provide stimulation at a next (first) pulse width value, as shown in FIG. 8. This first pule width value (e.g., 50 μs) can be entered using the stimulation parameter interface 132. The clinician can then select instruction 200 to measure the ENT for this pulse width. As before, the external device can cause the IPG 100 to increase the amplitude I until an ECAP is detectable (either using extraction or visualization), or can decreasing I until ECAPs are no longer detectable. The user can then enter a next pulse width to test (e.g., 100 μs), and measure the ENT at this pulse width by again selecting instruction 200, etc. This results in building a data table 200 of (PW, ENT) values, as shown in FIG. 8, which data table can be stored in the external device. It should be understood that step 182 essentially involves test stimulation in the sense that such stimulation may involve testing at pulse widths that aren't necessarily therapeutically optimal for the patient.

Step 184 determines the ENT=f(PW) relationship 170 using the data in data table 200. This step was described earlier with respect to FIG. 11. Once relationship 170 is determined, it can be stored in the external deice in step 186.

Next is step 188, a therapeutic pulse width to be used for the patient is entered into the GUI (again using stimulation parameters interface 132 for example). In the depicted example, this pulse width value is 200 μs, which is assumed here to be the pulse width that has otherwise been deemed optimal to provide therapeutic stimulation for the patient. While an ENT value could be measured at this optimal pulse width, this is not necessary, because the ENT at PW=200 μs can be estimated using relationship 170 as just determined, which occurs at step 190. In this example, it is assumed using relationship 170 that ENT=1.6 mA at PW=200 μs.

From this estimated ENT value, and at step 192, one or more physiological thresholds like pth or dth can be estimated using the relationship 140a and 140b described earlier. For example purposes, it is only assumed that a single physiological threshold (pth) is determined at step 192. Plugging ENT=1.6 mA into relationship 140a yields pth=1.50, which as before can be auto-populated in GUI 82 at threshold interface 136 (FIG. 8). This determined value for pth can be optionally confirmed at step 194, similar to what was described earlier at step 158 in FIG. 10, and as before can be transmitted to the patient external controller 60 or 10 to control stimulation to useful effect at step 196.

If later the pulse width of the patient's stimulation is changed (step 196), the physiological threshold(s) can be automatically adjusted without need to take further ENT measurements, because relationships 170, 140a, and/or 140b can be used to adjust the threshold(s). In this regard, and as shown in FIG. 12, algorithm 180 can revert back to step 190, where a new ENT value is predicted at the new pulse width using relationship 170, and at step 192 a new physiological threshold(s) (e.g., pth) can be determined using the new ENT value using relationship 140a. In short, algorithm 180 is able to estimate physiological thresholds such as pth and dth using both measured ENT values and pulse width. As was the case earlier, aspects of algorithm 180 can be executed both at the external device and the IPG 100.

To summarize, algorithm 180 (FIG. 12) is more flexible than algorithm 150 (FIG. 10) in that physiological thresholds can be calibrated for a wider range of potential variations in a patient's stimulation program, and in particular when the pule width of the pulses is varied. However, in either case, physiological thresholds are determined automatically, and based on objective ENT measurements, which makes determining these physiological thresholds easier for both the clinician and the patient. It also allows physiological thresholds to be updated without the need for intervention by the clinician. For example, physiological thresholds such as pth and dth can be adjusted on the fly by the patient, or even automatically by the system. In this regard, note that the algorithms 150 can also operate at least in part on a patient's external controller 60. The controller 60 can automatically periodically run either of algorithms 150 or 180 to measure ENTs (possibly at different pulse widths), and to adjust physiological thresholds accordingly, which in turn affects the patient's stimulation. Adjusting dth at the external controller 60 can limit the amplitude I the patient can prescribe, which keeps the patient safe and comfortable. Adjusting pth at the external controller 60 helps to ensure for example that the patient's stimulation will reliably remain sub-perception or supra-perception by constrain the amplitude that the patient can prescribe, etc.

While described in the context of determining physiological thresholds such as pth and dth, it should be understood that the disclosed techniques may also be used to determine target values for stimulation. In this regard, an optimal stimulation amplitude I for a patient can relate to physiological thresholds such as pth and dth. For example, an optimal stimulation amplitude I may comprise pth, a percentage of pth (e.g., I=70% pth), or a particular value between pth and dth (e.g., a midpoint value such as pth+[dth−pth/2]). Because physiological thresholds pth and dth can be determined using ENTs as described above, and because a desired amplitude threshold I can be based on or predicted using pth and/or dth, ENTs can be used to predict and/or adjust amplitude I.

Although particular embodiments of the present invention have been shown and described, the above discussion is not intended to limit the present invention to these embodiments. It will be obvious to those skilled in the art that 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 alternatives, modifications, and equivalents that may fall within the spirit and scope of the present invention as defined by the claims.

Automatic Calibration in an Implantable Stimulator Device Having Neural Sensing Capability

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