Abstract: Methods and systems for using sensed evoked neural responses for informing aspects of neurostimulation therapy are disclosed. Electrical signals may be recorded during the provision of electrical stimulation to a patient's neural tissue. The electrical signals may be processed and analyzed using one or more classification criteria to determine if the electrical signals contain a neural response of interest. Examples of such neural responses include evoked neural responses that are oscillatory and/or resonant in nature. If the electrical signals include such responses of interest, one or more features may be extracted from the signals and used as biomarkers for informing aspects of neurostimulation therapy, such as directing lead placement, optimizing stimulation parameters, closed-loop feedback control of stimulation, and the like. Various methods and systems described herein are particularly relevant in the context of multi-site stimulation paradigms, such as coordinated reset neuromodulation.

Abstract: Disclosed herein is a spinal implant with a solid frame and a porous inner layer. The implant may have a cavity defined by the porous inner layer. The solid frame may have one or more ribs extending from a medial wall to a lateral wall. The thickness of the porous layer may vary relative the thickness of the solid frame at various locations. An inserter to place a spinal implant and a method to perform same are also disclosed.

Abstract: A system may include an electrostimulator configured to provide electrostimulation to a neural target patient via electrodes on a lead, a sensing circuit configured to sense, at a plurality of sensing locations, evoked responses (ERs) to the electrostimulation, a user interface, and a controller operably connected to the electrostimulator, the sensing circuit and the user interface. The controller may be configured to deliver the electrostimulation in accordance with a stimulation setting, determine the sensed ERs to the electrostimulation delivered in accordance with a sensing setting and the stimulation setting, determine acceptance criteria using user input received via the user interface, compare the sensed ERs to the acceptance criteria to provide a comparison result, and display on the user interface an indicator of the comparison result.

Abstract: A method for adapting stimulation by a stimulation system to a change in a symptom, therapeutic effect, or side effect includes detecting a change in a symptom of a disease or disorder or in a therapeutic effect or a side effect of stimulation by the stimulation system; in response to the detecting, determining, by the stimulation system, a modification of one or more stimulation parameter values to adapt to the change in the symptom, the therapeutic effect, or the side effect; and at least one of the following: 1) suggesting to the patient or to a clinician adoption of the modification and, upon receiving affirmation from the patient or the clinician, stimulating the patient according to the modification of the one or more stimulation parameter values, or 2) automatically stimulating the patient according to the modification of the one or more stimulation parameter values.

Abstract: This document discusses a computer-implemented method of operating a neurostimulation device to deliver electrical neurostimulation when connected to an implantable stimulation lead. The method includes delivering neurostimulation to a subject that produces evoked potential signals, sensing the evoked potential signals resulting from the neurostimulation, detecting changes in the sensed evoked potential signals in response to a change in at least one of the number of repeated presentations of the neurostimulation or a change in a parameter of the first neurostimulation, and producing an indication of proximity of the stimulation lead to a preferred lead location according to the detected changes in the evoked potential signals.

Abstract: Methods and systems for using sensed evoked neural responses for informing aspects of neurostimulation therapy are disclosed. Electrical signals may be recorded during the provision of electrical stimulation to a patient's neural tissue. The electrical signals may be processed and analyzed using one or more classification criteria to determine if the electrical signals contain a neural response of interest. Examples of such neural responses include evoked neural responses that are oscillatory and/or resonant in nature. If the electrical signals include such responses of interest, one or more features may be extracted from the signals and used as biomarkers for informing aspects of neurostimulation therapy, such as directing lead placement, optimizing stimulation parameters, closed-loop feedback control of stimulation, and the like. Various methods and systems described herein are particularly relevant in the context of multi-site stimulation paradigms, such as coordinated reset neuromodulation.

Abstract: Methods and systems for planning a trajectory for implanting electrical stimulation leads in a patient's brain are described. The methods and systems rank candidate trajectories based on their expected therapeutic efficacies, as well as other criteria. Optimized stimulation parameters are determined for each of the candidate trajectories and therapeutic efficacies using the optimized parameters are predicted.

Abstract: An example a neurostimulation system may include one or more sensors configured to sense a measure of tissue heating caused by neurostimulation, a stimulation output circuit configured to deliver the neurostimulation, and a stimulation control circuit configured to control the delivery of the neurostimulation using stimulation parameters. The stimulation control circuit may include temperature sensing circuitry and stimulation parameter circuitry. The temperature sensing circuitry may be configured to receive the measure of tissue heating and to determine a temperature parameter representing a temperature or a temperature change using the received measure of tissue heating.

Abstract: Incorrect connection or mapping of leads' proximal terminals to the ports of an Implantable Stimulator Device (ISD), such as an implantable pulse generator or an external trial stimulator, is a concern, and this disclosure is directed to use of measurement and identification algorithms to either determine that leads are properly connected to their assigned ISD ports, or to determine which leads are connected to the ports even if the leads are not preassigned to the ports. Particular focus is given in the disclosed technique to assessing leads that comprise larger number of electrodes than are supported at each port, and thus have more than one proximal terminal that connect to more than one port of the ISD.

Abstract: An example of a system for delivering neurostimulation from a stimulation device may include a programming control circuit and a programming control circuit. The programming control circuit may be configured to generate information for programming the stimulation device to deliver the neurostimulation according to a pattern of neurostimulation pulses. The stimulation programming circuit may be configured to: receive goal option(s) selected from a plurality of goal options each including at least one goal for deep brain stimulation; select programmability option(s) associated with the received goal option(s) from a plurality of programmability options each allowing one or more aspects of the pattern of neurostimulation pulses and/or its delivery to be programmable; receive programming information required by the selected programmability option(s); and determine the pattern of neurostimulation pulses for the selected goal option(s) using the received programming information.

Abstract: Methods and systems for planning a trajectory for implanting electrical stimulation leads in a patient's brain are described. The methods and systems rank candidate trajectories based on their expected therapeutic efficacies, as well as other criteria. Optimized stimulation parameters are determined for each of the candidate trajectories and therapeutic efficacies using the optimized parameters are predicted.

Abstract: An example of a system for programming neurostimulation according to a stimulation configuration may include stimulation configuration circuitry, volume definition circuitry, stimulation effect circuitry, and recording circuitry. The stimulation configuration circuitry may be configured to determine the stimulation configuration. The volume definition circuitry may be configured to determine stimulation field model(s) (SFM(s)) each representing a volume of tissue activated by the neurostimulation. The stimulation effect circuitry may be configured to determine a stimulation effect type for each tagging point specified for the SFM(s) and to tag the SFM(s) at each tagging point with the stimulation effect type determined for that tagging point. The stimulation effect type for each tagging point is a type of stimulation resulting from the neurostimulation as measured at that tagging point.

Abstract: A computer implemented system and method provides a volume of activation (VOA) estimation model that receives as input two or more electric field values of a same or different data type at respective two or more positions of a neural element and determines based on such input an activation status of the neural element. A computer implemented system and method provides a machine learning system that automatically generates a computationally inexpensive VOA estimation model based on output of a computationally expensive system.

Abstract: Techniques and circuitry are disclosed that provide DC offset compensation to equate the DC values of the inputs to sense amp circuitry used to sense neural responses in a stimulator device. When a DC offset is present at the inputs to the sense amp circuitry, the stimulation circuitry is used to remove this DC offset by providing one or more charge imbalanced pulses that are either net cathodic or net anodic. Control of the stimulation circuitry can occur using a DC offset compensation algorithm programmed into control circuitry of the stimulator device. Use of the stimulation circuitry itself to provide DC offset compensation is beneficial because it is already present in the stimulator device, and is able to provide larger amplitude currents to remove the DC offset more quickly.

Abstract: An example of a system for programming neurostimulation according to a stimulation configuration may include stimulation configuration circuitry, volume definition circuitry, stimulation effect circuitry, and recording circuitry. The stimulation configuration circuitry may be configured to determine the stimulation configuration. The volume definition circuitry may be configured to determine stimulation field model(s) (SFM(s)) each representing a volume of tissue activated by the neurostimulation. The stimulation effect circuitry may be configured to determine a stimulation effect type for each tagging point specified for the SFM(s) and to tag the SFM(s) at each tagging point with the stimulation effect type determined for that tagging point. The stimulation effect type for each tagging point is a type of stimulation resulting from the neurostimulation as measured at that tagging point.

Abstract: A computer implemented system and method facilitates a cycle of generation, sharing, and refinement of volumes related to stimulation of anatomical tissue, such as brain or spinal cord stimulation. Such volumes can include target stimulation volumes, side effect volumes, and volumes of estimated activation. A computer system and method also facilitates analysis of groups of volumes, including analysis of differences and/or commonalities between different groups of volumes.

Abstract: Methods and systems for detecting if a stimulation lead implanted in a patient's brain has moved. Lead movement occurring between a first time and a second time may be determined by comparing features extracted from evoked potentials recorded at the two times. The disclosed methods and systems are particularly useful for determining if a stimulation lead has moved between the time it was implanted in the patient's brain and the time that stimulation parameters are being optimized. Lead movement during implantation, during parameter optimization, and during or between other lead optimization processes may be determined as well.

Abstract: A computer implemented system and method facilitates a cycle of generation, sharing, and refinement of volumes related to stimulation of anatomical tissue, such as brain or spinal cord stimulation. Such volumes can include target stimulation volumes, side effect volumes, and volumes of estimated activation. A computer system and method also facilitates analysis of groups of volumes, including analysis of differences and/or commonalities between different groups of volumes.

Abstract: Methods and systems for detecting if a stimulation lead implanted in a patient's brain has moved. Lead movement occurring between a first time and a second time may be determined by comparing features extracted from evoked potentials recorded at the two times. The disclosed methods and systems are particularly useful for determining if a stimulation lead has moved between the time it was implanted in the patient's brain and the time that stimulation parameters are being optimized. Lead movement during implantation, during parameter optimization, and during or between other lead optimization processes may be determined as well.

Abstract: A method for optimizing stimulation for a patient having a stimulator device such as a Deep Brain Stimulation (DBS) device is disclosed. Test stimulation is provided at initial combinations of lead positions and values of a stimulation parameter such as amplitude, neural potentials are measured for each combination, and a neural response score is determined using the measured neural potentials. A next combination of position and a value of the stimulation parameter to test is determined using the neural response scores. This process repeats iteratively until a stopping criterium is met. The neural response scores and then used determine optimal therapeutic stimulation for the patient. Neural response measurements can also be used to exclude certain positions or stimulation values during subsequent optimization testing.