Abstract: Systems and methods for optimizing neuromodulation field design for pain therapy are discussed. An exemplary neuromodulation system includes an electrostimulator to stimulate target tissue to induce paresthesia, a data receiver to receive pain data including pain sites experiencing pain, and to receive patient feedback on the induced paresthesia including paresthesia sites experiencing paresthesia. The neuromodulation system includes a processor circuit configured to generate a spatial correspondence indication between the pain sites and the paresthesia sites over one or more dermatomes, determine an anodic weight and a cathodic weight for each of multiple electrode locations using the spatial correspondence indication, and generate a stimulation field definition for neuromodulation pain therapy.

Abstract: New waveforms for use in an implantable pulse generator or external trial stimulator are disclosed which mimic actively-driven biphasic pulses, and which are particularly useful for providing sub-perception Spinal Cord Stimulation therapy using low frequency pulses. The waveforms comprise anodic and cathodic pulses which are effectively monophasic in nature, although low-level, non-therapeutic charge recovery can also be used.

Abstract: An implantable stimulator can control delivery of the neurostimulation to a patient according to a stimulation configuration and adjust the stimulation configuration by using a closed-loop control algorithm. In an example, the system may include a remote controller (RC) configured for use by the patient. The RC may transmit stimulator adjustment information to the implantable stimulator. The stimulator adjustment information may include direct control adjustment information for adjusting the stimulation configuration and adaptation adjustment information for adjusting the closed-loop control algorithm. The RC may generate the stimulator adjustment information based on patient adjustment instructions.

Abstract: An example of a system for delivering neurostimulation may include a programming control circuit and a stimulation control circuit. The programming control circuit may be configured to generate stimulation parameters controlling delivery of the neurostimulation according to a stimulation configuration. The stimulation control circuit may be configured to specify the stimulation configuration, and may include volume definition circuitry and stimulation configuration circuitry. The volume definition circuitry may be configured to determine one or more test volumes, determine a clinical effect resulting from the one or more test volumes each being activated by the neurostimulation, and determine a target volume using the determined clinical effect. The stimulation configuration circuitry may be configured to generate the specified stimulation configuration for activating the target volume.

Abstract: An example of a system to program a neuromodulator to deliver neuromodulation to a neural target using a plurality of electrodes may comprise a programming control circuit configured to determine target energy allocations for the plurality of electrodes based on at least one target pole to provide a target sub-perception modulation field, and normalize the target sub-perception modulation field, including determine a time domain scaling factor to account for at least one property of a neural target or of a neuromodulation waveform, and apply the time domain scaling factor to the target energy allocations.

Abstract: Methods and systems for spinal cord stimulation (SCS) are disclosed. The methods and systems involve using electrode leads implanted within the patient's spinal column to record neural responses evoked by the stimulation. The disclosed neural responses are different in several respects from electrical responses that have previously been measured in the context of SCS, such as stimulation artifacts and evoked compound action potentials (ECAPs). The disclosed neural responses typically occur later in time following the evoking stimulation pulse. Another distinguishing feature is that disclosed neural responses are generally most prominently observed with consistent, relatively unchanging amplitudes when the evoking stimulation frequency is ultra-low, for example, about 10 Hz or less.

Abstract: A sensing electrode selection algorithm is disclosed for use with an implantable pulse generator having an electrode array. The algorithm automatically selects optimal sensing electrodes in the array to be used with a pre-determined stimulation therapy appropriate for the patient. The algorithm preferably senses stimulation artifacts using different sensing electrodes, and more specifically different sensing electrode pairs as is appropriate when differential sensing is used. The algorithm further preferably senses these stimulation artifacts with the patient placed in two or more postures. The algorithm processes the stimulation artifact features measured at the different sensing electrodes and at the different postures to automatically determine one or more sensing electrode pairs that best distinguishes the two or more postures given the prescribed stimulation therapy.

Abstract: Methods and systems for providing neuromodulation therapy are disclosed. The methods and systems are configured to sense an evoked neural response and use the evoked neural response as feedback for providing neuromodulation therapy. Methods of reducing stimulation artifacts that obscure the sensed evoked neural response are disclosed. The methods of artifact reduction include recording a stimulation artifact in the absence of an evoked neural response, aligning and scaling the stimulation artifact with respect to the obscured signal, and subtracting the aligned and scaled artifact from the obscured signal.

Abstract: Methods and systems for providing closed loop control of stimulation provided by an implantable stimulator device are disclosed herein. The disclosed methods and systems use a neural feature prediction model to predict a neural feature, which is used as a feedback control variable for adjusting stimulation. The predicted neural feature is determined based on one or more stimulation artifact features. The disclosed methods and systems can be used to provide closed loop feedback in situations, such as sub-perception therapy, when neural features cannot be readily directly measured.

Abstract: An example of a neurostimulation system may include a storage device for storing data representing physiological signals and a user interface including a user input, a display screen, and a presentation control circuit. The user input may be configured to receive a selection of signal(s) from the physiological signals and a selection of viewing mode from viewing modes including a metric mode and/or a presence mode. The metric mode allows for visualization of a signal property indicated by a parameter measured from the selected signal(s). The presence mode allows for viewing presence of a feature in the selected signal(s). The presentation control circuit may be configured to allow for the selection of the signal(s) and the viewing mode, to determine a segment of each of the selected signal(s) for presentation according to the selected viewing mode, and to present the determined segment on the display screen.

Abstract: An examples of a system for delivering neurostimulation to a patient may include a stimulation output circuit configured to deliver the neurostimulation, a sensing circuit configured to sense a neural signal indicative of neural responses to the neurostimulation, and stimulation control circuit. The stimulation control circuit may be configured to control the delivery of the neurostimulation using a plurality of stimulation parameters and may be configured to detect morphological features of the neural responses, to produce a neural response parameter using the detected morphological features, to detect a change in the sensed neural signal, to analyze the produced neural response parameter for attributing the detected change to one of a neural activation change in the patient or a body movement of the patient, and to control a dynamically controlled stimulation parameter of the plurality of stimulation parameters using the sensed neural signal and an outcome of the analysis.

Abstract: Systems and methods for closed-loop control of electrostimulation based on signal features derived from evoked neural activities are disclosed. A system comprises an electrostimulator to deliver a stimulation therapy, a sensing circuit to sense an evoked response induced by the stimulation therapy, and a controller circuit to identify, from a plurality of candidate signal features, a target signal feature that satisfies a performance criterion for distinguishing a first stimulation effect according to a first stimulation setting from a second stimulation effect according to a different second stimulation setting. The target signal feature can be identified based on evaluations of a discrimination metric for each of the candidate signal features. The controller circuit can determine a value of the target signal feature from the sensed evoked response, and control the electrostimulator to adjust the stimulation therapy based on the value of the target signal feature.

Abstract: Methods and systems for providing neuromodulation therapy are disclosed. The systems include an Implantable Pulse Generator (IPG) or External Trial Stimulator (ETS) that is capable of sensing an Evoked Compound Action Potential (ECAP), and (perhaps in conjunction with an external device) is capable of adjusting a stimulation program while based on the sensed ECAP. The stimulation program may include a pre-pulse component that may be adjusted based on the sensed ECAP. Moreover, stimulation may be applied to neural elements timed to coincide with the arrival of ECAPs at those neural elements. The stimulation may enhance or suppress activation of those neural elements.

Abstract: A system for delivering electrical pulse stimulation to a subject includes a remote control device configured to at least intermittently transmit temporal pulse pattern programming and a stimulation device comprising a control interface, at least one electrode in electrical communication with the control interface, and an input device in at least intermittent communication with the remote control device to receive the temporal pulse pattern programming. The stimulation device is configured to deliver electrical pulse stimulation to a subject via the at least one electrode according to the temporal pulse pattern programming.

Abstract: Methods and systems for spinal cord stimulation (SCS) are disclosed. The methods and systems involve using electrode leads implanted within the patient's spinal column to record neural responses evoked by the stimulation. The disclosed neural responses are different in several respects from electrical responses that have previously been measured in the context of SCS, such as stimulation artifacts and evoked compound action potentials (ECAPs). The disclosed neural responses typically occur later in time following the evoking stimulation pulse. Another distinguishing feature is that disclosed neural responses are generally most prominently observed with consistent, relatively unchanging amplitudes when the evoking stimulation frequency is ultra-low, for example, about 10 Hz or less.

Abstract: Methods and systems are described 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 system and method for extracting a cardiac signal from a spinal signal include measuring a spinal signal at one or more electrodes that are connected to a neurostimulator and implanted within a patient's spinal canal and processing the spinal signal to extract the cardiac signal, which includes features that are representative of the patient's cardiac activity. Processing the spinal signal to extract the cardiac signal can include filtering the spinal signal, or use of model reduction schemes such as independent component analysis. The extracted cardiac signal can include a number of features that correspond to an electrocardiogram and can be used to determine the patient's heart rate and/or to detect a cardiac anomaly. Cardiac features that are determined from the cardiac signal can additionally be used to adjust parameters of the stimulation that is provided by the neurostimulator.

Abstract: Methods and systems are described 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: This document discusses a computer-implemented method of calibration of an implantable neurostimulation device. The method includes sensing one or more symptoms of a neurological condition of a subject using a sensor external to the neurostimulation device; delivering neurostimulation to the subject using the neurostimulation device and adjusting neurostimulation parameters based on the sensed symptom; sensing one or more neural response signals resulting from the neurostimulation using a sensor of the neurostimulation device; correlating the sensed symptom with the one or more sensed neural response signals; determining a target neural response using the correlating; and recurrently adjusting the neurostimulation parameters according to a comparison of subsequently sensed neural response signals to the target neural response signal.

Abstract: An example of a system for delivering neurostimulation and sensing one or more signals may include a programming control circuit and a parameter control circuit. The programming control circuit may be configured to control the delivery of the neurostimulation according to stimulation parameters and the sensing of a target neural signal including target neural responses according to sensing parameters. The parameter control circuit may be configured to determine the stimulation parameters and the sensing parameters and may include a recording analyzer. The recording analyzer may be configured to evaluate a sequence of test recording configurations each including a set of recording configuration parameters selected from the stimulation parameters and the sensing parameters and to determine one or more recording configurations suitable for detection of the target neural responses using an outcome of the evaluation.