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.

Abstract: Methods and systems for providing stimulation to a patient's brain using one or more electrode leads implanted in the patient's brain are described. The methods and systems use evoked potentials (EPs) and other indicators of therapeutic effectiveness/side effects to provide closed-loop control of the stimulation. Some embodiments involve recording EPs and using one or more features of the EPs to model how the stimulation activates networks within the patient's brain. A control algorithm can be used to maintain the network activation within a predetermined ranges.

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: The types of electrode leads that are connected to an implantable medical device are determined based on electrical parameters that are measured at the electrodes that are positioned on the leads. The different types of known electrode leads have different physical electrode arrangements that impact the measured electrical parameters. Properties in the measured electrical parameters that are indicative of the physical arrangements of electrodes of known types of electrode leads are utilized to determine the types of leads that are connected to the implantable medical device.

Abstract: An example of a neurostimulation system may include a stimulation output circuit to deliver neurostimulation to evoke responses from a patient using an evoking configuration, a sensing input circuit to sense one or more signals including the evoked responses using a recording configuration, and a control circuit. The control circuit may be configured to control the delivery of the neurostimulation using stimulation parameters including the evoking configuration, to control the sensing of the evoked responses using sensing parameters including the recording configuration, and to determine an evoking-recording parameter set by evaluating a sequence of evoking-recording parameter sets. The evoking-recording parameter set may include a set of the stimulation parameters suitable for controlling the stimulation output circuit to deliver the neurostimulation to evoke a target response and a set of the sensing parameters suitable for controlling the sensing input circuit to record the evoked target response.

Abstract: Techniques are described for providing a therapeutic pseudo-constant DC current in an implantable stimulator using pulses whose positive and negative phases are not charge balanced. Such charge imbalanced pulses act to charge any capacitance in the current path between selected electrode nodes, such as the DC-blocking capacitors and/or any inherent capacitance such as those present at the electrode/tissue interface. These charged capacitances act during quiet periods between the pulses to induce a pseudo-constant DC current. Beneficially, these DC currents can be small enough to stay within charge density limits and hence not corrode the electrode or cause tissue damage, and further can be controlled to stay within such limits or for other reasons. Graphical user interface (GUI) aspects for generating the charge imbalanced pulses and for determining and/or controlling the pseudo-constant DC current are also provided.

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: The types of electrode leads that are connected to an implantable medical device are determined based on electrical parameters that are measured at the electrodes that are positioned on the leads. The different types of known electrode leads have different physical electrode arrangements that impact the measured electrical parameters. Properties in the measured electrical parameters that are indicative of the physical arrangements of electrodes of known types of electrode leads are utilized to determine the types of leads that are connected to the implantable medical device.

Abstract: Methods and systems for using evoked neural response to inform aspects of deep brain stimulation therapy are disclosed. According to some embodiments, a series of evoked neural response signals are recorded, and one or more waveform features are extracted from each of the signals. The waveform features can be used as biomarkers and or control signals for informing aspects of the therapy, such as lead implantation/localization, optimization of stimulation parameters, and/or closed loop feedback for maintaining chronic therapy. Embodiments include a check to determine and classify if any of the recorded neural response signals or portions thereof are corrupted. In the event that any of the signals are corrupted, values for the waveform features for the corrupted signals are interpolated using uncorrupted neural response signals in the series and/or uncorrupted portions of the problem neural response signal.

Abstract: This document discusses a medical system for coupling to one or more implantable electrodes. The medical system includes a sensing circuit, memory, and processing circuitry. The sensing circuit is configured to sense one or more neural signal representative of neural activity of a subject when connected to an implantable electrode of the one or more implantable electrodes, and the memory is to store a reference signal that is representative of a neural response associated with a state of arousal at or near an anatomical location of the implantable electrode. The processing circuitry is configured to compare the one or more sensed neural signals to the reference signal, and to determine a depth of anesthesia of the subject according to the comparison of the one or more sensed neural signals and the reference signal.

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.