Abstract: An apparatus and method are disclosed for providing efficient stimulation. As an example, a switched mode power supply can be configured to generate a dynamic compliance voltage based on a stimulus waveform that can be non-rectangular. An output stimulation signal can be supplied to one or more outputs based on the compliance voltage.

Abstract: This document discloses, among other things, systems and methods for determining volume of activation for spinal cord stimulation (“SCS”) using a finite element model (FEM) circuit to determine a FEM of an implanted electrode and a spinal cord in which the electrode is implanted, a Fourier FEM solver circuit to calculate a potential distribution in the spinal cord using information from the FEM circuit and a capacitive component of at least one of the implanted electrode and the spinal cord, and a volume of activation (VOA) circuit to predict a VOA using the potential distribution and a neuron model.

Abstract: One embodiment provides a computer-implemented method that includes storing a volume of tissue activation (VTA) data structure that is derived from analysis of a plurality of patients. Patient data is received for a given patient, the patient data representing an assessment of a patient condition. The VTA data structure is evaluated relative to the patient data to determine a target VTA for achieving a desired therapeutic effect for the given patient.

Abstract: A computer-implemented method for determining the volume of activation of neural tissue. In one embodiment, the method uses one or more parametric equations that define a volume of activation, wherein the parameters for the one or more parametric equations are given as a function of an input vector that includes stimulation parameters. After receiving input data that includes values for the stimulation parameters and defining the input vector using the input data, the input vector is applied to the function to obtain the parameters for the one or more parametric equations. The parametric equation is solved to obtain a calculated volume of activation.

Abstract: A computer-assisted method can include defining a target volume of tissue activation to achieve a desired therapeutic effect for an identified anatomic region. At least one parameter can be computed for an electrode design as a function of the defined target volume of tissue activation. The computed at least one parameter can be stored in memory for the electrode design, which parameter can be utilized to construct an electrode.

Abstract: One embodiment provides a computer-implemented method that includes storing a volume of tissue activation (VTA) data structure that is derived from analysis of a plurality of patients. Patient data is received for a given patient, the patient data representing an assessment of a patient condition. The VTA data structure is evaluated relative to the patient data to determine a target VTA for achieving a desired therapeutic effect for the given patient.

Abstract: This document discusses, among other things, brain stimulation models, systems, devices, and methods, such as for deep brain stimulation (DBS) or other electrical stimulation. In an example, volumetric imaging data representing an anatomical volume of a brain of a patient can be obtained and transformed to brain atlas data. A patient-specific brain atlas can be created using the inverse of the transformation to map the brain atlas data onto the volumetric imaging data and a volume of influence can be calculated using the patient-specific brain atlas. In certain examples, the volume of influence can include a predicted volume of tissue affected by an electrical stimulation delivered by an electrode at a corresponding at least one candidate electrode target location.

Abstract: This document discusses, among other things, brain stimulation models, systems, devices, and methods, such as for deep brain stimulation (DBS) or other electrical stimulation. In an example, volumetric imaging data representing an anatomical volume of a brain of a patient can be obtained and transformed to brain atlas data. A patient-specific brain atlas can be created using the inverse of the transformation to map the brain atlas data onto the volumetric imaging data and a volume of influence can be calculated using the patient-specific brain atlas. In certain examples, the volume of influence can include a predicted volume of tissue affected by an electrical stimulation delivered by an electrode at a corresponding at least one candidate electrode target location.

Abstract: A cognitive and/or motor skill testing system and method may include a processor that records respective time information for each of multiple positions of a display device that are traced during administration of a test, that determines speed and/or velocity values based on the recorded time information, and that outputs test result information based on the determined values. The test result information may be based on a comparison between a graphed curve of such values to an ideal curve. The positions may correspond to a path between displayed targets whose size and/or distance therebetween depend on past test performance. The system and/or method may output a change expected with a change to therapy parameters for a patient, where the expected change is determined based on changes which occurred in other patients having similar test results and therapy parameters as those of the patient.

Abstract: An apparatus is disclosed for providing efficient stimulation. As an example, a variable compliance regulator can be connected to supply a compliance voltage to a power supply rail, which compliance voltage can vary dynamically based on a stimulus waveform. A pulse generator can be configured to provide an output waveform to one or more output based on the stimulus waveform for delivery of electrical therapy.

Abstract: This document discusses, among other things, systems and methods for determining volume of activation for deep brain stimulation (“DBS”) using a finite element model (FEM) circuit to determine a FEM of an implanted electrode and a tissue medium in which the electrode is implanted, a Fourier FEM solver circuit to calculate a potential distribution in the tissue medium using information from the FEM circuit and a capacitive component of at least one of the implanted electrode and the tissue medium, and a volume of activation (VOA) circuit to predict a VOA using the potential distribution and a neuron model.

Abstract: This document discusses, among other things, systems and methods for determining volume of activation for deep brain stimulation (“DBS”) using a finite element model (FEM) circuit to determine a FEM of an implanted electrode and a tissue medium in which the electrode is implanted, a Fourier FEM solver circuit to calculate a potential distribution in the tissue medium using information from the FEM circuit and a capacitive component of at least one of the implanted electrode and the tissue medium, and a volume of activation (VOA) circuit to predict a VOA using the potential distribution and a neuron model.

Abstract: A system and method can provide for conducting a stimulation of anatomic regions to treat a neuromotor, neurocognitive or neuromotor and neurocognitive disorder, according to which stimulation, motor regions are stimulated, while creep of current to non-motor regions is minimized. Stimulation parameters can be selected based on at least one dual task test that involves cognitive and motor functions, wherein the motor function is postural stability.

Abstract: method for identifying and activating specific axonal pathways for achieving therapeutic benefits during a neural stimulation, such as deep brain stimulation. Clinical data, diffusion tensor tractography, and computer models of patient-specific neurostimulation may be used to identify particular axonal pathways activated by deep brain stimulation and to determine their correlations with specific clinical outcomes.

Abstract: One embodiment provides a computer-implemented method that includes storing a volume of tissue activation (VTA) data structure that is derived from analysis of a plurality of patients. Patient data is received for a given patient, the patient data representing an assessment of a patient condition. The VTA data structure is evaluated relative to the patient data to determine a target VTA for achieving a desired therapeutic effect for the given patient.

Abstract: This document discusses, among other things, brain stimulation models, systems, devices, and methods, such as for deep brain stimulation (DBS) or other electrical stimulation. In an example, a target volume of activation (VOA) can be received, a test VOA can be simulated, and at least one of a target electrode location or parameter can be provide using a relationship between the target VOA and the test VOA.

Abstract: A computer-implemented method for determining the volume of activation of neural tissue. In one embodiment, the method uses one or more parametric equations that define a volume of activation, wherein the parameters for the one or more parametric equations are given as a function of an input vector that includes stimulation parameters. After receiving input data that includes values for the stimulation parameters and defining the input vector using the input data, the input vector is applied to the function to obtain the parameters for the one or more parametric equations. The parametric equation is solved to obtain a calculated volume of activation.

Abstract: A system and method may provide for conducting a stimulation of anatomic regions to treat a neuromotor, neurocognitive or neuromotor and neurocognitive disorder, according to which stimulation, motor regions are stimulated, while creep of current to non-motor regions is minimized. Stimulation parameters may be selected based on tests of motor function, tests of cognitive function, and tests of a combination of motor and cognitive functions.

Abstract: This document discloses, among other things, systems and methods for determining volume of activation for spinal cord stimulation (“SCS”) using a finite element model (FEM) circuit to determine a FEM of an implanted electrode and a spinal cord in which the electrode is implanted, a Fourier FEM solver circuit to calculate a potential distribution in the spinal cord using information from the FEM circuit and a capacitive component of at least one of the implanted electrode and the spinal cord, and a volume of activation (VOA) circuit to predict a VOA using the potential distribution and a neuron model.

Abstract: This document discusses, among other things, brain stimulation models, systems, devices, and methods, such as for deep brain stimulation (DBS) or other electrical stimulation. A model computes a volume of influence region for a simulated electrical stimulation using certain stimulation parameters, such as amplitude, pulsewidth, frequency, pulse morphology, electrode contact selection or location, return path electrode selection, pulse polarity, etc. The model uses a non-uniform tissue conductivity. This accurately represents brain tissue, which has highly directionally conductive neuron pathways yielding a non-homogeneous and anisotropic tissue medium. In one example, the non-uniform tissue conductivity is obtained from diffusion tensor imaging (DTI) data. In one example, a second difference of an electric potential distribution is used to define a volume of activation (VOA) or similar volume of influence.