Abstract: A method or system for facilitating the determining and setting of stimulation parameters for programming an electrical stimulation system using closed loop programming is provided. For example, pulse generator feedback logic is executed by a processor to interface with control instructions of an implantable pulse generator by incorporating one or more machine learning engines to automatically generate a proposed set of stimulation parameter values that each affect a stimulation aspect of the implantable pulse generator, receive one or more clinical responses and automatically generate a revised set of values taking into account the received clinical responses, and repeating the automated receiving of a clinical response and adjusting the stimulation parameter values taking the clinical response into account, until or unless a stop condition is reach or the a therapeutic response is indicated within a designated tolerance.

Abstract: An implantable electrical stimulation lead includes a lead body; terminals disposed along the proximal portion of the lead body; electrodes disposed along the distal portion of the lead body, the electrodes including at least one segmented electrode; and an asymmetric marker disposed along the distal portion of the lead body and including a first ring and a longitudinal band extending longitudinally from the first ring. The asymmetric marker and lead body are formed of different materials that are distinguishable from each other in the radiological images to facilitate radiological determination of the rotational orientation of the lead when implanted. The marker may also include one or more of a longitudinal extension, a second ring, and non-straight longitudinal edges. The marker may also include the longitudinal band and longitudinal extension without a ring.

Abstract: Methods and systems for electrical stimulation can include obtaining a biosignal of the patient; altering at least one stimulation parameter of an electrical stimulation system in response to the biosignal; and delivering an electrical stimulation current to one or more selected electrodes of the electrical stimulation system using the at least one stimulation parameter. In some embodiments, a power spectrum is determined from the biosignal. In some embodiments, the biosignal is at least two different biosignals measured at the same or different locations on the patient and a coherence, correlation, or association between the two biosignal is determined.

Abstract: An electrical stimulation system includes an implantable control module configured and arranged for implantation in a body of a patient. The implantable control module includes a processor that generates and delivers electrical stimulation pulses or pulse bursts at a pathological frequency or with a temporal separation between pulses or pulse bursts individually selected based on a pre-determined distribution function based on a pre-selected pathological frequency.

Abstract: An electrical stimulation system includes an implantable control module configured and arranged for implantation in a body of a patient. The implantable control module includes a processor that generates and delivers electrical stimulation pulses or pulse bursts at a pathological frequency or with a temporal separation between pulses or pulse bursts individually selected based on a pre-determined distribution function based on a pre-selected pathological frequency.

Abstract: An example of a system for programming a neurostimulator may include a storage device and a pattern generator. The storage device may store a pattern library and one or more neuronal network models. The pattern library may include fields and waveforms of neuromodulation. The one or more neuronal network models may each be configured to allow for evaluating effects of one or more fields in combination with one or more waveforms in treating one or more indications for neuromodulation, and may include a region of interest (ROI) model representing a specified ROI including a neural target and divided into a plurality of sub-regions. The pattern generator may be configured to construct and approximately optimize a spatio-temporal pattern of neurostimulation and/or its building blocks using at least one neuronal network model.

Abstract: An example of a system for programming a neurostimulator may include a storage device and a pattern generator. The storage device may store a pattern library and one or more neuronal network models. The pattern library may include fields and waveforms of neuromodulation. The one or more neuronal network models may each be configured to allow for evaluating effects of one or more fields in combination with one or more waveforms in treating one or more indications for neuromodulation. The one or more neuronal network models may include a first pain model configured to allow for optimization of neurostimulation using paresthesia, the second pain model configured to allow optimization of neurostimulation using anatomy. The pattern generator may be configured to construct and approximately optimize a spatio-temporal pattern of neurostimulation and/or its building blocks using at least one or more of the first pain model or the second pain model.

Abstract: An example of a system for programming a neurostimulator may include storage device and a pattern generator. The storage device may store a pattern library and one or more neuronal network models. The pattern library may include fields and waveforms of neuromodulation. The one or more neuronal network models may each be configured to allow for evaluating effects of one or more fields in combination with one or more waveforms in treating one or more indications for neuromodulation. The pattern generator may be configured to construct and approximately optimize a spatio-temporal pattern of neurostimulation and/or its building blocks for a specified range of varying conditions using at least one neuronal network model.

Abstract: An example of a system for programming a neurostimulator may include a storage device and a pattern generator. The storage device may store a pattern library and one or more neuronal network models. The pattern library may include fields and waveforms of neuromodulation. The one or more neuronal network models may each be configured to allow for evaluating effects of one or more fields in combination with one or more waveforms in treating one or more indications for neuromodulation. The pattern generator may be configured to construct and approximately optimize a spatio-temporal pattern of neurostimulation and/or its building blocks using at least one neuronal network model.

Abstract: An example of a system for programming a neurostimulator may include a storage device and a pattern generator. The storage device may store a pattern library and one or more neuronal network models. The pattern library may include fields and waveforms of neuromodulation. The one or more neuronal network models may each be configured to allow for evaluating effects of one or more fields in combination with one or more waveforms in treating one or more indications for neuromodulation. The pattern generator may be configured to construct and approximately optimize a spatio-temporal pattern of neurostimulation and/or its building blocks using at least one neuronal network model. The spatio-temporal pattern of neurostimulation may include a series of sub-patterns for treating an indication of the one or more indications for neuromodulation.

Abstract: A method for electrical stimulation of a patient includes a) implanting at least a portion of an electrical stimulation lead; b) stimulating the patient using the electrical stimulation lead at multiple test stimulation amplitudes; c) observing a response for each of the test stimulation amplitudes; d) selecting a working stimulation amplitude based on the responses from a group consisting of the test stimulation amplitudes and, optionally, a default stimulation amplitude; e) stimulating the patient using the electrical stimulation lead and the working amplitude at multiple test duty cycles; f) observing a response for each of the test duty cycles; g) selecting a working duty cycle based on the responses from a group consisting of the test duty cycles and, optionally, a default duty cycle; and h) stimulating the patient using the electrical stimulation lead, the working amplitude, and the working duty cycle.

Abstract: A method and system for identifying a rotational orientation of an implanted electrical stimulation lead utilize radiological images of the lead. The lead has an asymmetric marker with a longitudinal band extending around a portion of the circumference of the lead. The method and system includes obtaining radiological images of the lead; generating an isosurface image from the radiological images and displaying the isosurface image on a display device, where the isosurface image comprises an image of the longitudinal band of the marker; identifying a bulge in the isosurface image corresponding the longitudinal band of the marker; and determining a rotational orientation of the lead based on the rotational orientation of the bulge in the isosurface image.

Abstract: An example of a system may include a processor and a memory device comprising instructions, which when executed by the processor, cause the processor to: access a patient metric of a subject; use the patient metric as an input to a machine learning algorithm, the machine learning algorithm to search a plurality of neuromodulation parameter sets and to identify a candidate neuromodulation parameter set of the plurality of neuromodulation parameter sets, the candidate neuromodulation parameter set designed to produce a non-regular waveform that varies over a time domain and a space domain; and program a neuromodulator using the candidate neuromodulation parameter set to stimulate the subject.

Abstract: Systems and methods for determining a rotational orientation of a lead for use in electrostimulation of a body tissue are disclosed. A system may receive image data of at least a portion of the lead including image data of a marker configured to identify a rotational orientation of the lead. The system may receive at least one template of the lead having a specified rotational orientation. Each template may include a reference data cube and a reference marker direction vector. The system may generate a target data cube of the marker using the image data of the marker, and register the reference data cube to the target data cube to produce a transformation operator. The system may estimate the rotational orientation of the lead using the reference marker direction vector and the determined transformation operator.

Abstract: A system for identifying potential portions of a body in which electrical stimulation to treat a condition or disorder affects at least one symptom of the condition or disorder, stimulation effect, or side effect performs the following acts: obtaining, for each of multiple stimulation instances, an estimation of a region of the body stimulated during the stimulation instance and a score for each of at least one symptom, stimulation effect, or stimulation side effect; and determining, for each of multiple portions of the body using the scores and the estimates in a permutation test, a likelihood that stimulation of that portion of the body affects at least one symptom, stimulation effect, or stimulation side effect. In other embodiments, the system sets up a relationship between the outcomes of stimulation and influence of a particular part of the body on the outcome, and derives this influence using a pseudoinverse.

Abstract: An electrical stimulation system includes an implantable control module configured and arranged for implantation in a body of a patient. The implantable control module includes a processor that generates and delivers electrical stimulation pulses or pulse bursts at a pathological frequency or with a temporal separation between pulses or pulse bursts individually selected based on a pre-determined distribution function based on a pre-selected pathological frequency.

Abstract: Methods and systems for electrical stimulation can include obtaining a biosignal of the patient; altering at least one stimulation parameter of an electrical stimulation system in response to the biosignal; and delivering an electrical stimulation current to one or more selected electrodes of the electrical stimulation system using the at least one stimulation parameter. In some embodiments, a power spectrum is determined from the biosignal. In some embodiments, the biosignal is at least two different biosignals measured at the same or different locations on the patient and a coherence, correlation, or association between the two biosignal is determined.

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: 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.