Abstract: A system may include a training system configured for training or improving a nervous system by responding to an event. The training system may include a neuromodulator configured for delivering neuromodulation to a nervous system, an event detector configured for detecting the event and sending a signal to the neuromodulator when the event is detected, and a timer configured for timing a predefined time period after receiving the signal. The neuromodulator may be configured to change neuromodulation to the nervous system at the end of the time period. The predefined time period may be a programmable time period in some embodiments.

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: An example method of operating a neuromodulation device to modify or achieve a desired arousal state in a patient may include determining the patient's desired arousal state, detecting one or more signals that are related to the desired arousal state, where the one or more signals are sensed from the patient or provided by an external source. The method also includes determining, via a controller circuit, a therapy parameter setting for the neuromodulation device based on the one or more signals, and generating, via the controller circuit, a control signal in the neuromodulation device to initiate or adjust an arousal state therapy program in accordance with the therapy parameter setting.

Abstract: Method and systems are described for identifying electrodes for stimulation of a patient using a stimulation system. The stimulation system includes at least one stimulation lead implanted in a patient and having electrodes disposed thereon. The method includes obtaining a plurality of bioelectrical signals, wherein each of the bioelectrical signals is obtained using a different one, or a different combination, of the electrodes; analyzing a dataset including the bioelectrical signals to identify at least one fundamental component of the dataset, each of the at least one fundamental component identifying a contribution of one or more of the electrodes to the fundamental component; and using at least one of the at least one fundamental component to identify one or more of the electrodes for stimulation according to the contribution of each of the one or more of the electrodes to the at least one of the at least one fundamental component.

Abstract: Methods of providing electrical neural modulation to a patient's brain are disclosed herein. The methods involve differentially modulating two or more target regions of the brain. For example, a first target region may be provided with an electrical neural modulation signal that activates that target region while a second target region is provided with an electrical neural modulation signal that suppresses or deactivates that target region. As the implantable pulse generators (IPGs) described herein include independent current sources, such differential modulation can be provided with a single IPG.

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: 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: Systems and methods for optimizing electrostimulation in a patient is discussed. An exemplary system includes an implantable stimulator to provide electrostimulation, a programming device for in-clinic stimulation testing, an a therapy titration device for in-home therapy titration. In response to electrostimulation delivered in accordance with first stimulation settings defined in an electrode configuration and parameter value search space, the programing device evaluates patient clinical response in the patient, and determines a subspace of the search space based on the clinical response. During an in-home therapy titration phase, the therapy titration device can use cloud-based services to evaluate clinical responses to electrostimulation in accordance with candidate stimulation settings defined in the identified subspace.

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: 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: 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 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: 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 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 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 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 providing electrostimulation to a neural target are discussed. An example system comprises an implantable stimulator and a controller. The implantable stimulator can provide burst stimulation comprising a pulse train followed by a pulse-free period. The controller can detect an indication of frequency drift of an intrinsic oscillatory neural activity, and in response to the indication of frequency drift, calibrate a burst stimulation parameter including a burst frequency or a timing for initiating the burst stimulation at a particular phase of an oscillation cycle of the intrinsic oscillatory neural activity. The controller can generate a control signal to the implantable stimulator to generate burst stimulation in accordance with the calibrated burst stimulation parameter.

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.