Abstract: Techniques are disclosed to automate determination of therapy parameter values for adaptive deep brain stimulation (aDBS). A medical device may determine differences in power values between a present and a previous power value. Based on the difference being greater than or equal to a threshold value, the medical device may iteratively adjust a present therapy parameter value until the difference in the power values between a present and a previous power value is less than the threshold value.

Abstract: Techniques are described to determine a location of at least one oscillatory signal source in a patient. Processing circuitry may determine expected electrical signal levels based on a hypothetical location of the at least one oscillatory signal source. Processing circuitry may determine the electrical signal levels and determine an error value based on the expected electrical signal levels and the determined electrical signal levels. Processing circuitry may adjust the hypothetical location of the at least one oscillatory signal source until the error value is less than or equal to a threshold value, including the example where the error value is minimized.

Abstract: Techniques are described determining electrodes that are proximate or distal to location of an oscillatory signal source in a patient based on current source densities (CSDs). Processing circuitry may determine, for one or more electrodes of a plurality of electrodes, respective time-varying measurements of CSDs, aggregate, for the one or more electrodes of the plurality electrodes, the respective time-varying measurements of the CSDs to generate respective average level values for the one or more electrodes of the plurality of electrodes, determine, for one or more electrodes of the plurality of electrodes, respective phase-magnitude representations of the time-varying measurements of the CSDs. The respective phase-magnitude representations are indicative of respective magnitudes and phases of a particular frequency component of respective time-varying measurements of the CSDs.

Abstract: Techniques are disclosed for using probabilistic entropy to select electrodes with fewer artifacts for controlling adaptive electrical neurostimulation. In one example, a plurality of electrodes sense bioelectrical signals of a brain of a patient. Processing circuitry determines, for each bioelectrical signal sensed at a respective electrode of the plurality of electrodes, a probabilistic entropy value of the bioelectrical signal. The processing circuitry compares each of the respective probabilistic entropy values of the bioelectrical signal to respective entropy threshold values and selects, based on the comparisons, a subset of electrodes of the plurality of electrodes. The processing circuitry controls, based on the bioelectrical signals sensed via respective electrodes of the subset of electrodes and excluding the bioelectrical signals of the plurality of bioelectrical signals sensed via respective electrodes not in the subset of electrodes, delivery of electrical stimulation therapy to the patient.

Abstract: Techniques are described to determine a location of at least one oscillatory signal source in a patient. Processing circuitry may determine expected electrical signal levels based on a hypothetical location of the at least one oscillatory signal source. Processing circuitry may determine the electrical signal levels and determine an error value based on the expected electrical signal levels and the determined electrical signal levels. Processing circuitry may adjust the hypothetical location of the at least one oscillatory signal source until the error value is less than or equal to a threshold value, including the example where the error value is minimized.

Abstract: Techniques are disclosed for using probabilistic entropy to select electrodes with fewer artifacts for controlling adaptive electrical neurostimulation. In one example, a plurality of electrodes sense bioelectrical signals of a brain of a patient. Processing circuitry determines, for each bioelectrical signal sensed at a respective electrode of the plurality of electrodes, a probabilistic entropy value of the bioelectrical signal. The processing circuitry compares each of the respective probabilistic entropy values of the bioelectrical signal to respective entropy threshold values and selects, based on the comparisons, a subset of electrodes of the plurality of electrodes. The processing circuitry controls, based on the bioelectrical signals sensed via respective electrodes of the subset of electrodes and excluding the bioelectrical signals of the plurality of bioelectrical signals sensed via respective electrodes not in the subset of electrodes, delivery of electrical stimulation therapy to the patient.

Abstract: Techniques are described determining electrodes that are proximate or distal to location of an oscillatory signal source in a patient based on current source densities (CSDs). Processing circuitry may determine, for one or more electrodes of a plurality of electrodes, respective time-varying measurements of CSDs, aggregate, for the one or more electrodes of the plurality electrodes, the respective time-varying measurements of the CSDs to generate respective average level values for the one or more electrodes of the plurality of electrodes, determine, for one or more electrodes of the plurality of electrodes, respective phase-magnitude representations of the time-varying measurements of the CSDs. The respective phase-magnitude representations are indicative of respective magnitudes and phases of a particular frequency component of respective time-varying measurements of the CSDs.

Abstract: Techniques are disclosed to automate determination of therapy parameter values for adaptive deep brain stimulation (aDBS). A medical device may determine differences in power values between a present and a previous power value. Based on the difference being greater than or equal to a threshold value, the medical device may iteratively adjust a present therapy parameter value until the difference in the power values between a present and a previous power value is less than the threshold value.

Abstract: Systems, methods and apparatus for determining and/or programming stimulation settings for a pulse generator capable of steering current to a deep brain stimulation array are disclosed. Individual patient brain geometry and lead specific geometry data can be used to generate a maximum activation function curve. Optimization methods can be used to find stimulation settings that are as close as possible to achieving the value of the maximum activation function curve.

Abstract: Systems and methods for programming multi-electrode neuromodulation systems, with applications for at least deep brain stimulation (DBS) therapy. One or more configurations can be generated and presented to a user for selection. The selected configurations can be settings for programming a pulse generator. The one or more configurations can be Pareto optimal in terms of one or more objective values and can be generated using a particle swarm optimization. The generated configurations can be visualized on a Pareto front for user selection. Objective values can include minimizing power use, maximizing activation of neural pathways and/or regions of interest, minimizing activation of neural pathways and or regions of avoidance, and maximizing or minimizing the distance to sources of sensed functional data.

Abstract: Systems and methods for programming multi-electrode neuromodulation systems, with applications for at least deep brain stimulation (DBS) therapy. One or more configurations can be generated and presented to a user for selection. The selected configurations can be settings for programming a pulse generator. The one or more configurations can be Pareto optimal in terms of one or more objective values and can be generated using a particle swarm optimization. The generated configurations can be visualized on a Pareto front for user selection. Objective values can include minimizing power use, maximizing activation of neural pathways and/or regions of interest, minimizing activation of neural pathways and or regions of avoidance, and maximizing or minimizing the distance to sources of sensed functional data.

Abstract: Systems, methods and apparatus for determining and/or programming stimulation settings for a pulse generator capable of steering current to a deep brain stimulation array are disclosed. Individual patient brain geometry and lead specific geometry data can be used to generate a maximum activation function curve. Optimization methods can be used to find stimulation settings that are as close as possible to achieving the value of the maximum activation function curve.