Probabilistic entropy for detection of periodic signal artifacts
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.
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