Method and system for automated neuromodulation through machine learning

Abstract

An automated neuromodulation system which uses patient feedback during a training phase in combination with machine learning to automatically provide optimal nerve stimulation parameters based on the patient's needs without patient input. The automated neuromodulation system generally includes a lead which is implanted in a patient for treatment of a wide range of conditions, such as chronic pain. The patient is provided with a remote control through which the patient may provide either positive or negative feedback relating to how the patient is responding to electrical stimulation in different situations. A control unit monitors feedback from the patient as well as information and data from the time of feedback, such as the patient's position, orientation, speed of movement, or other considerations. Using machine learning, the control unit may process the feedback and data to formulate an optimized neuromodulation protocol and criteria which may be automatically applied to the patient.