Therapy for the treatment of disorders in the nervous system by means of classification of detected tremors through machine learning

A method, comprising the steps of:

• receiving, by processing circuitry (13), episode data for an episode stored by a medical device (11) of a patient (P), wherein the episode is associated with a period of time, and the episode data comprises an electroencephalogram or data derived from neural activity in the brain (B) sensed by the medical device (11) during the period of time;
• applying, by the processing circuitry (13), one or more machine learning models to the episode data, the one or more machine learning models configured to output a respective likelihood value for each of a plurality of tremor type classifications, each of the likelihood values representing a likelihood that the respective tremor type classification occurred at any point during the period of time;
• and
• based on the application of the one or more machine learning models to the episode data, deriving, by the processing circuitry (13) and for each of the tremor type classifications, class activation data indicating varying likelihoods of the classification over the period of time;
• and displaying, by the processing circuitry (13) and to a user, a graph of the varying likelihoods of the tremor type classifications over the period of time.