Ai/ml-based closed-loop spinal cord stimulation (scs)

Abstract

A method comprising receiving, by a machine learning system, evoked compound action potential (ECAP) signals from a spinal cord stimulation device implanted in a patient, wherein the machine learning system continuously monitors biomarkers of the patient through the ECAP signals and automatically modifies stimulation parameters of the spinal cord stimulation device based on the monitored biomarkers, wherein the machine learning system receives Internet of Things (IoT) data from a plurality of IoT devices and trains a machine learning model using the IoT data to generate optimized programming parameters for the spinal cord stimulation device, and wherein the machine learning system clusters patients into groups based on at least one of medical conditions and demographics to generate additional insights for the optimized programming parameters.

Dependencies are inferred from the claim text.