Machine learning for adaptive deep brain stimulation in Parkinson's disease: closing the loop.

ABSTRACT: Parkinson's disease (PD) is the second most common neurodegenerative disease bearing a severe social and economic impact. So far, there is no known disease modifying therapy and the current available treatments are symptom oriented. Deep Brain Stimulation (DBS) is established as an effective treatment for PD, however current systems lag behind today's technological potential. Adaptive DBS, where stimulation parameters depend on the patient's physiological state, emerges as an important step towards "smart" DBS, a strategy that enables adaptive stimulation and personalized therapy. This new strategy is facilitated by currently available neurotechnologies allowing the simultaneous monitoring of multiple signals, providing relevant physiological information. Advanced computational models and

SUBMITTER: Oliveira AM 

PROVIDER: S-EPMC10576725 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature