The adaptive deep brain stimulation challenge

Mattia Arlotti, Manuela Rosa, Sara Marceglia, Sergio Barbieri, Alberto Priori

Research output: Contribution to journalArticlepeer-review


Sub-optimal clinical outcomes of conventional deep brain stimulation (cDBS) in treating Parkinson's Disease (PD) have boosted the development of new solutions to improve DBS therapy. Adaptive DBS (aDBS), consisting of closed-loop, real-time changing of stimulation parameters according to the patient's clinical state, promises to achieve this goal and is attracting increasing interest in overcoming all of the challenges posed by its development and adoption. In the design, implementation, and application of aDBS, the choice of the control variable and of the control algorithm represents the core challenge. The proposed approaches, in fact, differ in the choice of the control variable and control policy, in the system design and its technological limits, in the patient's target symptom, and in the surgical procedure needed. Here, we review the current proposals for aDBS systems, focusing on the choice of the control variable and its advantages and drawbacks, thus providing a general overview of the possible pathways for the clinical translation of aDBS with its benefits, limitations and unsolved issues.

Original languageEnglish
Pages (from-to)12-17
Number of pages6
JournalParkinsonism and Related Disorders
Publication statusPublished - 2016


  • Adaptive deep brain stimulation
  • Basal ganglia local field potentials
  • Control variable
  • Parkinson's disease

ASJC Scopus subject areas

  • Geriatrics and Gerontology
  • Clinical Neurology
  • Neurology


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