Artificial intelligence in deep brain stimulation for movement disorders: a systematic review and technology readiness assessment.
Artificial intelligence in deep brain stimulation for movement disorders: a systematic review and technology readiness assessment.
Where did the research take place?
The study site has not been established. Author addresses may differ from where the research occurred.
Sfax, TN · Author affiliation
Department of Neurosurgery, Military University Hospital of Sfax, Sfax, Tunisia.Location evidence
FR · Author affiliation · country only
Institut du Neurone, Montferrier sur Lez, France.Location evidence
Edinburgh, GB · Author affiliation
Edinburgh Medical School, University of Edinburgh, Edinburgh, UK.Location evidence
London, GB · Author affiliation
Functional Neurosurgery Unit, Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, UK.Location evidence
Lausanne, CH · Author affiliation
Department of Clinical Neuroscience, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.Location evidence
Grenoble, FR · Author affiliation
Department of Neurosurgery, CHU of Grenoble and Grenoble Alpes University, Grenoble, France.Location evidence
Milan, IT · Author affiliation
Department of Biomedical Sciences, Humanitas University, Milan, Italy.Location evidence
Umeå, SE · Author affiliation
Department of Clinical Science, Neuroscience, Umeå University, Umeå, Sweden.Location evidence
Hannover, DE · Author affiliation
Department of Neurosurgery, Hannover Medical School, Hannover, Germany.Location evidence
Berlin, DE · Author affiliation
Department of Neurology, Charité- Universitätsmedizin Berlin, Berlin, Germany.Location evidence
Geneva, CH · Author affiliation
Neuro-X Institute, Ecole Polytechnique Fédérale de Lausanne, Geneva, Switzerland.Location evidence
Würzburg, DE · Author affiliation
Department of Neurology, Julius Maximilians University Hospital Würzburg, Würzburg, Germany.Location evidence
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Original abstract
Artificial intelligence (AI) is increasingly explored across deep brain stimulation (DBS) for movement disorders, yet whether current systems are approaching deployment remains unclear. To characterise their scope, validation maturity, and translational readiness, we systematically evaluated 239 peer-reviewed studies published between 2000 and 2025, assessing AI methods, validation practices, and barriers constraining clinical translation. Research was dominated by Parkinson's disease and subthalamic nucleus targeting, with limited coverage of other disorders and targets. Most studies reported encouraging internal performance; however, external validation was rare, evaluations remained predominantly retrospective and single-centre, and more than one-quarter involved small-sample, high-dimensional datasets with elevated overfitting risk. Technology readiness assessment revealed that most systems remain at early-to-intermediate translational stages, constrained more by limited validation than by algorithmic inadequacy, compounded by the biological heterogeneity and dynamic complexity inherent to DBS. Nevertheless, emerging external and prospective studies suggest a field moving toward clinical maturity, with promising applications in targeting, programming, outcome prediction, and adaptive therapy delivery.