Researchers at Amsterdam University Medical Centres deploy AI to analyse local field potentials recorded by Medtronic’s Percept PC deep brain stimulation system. By correlating spectral features from implanted electrodes with smartwatch kinematics and clinical ratings, they aim to generate patient‐specific neuronal fingerprints to optimize stimulation for Parkinson’s disease in real‐world settings.
Key points
- Longitudinal multimodal dataset of 100 Parkinson’s patients with sensing‐enabled STN DBS.
- AI algorithms correlate LFP spectral power and volatility with wearable kinematic metrics and UPDRS scores.
- Patient‐specific neuronal fingerprints drive development of adaptive, responsive DBS programming.
Why it matters: This AI‐driven approach represents a shift toward personalized, responsive brain stimulation, potentially improving efficacy and reducing side effects compared to continuous DBS.
Q&A
- What is a neuronal fingerprint?
- How does BrainSense Timeline work?
- Why use wearable inertial sensors?