A Simulation Framework for Adaptive Closed-Loop Deep Brain Stimulation in Pathological Tremor Suppression

Parkinson’s disease and essential tremor cause disruptive shaking that can make everyday tasks difficult. Currently, deep brain stimulation (DBS) devices run continuously, which drains battery life and can sometimes cause unwanted side effects. In this study, we designed and simulated a smarter, adaptive DBS system. Instead of running all the time, it detects tremor signals in real time and delivers stimulation precisely timed to cancel out the shaking. Our simulation included a realistic tremor model and tested three different detection methods, combined with an adaptive controller that syncs stimulation with the tremor’s rhythm. Results showed that while accurate tremor detection remains a challenge, the adaptive approach could theoretically reduce tremor by ۶۸.۴% under ideal detection, all while using over ۴,۰۰۰ times less energy than conventional DBS. This work underscores how important timing is in effective tremor suppression and lays the groundwork for future energy-saving, responsive neurostimulation devices.

کلیدواژه ها:

Closed-loop DBS ، Neuromodulation ، Tremor suppression ، Phase-Locked control