OBJECTIVE: Pilot study to evaluate computer-guided deep brain stimulation (DBS) programming designed to optimize stimulation settings using objective motion sensor-based motor assessments. MATERIALS AND METHODS: Seven subjects (five males; 54-71 years) with @entity191 ( @entity191 ) and recently implanted DBS systems participated in this pilot study. Within two months of lead implantation, the subject returned to the clinic to undergo computer-guided programming and parameter selection. A motion sensor was placed on the index finger of the more affected hand. Software guided a monopolar survey during which monopolar stimulation on each contact was iteratively increased followed by an automated assessment of @entity400 and @entity2845 . After completing assessments at each setting, a software algorithm determined stimulation settings designed to minimize symptom severities, side effects, and battery usage. RESULTS: Optimal DBS settings were chosen based on average severity of motor symptoms measured by the motion sensor. Settings chosen by the software algorithm identified a therapeutic window and improved @entity400 and @entity2845 by an average of 35.7% compared with baseline in the "off" state (p < 0.01). CONCLUSIONS: Motion sensor-based computer-guided DBS programming identified stimulation parameters that significantly improved @entity400 and @entity2845 with minimal clinician involvement. Automated motion sensor-based mapping is worthy of further investigation and may one day serve to extend programming to populations without access to specialized DBS centers.

Computer-Guided Deep Brain Stimulation Programming for XXXX .

@entity2845 :: ('MESH:D018476', 'Disease') :: ['bradykinesia'] @entity400 :: ('MESH:D014202', 'Disease') :: ['tremor'] @entity191 :: ('MESH:D010300', 'Disease') :: ['PD', "Parkinson's disease"]
@entity191 :: (MESH:D010300,Disease) :: ['Parkinson's Disease']
