The objective is to design, build, and clinically assess DBS-Expert, an expert system for optimizing the postoperative programming of deep brain stimulation (DBS) systems in patients with movement disorders such as Parkinson's disease (PD). DBS-Expert will use motion sensor based assessments to develop a functional map and algorithms for navigating the programming parameter space that maximize symptomatic benefits while minimizing side effects and battery consumption. The clinical utility of DBS for the treatment of movement disorders such as PD is well been established. However, there is a great disparity in outcomes among DBS recipients due to varied postoperative management, particularly concerning DBS programming optimization. Most programmers have only a cursory understanding of electrophysiology and lack the expertise or time required to determine an optimal set of DBS parameters (contact, polarity, frequency, pulse width, and amplitude) out of the thousands of possible combinations. DBS-Expert will remove the guesswork from programming and take the responsibility out of the hands of the clinicians by providing an expert system that efficiently determines appropriate DBS settings. DBS-Expert will be designed for use by a general practitioner or nurse rather than by a neurologist or neurophysiologist with years of experience in DBS programming and disease management. For the first postoperative programming session, the DBS-Expert will perform an automated monopolar survey. The patient will wear our existing motion sensor unit and perform motor assessments at various DBS settings. Stimulation will be incrementally increased from zero at each contact until symptoms stop improving as measured by a motion sensor unit or side effects appear. The monopolar survey will help determine the functional anatomy around the lead site and narrow the search space for determining an optimal set of programming parameters. This therapeutic window will be valuable at the initial postoperative programming session as well as all future adjustment sessions. In Phase I, we aim to demonstrate technical feasibility by developing software for automated functional mapping of the DBS programming parameter space and clinical feasibility by developing algorithms that efficiently navigate the programming parameter space and output settings that reduce symptoms, side effects, and battery usage as well or better than would an expert clinician programmer. Ten subjects with PD and a DBS implant will participate in a clinical study in which the DBS-Expert prototype guides the subjects through assessments as part of a constant-current monopolar review. A functional map will be developed and algorithms will determine an optimal set of DBS settings. Subject symptom severities, side effects, and battery usage will be compared to that of an experience DBS programmer. The final DBS-Expert system resulting from Phase I and II development will greatly expand the accessibility of DBS for patients not located near specialized centers by removing the programming burden from a few expert clinicians thereby equalizing care across the country.
Public Health Relevance: The clinical utility of deep brain stimulation (DBS) for the treatment of movement disorders such as Parkinson's disease has been well established; however, there is a great disparity in outcomes among DBS recipients due to varied postoperative management, particularly concerning the choosing of an optimal set of programming parameters from the thousands of possible combinations. The proposed system will use motion sensor based assessments to develop a functional map and algorithms to determine a set of programming parameters that maximize symptomatic benefits while minimizing side effects and battery consumption.
Public Health Relevance Statement: The clinical utility of deep brain stimulation (DBS) for the treatment of movement disorders such as Parkinson's disease has been well established; however, there is a great disparity in outcomes among DBS recipients due to varied postoperative management, particularly concerning the choosing of an optimal set of programming parameters from the thousands of possible combinations. The proposed system will use motion sensor based assessments to develop a functional map and algorithms to determine a set of programming parameters that maximize symptomatic benefits while minimizing side effects and battery consumption.
NIH Spending Category: Bioengineering; Brain Disorders; Clinical Research; Neurodegenerative; Neurosciences; Parkinson's Disease; Rehabilitation
Project Terms: Address; Adverse effects; Affect; Algorithms; Anatomy; base; Bradykinesia; Caring; Clinic; Clinical; Clinical Research; Computer software; Consumption; cost efficient; Country; Deep Brain Stimulation; design; Development; Diagnostic; Disease Management; Dyskinetic syndrome; electric field; Electric Stimulation; Electrophysiology (science); experience; Expert Systems; Freedom; Frequencies (time pattern); Future; Gait; General Practitioners; Hand; Home environment; Implant; improved; Intelligence; Lead; Manufacturer Name; Maps; Measures; Modeling; Motion; Motor; Movement Disorders; Neurologist; neurotechnology; NIH Program Announcements; Nurses; Outcome; Output; Parkinson Disease; Patients; Phase; Physiologic pulse; Postoperative Period; Process; programs; prototype; response; sensor; Severities; Shapes; Site; software development; Software Tools; Specialized Center; success; Surveys; Symptoms; System; Technology; Therapeutic; Time; Tissues; tool; Tremor; Width
