SBIR-STTR Award

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

The objective is to engineer, build, and clinically validate DBS-Expert, an expert system for optimizing postoperative programming of deep brain stimulation (DBS) in patients with movement disorders such as Parkinson's disease (PD). The clinical utility of DBS for treatment of PD is well established. However, great outcome disparity exists among recipients due to varied postoperative management, particularly concerning DBS programming optimization. Many programmers have only a cursory understanding of electrophysiology and lack expertise and/or time required to determine an optimal set of DBS parameters from thousands of possible combinations. DBS-Expert will improve outcomes and equalize care across the country for patients not in close proximity to DBS specialty centers. The primary innovations include 1) automated functional mapping based on objective motion sensor-based motor assessments that will intelligently navigate the DBS parameter space to guide the programming session and 2) intelligent algorithms that will find a set of parameters that optimize for efficacy while minimizing side effects and battery usage. The clinically deployable DBS-Expert system will include wireless wearable motion sensors, a tablet software app, and secure cloud storage. The app will include a simple interface to guide the programming session, collect all sensor and stimulation data, and adjust DBS settings. For typical use, the system will start by performing automated monopolar survey to determine the patient-specific 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 and simplify subsequent adjustment sessions. In Phase I, subjects with PD wore our existing Kinesia motion sensor while prototype software guided an automated monopolar survey. Stimulation was incrementally increased at each contact until symptoms stopped improving or side effects appeared. Search algorithms were successfully developed to automatically identify optimal DBS stimulation parameters. Parameters chosen by the algorithms improved symptoms by nearly 36% or maintained therapeutic benefits while reducing stimulation amplitude to decrease battery usage. Phase II will include 1) developing an app to integrate the successful Phase I prototype functional mapping software with DBS IPG programmer communication protocols to streamline use, 2) a multi-center clinical evaluation to optimize specific functional mapping protocols and parameter space navigation algorithms, and 3) integration of the optimal search algorithm and bidirectional communication protocols into a commercially viable product. We hypothesize DBS-Expert will improve patient outcomes, access to care, clinician and patient experience, battery usage, and frequency and duration of follow-up programming sessions compared to traditional programming practices.

Public Health Relevance Statement:


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 intelligent algorithms to determine a set of programming parameters that maximize symptomatic benefits while minimizing side effects and battery consumption.

NIH Spending Category:
Assistive Technology; Bioengineering; Brain Disorders; Clinical Research; Neurodegenerative; Neurosciences; Parkinson's Disease; Rehabilitation

Project Terms:
Address; Adverse effects; Affect; Algorithms; Anatomy; base; Boston; Bradykinesia; Caring; Clinic; Clinical; Communication; Computer software; Consumption; Country; Data; Data Collection; Deep Brain Stimulation; Dyskinetic syndrome; electric field; Electric Stimulation; Electrophysiology (science); Engineering; experience; Expert Systems; follow-up; Frequencies (time pattern); Future; Gait; Health Services Accessibility; Home environment; Imagery; Implant; improved; innovation; Lead; Letters; Manufacturer Name; Maps; Measures; Medical; medical specialties; Modeling; Motion; Motor; Movement Disorders; Multi-Institutional Clinical Trial; neurotechnology; Outcome; Parkinson Disease; Patients; Phase; Phase III Clinical Trials; Physiologic pulse; Population; Postoperative Period; Process; product development; programs; Protocols documentation; prototype; public health relevance; Recording of previous events; research clinical testing; response; Saint Jude Children's Research Hospital; Secure; sensor; Shapes; Site; Surveys; symptomatic improvement; Symptoms; System; Tablets; Techniques; Therapeutic; Time; Tissues; Tremor; Validation; visual map; Width; Wireless Technolog