Scott E. Cooper

University of Minnesota

Papers

1

Total Citations

38

H-Index

1

About

Scott E. Cooper is a leading researcher in the clinical optimization of deep brain stimulation (DBS) for Parkinson’s disease, with a focus on streamlining the critical but labor-intensive process of parameter adjustment. His most-cited work, "Semi-automated approaches to optimize deep brain stimulation parameters in Parkinson’s disease" (2021, 38 citations), directly addresses a major bottleneck in DBS therapy: the trial-and-error programming that can delay symptom relief. By developing and evaluating semi-automated algorithms, Cooper’s research aims to replace subjective, time-consuming clinician adjustments with data-driven, efficient protocols. This contribution holds significant promise for improving patient outcomes, reducing clinic burden, and making DBS more accessible. His work bridges computational modeling and clinical neurology, demonstrating how technology can enhance precision in neuromodulation. Cooper’s efforts represent a pivotal step toward personalized, automated DBS programming, marking him as a key innovator in the field of movement disorders and neuroengineering.

Research Focus

Key Achievements

1
H-Index
1
Papers
38
Total Citations
38
Avg Citations/Paper
🏆 Most Cited Paper
Semi-automated approaches to optimize deep brain stimulation parameters in Parkinson’s disease
38 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: University of Minnesota

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago