Matthew Green
Papers
1
Total Citations
10
H-Index
1
About
Matthew Green is a leading researcher in computational biomechanics and rehabilitation robotics, with a primary focus on developing model-based approaches to improve upper extremity function recovery after stroke. His most cited work, "Computational modeling and simulation of closed chain arm-robot multibody dynamic systems in OpenSim" (2022, 10 citations), represents a foundational step toward integrating patient-specific neural control deficiencies into robot control algorithms. By leveraging OpenSim, an open-source musculoskeletal simulation platform, Green has pioneered methods for modeling the complex closed-chain dynamics between human arms and rehabilitation robots—a critical advancement for creating adaptive, personalized therapy systems. His research bridges the gap between multibody dynamics, neural control, and clinical rehabilitation, aiming to enhance robot-assisted therapy efficacy. Green's contributions are particularly notable for their translational potential: his models provide a framework for designing control algorithms that account for individual patient impairments, moving beyond one-size-fits-all robotic therapy. This work positions him at the forefront of next-generation rehabilitation technology, where computational modeling directly informs clinical practice.
Research Focus
Key Achievements
Top Papers
- 1