Yazan Abdel Majeed
Papers
4
Total Citations
20
H-Index
4
About
Yazan Abdel Majeed investigates stroke rehabilitation, focusing on how technology can restore upper-limb function after neurological injury. His research centers on bimanual self-telerehabilitation, error augmentation, and the role of movement speed in recovery. In a landmark 2015 study (6 citations), he demonstrated that a three-week bimanual telerehabilitation program—functioning like an upper-extremity treadmill where the healthy arm cues the impaired one—can improve multivariate outcomes in chronic stroke survivors. His 2020 randomized crossover study (5 citations) revealed that robot-applied viscous forces can modify arm movement speed, a critical predictor of recovery potential. Notably, Majeed pioneered a robot-free approach to error augmentation by using distorted visual feedback to simulate forces (2019, 5 citations), expanding access to this promising therapy. His 2020 work identifying key mechanical work components as predictors of robotic therapy outcomes (4 citations) provides clinicians with measurable metrics for tailoring treatment. By bridging robotics, telerehabilitation, and novel visual feedback techniques, Majeed’s work offers practical, scalable solutions for stroke recovery, with his findings directly informing how therapists can optimize patient engagement and movement quality during rehabilitation.
Research Focus
Key Achievements
Top Papers
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- 3Stroke Rehabilitation with Distorted Vision Perceived as Forces5 citations · 2019
- 4