Elliana Ismail
Papers
2
Total Citations
8
H-Index
2
About
Elliana Ismail’s research lies at the intersection of robotics and neurorehabilitation, with a focused commitment to improving post-stroke recovery. Her work addresses two critical challenges in the field: the repetitive nature of rehabilitation exercises and the limited availability of therapists for long-term care. Ismail’s major contribution is the development of a hybrid controller for robot-assisted rehabilitation, which integrates the Chedoke-McMaster Stroke Assessment—a clinical tool for evaluating motor impairment—into an automated system. This innovation allows robotic devices to adapt therapy in real-time based on a patient’s functional status, moving beyond rigid, pre-programmed routines to deliver personalized, responsive treatment. Her most-cited paper, “A Hybrid Controller with Chedoke-McMaster Stroke Assessment for Robot-Assisted Rehabilitation” (2012, 6 citations), and its companion study (2 citations) lay the groundwork for more intelligent, patient-centered rehabilitation technologies. While her citation counts are modest, Ismail’s work is notable for its early and creative synthesis of clinical assessment scales with control engineering—a forward-thinking approach that anticipates the growing demand for adaptive, accessible robotic therapy. Her research offers a valuable blueprint for engineers and clinicians seeking to make rehabilitation both more effective and more widely available.
Research Focus
Key Achievements
Top Papers
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