Faranak Akbarifar
Papers
2
Total Citations
16
H-Index
2
About
Faranak Akbarifar is a researcher advancing the intersection of artificial intelligence, robotics, and clinical neurology, with a primary focus on stroke rehabilitation and motor impairment assessment. Her work addresses critical limitations in conventional clinical evaluations, which often rely on subjective visual and physical assessments that miss subtle neurological deficits. Akbarifar’s major contributions include pioneering the use of virtual reality-augmented robotic systems for computer-aided identification of stroke-associated motor impairments, offering objective, quantifiable movement measurements. More recently, she has developed innovative methods using evidential networks and uncertainty-based refinement to optimize stroke detection, achieving 12 citations for this 2025 work alone. Her research demonstrates how interactive robotic devices and AI-driven uncertainty modeling can enhance diagnostic precision and treatment evaluation. With a growing citation impact, Akbarifar’s work is shaping the future of neurorehabilitation by providing clinicians with more sensitive, data-driven tools for assessing post-stroke deficits and guiding personalized therapy.
Research Focus
Key Achievements
Top Papers
- 1
- 2