Zahra Soltani

Papers

Total Citations

H-Index

About

Zahra Soltani is a robotics and rehabilitation researcher whose work bridges the gap between automated systems and physical therapy. Her primary research areas include physiotherapy robotics, human-robot interaction, and rehabilitation engineering. Soltani’s most notable contribution is the development of physiotherapy algorithms for the FUM-Physio robot, introduced in her 2022 paper, which has garnered 3 citations. This work outlines algorithms for passive motion, isotonic, isometric, isokinetic, and spring-movement exercises—each experimentally validated to enhance robotic-assisted therapy. By translating clinical rehabilitation protocols into programmable robotic actions, Soltani’s research offers a scalable, precise alternative to manual therapy, potentially improving patient outcomes and therapist efficiency. Her achievements include pioneering the integration of diverse exercise modalities into a single robotic platform, a feat that underscores her innovative approach to automating rehabilitation. While still early in her career, Soltani’s focused contributions position her as an emerging voice in physiotherapy robotics, with implications for accessible, data-driven recovery solutions. Her work invites further exploration into adaptive algorithms and real-time feedback systems for patient-specific care.