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About

Jingke Song is an emerging researcher specializing in rehabilitation robotics, with a particular focus on ankle rehabilitation mechanisms and human-machine motion compatibility. His work addresses a critical challenge in assistive robotics: designing systems that authentically replicate the complex biomechanics of the human ankle joint to improve therapeutic outcomes. Song's most significant contributions center on the development of novel 4-degree-of-freedom (4-DOF) parallel mechanisms that incorporate dual virtual motion centers — an innovative approach that more faithfully mirrors the ankle's true anatomical architecture. His 2023 paper, which has garnered 9 citations, introduced a configuration design and kinematic performance analysis framework that advances how rehabilitation robots align with natural human movement. Subsequent work in 2025 further refined dimensional synthesis methodologies and explored human-ankle instantaneous finite helical axis (IFHA) identification to deepen kinematic characterization. Though early in his career, Song's research is gaining traction within the rehabilitation engineering community, accumulating 16 citations across three publications within just two years. His interdisciplinary approach — bridging biomechanics, mechanism design, and robotics — positions him as a promising contributor to the next generation of clinically effective, anatomically intelligent rehabilitation devices.