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About

Yuko Ohno is a pioneering researcher at the intersection of robotics, rehabilitation engineering, and human–robot interaction. Her work centers on developing assistive robots that enhance mobility and care, with a particular focus on sit-to-stand (STS) movement assistance—a critical daily activity for elderly and disabled individuals. Ohno’s major contributions include fault classification methods for nursing care robots using discriminant analysis (30 citations), quantitative evaluation of self-reliance support robots through relative phase analysis (22 citations), and biosignal-based relaxation assessment for head-care robots (9 citations). She has also advanced tactile sensing for minimally invasive surgery through compound eye type endoscopes (8 citations) and developed attachable standing-assist robots for motorized beds (4 citations). Her recent work (2025) explores spatial muscle synergy networks to model STS transitions with and without robotic assistance, demonstrating her ongoing commitment to understanding the biomechanical and psychological dimensions of human–robot collaboration. With cumulative citations exceeding 80 and a consistent focus on user-centered evaluation—including fault detection during psychologically challenging movements—Ohno’s research is shaping safer, more responsive assistive technologies for aging populations and rehabilitation settings.