Papers
32
Total Citations
489
H-Index
13
About
Izumi Kondo is a prominent researcher whose work spans rehabilitation robotics, assistive care technology, and, more recently, AI-driven human-robot collaboration. With a career dedicated to improving quality of life for older adults and individuals with neurological conditions, Kondo has made foundational contributions to the development and clinical evaluation of robotic systems in healthcare settings. Kondo's early work, including a 2012 preliminary trial of postural strategy training for patients with central nervous system disorders, laid the groundwork for subsequent high-impact studies. A 2017 cross-over trial demonstrating the superiority of balance exercise assist robot (BEAR) training over conventional methods for frail older adults garnered 61 citations, establishing clinical credibility for therapeutic robotics. His sustained focus on transfer support robots in nursing facilities — examining caregiver burden reduction, verbal communication outcomes, and long-term deployment — reflects a rigorous, real-world approach to assistive technology adoption. More recently, Kondo has extended his reach into socially assistive robots for dementia care and large language model-enhanced robot manipulation, the latter accumulating 77 citations since 2024. Across over a decade of research, his work has collectively shaped evidence-based frameworks for integrating robots into clinical and care environments, influencing both engineering design and frontline healthcare practice.
Research Focus
Key Achievements
Top Papers
- 1Enhancing the LLM-Based Robot Manipulation Through Human-Robot Collaboration77 citations · 2024
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