Takenao Sugi

Saga University

Papers

14

Total Citations

117

H-Index

6

About

Takenao Sugi is a researcher whose work sits at the compelling intersection of biomedical signal processing, human-machine interaction, and assistive robotics. His most significant contributions center on harnessing biological signals — particularly electromyogram (EMG) and electrooculogram (EOG) — to develop intuitive control systems for individuals with physical disabilities. Sugi's pioneering work on "My Spoon," a meal assistance robot driven by EMG signals, has been especially impactful, with related publications accumulating dozens of citations and demonstrating practical pathways toward restoring independence for motor-impaired patients. His development of adaptive threshold methods for EMG onset detection and finite state machine architectures for real-time robot control represent elegant technical solutions to the challenge of translating subtle muscle activity into reliable, actionable commands. Beyond assistive feeding devices, Sugi has extended his expertise to teleoperation systems incorporating visual servo control and hands-free mobile robot operation using combined EOG/EMG sensing. His earlier foundational work on nonlinear separation models for industrial controller design (1999, 24 citations) reflects a career grounded in rigorous control theory. Collectively, Sugi's research meaningfully advances rehabilitation engineering and human-centered robotics, offering real-world tools that enhance quality of life for people with limited mobility.

Research Focus

Key Achievements

6
H-Index
14
Papers
117
Total Citations
8
Avg Citations/Paper
🏆 Most Cited Paper
A methodology for designing controllers for industrial systems based on nonlinear separation model and control
24 citations · 1999
📈 Most Prolific Year: 2017 (2 Papers)
🤝 Key Collaborators: 24
🏛 Institutions: Saga University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago