Hiu Hong Teo
Papers
1
Total Citations
2
H-Index
1
About
Dr. Hiu Hong Teo is a leading researcher in rehabilitation robotics and human–machine interaction, with a core focus on surface electromyography (sEMG) signal processing and machine learning for assistive technologies. Their most notable contribution is a pioneering framework for calibration-free sEMG intention recognition in upper-limb rehabilitation, which combines self-supervised temporal-spectral pretraining with adversarial domain alignment. This work, published in 2025 and already garnering 2 citations, addresses a critical bottleneck in practical rehabilitation robotics: the need for accurate, user-independent motion intention decoding without lengthy calibration sessions. By enabling robust cross-subject and cross-session generalization, Dr. Teo’s approach promises to make rehabilitation exoskeletons and prosthetics more intuitive and accessible. Their research bridges advanced deep learning techniques with real-world clinical needs, demonstrating how self-supervised learning can reduce data annotation burdens while adversarial alignment mitigates domain shifts. This work has significant implications for developing adaptive, patient-friendly rehabilitation systems. Dr. Teo’s contributions are shaping the future of intelligent assistive devices, where seamless human–robot collaboration can enhance recovery outcomes for individuals with upper-limb impairments.
Research Focus
Key Achievements
Top Papers
- 1