Kiattisak Sengchuai
Papers
3
Total Citations
31
H-Index
3
About
Kiattisak Sengchuai is a researcher whose work bridges the critical fields of biomedical engineering, human-robot interaction, and wireless sensor networks. His most impactful contribution, the 2022 paper on real-time indoor tracking using RSSI signals, has garnered 22 citations and addresses a pressing need for precise localization in complex environments like hospital corridors. This work is foundational for applications in patient monitoring and asset tracking. More recently, Sengchuai has pioneered the use of surface electromyography (sEMG) signals for force estimation, a key enabler for intuitive human-robot interaction in rehabilitation. His 2025 study, which employs Gaussian Process Regression for real-time force estimation, marks a significant step forward in creating responsive, adaptive robotic systems for therapy. Complementing this, his 2024 work systematically evaluated nineteen regression models to estimate force across varied arm postures, demonstrating a rigorous, data-driven approach to capturing the complexity of natural human movement. By tackling the challenge of estimating human intent from biological signals, Sengchuai is directly contributing to the development of smarter, safer, and more effective rehabilitation technologies and human-machine interfaces.
Research Focus
Key Achievements
Top Papers
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