Papers
2
Total Citations
8
H-Index
2
About
Dehao Wu is a researcher whose work lies at the intersection of biomedical signal processing, sensor fusion, and intelligent systems for human motion analysis. His primary research areas include gait event detection, inertial measurement unit (IMU) signal processing, and hybrid localization techniques for challenging environments. Wu’s most notable contribution is the development of a fuzzy logic model for gait event detection using IMU signals from lower limbs, a method that enhances the accuracy and reliability of gait recognition—a critical component in rehabilitation, sports science, and human-robot interaction. This work, published in 2024, has already garnered 6 citations, reflecting its timely relevance and potential for real-world application. Earlier, Wu explored sensor fusion in a hybrid underwater acoustic and radio frequency localization system for enclosed spaces, demonstrating his versatility in addressing complex positioning challenges. His research not only advances theoretical frameworks but also offers practical solutions for wearable technology and autonomous systems. With a growing citation footprint and a focus on bridging signal processing with artificial intelligence, Dehao Wu is emerging as a promising voice in the field of intelligent sensing and biomechanics.
Research Focus
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Top Papers
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