Koldo Basterretxea
Papers
3
Total Citations
29
H-Index
3
About
Koldo Basterretxea’s research sits at the intersection of embedded intelligence, human-robot interaction, and reconfigurable computing. His most cited work, “Efficient Algorithms for Accelerometer-Based Wearable Hand Gesture Recognition Systems” (2015, 21 citations), addresses the growing need for natural human-robot interaction in industrial and domestic settings. By developing user-specific gesture recognition systems using a single tri-axial accelerometer, Basterretxea enabled more intuitive control of robotic systems without bulky hardware. In parallel, his work on “Scalable Architecture for High-Speed Multidimensional Fuzzy Inference Systems” (2011, 5 citations) advanced the field of fuzzy logic hardware implementation. He proposed a Takagi–Sugeno-based architecture on reconfigurable hardware that balances scalability, high performance, and flexibility—critical for real-time decision-making in autonomous systems. His 2014 paper on a fault-tolerant single-chip intelligent agent with feature extraction capability further demonstrates his commitment to robust, compact embedded AI. While his citation counts are modest, Basterretxea’s contributions are foundational for researchers building efficient, wearable, and fault-tolerant intelligent systems for robotics and edge computing.
Research Focus
Key Achievements
Top Papers
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