F. Astudillo

Papers

Total Citations

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About

F. Astudillo is a researcher focused on the intersection of biomedical signal processing and human-robot interaction, with a particular emphasis on assistive technologies. Their key research area involves the detection of human motion intention through the analysis of electromyographic (EMG) signals, a critical component for developing intuitive control systems for wearable robotic devices such as exoskeletons. Astudillo’s most cited work, “Lower limbs motion intention detection by using pattern recognition” (2018), demonstrates a foundational approach to decoding neural commands from muscle activity, enabling seamless human-robot interfaces. This contribution, with 4 citations, lays important groundwork for enhancing mobility assistance for individuals with motor impairments. By advancing pattern recognition techniques for EMG signals, Astudillo’s research directly supports the creation of more responsive and natural exoskeleton control, bridging the gap between human intent and machine action. Their work represents a meaningful step toward practical, real-world applications in rehabilitation and assistive robotics, highlighting a commitment to improving quality of life through innovative human-machine collaboration.