Juan Mantilla-Brito

Papers

Total Citations

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About

Juan Mantilla-Brito is a researcher in biomedical engineering and human-machine interaction, with a focus on embedded systems for real-time biosignal processing. His most-cited work, "Embedded System for Hand Gesture Recognition Using EMG Signals: Effect of Size in the Analysis Windows" (2019), has garnered 8 citations, establishing his early contributions to the field of electromyography (EMG)-based gesture recognition. Mantilla-Brito’s research centers on developing efficient, low-latency algorithms for interpreting muscle activity, particularly by optimizing analysis window sizes to improve accuracy in embedded platforms. This work is critical for advancing prosthetics, wearable devices, and assistive technologies, where real-time responsiveness is paramount. His approach bridges hardware-software co-design and signal processing, enabling compact, power-efficient systems for gesture classification. While his citation count reflects a growing niche, his methodology has implications for broader applications in rehabilitation engineering and human-robot interaction. Mantilla-Brito’s contributions highlight the importance of balancing computational constraints with algorithmic performance, offering a foundation for future innovations in portable, EMG-driven interfaces. His ongoing efforts continue to explore the intersection of embedded systems and biomedical signal analysis, aiming to make intuitive, non-invasive control systems more accessible.