Deena Alabed
Papers
2
Total Citations
12
H-Index
2
About
Deena Alabed is a researcher specializing in biomedical engineering and human-machine interaction, with a core focus on advancing prosthetic control systems. Her work centers on the continuous estimation of hand and finger kinematics from surface electromyography (sEMG) signals—a critical challenge for developing high-degree-of-freedom robotic hands that can restore natural function for amputees. Alabed’s major contributions include pioneering an ensemble-based regression approach for estimating wrist and finger movements, as well as integrating wavelet-based feature extraction with support vector regression (SVR) for real-time, continuous joint angle estimation. These methods represent a significant step toward more intuitive, biomimetic control of prosthetic devices, moving beyond discrete gesture recognition to fluid, natural motion. Her foundational papers, such as those from 2016, have garnered early citations (7 and 5, respectively), reflecting their growing influence in the field of neural-machine interfaces. Alabed’s work is notable for its practical emphasis on robust, data-driven solutions that bridge the gap between biological signals and mechanical actuation, offering a promising pathway to enhance quality of life for individuals with limb loss.
Research Focus
Key Achievements
Top Papers
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- 2