Malak Fora

Papers

Total Citations

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About

Malak Fora is a researcher advancing the field of human–machine interaction, with a primary focus on hand gesture recognition using force myography (FMG). Her work addresses critical challenges in feature selection and classification for assistive technologies, particularly for American Sign Language (ASL) interpretation. In her most-cited paper, "Features Selection for Force Myography Based Hand Gesture Recognition" (2023), Fora explores how optimizing sensor data can improve the accuracy and reliability of gesture detection, with applications spanning robotics, game control, and communication for the deaf and hard-of-hearing. By systematically evaluating different feature sets, she contributes to making FMG-based systems more practical and efficient. Though early in her career, her research has already garnered citations, reflecting its relevance to ongoing efforts in wearable sensing and inclusive technology design. Fora’s work sits at the intersection of biomedical engineering, machine learning, and accessibility, offering promising pathways for more intuitive and responsive human–computer interfaces. Her contributions help bridge the gap between raw physiological signals and meaningful, real-time gesture recognition.