Anas Ibrahim

Papers

Total Citations

H-Index

About

Dr. Anas Ibrahim is a leading researcher in human–machine interaction and assistive rehabilitation technologies, with a focus on intelligent gesture recognition systems for stroke survivors. His most cited work, "Design of User-Independent Hand Gesture Recognition Using Multilayer Perceptron Networks and Sensor Fusion Techniques" (2019, 25 citations), addresses a critical global health challenge: according to the World Health Organization, stroke is the third leading cause of disability, often resulting in hemiparesis that impairs daily living activities. Dr. Ibrahim’s key contribution lies in developing robust, user-independent gesture recognition frameworks that combine multilayer perceptron networks with sensor fusion—enabling reliable control of assistive devices without requiring per-user calibration. This innovation directly supports motor rehabilitation by allowing patients to interact naturally with therapeutic interfaces. Beyond this flagship paper, his body of work consistently bridges machine learning and biomedical engineering, aiming to restore functional independence for individuals with motor impairments. With growing citation impact, Dr. Ibrahim’s research is shaping the next generation of accessible, intelligent rehabilitation tools, offering hope for more effective, personalized recovery pathways.