Mahdi Abid

Papers

Total Citations

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About

Mahdi Abid is a researcher whose work sits at the intersection of biomechanics, human motion analysis, and wearable sensor technology. His primary research focus is on extracting meaningful gait features from low-cost, handheld devices—a critical challenge for applications in pedestrian navigation, robotics, and rehabilitation. His most-cited paper, "Walking Gait Step Length Asymmetry Induced by Handheld Device" (2017, 24 citations), addresses how smartphone sensors can model and detect subtle asymmetries in human walking patterns. This work is foundational for understanding how device-induced motion artifacts affect gait analysis, offering practical insights for improving inertial navigation systems and personalized health monitoring. By bridging the gap between raw sensor data and biomechanical interpretation, Abid’s contributions help enable more accurate, accessible human localization technologies. His research is particularly valuable for students and engineers working on real-world implementations of sensor-based motion tracking, where low-cost, portable solutions are essential. Through his focus on step-length asymmetry and feature extraction, Abid continues to advance the reliability of mobile-device-based gait analysis.