Imran Mahmood
Papers
2
Total Citations
6
H-Index
2
About
Imran Mahmood is a researcher focused on the intersection of wearable robotics, sensor-based perception, and human gait analysis. His work centers on developing intelligent systems that enhance mobility assistance, particularly through the use of probabilistic models and Bayesian frameworks. In his highly cited 2017 paper, "Prediction of gait events in walking activities with a Bayesian perception system," Mahmood introduced a robust method for anticipating gait events using wearable sensors, combining real-time observations with decision-making processes to improve the accuracy and reliability of assistive technologies. This contribution is foundational for advancing the real-world deployment of gait-assistive robots. His 2020 work, "Assistive Gait Wearable Robots—From the Laboratory to the Real Environment," further explores the challenges of transitioning these systems from controlled lab settings to dynamic, everyday environments. With a growing citation impact, Mahmood’s research is shaping the future of human-robot interaction in rehabilitation and mobility support, offering practical solutions for individuals with walking impairments.
Research Focus
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Top Papers
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