Ahmad Rezaei
Papers
1
Total Citations
43
H-Index
1
About
Ahmad Rezaei’s research lies at the intersection of wearable technology, biomechanics, and machine learning, with a focus on advancing human health monitoring. His most-cited work, “Estimation of Knee Joint Angle Using a Fabric-Based Strain Sensor and Machine Learning: A Preliminary Investigation” (2018, 43 citations), introduces a novel wearable system that combines a stretchable, fabric-based strain sensor with machine learning algorithms to accurately estimate knee joint angles. This preliminary study demonstrates the potential for low-cost, non-intrusive monitoring of knee kinematics, with promising applications in in-home rehabilitation and long-term tracking of movement disorders. By addressing the need for accessible, real-time data on joint function, Rezaei’s work contributes to the growing field of smart textiles and personalized healthcare. His research is particularly impactful for patients with knee disorders, offering a pathway toward improved recovery outcomes and continuous health assessment. With a focus on practical, scalable solutions, Rezaei’s contributions highlight the synergy between sensor technology and data-driven analysis, paving the way for future innovations in wearable health systems.
Research Focus
Key Achievements
Top Papers
- 1