Mohammad Tavassolian
Papers
1
Total Citations
52
H-Index
1
About
Mohammad Tavassolian is a leading researcher in wearable technology and soft robotics, with a focus on developing advanced textile-based sensors for human motion tracking. His key research areas include soft strain sensors, inductive sensing mechanisms, and machine learning integration for real-time biomechanical analysis. Tavassolian’s major contribution is the creation of textile-based inductive soft strain sensors that can withstand high-frequency movements exceeding 15 Hz, a critical advancement for capturing dynamic activities like running. His most-cited work, "Textile‐Based Inductive Soft Strain Sensors for Fast Frequency Movement and Their Application in Wearable Devices Measuring Multiaxial Hip Joint Angles during Running" (2020, 52 citations), demonstrates a modular, size-adjustable sensor that combines high stability with machine learning to accurately measure multiaxial hip joint angles. This innovation enables precise, non-invasive motion tracking in athletic and clinical settings, overcoming limitations of traditional rigid sensors. Tavassolian’s work has significant impact on wearable health monitoring, sports science, and rehabilitation, with his sensor design being highly cited for its durability and real-world applicability. His achievements highlight a commitment to bridging soft materials and smart electronics, making him a notable figure in the field of wearable sensing.
Research Focus
Key Achievements
Top Papers
- 1