Mohsen Gholami
Papers
1
Total Citations
43
H-Index
1
About
Mohsen Gholami’s research lies at the intersection of wearable technology, biomechanics, and machine learning, with a focus on developing intelligent systems for 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 strain sensor with machine learning algorithms to accurately estimate knee joint angles. This preliminary investigation demonstrates significant potential for in-home rehabilitation and long-term tracking of knee disorders, offering a non-invasive, low-cost alternative to traditional motion capture systems. Gholami’s contributions advance the field of smart textiles and sensor-based health monitoring, enabling more accessible and continuous kinematic assessment. His work has been recognized for its practical implications in clinical and home settings, bridging the gap between sensor technology and real-world healthcare applications. With growing citation impact, Gholami continues to shape the development of wearable systems that empower patients and clinicians with real-time, data-driven insights into joint health and mobility.
Research Focus
Key Achievements
Top Papers
- 1