Terrell R. Bennett

The University of Texas at Dallas

Papers

1

Total Citations

25

H-Index

1

About

Terrell R. Bennett is a researcher whose work sits at the intersection of biomechanics, wearable sensing, and human motion estimation. His primary research focuses on developing computational methods to model and track human gait using low-cost, portable sensors. In his most cited work, "An extended Kalman filter to estimate human gait parameters and walking distance" (2013, 25 citations), Bennett introduced a novel approach that models the human leg as a two-link revolute robot, using inertial measurement units placed on the thigh and shin to estimate joint angles and walking distance. This work is notable for bridging robotics-inspired kinematic models with real-world human motion, enabling accurate gait analysis outside of traditional lab settings. Bennett’s contributions are particularly impactful for applications in rehabilitation, prosthetics, and mobile health monitoring, where continuous, unobtrusive tracking of movement is essential. By combining sensor fusion techniques with biomechanical modeling, his research has laid groundwork for more accessible and practical human motion analysis systems.

Research Focus

Key Achievements

1
H-Index
1
Papers
25
Total Citations
25
Avg Citations/Paper
🏆 Most Cited Paper
An extended Kalman filter to estimate human gait parameters and walking distance
25 citations · 2013
📈 Most Prolific Year: 2013 (1 Papers)
🤝 Key Collaborators: 2
🏛 Institutions: The University of Texas at Dallas

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago