Research Interests

Seeking to use wearable and portable sensing for widespread biomechanical assessment outside of gait laboratories. To that end, I leverage machine learning principles to extract biomechanical information from IMU data and cellphone-based videos, study sensor placement errors, and search for optimal sensor configurations. Target applications include walking gait monitoring, gait training, and injury prevention.

Degrees

Ph.D. in Mechanical Engineering, Shanghai Jiao Tong University University, 2021

Representative Publications

Tan, Tian, et al. “A scoping review of portable sensing for out-of-lab anterior cruciate ligament injury prevention and rehabilitation.” NPJ Digital Medicine 6.1 (2023): 46.
Tan, Tian, et al. “IMU and smartphone camera fusion for knee adduction and knee flexion moment estimation during walking.” IEEE Transactions on Industrial Informatics 19.2 (2022): 1445-1455.
Tan, Tian, Zachary A. Strout, and Peter B. Shull. “Accurate impact loading rate estimation during running via a subject-independent convolutional neural network model and optimal IMU placement.” IEEE Journal of Biomedical and Health Informatics 25.4 (2020): 1215-1222.