Title:

Lab Manager

Office Information:

4402E Engineering Building III
NC State University
Phone: 919-515-8541

Education:

Ph.D., Mechanical Engineering & Applied Mechanics, University of Rhode Island
M.Sc., Mechatronics, Beijing Institute of Technology
B.S., Mechatronics, Beijing Institute of Technology

Email:

mliu10@ncsu.edu

Lab Site:

http://nrel.bme.unc.edu

Additional Links:

http://clear.bme.unc.edu

Research and Publications:

Dr. Liu’s research interests include: design and control of powered prostheses, human motion analysis, wearable sensors, robots, nonlinear dynamics, nonlinear time series analysis, and image processing.

M. Liu, F. Zhang, H. Huang, "An Adaptive Classification Strategy for Reliable Locomotion Mode Recognition", Sensors 17(9), 2020, 2017

A. Brandt, Y. Wen, M. Liu, H. Huang, "Interactions between transfemoral amputees and a powered knee prosthesis during load carriage", Scientific Reports, 7(1): 14480, 2017

M. Liu, D. Wang, H. Huang, Development of an Environment-Aware Locomotion Mode Recognition System for Powered Lower Limb Prostheses, Neural Systems and Rehabilitation Engineering, IEEE Transactions, 24(4) pp. 434-43, 2016.

F. Zhang, M. Liu, & H. Huang, Effects of locomotion mode recognition errors on volitional control of powered above-knee prostheses. Neural Systems and Rehabilitation Engineering, IEEE Transactions on, 23(1), 64-72, 2015.

F. Zhang, M. Liu, S. Harper, M. Lee, and H. Huang, Engineering Platform and Experimental Protocol for Design and Evaluation of a Neurally-controlled Powered Transfemoral Prosthesis, Journal of visualized experiments: JoVE 89, 2014.

M. Liu, F. Zhang, P. Datseris, and H. Huang, Improving Finite State Impedance Control of Active-Transfemoral Prosthesis Using Dempster-Shafer Based State Transition Rules, Journal of Intelligent and Robotic Systems 76(3-4), 461-474, 2014.

D. Chelidze and M. Liu, Reconstructing slow-time dynamics from fast-time measurements, Philosophical Transactions of the Royal Society A, 366: 729-745, 2008.

M. Liu and D. Chelidze, Identifying Damage using Local Flow Variation Method, Smart Materials and Structures 15 (6): 1830-1836, 2006.

D. Chelidze and M. Liu, Dynamical Systems Approach to Fatigue Damage Identification, Journal of Sound and Vibration 281:887-904, 2005.