Room 109, Academy of Medical Engineering and Translational Medicine, Tianjin University
Lin Meng received her Ph.D. degree from the Division of Biomedical Engineering, University of Glasgow, Glasgow, U.K., in 2016 and worked as a Research Associate at the Department of Biomedical Engineering, University of Strathclyde, Glasgow, UK from 2016 and 2018. Lin is currently an Associate Professor with the Tianjin International Joint Research Centre for Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China. She has worked in multidisciplinary research involving neuroscience, robotic control, and human motor rehabilitation and published peer-reviewed articles on high impact international journals such as IEEE Sensors Journal, Computer Methods in Biomechanics and Biomedical Engineering, etc . Her current research interests include human motion analysis, neuro-motor control mechanism, lower-limb assistive and rehabilitation robot, human early detection of cognitive and motion decline based on wearable sensors.
- Bachelor’s Degree| Tianjin University| Biomedical Enginering| 2008
- Master’s Degree| Tianjin University| Biomedical Engineering| 2010
- Doctoral degree| University of Glasgow| Biomedical Engineering| 2016
- Early detection of cognitive and motion decline based on wearable sensors
- Lower-limb assistive and rehabilitation robot
- Neuro-motion control mechanism
- Human motion analysis
2010.9-2011.5Neural Engineering and Rehabilitation Lab | Tianjin University | Research Assistant
2016.7-2018.7Department of Biomedical Engineerign | University of Strathclyde | Research Associate
-  ZJ Xue, D Ming, C Zhang, L Meng, BK W, SJ Jin, “Precision Extraction of Gait Feature and Identity Authentication”, Nanotechnology and Precision Engineering, 2009 July, 7(4), 319-323.
-  G Sabata, C Macleod, E B Esteban-Herreros, L Meng, M C Tejada. Motor Control and Emerging Therapies for Improving Mobility in Patients with Spasticity. In Emerging Therapies in Neurorehabilitation, pp 147-169. Springer Berlin Heidelberg, 2014.
-  C A Macleod, L Meng, B A Conway, and B Porr. Reflex control of robotic gait using human walking data. PloS ONE, 9(10): e109959, 2014.
-  L Meng*, C A Macleod, B Porr, H Gollee. A novel multichannel functional electrical stimulation (FES) walking system based on bio-inspired reflexive robotic control. Proceddings of the iMeche, Part H: Journal of Engineering in Medicine, 2017, 23(4), 315-325.
-  L Meng*, B Porr, and H Gollee. Technical developments of functional electrical stimulation to restore gait functions: sensing, control strategies and current commercial systems. Chinese Journal of Scientific Instrument, 2017(6), 1319-1334.
-  L Meng*, C A Macleod, B Porr, and H Gollee. Bipedal robotic walking control derived from analysis of human locomotion. Biological Cybernetics, 2018(2), 1-14.
-  S Jiang, H Qi,, J Zhang, S Zhang, R Xu, Y Liu, L Meng, D Ming. A Pilot Study on Falling-Risk Detection Method Based on Postural Perturbation Evoked Potential Features. Sensors 2019(19), 5554.
-  L Millar, L Meng, P Rowe. Routine clinical motion analysis: comparison of a bespoke real-time protocol to current clinical methods. Computer Methods in Biomechanics and Biomedical Engineering, 2019, 22(2), 149-158.
-  L Meng*, C Childs, A Buis. Evaluation of functional methods of joint centre determination for quasi-planar movement. PLOS ONE. 2019, 14(1), e0210807.
-  L Meng*, U M Hernandez, C R Childs, A A. Dehghani-Sanij, A Buis. A Practical Gait Feedback Method Based on Wearable Inertial Sensors for a Drop Foot Assistance Device. IEEE Sensors Journal, 19(24), 12235-12243.
-  L Meng*, L Millar, C Childs, A Buis. A strathclyde cluster model for gait kinematic measurement using functional methods: a study of inter-assessor reliability analysis with comparison to anatomical models. Computer Methods in Biomechanics and Biomedical Engineering, 2020.