Helen J. Huang received her bachelor's degree in materials science and engineering at the Massachusetts Institute of Technology, and her master's and doctorate in biomedical engineering at the University of Michigan, Ann Arbor. She worked at Michelin North America as a materials engineer prior to her graduate studies. She was a postdoctoral fellow on the University of Colorado NIH T32 Aging Grant, and an assistant research scientist in the Human Neuromechanics Laboratory directed by Daniel Ferris at the University of Michigan, prior to joining UCF in December 2015.

Huang directs the UCF Biomechanics, Rehabilitation, and Interdisciplinary Neuroscience Laboratory. Members of the BRaIN Lab team include students from biomedical engineering, mechanical engineering, electrical engineering, and biomedical sciences. The BRaIN team studies motor adaptation and neuromechanics of gait and locomotor tasks. Their research currently focuses on investigating brain dynamics underlying motor adaptation, gait, balance and interlimb coordination in young and older adults. The BRaIN team also works on developing robotic exercise devices for gait rehabilitation and fall interventions, and on developing new methods for recording and analyzing electroencephalography (EEG) and electromyography (EMG).

• Bradford, DE., DeFalco, A., Perkins, ER., Carbajal, I., Kwasa, J., Goodman, FR., Jackson, F., Richardson, LNS.*, Woodley, N., Neuberger, L., Sandoval, JA., Huang, HJ. +, & Joyner, KJ. (2022). Whose Signals Are Being Amplified? Toward a More Equitable Clinical Psychophysiology. Clinical Psychological Science, 21677026221112117. https://doi.org/10.1177/21677026221112117


• Li, J., and Huang, HJ. “Small Directional Treadmill Perturbations Induce Differential Gait Stability Adaptation.” Journal of Neurophysiology 127 (1): 38–55. (2022) https://doi.org/10.1152/jn.00091.2021


• Castano, CR. & Huang, HJ. Speed-related but not detrended gait variability increases with more sensitive self-paced treadmill controllers at multiple slopes. PLoS One 16, e0251229 (2021). doi: http://dx.doi.org/10.1371/journal.pone.0251229


• Shirazi, SY.  & Huang, HJ. Differential Theta-Band Signatures of the Anterior Cingulate and Motor Cortices During Seated Locomotor Perturbations. IEEE Trans. Neural Syst. Rehabil. Eng. 29, 468–477 (2021). doi: 10.1109/TNSRE.2021.3057054


• Li, J., Wang, P. & Huang, HJ. Dry Epidermal Electrodes Can Provide Long-Term High Fidelity Electromyography for Limited Dynamic Lower Limb Movements. Sensors 20, 4848 (2020). doi: 10.3390/s20174848


• Shirazi, SY. & Huang, HJ. More Reliable EEG Electrode Digitizing Methods Can Reduce Source Estimation Uncertainty, but Current Methods Already Accurately Identify Brodmann Areas. Front. Neurosci. 13, 1159. doi: 10.3389/fnins.2019.01159


• Wang X, Li J, Song H, Huang H, and Gou J (2018) Highly Stretchable and Wearable Strain Sensor Based on Printable Carbon Nanotube Layers/Polydimethylsiloxane Composites with Adjustable Sensitivity. ACS Applied Materials & Interfaces. doi: 10.1021/acsami.7b17766


• Banks CL, Huang HJ, Little VL, Patten C (2017) Electromyography Exposes Heterogeneity in Muscle Co-Contraction following Stroke. Frontiers in Neurology – Stroke. 2017;8. Article 699. doi: 10.3389/fneur.2017.00699


• Shadmehr R, Huang HJ, Ahmed AA (2016). A Representation of Effort in Decision-Making and Motor Control. Current Biology. 26(14):1929-34. doi: 10.1016/j.cub.2016.05.065.


• Kline JE, Huang HJ and Ferris DP (2016) Cortical spectral activity and connectivity during active and viewed arm and leg movement. Frontiers in Neuroscience. 10:91. doi: 10.3389/fnins.2016.00091.


• Snyder KL, Kline JE, Huang HJ, and Ferris DP (2015). Independent component analysis of gait-related movement artifact recorded using EEG electrodes during treadmill walking. Frontiers in Human Neuroscience. 9:639. doi: 10.3389/fnhum.2015.00639. PubMed PMID: 26648858.


• Kline JE, Huang HJ, Snyder KL, and Ferris DP (2015). Isolating gait-related movement artifacts in electroencephalography during human walking. Journal of Neural Engineering. 12(4):046022. doi: 10.1088/1741-2560/12/4/046022. PubMed PMID: 26083595.