He (Helen) Huang

Helen’s research interest lies in science and technology that can establish and enhance a symbiotic relationship between humans and wearable assitive machines in order to augment motor function for individuals with disabilities. Her research goal is to create breakthroughs in human-machine symbiotic (HMS) systems that empower disabled people to lead more active and productive lives.






To achieve this overarching goal, her current research focuses on understanding how limb amputees and robotic prostheses interact with each other and their environments and development of advanced control for robotic prostheses, which are adaptive, efficient, and safe, in order to restore the motor function in individuals with limb amputations. Three research thrusts have been formulated in my lab:

Thrust 1: Investigation of neuromuscular control and sensorimotor integration in limb amputees and development of neural-machine interfaces for neural control of robotic prosthetic limbs

Thrust 2: Investigation of wearer-machine co-adaptation and development of optimal adaptive control for robotic prostheses that provide personalized assistance and can adapt to changes in wearers and environments.

Thrust 3: Investigation of error correction and tolerance in human-machine symbiotic (HMS) systems and development of fault tolerant control for robotic prosthetic legs to improve the wearer’s stability and safety

*For current projects and open opportunities, check our lab or CLEAR websites

Research Interests

Wearable robotics
Neural-machine interface
Robotic prosthetics and exoskeleton
Optimal adaptive control
Human-robot interaction


A Novel Framework to Facilitate User Preferred Tuning for a Robotic Knee Prosthesis
Alili, A., Nalam, V., Li, M., Liu, M., Feng, J., Si, J., & Huang, H. (2023), IEEE Transactions on Neural Systems and Rehabilitation Engineering, 31, 895–903. https://doi.org/10.1109/TNSRE.2023.3236217
A simplified model for whole-body angular momentum calculation
Liu, M., Naseri, A., Lee, I.-C., Hu, X., Lewek, M. D., & Huang, H. (2023), MEDICAL ENGINEERING & PHYSICS, 111. https://doi.org/10.1016/j.medengphy.2022.103944
Offline Evaluation Matters: Investigation of the Influence of Offline Performance on Real-Time Operation of Electromyography-Based Neural-Machine Interfaces
Hinson, R. M., Berman, J., Filer, W., Kamper, D., Hu, X., & Huang, H. (2023), IEEE Transactions on Neural Systems and Rehabilitation Engineering, 31, 680–689. https://doi.org/10.1109/TNSRE.2022.3226229
Reinforcement Learning Control With Knowledge Shaping
Gao, X., Si, J., & Huang, H. (2023), IEEE Transactions on Neural Networks and Learning Systems. https://doi.org/10.1109/TNNLS.2023.3243631
A New Robotic Knee Impedance Control Parameter Optimization Method Facilitated by Inverse Reinforcement Learning
Liu, W., Wu, R., Si, J., & Huang, H. (2022), IEEE ROBOTICS AND AUTOMATION LETTERS, 7(4), 10882–10889. https://doi.org/10.1109/LRA.2022.3194326
Admittance Control Based Human-in-the-Loop Optimization for Hip Exoskeleton Reduces Human Exertion during Walking
Nalam, V., Tu, X., Li, M., Si, J., & Huang, H. H. (2022), Proceedings - IEEE International Conference on Robotics and Automation, 6743–6749. https://doi.org/10.1109/ICRA46639.2022.9811553
Characterizing Prosthesis Control Fault During Human-Prosthesis Interactive Walking Using Intrinsic Sensors
Naseri, A., Liu, M., Lee, I.-C., Liu, W., & Huang, H. (2022), IEEE ROBOTICS AND AUTOMATION LETTERS, 7(3), 8307–8314. https://doi.org/10.1109/LRA.2022.3186503
Cognitive Workload Classification of Upper-limb Prosthetic Devices
Park, J., Berman, J., Dodson, A., Liu, Y., Matthew, A., Huang, H., … Zahabi, M. (2022), Proceedings of the 2022 IEEE International Conference on Human-Machine Systems, ICHMS 2022. https://doi.org/10.1109/ICHMS56717.2022.9980676
Design of EMG-driven Musculoskeletal Model for Volitional Control of a Robotic Ankle Prosthesis
Shah, C., Fleming, A., Nalam, V., Liu, M., & Huang, H. (2022), 2022 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), pp. 12261–12266. https://doi.org/10.1109/IROS47612.2022.9981305
Design of EMG-driven musculoskeletal model for volitional control of a robotic ankle prosthesis
Shah, C., Fleming, A., Nalam, V., & Huang, H. (2022), ArXiv. Retrieved from http://www.scopus.com/inward/record.url?eid=2-s2.0-85125688202&partnerID=MN8TOARS

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He (Helen) Huang