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Full List of Publications

Accepted or Published Journal Articles

  1. X. Gao, J. Si, H. Huang, “Value Function Based Reinforcement Learning Control with Knowledge Shaping”, IEEE Trans Neural Network and Learning Systems, 2023 （Accepted)
  2. A. Alili, V. Nalam, M. Li, M. Liu, J. Feng, J. Si, H Huang, “A Novel Framework to Facilitate User Preferred Tuning for a Robotic Knee Prosthesis”, IEEE Trans on Neural System and Rehabilitation Engineering, V31, pp 895– 903, 2023
  3. M Liu*, A. Naseri, IC Lee, X. Hu, M. Lewek, H Huang, “A Simplified Model for Whole-body Angular Momentum Calculation”, Medical Engineering and Physics, 111, 103944, 2023
  4. R. Hinson, J. Berman, W. Filler, D. Kamper, H. Huang, “Offline Evaluation Matters: Investigation of the Influence of Offline Performance on Real-time Operation of Electromyography-based Neural-Machine Interfaces”, IEEE Trans on Neural System and Rehabilitation Engineering, 2023, (Accepted)
  5. BL Fylstra, IC Lee, M. Lewek, H. Huang, “Human-prosthesis cooperation: combining adaptive prosthesis control with visual feedback guided gait”, Journal of NeuroEngineering and Rehabilitation, 2022
  6. M. Li, W. Liu, J. Si, J. Stallrich, H. Huang*, “Hierarchical Optimization for Control of Robotic Knee Prostheses Toward Improved Gait Symmetry”, IEEE Trans on Biomedical Engineering, 2022 (Accepted)
  7. J. Berman, R. Hinson, I Lee, H. Huang, “Harnessing Machine Learning and Physiological Knowledge for a Novel EMG-Based Neural-Machine Interface”, IEEE Trans on Biomedical Engineering, 2022 (Accept)
  8. I. Lee, M. Liu, M. Lewek, X. Hu, W. Filer, H. Huang, “Towards Safe Wearer-Prosthesis Interaction: Evaluation of Gait Stability and Human Compensation Strategy under Faults in Robotic Transfemoral Prostheses”, IEEE Trans on Neural System and Rehabilitation Engineering, 2022
  9. L. Vargas, H. Huang, Y. Zhu, X. Hu, “Resembled Tactile Feedback for Object Recognition using Prosthetic Hand”, IEEE Robotic and Automation Letter, 2022
  10. Q. Zhang, V. Nalam, X. Tu, M. Li, J. Si, M. Lewek, H. Huang*, “Imposing Healthy Hip Movement Pattern and Range by Exoskeleton Control for Individualized Assistance”, IEEE Robotic and Automation Letter, 2022
  11. W. Liu, R. Wu, J. Si*, H. Huang*, “A New Robotic Knee Impedance Control Parameter Optimization Method Facilitated by Inverse Reinforcement Learning”, IEEE Robotic and Automation Letter, 2022
  12. A. Naseri, M Liu, IC Lee, W. Liu, H. Huang*, “Characterizing Prosthesis Control Fault during Human-Prosthesis Interactive Walking Using Intrinsic Sensors”, IEEE RAL, 2022
  13. R. Hinson, K Saul, D. Kamper, H. Huang*, “Sensitivity Analysis Guided Improvement of an Electromyogram-driven Lumped Parameter Musculoskeletal Hand Model”, J of Biomechanics, 2022
  14. R. Wu, M. Li, W. Liu, Z. Yao, J. Si*, H Huang, “Reinforcement Learning Impedance Control of a Robotic Prosthesis to Coordinate with Human Intact Knee Motion” IEEE RAL, 2022
  15. J Yuan, X. Bai, B. Driscoll, M. Liu, Huang, F. Jing*, “Standing and Walking Attention Visual Field (SWAVF) Task: A New Method to Assess Visuospatial Attention During Walking”, Applied Ergonomics, 2022
  16. S. Yao, W. Zhou, R. Hinson, P. dong, S. Wu, J. Lves, X. Hu, H. Huang, Y. Zhu. “Ultrasoft Breathable Dry Electrodes for Electrophysiological Sensing and Myoelectric Control”, Advance Materials Technologies, pp. 210637, 2022
  17. M. Li, B. Zhong, E. Lobaton, H Huang, “Fusion of Human Gaze and Machine Vision for Predicting Intended Locomotion Mode”, IEEE Trans Neural System and Rehabilitation, 2022
  18. IC Lee, B Fylstra, M Liu, T Lenzi, H Huang, “Is there a trade-off between economy and task goal variability in transfemoral amputee gait?” Journal of NeuroEngineering and Rehabilitation, 2022
  19. N. Rubin, Y. Zheng, H. Huang, X. Hu, “Finger Force estimation of individual fingers using motor unit discharges across multiple forearm postures”, IEEE Trans on Biomed Engr, 2022
  20. W Liu, J. Zhong, R. Wu, B. Flystra, J Si, H. Huang, “ Inferring Human-Robot Performance Objectives during Locomotion using Inverse Reinforcement Learning and Inverse Optimal Control”, IEEE Robotic and Automation Letter, 2022
  21. L Vargas, H Huang, Y Zhu, X Hu, “Evoked Tactile Feedback and Control Scheme on Functional Utility of Prosthetic Hand”, IEEE Robotic and Automation Letter, 2022
  22. V. Nalam, H Huang, “Empower prosthesis users with a hip exoskeleton”, Nature Medicine, 2021 (Invited Commentary)
  23. L Vargas, H Huang, Y Zhu, X Hu, “Object Recognition via Evoked Sensory Feedback during Control of a Prosthetic Hand”, IEEE Robotic and Automation Letter, 2021 (Accepted; Available Online)
  24. L Vargas, H Huang, Y Zhu, X Hu, “Closed-loop control of a prosthetic finger via evoked proprioceptive information”, Journal of Neural Engineering, 2021 (Accepted; Available Online)
  25. M Li, Y. Wen, X. Gao, J. Si*, H Huang*, “Towards Expedited Impedance Tuning of a Robotic Prosthesis for Personalized Gait Assistance by Reinforcement Learning Control”, IEEE Trans Robotics, 2021 (Accepted; Available Online)
  26. R Wu, Z. Yao, J. Si, H. Huang, “Robotic Knee Tracking Control to Mimic the Intact Human Knee Profile Based on Actor-critic Reinforcement Learning”, IEEE/CAA Journal of Automatica Sinica, 2021 (Accepted; Available Online)
  27. A Fleming, N. Stafford, S. Huang, X. Hu, DP Ferris*, H Huang*, “Myoelectric Control of Robotic Lower Limb Prostheses: A Review of Electromyography Interfaces, Control Paradigms, Challenges and Future Directions”, Journal of Neural Engineering, 18041004, 2021
  28. H. Huang, J. Si, A. Brandt, M. Li, “Taking Both Sides: Seeking Symbiosis Between Intelligent Prostheses and Human Motor Control during Locomotion”, Current Opinion on Biomedical Engineering (invited paper), V20, 100314, 2021
  29. L. Vargas, H. Huang, Y. Zhu, X. Hu*, “Static and Dynamic Proprioceptive Recognition through Vibrotactile Stimulation”, Journal of Neural Engineering, 2021
  30. D. Farina., Vujaklija, I., Brånemark, R., Bull, A.M., Dietl, H., Graimann, B., Hargrove, L.J., Hoffmann, K.P., Huang, H.H., Ingvarsson, T. Janusson, H.B., K Kristjansson, T. Kuiken, S. Micera, T. Stieglitz, A. Sturma, D. Tyler, R. Weir, and OC Aszmann; “Toward higher-performance bionic limbs for wider clinical use”, Nature Biomedical Engineering, pp.1-13. 2021
  31. B. Zhong, R. L. da Silva, M. Tran, H. Huang and E. Lobaton, “Efficient Environmental Context Prediction for Lower Limb Prostheses,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2021 (Accepted)
  32. X Gao; Si, Jennie; Wen, Yue; Li, Minhan; Huang, He, “Reinforcement Learning Control of Robotic Knee with Human in the Loop by Flexible Policy Iteration”, IEEE TNNLS, 2021 (Accepted)
  33. L Pan, H Huang, “A Robust Model-Based Neural-Machine Interface across Different Loading Conditions”, Biomedical Signal Processing and Control, 67, 102509. 2021
  34. J Tabor, Jordan, Talha Agcayazi, Aaron Fleming, Brendan Thompson, Ashish Kapoor, Ming Liu, Michael Lee, He Huang, Alper Bozkurt, and Tushar K. Ghosh. “Textile-based Pressure Sensors for Monitoring Prosthetic-Socket Interfaces.” IEEE Sensors Journal, 2021
  35. A Fleming, S. Huang, E. Buxton, F. Hodges, He Huang, “Direct Continuous EMG control of a Powered Prosthetic Ankle for Improved Postural Control after Guided Physical Training: a Case Study”, Wearable Technology, V2, e3, 2021
  36. J. Yuan, J,  E. Kline, M. Liu, H Huang, J. Feng*, “Cognitive measures during walking with and without lower-limb prosthesis: protocol for a scoping review”, BMJ Open, 2021
  37. W. Wu, K Saul, He Huang* “Using reinforcement learning to estimate joint moments: An alternative solution to musculoskeletal-based biomechanics”, ASME Journal of Biomechanical Engineering, 2021
  38. IC. Lee*, M. Pacheco, M. Lewek, H. Huang, “Perceiving amputee gait from biological motion: kinematics cues and effect of experience level”, Scientific Reports, 2020 (Accepted)
  39. B. Fylstra, IC Lee, S Huang, A. Brandt, M. Lewek, H. Huang*, “Human-Prosthesis Coordination: A Preliminary Study Exploring Coordination With A Powered Ankle-Foot Prosthesis”, Clinical Biomechanics, 2020
  40. W. Wu, S. Yao, Y. Liu, X. Hu, H. Huang, Y Zhu*, “Buckle-delamination enabled stretchable silver nanowire conductors”, ACS Applied Materials and Interfaces, 2020
  41. M. Liu*, D. Kamper, H. Huang, “An Easy-to-Use Socket-Suspension Monitoring System for Lower Limb Amputees”, IEEE Transactions on Instrumentation & Measurement, 2020
  42. B. Zhong, H. Huang*, E. Lobaton*, “Reliable Vision-Based Grasping Target Recognition for Upper-limb Prostheses”, IEEE Trans on Cybernetics, 2020 (Accepted)
  43. L. Pan, L. Vargas, X. Hu, Y. Zhu, H. Huang*, “Evoking Haptic Sensations in the Foot through High-Density Transcutaneous Electrical Nerve Stimulations”, Journal of Neural Engineering, 2020 (Accepted)
  44. Y. Wen, M. Li, J. Si, H. Huang, “Wearer-Prosthesis Interaction for Symmetrical Gait: A Study Enabled by Reinforcement Learning Prosthesis Control”, IEEE Transactions on Neural System and Rehabilitation Engineering, 2020
  45. B. Zhong, RL da Silva, M. Li, H. Huang*, E. Lobaton*, “Environmental context Prediction for Lower Limb Prosthesis with Uncertainty Quantification”, IEEE Trans on Automation Science and Engineering, 18(2), pp 458-70, 2021
  46. M. McKnight, J. Tabor, T. Agcayazi, A. Fleming, T. Ghosh, H. Huang, A. Bozkurt*, “Fully-textile Insole Seam-line for Multi-modal Sensor Mapping”, IEEE Sensor, 2020
  47. J. Stallings, MD Islam, AM Staicu, D. Crouch, L. Pan, H. Huang, “Optimal EMG Placement for a Robotic Prosthesis Controller with Sequential, Adaptive Functional Estimation”, Annals of Applied Statistics, 2020
  48. L. Vargas, H. Huang, Y. Zhu, X Hu, “Object shape and surface topology recognition using tactile feedback evoked through transcutaneous nerve stimulation”, IEEE Trans on Haptics, 2020
  49. Y. Wen, J Si, A. Brandt, X. Gao, H. Huang*, “Online Reinforcement Learning Control for the Personalization of a Robotic Knee Prosthesis”, IEEE Transactions on Cybernetics, 50(6), pp. 2346 – 2356, 2020 (Research News at NC State https://news.ncsu.edu/2019/01/reinforcement-learning-expedites-tuning-of-robotic-prosthetics/and IEEE Spectrum https://spectrum.ieee.org/the-human-os/biomedical/bionics/ai-helps-humans-walk-on-robot-prosthetic-knee)
  50. A. Brandt*, H. Huang, “Effects of Extended Stance Time on a Powered Knee Prosthesis and Gait Symmetry on Unilateral Amputees’ Lateral Control of Balance during Walking”, Journal of Neuroengineering and Rehabilitation, 16(1):151, 2019
  51. L. Vargas, H. Shin, H. Huang, Y. Zhu, X. Hu*; “Object Stiffness Recognition using Haptic Feedback Delivered through Transcutaneous Proximal Nerve Stimulation.” Journal of Neural Engineering, 2019
  52. A. Brandt, W. Riddick, J. Stallrich, M. Lewek, H. Huang*, “Effects of Extended Powered Knee Prosthesis Stance Time via Visual Feedback on Gait Symmetry of Individuals with Unilateral Amputation: A Preliminary Study”, Journal of NeuroEngineering and Rehabilitation, 16:112, 2019
  53. L. Pan, D. Crouch, H. Huang*, “Comparing EMG-based human-machine interfaces for estimating continuous, coordinated movements”, IEEE Transactions on Neural System and Rehabilitation Engineering, 2019
  54. T. Zhang*, H Huang#,“Development of a Modular Clutchable Soft Actuator for Reconfigurable Wearable Exoskeletons”, IEEE Trans on Mechatronics, 2019
  55. L. Vagar, G. Whitehouse, H. Huang,Y. Zhu, X. Hu*, “Evoked Haptic Sensation in the Hand with Concurrent Non- Invasive Nerve Simulation”, IEEE Trans on Biomedical Engineering, 2019
  56. A. Fleming, S. Huang, H. Huang*, “Proportional Myoelectric Control of a Virtual Inverted Pendulum using Residual Antagonistic Muscles: Toward Voluntary Postural Control”, IEEE Transactions on Neural System and Rehabilitation Engineering, 27(7),1473-82,2019
  57. T. Zhang*, Minh Tran, H. Huang#, “Admittance shaping-based assistive control of SEA-driven hip exoskeleton”, IEEE Transactions on Mechatronics, 24(4), pp. 1508 – 1519, 2019
  58. M. Zahabi, M White, W Zhang, AT. Winslow, F Zhang, H Huang, DB Kaber*, “Application of Cognitive Task Performance Modeling for Assessing Usability of Transradial Prostheses”, IEEE Human-Machine Systems,49(4), 381-7; 2019
  59. Q. Qin, S. Yao, H. Huang,Y Zhu*, “Electrocardiogram of a Silver Nanowire Based Dry Electrode: Quantitative Comparison with the Standard Ag/AgCl Gel Electrode”, IEEE Access,V7, pp. 20789-800, 2019
  60. S. Huang*, H. Huang#,“Voluntary Control of Residual Antagonistic Muscles in Transtibial Amputees: Reciprocal Activation, Co-activation, and Implications for Direct Neural Control of Powered Lower Limb Prostheses”, IEEE Transactions on Neural System and Rehabilitation Engineering, 27(1), 85-95, 2019
  61. DL Crouch*, L. Pan, W. Filer, J. Stallings, H Huang#, “Comparing surface and intramuscular Electromyography for real-time control of a musculoskeletal model-based neural-machine interface: a pilot study”, IEEE Transactions on Neural System and Rehabilitation, 26(9), 1735-1744, 2018
  62. H Shin, Z, Watkins^, H. Huang, Y. Zhu, X. Hu*, “Evoked haptic sensations in the hand via non-invasive proximal nerve stimulation”, Journal of Neural Engineering,15 046005, 2018
  63. L. Pan, D. Crouch, H Huang*, “Myoelectric Control based on a Generic Musculoskeletal Model: Towards A Multi-User Neural-Machine Interface”,IEEE Transactions on Neural System and Rehabilitation, 26(7), pp. 1435 – 1442, 2018(https://news.ncsu.edu/2018/05/generic-model-prosthetic-2018/The original news at NC State was also highlighted by UNC, NSF Science 360, P&O Edge, Science Daily, etc.)
  64. T. Zhang*, H. Huang#,“Industrial handling augmentation by a lower-back robotic exoskeleton”, IEEE Robotics and Automation Magazine, 25(2), 95-106, 2018
  65. S. Huang*, H. Huang#,“Voluntary Control of Residual Antagonistic Muscles in Transtibial Amputees: Feedforward Ballistic Contractions and Implications for Direct Neural Control of Powered Lower Limb Prostheses”,IEEE Transactions on Neural System and Rehabilitation, 26(4), pp. 894-903, 2018
  66. L Resnik*, H. Huang*, A. Winslow, D. Crouch, F. Zhang, N. Wolk, “Evaluation of EMG pattern recognition for upper limb prosthesis control: a case study in comparison with direct myoelectric control”, Journal of Neuroengineering and Rehabilitation, 15(1), P.23, 2018
  67. T Zhang*, Minh Tran^, H. Huang,“Design and experimental verification of hip exoskeleton with balance capacities for walking assistance” IEEE Transactions on Mechatronics, 23(1),pp. 274 – 285, 2018
  68. 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 (Featured on the front page of NSF Science 360 as a top story https://news.science360.gov/obj/story/07975f4d-0ac5-488c-ae17-52de5468c1a6/study-shows-need-adaptive-powered-knee-prosthesis-assist-amputees)
  69. M White, W Zhang, M Zahabi, AT. Winslow, F Zhang, H Huang, D Kaber*, “Usability comparison of conventional direct control versus pattern recognition control of transradial prostheses”, IEEE Transactions onHuman-Machine Systems, 47(6), pp.1146-52, 2017
  70. M. Liu, F. Zhang, H. Huang*, “An Adaptive Classification Strategy for Reliable Locomotion Mode Recognition”, Sensors, 17(9): 2020, 2017
  71. Y. Wen, J. Si, X. Gao, S. Huang, H. Huang*, “A new powered lower limb prosthesis control framework based on adaptive dynamic programming”, IEEE Trans on Neural Network and Learning Systems, 28(9), pp. 2215-20, 2017
  72. F. Zhang, P. Bohlen, M. Lewek, H. Huang*, “Prediction of intrinsically caused trips in individuals with stroke”, IEEE Trans Neural Syst Rehabil Eng, 25(8), pp.1202-10,2017
  73. DL Crouch*,H. Huang, “Musculoskeletal model-based control interface mimics physiologic hand dynamics during path tracing task”, Journal of Neural Engineering, 14(3), 036008, 2017
  74. DL Crouch*, H. Huang, “Lumped-Parameter EMG-Driven Musculoskeletal Hand Model: A Potential Platform For Real-Time Control”, Journal of Biomechanics, 49(16), pp.3901-07, 2016
  75. H. Huang*, D. Crouch, M. Liu, G. Sawicki, D. Wang. “A cyber expert system for auto-tuning powered prosthesis impedance control parameters”,Annals Biomedical Engineering, 44(5), pp. 1613-24, 2016 (featured on the front page of NSF website and NSF Science channelhttp://science360.gov/obj/video/182b2562-155f-455a-9926-af5544ead9e6/nsf-science-now-episode-37)
  76. M Liu, D. Wang, H. Huang*,“Development of an environment-aware locomotion mode recognition system for powered lower limb prostheses”, IEEE Trans Neural Syst Rehabil Eng, 24(4) pp. 434-43, 2016
  77. L. Contreras-Vidal*, A. Kilicarslan, H. Huang, R. G. Grossman, “Human-Centered design of wearable neuroprostheses and exoskeletons”, AI Magazine, 36(4), 12-22, 2015
  78. F. Zhang*, M. Liu, H. Huang, “Investigation of timing to switch control mode in powered knee prostheses during task transitions”, PLoS One, (10) 7, 2015
  79. X. Zhang, H. Huang*,“A real-time, practical sensor fault-tolerant module for robust EMG pattern recognition”, Journal of NeuroEngineering and Rehabilitation,12:18, 2015
  80. A Myer, H. Huang, Y. Zhu*, “Wearable Silver Nanowire Dry Electrodes for Bioelectronic Sensing”, RSC Advances, 5(15), pp. 11627-32, 2015
  81. Hefferman, F. Zhang, M. Nunnery, H. Huang*, “Integration of surface EMG sensors with the transfemoral amputee socket: a comparison of four differing configurations”, Prosthetics and Orthotics International, (39) 2, 166-1732015
  82. F. Zhang, M. Liu, H. Huang*, “Effects of locomotion mode recognition errors on volitional control of powered above-knee prostheses”, IEEE Trans Neural Syst Rehabil Eng, 23(1), pp. 64-72, 2015 (featured by NSF Science Channel http://science360.gov/obj/video/b8e8abba-a1fc-49c8-a1c1-ab7e42dd1d35/nsf-science-now-episode-29)
  83. F. Zhang, M. Liu, S.Harper,M Lee,H. Huang*, “Engineering Platform and Experimental Protocol for Design and Evaluation of a Neurally-controlled Powered Transfemoral Prosthesis”, Journal of Visualized Experiments, (89), e51059,2014
  84. L. Liu*, F Zhang, P. Datseris, H. Huang#, “Improving finite state impedance control of active transfemoral prostheses using Dempster-Shafer state transition rules”, Journal of Intelligent and Robotic Systems,(76) 3-4, pp 461-74,2014
  85. F Zhang*, H. Huang#, “Source selection for real-time user intent recognition towards volitional control of artificial legs”, IEEE Journal of Biomedical and Health Informatics,17(5), 907-914, 2013
  86. L Du, F. Zhang, M. Liu, H. Huang*, “Towards Design of an Environment-aware Adaptive Locomotion-Mode-Recognition System”, IEEE Trans Biomed Eng, 59(10): 2716-25, 2012
  87. X Zhang, Y. Liu, F. Zhang, Y. Sun, Q. Yang, H. Huang*, “On design and implementation of neural-machine interface for artificial legs”, IEEE Transactions on Industrial Informatics, Vol. 8(2), 418-29, 2012
  88. F Zhang, S.E. D’Andrea, M.J. Nunnery, S. Kay, H. Huang*. “Towards design of a stumble detector for artificial legs”. IEEE Trans Neural Syst Rehabil Eng, Vol. 19(5): 567-77, 2011
  89. Huang*, F. Zhang, L. Hargrove, Z. Dou, D. Rogers, K. Englehart, “Continuous Locomotion Mode Identification for Prosthetic Legs based on Neuromuscular-Mechanical Fusion”, IEEE Trans Biomed Eng, 58(1), pp2867-75,2011
  90. Cao, H He*, H Huang. “LIFT: A New Framework of Learning from Testing Data for Face Recognition”. Neurocomputing, 74(6), pp. 916-929, 2011
  91. Huang*, F Zhang, Y Sun, H He “Design of a Robust EMG Sensing Interface for Pattern Classification”, Journal of Neural Engineering, vol. 7(5), pp 0565, 2010
  92. Tkach, H Huang*, TA Kuiken#, “Stability of time-domain EMG features for prosthetic device control”, Journal of NeuroEngineering and Rehabilitation, 7(1):21, 2010
  93. H. Huang, P. Zhou*, G. Li, and T. Kuiken#, “Spatial filtering improves EMG classification accuracy following targeted muscle reinnervation,” Ann Biomed Eng, vol. 37, pp. 1849-57, 2009.
  94. H. Huang*, T. A. Kuiken#, and R. D. Lipschutz, “A strategy for identifying locomotion modes using surface electromyography,” IEEE Trans Biomed Eng, vol. 56, pp. 65-73, 2009.
  95. LA. Miller*, R. D. Lipschutz, K. A. Stubblefield, B. A. Lock, H. Huang, T. W. Williams, 3rd, R. F. Weir, and T. A. Kuiken#, “Control of a six degree of freedom prosthetic arm after targeted muscle reinnervation surgery,” Arch Phys Med Rehabil, vol. 89, pp. 2057-65, 2008.
  96. H. Huang,P. Zhou, G. Li, and T. A. Kuiken*, “An analysis of EMG electrode configuration fortargeted muscle reinnervation based neural machine interface,” IEEE Trans Neural Syst Rehabil Eng, vol. 16, pp. 37-45, 2008.
  97. P. Zhou, M. M. Lowery, K. B. Englehart, H. Huang, G. Li, L. Hargrove, J. P. Dewald, and T. A. Kuiken*, “Decoding a new neural machine interface for control of artificial limbs,” J Neurophysiol, vol. 98, pp. 2974-82, 2007.
  98. TG. Sugar*, J. He, E. J. Koeneman, J. B. Koeneman, R. Herman, H. Huang, R. S. Schultz, D. E. Herring, J. Wanberg, S. Balasubramanian, P. Swenson, and J. A. Ward, “Design and control of RUPERT: a device for robotic upper extremity repetitive therapy,” IEEE Trans Neural Syst Rehabil Eng, vol. 15, pp. 336-46, 2007.
  99. H. Huang, S. L. Wolf, and J. He*, “Recent developments in biofeedback for neuromotor rehabilitation,” J Neuroeng Rehabil, vol. 3, pp. 11, 2006.
  100. H. Huang, J. He*, R. Herman, and M. R. Carhart, “Modulation effects of epidural spinal cord stimulation on muscle activities during walking,” IEEE Trans Neural Syst Rehabil Eng, vol. 14, pp. 14-23, 2006.

Peer-Reviewed Conference Papers

  1. Wu, J Zhong, B. Wallace, X. Gao, H. Huang, J. Si, “Human-Robotic Prosthesis as Collaborating Agents for Symmetrical Walking”, NeurIPS, 2022 (Acceptance Rate =~25%)
  2. C Shah, A Fleming, V Nalam, M Liu, H Huang, “Design of EMG-Driven Musculoskeletal Model for Volitional Control of a Robotic Ankle Prosthesis”, 2022 IEEE IROS, 2022 (Acceptance Rate = ~40%)
  3. V Nalam, X Tu, M Li, M Liu, J. Si, H. Huang, “Admittance Control based Human-in-the-loop Optimization for Hip Exoskeleton: A New Approach “, 2022 IEEE ICRA, 2022 (Acceptance Rate = ~40%)
  4. J Berman, R Hinson, H Huang, “Comparing Reinforcement Learning Agents and Supervised Learning Neural Networks for EMG-Based Decoding of Continuous Movements”, IEEE EMBC, 2021
  5. F Popp, M Liu, H Huang, “Development of a Wearable Human-Machine Interface to Track Forearm Rotation via an Optical Sensor”, IEEE EMBC, 2021
  6. W Liu, A Fleming, IC Lee, H Huang “Direct myoelectric control modifies lower limb functional connectivity: a case study”, IEEE EMBC, 2021
  7. N Rubin, W Liu, X Hu, H Huang, “Common Neural Input within and across Lower Limb Muscles: A preliminary Study”, IEEE EMBC, 2021
  8. Alili, V Nalam, M Li, M Liu, J Si, H. Huang, “User Controlled Interface for Tuning Robotic Knee Prosthesis” 2021 IEEE/RSJ IROS 2021 (Acceptance Rate = ~40%)
  9. Upadhye, C. Shah, M Liu, G. Buckner, H. Huang, “A Powered Prosthetic Ankle Designed for Task Variability, Energy Efficiency, and Safety-A Concept Validation” 2021 IEEE/RSJ IROS 2021 (Acceptance Rate = ~40%)
  10. X Tu, M Li, M Liu, J Si, H Huang, “A Data-Driven Reinforcement Learning Solution Framework for Optimal and Adaptive Personalization of a Hip Exoskeleton“, IEEE ICRA, 2021 (Acceptance Rate = ~40%)
  11. A. Fleming, W Liu, H Huang, “Neural Coherence of Homologous Muscle Pairs during Direct EMG Control of Standing Posture in Transtibial Amputees”, 2020 International Conference on Neurorehabilitation (ICNR), 2020
  12. R Wu, M Li, J Si and H Huang, “Understanding Human-Prosthesis Interaction via Reinforcement Learning-based Echo Control: A case study”, 2020 International Conference on Neurorehabilitation (ICNR), 2020
  13. L. Vargas, H. Huang, Y. Zhu, X. Hu, “Stiffness Perception using Transcutaneous Electrical Stimulation during Active and Passive Prosthetic Control”, Conf Proc IEEE Eng Med Biol Soc, 2020
  14. J. Park, M. Zahabi, D. Kaber, J. Ruiz, H. Huang, “Evaluation of activities of daily living testbeds for assessing prosthesis device usability”, IEEE ICHMS, 2020
  15. X Gao, J. Si, Y. Wen, M. Li, H Huang, “Knowledge-Guided Reinforcement Learning Control for Robotic Lower Limb Prosthesis”, IEEE ICRA, 2020 (Acceptance Rate = ~40%)
  16. M. Li, et al. Gaze Fixation Comparisons Between Amputees and Able-bodied Individuals in Approaching Stairs and Level-ground Transitions: A pilot study, Conf Proc IEEE Eng Med Biol Soc, 2019
  17. M. Liu, A. Lupiani, H. Huang, Identify Kinematic Features for Powered Prosthesis Tuning, IEEE ICORR,2019
  18. A Fleming, H. Huang, Proportional Myoelectric Control of a Powered Ankle Prosthesis for Postural Control under Expected Perturbation: A Pilot Study,IEEE ICORR,2019
  19. M. Li, X. Gao, Y. Wen, J. Si, H Huang, Offline policy interaction-based reinforcement learning controller for online robotic knee prosthesis parameter tuning, IEEE ICRA, 2019 (Acceptance Rate= ~40%)
  20. Gao, Y. Wen, M. Li, J. Si, H. Huang, Robotic knee parameter tuning using approximate policy iteration, International Conference on Cognitive Systems and Signal Processing, Springer, Singapore. pp. 554-563, 2018
  21. Wen, X. Gao, J. Si, A. Brandt, M Li, H Huang, Robotic Knee Prosthesis Real-Time Control Using Reinforcement Learning with Human in the Loop, International Conference on Cognitive Systems and Signal Processing, Springer, Singapore. pp. 463-73, 2018
  22. L. Pan, A. Harmody^, H. Huang, A Reliable Multi-User EMG Interface Based on A Generic-Musculoskeletal Model against Loading Weight Changes, Conf Proc IEEE Eng Med Biol Soc, 2018
  23. L. Vargas, H. Huang, Y. Zhu, X. Hu, Merged Haptic Sensation in the Hand during Concurrent Non-Invasive Proximal Nerve Stimulation,Conf Proc IEEE Eng Med Biol Soc, 2018
  24. A. Fleming, S. Huang, H. Huang, Coordination of Voluntary Residual Muscle Contractions in Transtibial Amputees: a Pilot Study,Conf Proc IEEE Eng Med Biol Soc, 2018
  25. V. Vempalal^, H. Huang, M. Liu, A Practical Approach for Pistoning Evaluation for Lower Limb Amputees,Conf Proc IEEE Eng Med Biol Soc, 2018
  26. B. Fylstra, C. Dai, X. Hu, H. Huang, Characterizing Residual Muscle Properties in Lower Limb Amputees Using High Density EMG Decomposition: A Pilot Study,Conf Proc IEEE Eng Med Biol Soc, 2018
  27. JP Diaz-Paz, RL da Silva, B. Zhong, Huang, E. Lobaton, Visual Terrain Identification and Surface Inclination Estimation for Improving Human Locomotion with a Lower-Limb Prosthetic,Conf Proc IEEE Eng Med Biol Soc, 2018
  28. T. Agcayazi, M. MaKnight, P. Sotory, H. Huang, T. Ghosh, A. Bozkurt, “A Scalable Shear and Normal Force Sensor for Prosthetic Sensing”, Conf. Prof. IEEE SENSORS, pp 1-3, 2017
  29. T. Zhang, Minh Tran, H. Huang,“NREL-Exo: a 4-DoFs Wearable Hip Exoskeleton for Walking and Balance Assistance in Locomotion”Conf. Prof. IEEE IROS, pp. 508-13, 2017 (Acceptance Rate = 44%)
  30. Y. Wen, A. Brandt, M. Liu, J. Si, H. Huang, Comparing Parallel and Sequential Control Parameter Tuning for a Powered Knee Prosthesis,Conf. Proc. IEEE Systems, Man, Cybernetics, pp. 1716-21, 2017
  31. S. Chang, D. Crouch, H. Huang, “Effects of output speed threshold on real-time continuous EMG human-machine interface control”, Conf. Proc. IEEE Systems, Man, Cybernetics, pp. 1375-80,2017
  32. L. Pan, D. Crouch, H. Huang,Musculoskeletal Model for Simultaneous and Proportional Controlof 3-DOF Hand and Wrist Movements from EMG Signals, Conf. Proc. IEEE Neural Engineering, pp. 325-8, 2017
  33. W Zhang, M White, M Zahabi, AT. Winslow, F Zhang, H Huang, D Kaber, Cognitive Workload in Conventional Direct Control vs. Pattern Recognition Control of an Upper-limb Prosthesis, Conf Proc. IEEE International Conference on Systems, Man, and Cybernetics,pp.002335-002340,2016
  34. D. Crouch, H. Huang,Simple EMG-Driven Musculoskeletal Model Enables Consistent Control Performance During Path Tracing Tasks, Conf Proc IEEE Eng Med Biol Soc,pp. 1-4, 2016
  35. Y. Wen, M. Liu, J. Si, Huang,Adaptive Control of Powered Transfemoral Prostheses Based on Adaptive Dynamic Programming,Conf Proc IEEE Eng Med Biol Soc,pp. 5071-74, 2016 (EMBC Student Paper Competition Finalist)
  36. Brandt, M. Liu, H. Huang, Does the Impedance of Above-knee Powered Prostheses Need to Adjusted for Load-carrying Conditions? Conf Proc IEEE Eng Med Biol Soc,pp. 5075-78, 2016
  37. Zhang, M. Liu, H. Huang, Tolerance of Neural Decoding Errors for Powered Artificial Legs: a Pilot Study, Conf Proc IEEE Eng Med Biol Soc,pp. 4630 – 4633,2016
  38. Anna Winslow, Justin Brantley, Fangshi Zhu, José Contreras-Vidal, He Huang, Corticomuscular Coherence Variation throughout the Gait Cycle during Overground Walking: A Preliminary Investigation, Conf Proc IEEE Eng Med Biol Soc, 4634 – 4637, 2016
  39. Liu, P. Bohlen, H. Huang, Effect of Environmental Factors on Level of Tripping Disturbance: A Simulation Study, Conf Proc IEEE Eng Med Biol Soc,pp. 5038-41, 2016
  40. Justin Brantley, Trieu Phat Luu, Recep Ozdemir, Fangshi Zhu, Anna Winslow, He Huang, José Contreras-Vidal*, Noninvasive EEG Correlates of Overground and Stair Walking, Conf Proc IEEE Eng Med Biol Soc, 5729-32, 2016
  41. Zhang, M. Liu, H. Huang, Detection of Critical Errors of Locomotion Mode Recognition for Volitional Control of Powered Transfemoral Prostheses, 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society,pp. 1128-1131,2015
  42. Crouch, H. Huang, Musculoskeletal Model Predicts Multi-joint Wrist and Hand Movement From Limited EMG Control Signals,37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society,pp. 1132-1135, 2015
  43. Yang, F. Wu, M. Liu, H. Huang, An Optimization-based Approach for Prosthesis Dynamic Modeling and Parameter Identification,2015 Dynamic Systems and Control Conference, 2015
  44. Liu, F. Zhang, H. Huang.An Open and Configurable Embedded System for EMG Pattern Recognition Implementation for Artificial Arms.Proc of IEEE Engineering in Medicine and Biology Society. PP. 4095 – 4098,2014
  45. Myers, L. Du, H. Huang, Y. Zhu (2014). Novel Wearable EMG Sensors Based on Nanowire Technology. Proc of IEEE Engineering in Medicine and Biology Society. PP.1674 – 1677, 2014
  46. Zhang, H. Huang, “Practical implementation of robust sensor interface for EMG pattern recognition for artificial arm control”, International Conference on Advanced Limb Prosthetics (MEC’12),2014
  47. Wang, M. Liu, H. Huang, “Design of an expert system to automatically Calibrate impedance control for powered knee prostheses”, Conf Proc IEEE International Conference on Rehabilitation Robots, 2013
  48. Zhang, H. Huang, “Decoding Movement Intent of Patient with Multiple Sclerosis for the Powered Lower Extremity Exoskeleton”, Conf Proc IEEE Eng Med Biol Soc, pp. 4957-60, 2013
  49. Hernandez, X. Zhang, F. Zhang, Q. Yang, H.Huang,“Design and Implementation of a Low Power Mobile CPU Based Embedded System for Artificial Leg Control”, Conf Proc IEEE Eng Med Biol Soc, pp. 5769-72, 2013
  50. Zhang, H. Huang,Y. Qing, “Real-Time Implementation of a Self-Recovery EMG Pattern Recognition Interface for Artificial Arms”, Conf Proc IEEE Eng Med Biol Soc,pp.5926-29,2013
  51. Du, H. He, H. Huang,“Improving the performance of a neural-machine interface for prosthetic legs using adaptive pattern classifiers” Conf Proc IEEE Eng Med Biol Soc,pp.1571-4,2013
  52. Wang, L Du, H. Huang, “Terrain Recognition Improves the Performance of Neural-Machine Interface for Locomotion Mode Recognition”, International Conference on Computing, Networking and Communications, Workshops Cyber Physical System, pp. 87-92, 2013
  53. Zhang, M. Liu, H. Huang, “Preliminary Study of the Effect of User Intent Recognition Errors on Volitional Control of Powered Lower Limb Prostheses”, Conf Proc IEEE Eng Med Biol Soc, pp. 2768-2771, 2012
  54. Hernandez, F. Zhang, X. Zhang, H. Huang,Q. Yang, “Promise of a Low Power Mobile CPU Based Embedded System in Artificial Leg Control”, Conf Proc IEEE Eng Med Biol Soc, pp. 5250-5254, 2012
  55. Zhang, D. Wang, Q. Yang, H. Huang, “An Automatic and User-Driven Training Method for Locomotion Mode Recognition for Artificial Leg Control”, Conf Proc IEEE Eng Med Biol Soc, pp. 6116-6120, 2012
  56. Zhang,H. Huang, Q. Yang, “Implementing an FPGA System for Real-Time Intent Recognition for Prosthetic Legs”, Design Automation Conference, pp. 169-175, 2012 (Acceptance Rate = 24%)
  57. Zhang, H. Huang, “Real-time recognition of user intent for neural control of aritifcial legs”, International Conference on Advanced Limb Prosthetics (MEC’11),155-8, 2011
  58. Zhang, Z. Dou, M. Nunnery, and H. Huang, “Real-time implementation of an intent recognition system for artificial legs,”Conf Proc IEEE Eng Med Biol Soc, 2011, pp. 2997-3000, 2011.
  59. Zhang, H. Huang, and Q. Yang, “A special purpose embedded system for neural machine interface for artificial legs,”Conf Proc IEEE Eng Med Biol Soc, 2011, pp. 5207-10, 2011.
  60. Zhang, Z. Fang, M. Liu, and H. Huang, “Preliminary design of a terrain recognition system,” Conf Proc IEEE Eng Med Biol Soc, 2011, pp. 5452-5, 2011.
  61. Huang, Z. Dou, F. Zhang, and M. J. Nunnery, “Improving the performance of a neural-machine interface for artificial legs using prior knowledge of walking environment,”Conf Proc IEEE Eng Med Biol Soc, 2011, pp. 4255-8, 2011.
  62. Liu, F. Zhang, Y. L. Sun, and H. Huang, “Trust sensor interface for improving reliability of EMG-based user intent recognition,” Conf Proc IEEE Eng Med Biol Soc, vol. 2011, pp. 7516-20, 2011.
  63. Gao, F. Zhang, and H. Huang, “Investigation of sit-to-stand and stand-to-sit in an above knee amputee,” Conf Proc IEEE Eng Med Biol Soc, 2011, pp. 7340-3, 2011
  64. Liu, P. Datseris, and H. Huang, “A prototype for smart prosthetic legs: analysis and mechanical design,” in Proceeding of International Conference on Control, Robotics and Cybernetics. New Delhi, India: IEEE, March 21-23, Vol. 1. pp. 139-143, 2011.
  65. Zhang, W. DiSanto, J. Ren, Z. Dou, Q. Yang, H. Huang, “A Novel CPS System for Evaluating a Neural-Machine Interface for Artificial Legs”, in Proceeding of 2ndACM/IEEE International Conference on Cyber-Physical Systems, Chicago, IL, pp 67-76, 2011(10-page paper; Acceptance Rate = 27%)
  66. Zhang, Q Yang, H. Huang,“Design and implementation of a special purpose embedded system for Neural Machine Interface”, Conf Proc IEEE International Conference on Computer Design, Amsterdam, Netherland, pp 166-172, 2010 (Acceptance Rate = 20%)
  67. Huang, Y. Sun, Q, Yang, F. Zhang, X Zhang, Y. Liu, J. Ren, F. Sierra, “Integrating neuromuscular and cyber systems for neural control of artificial legs”, in Proceeding of First ACM/IEEE International Conference on Cyber-Physical Systems, Stockholm, Sweden,pp. 129-138, 2010 (10-page paper; Acceptance Rate = 28%)
  68. A Lin, X. Zhang, Huang, and Q. Yang, “Design and implementation of an embedded system for neural-controlled artificial legs,” in IEEE Workshop on Health Care Management. Venice, Italy, pp. 1-6, 2010
  69. J. Hargrove, H. Huang, A. E. Schultz, B. A. Lock, R. Lipschutz, and T. A. Kuiken, “Toward the development of a neural interface for lower limb prosthesis control,” Conf Proc IEEE Eng Med Biol Soc, vol. 1, pp. 2111-4, 2009.
  70. Xiao, H. Huang, Y. Sun, and Q. Yang, “Promise of embedded system with GPU in artificial leg control: Enabling time-frequency feature extraction from electromyography,” Conf Proc IEEE Eng Med Biol Soc, vol. 1, pp. 6926-9, 2009.
  71. Balasubramanian, H. Huang, and J. He, “Quantification of dynamic property of pneumatic muscle actuator for design of therapeutic robot control,” Conf Proc IEEE Eng Med Biol Soc, vol. 1, pp. 2734-7, 2006.
  72. Chen,H. Huang, W. Xu, R. I. Wallis, H. Sundaram, T. Rikakis, T. Ingalls, L. Olson, and J. He, “The design of a real-time, multimodal biofeedback system for stroke patient rehabilitation,” in The 14th Annual ACM International Conference on Multimedia. Santa Barbara: ACM Press: New York, pp. 763-72, 2006
  73. Huang, Y. Chen, W. Xu, H. Sundaram, L. Olson, T. Ingalls, T. Rikakis, and J. He, “Novel design of interactive multimodal biofeedback system for neurorehabilitation,”Conf Proc IEEE Eng Med Biol Soc, vol. 1, pp. 4925-8, 2006.
  74. Huang, T. Ingalls, L. Olson, K. Ganley, T. Rikakis, and J. He, “Interactive multimodal biofeedback for task-oriented neural rehabilitation,” Conf Proc IEEE Eng Med Biol Soc, vol. 3, pp. 2547-50, 2005.
  75. He, E. Koeneman, H. Huang, G. T. Sugar, R. Herman, and J. B. Koeneman, ” Design of a Robotic Upper Extremity Repetitive Therapy Device,” in Proceeding of IEEE 9th International conference on rehabilitation robotics. Chicago, IL, 2005, pp. 511-4.
  76. He, E. J. Koeneman, R. Schultz, D. Herring, J. Wanberg, H. Huang, T. Sugar, R. Herman, and J. B. Koeneman, “RUPERT: a Device for Robotic Upper Extremity Repetitive Therapy,” Conf Proc IEEE Eng Med Biol Soc, vol. 7, pp. 6844-7, 2005.
  77. Huangand H. Jiping, “Utilization of biomechanical modeling in design of robotic arm for rehabilitation of stroke patients,” Conf Proc IEEE Eng Med Biol Soc, vol. 4, pp. 2718-21, 2004.
  78. Huang, A. Papandreou-Suppappola, and H. Jiping, “Analysis of surface electromyogram during gait by modified mathcing pursuit decomposition,” in Conf Proc IEEE Eng Med Biol Soc, vol. 3. Cancun, Mexico, 2003, pp. 2402-5.
  79. R. Carhart, W. Willis, A. Thompson,H. Huang, S. D’Luzansky, J. Thresher, R. Herman, and J. He, “Mechanical and metabolic change in gait performance with spinal cord stimulation and reflex-FES,” in Conf Proc IEEE Eng Med Biol Soc, vol. 2. Cancun, Mexico, 2003, pp. 1558-61.
  80. Kuchi, R. Hiremagalur, H. Huang, M. Carhart, J. He, and S. Panchanathan, “DRAG: A Database for Recognition and Analysis of Gait,” in Proceeding of Internet Multimedia Management Systems, vol. 5242. Orlando, FL, 2003, pp. 115-24.
  81. Huang, J. He, M. Carhart, and R. Herman, “Change of muscle activation pattern by epidural stimulation on a SCI patient,” in Conf Proc IEEE Eng Med Biol Soc, vol. 1. Houston, TX, 2002, pp. 114-5.

Book Chapters

  1. S. Wolf, H. Huang, “Chapter 70: Evolution of Biofeedback in Physical Medicine and Rehabilitation”, in DeLisa’s Physical Medicine and Rehabilitation: Principles and Practice, 5thedition, eds. W. Frontera, Philadelphia: Lippincott Williams & Wilkins, 2010
  2. J. Si, & H.Huang, “Reinforcement Learning Control by Direct Heuristic Dynamic Programming”. In Women in Computational Intelligence (pp. 205-217). Springer, Cham.