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Full List of Publications

Accepted or Published Journal Articles

  1. F. Valero-Cuevas*, J. Finley, A. Orsborn, N. Fung, J. Hicks. H. Huang, D. Reinkensmeyer, N. Schweighofer, D. Weber, K. Steele, “NSF DARE – Transforming modeling in neurorehabilitation: four threads for catalyzing progress”, Journal of NeuroEngineering and Rehabilitation, 2024
  2. H. Huang, L. Hargrove, M. Ortiz-Catalan, J Sensinger, “Integrating upper-limb prostheses with the human body: technology advances, readiness, and roles in human–prosthesis interaction”, Annual Review of Biomedical Engineering, 2024
  3. Y Liu, J Berman, A Dodson, J Park, M Zahabi, H Huang, D. Kaber, “Human-Centered Evaluation of EMG-Based Upper-Limb Prosthetic Control Modes”, IEEE Transactions on Human-Machine Systems, 2024
  4. N. Rubin, R. Hinson, K. Saul, W. Filer, X Hu, H. Huang, “Modified motor unit properties in residual muscle following transtibial amputation”, Journal of Neural Engineering, 2024 (Accepted)
  5. N. Rubin, R. Hinson, K. Saul, X Hu, H. Huang, “Ankle Torque Estimation with Motor Unit Discharges in Residual Muscles following Lower-Limb Amputation”, IEEE Trans on Neural System and Rehabilitation Engineering,  2023
  6. A. Naseri, IC Lee, H. Huang, M. Liu*, “Investigating the Association of Quantitative Gait Stability Metrics with User Perception of Gait Interruption due to Control Faults during Human-Prosthesis Interaction”, IEEE Trans on Neural System and Rehabilitation Engineering,2023
  7. A. Fleming, W. Liu, and H Huang. “Neural Prosthesis Control Restores Near-Normative Neuromechanics in Standing Postural Control”,Science Robotics, 8, eadf5758, 2023 (Research News at NC State https://news.ncsu.edu/2023/10/robotic-ankles-move-naturally/ and has been featured on NSF News, National Academy of Engineering Frontiers website, etc.)
  8. LE Fisher, RA Gaunt, and H Huang. “Sensory Restoration for Improved Motor Control of Prostheses.”Current Opinion in Biomedical Engineering, 100498, 2023
  9. A. Abbas, A Fleming, V Nalam, M Liu, J Dean, and H Huang. “Abduction/Adduction Assistance From Powered Hip Exoskeleton Enables Modulation of User Step Width During Walking.” IEEE Transactions on Biomedical Engineering, 2023 (Awarded with “Feature Article” for Jan 2024 Issue)
  10. Y Hong, Y Zhao, J Berman, Y Chi, Y Li, H Huang, J. Yin*, “Angle-programmed tendril-like trajectories enable a multifunctional gripper with ultradelicacy, ultrastrength, and ultraprecision”, Nature Communication, 2023
  11. Perspective Article by H Huang and IC Lee: “AI enables symbiotic robotic prosthetics” in “Artificial intelligence meets medical robotics”, Science Magazine, 2023
  12. R. Hinson, J. Berman, IC Lee, W. Filler, H. Huang, “Offline Evaluation Matters: Investigation of the Influence of Offline Performance of EMG-based Neural-Machine Interfaces on User Adaptation, Cognitive Load, and Physical Efforts in a Real-Time Application”, IEEE Trans on Neural System and Rehabilitation Engineering, 2023, (Accepted)
  13. J Park, J Berman, A Dodson, J Liu, M Armstrong , H Huang, D Kaber, J Ruiz, M Zahabi*. “Assessing Workload in Using Electromyography (EMG)-based Prostheses”. Ergonomics. 2023
  14. X. Gao, J. Si, H. Huang, “Value Function Based Reinforcement Learning Control with Knowledge Shaping”, IEEE Trans Neural Network and Learning Systems, 2023 （Accepted)
  15. 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
  16. 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
  17. 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)
  18. 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
  19. 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)
  20. 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)
  21. 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
  22. L. Vargas, H. Huang, Y. Zhu, X. Hu, “Resembled Tactile Feedback for Object Recognition using Prosthetic Hand”, IEEE Robotic and Automation Letter, 2022
  23. 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
  24. 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
  25. 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
  26. 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
  27. 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
  28. 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
  29. 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
  30. 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
  31. 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
  32. 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
  33. 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
  34. 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
  35. V. Nalam, H Huang, “Empower prosthesis users with a hip exoskeleton”, Nature Medicine, 2021 (Invited Commentary)
  36. 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)
  37. 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)
  38. 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)
  39. 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)
  40. 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
  41. 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
  42. L. Vargas, H. Huang, Y. Zhu, X. Hu*, “Static and Dynamic Proprioceptive Recognition through Vibrotactile Stimulation”, Journal of Neural Engineering, 2021
  43. 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
  44. 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)
  45. 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)
  46. L Pan, H Huang, “A Robust Model-Based Neural-Machine Interface across Different Loading Conditions”, Biomedical Signal Processing and Control, 67, 102509. 2021
  47. 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
  48. 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
  49. 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
  50. 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
  51. 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)
  52. 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
  53. 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
  54. M. Liu*, D. Kamper, H. Huang, “An Easy-to-Use Socket-Suspension Monitoring System for Lower Limb Amputees”, IEEE Transactions on Instrumentation & Measurement, 2020
  55. B. Zhong, H. Huang*, E. Lobaton*, “Reliable Vision-Based Grasping Target Recognition for Upper-limb Prostheses”, IEEE Trans on Cybernetics, 2020 (Accepted)
  56. 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)
  57. 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
  58. 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
  59. 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
  60. 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
  61. 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
  62. 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)
  63. 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
  64. 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
  65. 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
  66. 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
  67. T. Zhang*, H Huang#,“Development of a Modular Clutchable Soft Actuator for Reconfigurable Wearable Exoskeletons”, IEEE Trans on Mechatronics, 2019
  68. 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
  69. 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
  70. 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
  71. 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
  72. 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
  73. 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
  74. 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
  75. 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
  76. 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.)
  77. T. Zhang*, H. Huang#,“Industrial handling augmentation by a lower-back robotic exoskeleton”, IEEE Robotics and Automation Magazine, 25(2), 95-106, 2018
  78. 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
  79. 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
  80. 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
  81. 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)
  82. 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
  83. M. Liu, F. Zhang, H. Huang*, “An Adaptive Classification Strategy for Reliable Locomotion Mode Recognition”, Sensors, 17(9): 2020, 2017
  84. 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
  85. 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
  86. 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
  87. 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
  88. 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)
  89. 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
  90. 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
  91. 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
  92. 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
  93. A Myer, H. Huang, Y. Zhu*, “Wearable Silver Nanowire Dry Electrodes for Bioelectronic Sensing”, RSC Advances, 5(15), pp. 11627-32, 2015
  94. 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
  95. 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)
  96. 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
  97. 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
  98. 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
  99. 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
  100. 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
  101. 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
  102. 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
  103. Cao, H He*, H Huang. “LIFT: A New Framework of Learning from Testing Data for Face Recognition”. Neurocomputing, 74(6), pp. 916-929, 2011
  104. 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
  105. Tkach, H Huang*, TA Kuiken#, “Stability of time-domain EMG features for prosthetic device control”, Journal of NeuroEngineering and Rehabilitation, 7(1):21, 2010
  106. 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.
  107. 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.
  108. 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.
  109. 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.
  110. 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.
  111. 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.
  112. H. Huang, S. L. Wolf, and J. He*, “Recent developments in biofeedback for neuromotor rehabilitation,” J Neuroeng Rehabil, vol. 3, pp. 11, 2006.
  113. 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. Yuan, X Bai, A Alili, M Liu, J Feng, and H Huang. “Finding a Natural Fit: A Thematic Analysis of Amputees’ Prosthesis Setting Preferences during User-Guided Auto-Tuning.” InProceedings of the Human Factors and Ergonomics Society Annual Meeting, p. 21695067231216121. Sage CA: Los Angeles, CA: SAGE Publications, 2023.
  2. A Alili, V Nalam, A Fleming, M. Liu, J Dean, He Huang, “Closed-Loop Feedback Control of Human Step Width During Walking by Mediolaterally Acting Robotic Hip Exoskeleton”, IEEE IROS, 2023 (Acceptance Rate =~40%)
  3. Z Yu, V Nalam*, A Alili, H Huang, “A Wearable Robotic Rehabilitation System for Neuro-Rehabilitation Aimed at Enhancing Mediolateral Balance”, IEEE IROS, 2023 (Acceptance Rate =~40%)
  4. A Naseri, M Liu*, IC Lee, He Huang, “Development and Online Validation of an Intrinsic Fault Detector for a Powered Robotic Knee Prosthesis”, IEEE IROS, 2023 (Acceptance Rate =~40%)
  5. Q Zhang, X Tu, J Si, M Lewek, H Huang*, “A Robotic Assistance Personalization Control Approach of Hip Exoskeletons for Gait Symmetry Improvement”, IEEE IROS, 2023 (Acceptance Rate =~40%)
  6. Hong, H. Huang, “Towards Personalized Impedance Control Using Principal Component Analysis for Powered Knee Prosthesis”, IEEE ICORR, 2023
  7. Driscol, M. Liu, and H. Huang, “1-D Manual Tracing Based on a High Density Haptic Stimulation Grid – a Pilot Effort”, 2023 IEEE World Haptics Conference (WHC) (Acceptance Rate =~45%)
  8. 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%)
  9. 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%)
  10. 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%)
  11. 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
  12. F Popp, M Liu, H Huang, “Development of a Wearable Human-Machine Interface to Track Forearm Rotation via an Optical Sensor”, IEEE EMBC, 2021
  13. W Liu, A Fleming, IC Lee, H Huang “Direct myoelectric control modifies lower limb functional connectivity: a case study”, IEEE EMBC, 2021
  14. N Rubin, W Liu, X Hu, H Huang, “Common Neural Input within and across Lower Limb Muscles: A preliminary Study”, IEEE EMBC, 2021
  15. 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%)
  16. 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%)
  17. 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%)
  18. 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
  19. 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
  20. 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
  21. 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
  22. 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%)
  23. 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
  24. M. Liu, A. Lupiani, H. Huang, Identify Kinematic Features for Powered Prosthesis Tuning, IEEE ICORR,2019
  25. A Fleming, H. Huang, Proportional Myoelectric Control of a Powered Ankle Prosthesis for Postural Control under Expected Perturbation: A Pilot Study,IEEE ICORR,2019
  26. 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%)
  27. 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
  28. 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
  29. 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
  30. 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
  31. 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
  32. V. Vempalal^, H. Huang, M. Liu, A Practical Approach for Pistoning Evaluation for Lower Limb Amputees,Conf Proc IEEE Eng Med Biol Soc, 2018
  33. 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
  34. 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
  35. 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
  36. 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%)
  37. 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
  38. 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
  39. 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
  40. 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
  41. 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
  42. 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)
  43. 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
  44. 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
  45. 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
  46. 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
  47. 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
  48. 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
  49. 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
  50. 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
  51. 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
  52. 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
  53. 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
  54. 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
  55. 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
  56. 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
  57. 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
  58. 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
  59. 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
  60. 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
  61. 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
  62. 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
  63. 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%)
  64. 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
  65. 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.
  66. 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.
  67. 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.
  68. 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.
  69. 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.
  70. 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
  71. 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.
  72. 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%)
  73. 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%)
  74. 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%)
  75. 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
  76. 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.
  77. 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.
  78. 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.
  79. 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
  80. 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.
  81. 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.
  82. 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.
  83. 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.
  84. 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.
  85. 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.
  86. 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.
  87. 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.
  88. 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.