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Research Project 1: Neural control of powered prosthetic legs

Recent advances in mechatronics have propelled the development of powered lower limb prostheses. These robotic devices are intended to provide active mechanical power to replace the lost physical capabilities in lower limb amputees due to their limb losses. Neural control of such lower limb wearable devices is essentialbut has not been successful. Our research objective is to create an innovative neural control system for powered lower limb prosthetics, which enable amputees to perform locomotor and nonlocomotor task intuitively, efficiently, and safely. The research is essential for reverse-engineering the neural control of human locomotion and innovating neural-machine interfacing systems. Our long-term goal is to develop true bionic legs that can improve the quality of life of patients with lower limb amputations.

 

Selected Publications Related to this Project:

 

Zhang, F, H Huang, Source Selection for Real-time User Intent Recognition towards Volitional Control of Artificial LegsIEEE Journal of Biomedical and Health Informatics, 2013 (Accepted)

 

Huang H, F Zhang, L Hargrove, Z. Dou, D Rogers, K. Englehart. Continuous Locomotion Mode Identification for Prosthetic Legs based on Neuromuscular-Mechanical FusionIEEE Trans Biomed Eng58(1), pp 2867-75,2011

 

Huang H, F Zhang, Y Sun, H He. Design of a Robust EMG Sensing Interface for Pattern ClassificationJournal of Neural Engineering, 7(5), 2010

 

Huang H, Kuiken T A, Lipschutz R. A Strategy for Identifying Locomotion Modes using Surface ElectromyographyIEEE Trans Biomed Eng, 56(1) 65-73 2009. 

 

 

Research Project 2: Building the foundation of clinical practice of EMG pattern recognition for prostheticarm control

Conventional prosthesis control (i.e. body-powered or proportional EMG control) is inadequate for multifunctional prostheses operation. Research in laboratory has shown that EMG pattern recognition enables upper limb amputees to control multiple degrees of freedom of a prosthesis intuitively and efficiently. Unfortunately, no commercially available prosthetic arms use EMG PR control scheme due to several challenges for clinical practice. Hence, the purpose of this project is to improve the function of upper limb prostheses by developing a reliable, robust, and clinically-viable prosthesis control system based on electromyography (EMG) pattern recognition (PR).

 

Selected Publications Related to this Project:

 

Tkach D, H Huang, TA Kuiken, Stability of time-domain EMG features for electromyographic  pattern recognitionJournal of NeuroEngineering and Rehabilitation, 7:21, 2010

 

Huang H,  Zhou P, Li G, Kuiken TA, Spatial Filters Improves EMG Classification Accuray Following Targeted Muscle ReinnervationAnnals of Biomedical Engineering, 37(9), 1849-57, 2009

 

Huang H,  Zhou P, Li G, Kuiken TAAn analysis of EMG electrode configuration for targeted muscle reinnervation based neural machine interfaceIEEE Transactions on Neural Systems and Rehabilitation Engineering, 16(1):37-45, Feb 2008

 

Zhou, P, Lowery MM, Englehart KB, Huang H, Li G, Hargrove L, Dewald JPA, and Kuiken TA, Decoding a New Neural-Machine Interface for Control of Artificial LimbsJournal of Neurophysiology, Vol 98, Issue 5, Nov. 2007, page 2974-82 

 

 

Research Project 3: Stumble recovery in lower limb amputees

Falls among lower limb amputees are prevalent and the consequences of falling can be serious. However, little, if any, information can be found in the literature related to the rate of falls among community dwelling amputee patients. Additionally, there is a scarcity of studies that provide information about the circumstances and activities that precipitate falls or the type of prosthetic components that are associated with falling.  

 

In our research group, we are interested in understanding the factors that contribute to balance instability in lower limb amputees, investigating biomechanics of lower limb amputees during stumbling, and developing advanced prosthesis control to enable active stumble recovery in leg amputees. 

 

Selected Publications Related to this Project:

 

Zhang F, S.E. D'Andrea, M.J. Nunnery, S. Kay, H. Huang. Towards design of a stumble detection system for artificial legs. IEEE Trans Neural Syst Rehabil EngVol. 19(5): 567-77, 2011

 

Zhang F., A. Burke, F. Sierra, S.E. D'Andrea, M.J. Nunnery, and H. Huang, " Neuromuscular response to stumbling in healthy subjects and patients with transfemoral amputations ", in The 40th Annual Meeting of Society for Neuroscience. San Diego, CA, 2010

 

 

Other Ongoing Projects
Multisensor fusion for locomotion mode recognition

Related publications:

 

Lin D, F Zhang, M Liu, H Huang, Towards design of an environment-aware adaptive locomotion-mode-recognition systemIEEE Trans Biomed. Eng59(10):2716-25, 2012

 

D. 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

 

Neural control of exoskeleton for neuromotor rehabilitation

Related publications:

 

F. Zhang, H. Huang, “Decoding Movement Intent of Patient with Multiple Sclerosis for the Powered Lower Extremity Exoskeleton”, Conf Proc IEEE Eng Med Biol Soc, 2013 (Accepted)

 

Intelligent control of powered artificial legs

Related publications:

 

D. Wang, M. Liu, H. Huang, “Design of An Expert System to Automatically Calibrate Impedance Control for Powered Knee Prostheses”, Conf Proc IEEE ICCOR, 2013, (Accepted)